simple research study example

How To Write A Research Paper

Step-By-Step Tutorial With Examples + FREE Template

By: Derek Jansen (MBA) | Expert Reviewer: Dr Eunice Rautenbach | March 2024

For many students, crafting a strong research paper from scratch can feel like a daunting task – and rightly so! In this post, we’ll unpack what a research paper is, what it needs to do , and how to write one – in three easy steps. 🙂

Overview: Writing A Research Paper

What (exactly) is a research paper.

How to write a research paper
Stage 1 : Topic & literature search
Stage 2 : Structure & outline
Stage 3 : Iterative writing
Key takeaways

Let’s start by asking the most important question, “ What is a research paper? ”.

Simply put, a research paper is a scholarly written work where the writer (that’s you!) answers a specific question (this is called a research question ) through evidence-based arguments . Evidence-based is the keyword here. In other words, a research paper is different from an essay or other writing assignments that draw from the writer’s personal opinions or experiences. With a research paper, it’s all about building your arguments based on evidence (we’ll talk more about that evidence a little later).

Now, it’s worth noting that there are many different types of research papers , including analytical papers (the type I just described), argumentative papers, and interpretative papers. Here, we’ll focus on analytical papers , as these are some of the most common – but if you’re keen to learn about other types of research papers, be sure to check out the rest of the blog .

With that basic foundation laid, let’s get down to business and look at how to write a research paper .

Overview: The 3-Stage Process

While there are, of course, many potential approaches you can take to write a research paper, there are typically three stages to the writing process. So, in this tutorial, we’ll present a straightforward three-step process that we use when working with students at Grad Coach.

These three steps are:

Finding a research topic and reviewing the existing literature
Developing a provisional structure and outline for your paper, and
Writing up your initial draft and then refining it iteratively

Let’s dig into each of these.

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Step 1: Find a topic and review the literature

As we mentioned earlier, in a research paper, you, as the researcher, will try to answer a question . More specifically, that’s called a research question , and it sets the direction of your entire paper. What’s important to understand though is that you’ll need to answer that research question with the help of high-quality sources – for example, journal articles, government reports, case studies, and so on. We’ll circle back to this in a minute.

The first stage of the research process is deciding on what your research question will be and then reviewing the existing literature (in other words, past studies and papers) to see what they say about that specific research question. In some cases, your professor may provide you with a predetermined research question (or set of questions). However, in many cases, you’ll need to find your own research question within a certain topic area.

Finding a strong research question hinges on identifying a meaningful research gap – in other words, an area that’s lacking in existing research. There’s a lot to unpack here, so if you wanna learn more, check out the plain-language explainer video below.

Once you’ve figured out which question (or questions) you’ll attempt to answer in your research paper, you’ll need to do a deep dive into the existing literature – this is called a “ literature search ”. Again, there are many ways to go about this, but your most likely starting point will be Google Scholar .

If you’re new to Google Scholar, think of it as Google for the academic world. You can start by simply entering a few different keywords that are relevant to your research question and it will then present a host of articles for you to review. What you want to pay close attention to here is the number of citations for each paper – the more citations a paper has, the more credible it is (generally speaking – there are some exceptions, of course).

Ideally, what you’re looking for are well-cited papers that are highly relevant to your topic. That said, keep in mind that citations are a cumulative metric , so older papers will often have more citations than newer papers – just because they’ve been around for longer. So, don’t fixate on this metric in isolation – relevance and recency are also very important.

Beyond Google Scholar, you’ll also definitely want to check out academic databases and aggregators such as Science Direct, PubMed, JStor and so on. These will often overlap with the results that you find in Google Scholar, but they can also reveal some hidden gems – so, be sure to check them out.

Once you’ve worked your way through all the literature, you’ll want to catalogue all this information in some sort of spreadsheet so that you can easily recall who said what, when and within what context. If you’d like, we’ve got a free literature spreadsheet that helps you do exactly that.

Don’t fixate on an article’s citation count in isolation - relevance (to your research question) and recency are also very important.

Step 2: Develop a structure and outline

With your research question pinned down and your literature digested and catalogued, it’s time to move on to planning your actual research paper .

It might sound obvious, but it’s really important to have some sort of rough outline in place before you start writing your paper. So often, we see students eagerly rushing into the writing phase, only to land up with a disjointed research paper that rambles on in multiple

Now, the secret here is to not get caught up in the fine details . Realistically, all you need at this stage is a bullet-point list that describes (in broad strokes) what you’ll discuss and in what order. It’s also useful to remember that you’re not glued to this outline – in all likelihood, you’ll chop and change some sections once you start writing, and that’s perfectly okay. What’s important is that you have some sort of roadmap in place from the start.

You need to have a rough outline in place before you start writing your paper - or you’ll end up with a disjointed research paper that rambles on.

At this stage you might be wondering, “ But how should I structure my research paper? ”. Well, there’s no one-size-fits-all solution here, but in general, a research paper will consist of a few relatively standardised components:

Introduction
Literature review
Methodology

Let’s take a look at each of these.

First up is the introduction section . As the name suggests, the purpose of the introduction is to set the scene for your research paper. There are usually (at least) four ingredients that go into this section – these are the background to the topic, the research problem and resultant research question , and the justification or rationale. If you’re interested, the video below unpacks the introduction section in more detail.

The next section of your research paper will typically be your literature review . Remember all that literature you worked through earlier? Well, this is where you’ll present your interpretation of all that content . You’ll do this by writing about recent trends, developments, and arguments within the literature – but more specifically, those that are relevant to your research question . The literature review can oftentimes seem a little daunting, even to seasoned researchers, so be sure to check out our extensive collection of literature review content here .

With the introduction and lit review out of the way, the next section of your paper is the research methodology . In a nutshell, the methodology section should describe to your reader what you did (beyond just reviewing the existing literature) to answer your research question. For example, what data did you collect, how did you collect that data, how did you analyse that data and so on? For each choice, you’ll also need to justify why you chose to do it that way, and what the strengths and weaknesses of your approach were.

Now, it’s worth mentioning that for some research papers, this aspect of the project may be a lot simpler . For example, you may only need to draw on secondary sources (in other words, existing data sets). In some cases, you may just be asked to draw your conclusions from the literature search itself (in other words, there may be no data analysis at all). But, if you are required to collect and analyse data, you’ll need to pay a lot of attention to the methodology section. The video below provides an example of what the methodology section might look like.

By this stage of your paper, you will have explained what your research question is, what the existing literature has to say about that question, and how you analysed additional data to try to answer your question. So, the natural next step is to present your analysis of that data . This section is usually called the “results” or “analysis” section and this is where you’ll showcase your findings.

Depending on your school’s requirements, you may need to present and interpret the data in one section – or you might split the presentation and the interpretation into two sections. In the latter case, your “results” section will just describe the data, and the “discussion” is where you’ll interpret that data and explicitly link your analysis back to your research question. If you’re not sure which approach to take, check in with your professor or take a look at past papers to see what the norms are for your programme.

Alright – once you’ve presented and discussed your results, it’s time to wrap it up . This usually takes the form of the “ conclusion ” section. In the conclusion, you’ll need to highlight the key takeaways from your study and close the loop by explicitly answering your research question. Again, the exact requirements here will vary depending on your programme (and you may not even need a conclusion section at all) – so be sure to check with your professor if you’re unsure.

Step 3: Write and refine

Finally, it’s time to get writing. All too often though, students hit a brick wall right about here… So, how do you avoid this happening to you?

Well, there’s a lot to be said when it comes to writing a research paper (or any sort of academic piece), but we’ll share three practical tips to help you get started.

First and foremost , it’s essential to approach your writing as an iterative process. In other words, you need to start with a really messy first draft and then polish it over multiple rounds of editing. Don’t waste your time trying to write a perfect research paper in one go. Instead, take the pressure off yourself by adopting an iterative approach.

Secondly , it’s important to always lean towards critical writing , rather than descriptive writing. What does this mean? Well, at the simplest level, descriptive writing focuses on the “ what ”, while critical writing digs into the “ so what ” – in other words, the implications. If you’re not familiar with these two types of writing, don’t worry! You can find a plain-language explanation here.

Last but not least, you’ll need to get your referencing right. Specifically, you’ll need to provide credible, correctly formatted citations for the statements you make. We see students making referencing mistakes all the time and it costs them dearly. The good news is that you can easily avoid this by using a simple reference manager . If you don’t have one, check out our video about Mendeley, an easy (and free) reference management tool that you can start using today.

Recap: Key Takeaways

We’ve covered a lot of ground here. To recap, the three steps to writing a high-quality research paper are:

To choose a research question and review the literature
To plan your paper structure and draft an outline
To take an iterative approach to writing, focusing on critical writing and strong referencing

Remember, this is just a b ig-picture overview of the research paper development process and there’s a lot more nuance to unpack. So, be sure to grab a copy of our free research paper template to learn more about how to write a research paper.

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How To Write A Research Paper

Research Paper Example

Research Paper Example - Examples for Different Formats

Published on: Jun 12, 2021

Last updated on: Feb 6, 2024

Research Paper Example for Different Formats

A research paper typically consists of several key parts, including an introduction, literature review, methodology, results, and annotated bibliography .

When writing a research paper (whether quantitative research or qualitative research ), it is essential to know which format to use to structure your content. Depending on the requirements of the institution, there are mainly four format styles in which a writer drafts a research paper:

Letâs look into each format in detail to understand the fundamental differences and similarities.

Research Paper Example APA

If your instructor asks you to provide a research paper in an APA format, go through the example given below and understand the basic structure. Make sure to follow the format throughout the paper.

APA Research Paper Sample (PDF)

Research Paper Example MLA

Another widespread research paper format is MLA. A few institutes require this format style as well for your research paper. Look at the example provided of this format style to learn the basics.

MLA Research Paper Sample (PDF)

Research Paper Example Chicago

Unlike MLA and APA styles, Chicago is not very common. Very few institutions require this formatting style research paper, but it is essential to learn it. Look at the example given below to understand the formatting of the content and citations in the research paper.

Chicago Research Paper Sample (PDF)

Research Paper Example Harvard

Learn how a research paper through Harvard formatting style is written through this example. Carefully examine how the cover page and other pages are structured.

Harvard Research Paper Sample (PDF)

Examples for Different Research Paper Parts

A research paper is based on different parts. Each part plays a significant role in the overall success of the paper. So each chapter of the paper must be drafted correctly according to a format and structure.

Below are examples of how different sections of the research paper are drafted.

Research Proposal Example

A research proposal is a plan that describes what you will investigate, its significance, and how you will conduct the study.

Research Proposal Sample (PDF)

Abstract Research Paper Example

An abstract is an executive summary of the research paper that includes the purpose of the research, the design of the study, and significant research findings.

It is a small section that is based on a few paragraphs. Following is an example of the abstract to help you draft yours professionally.

Abstract Research Paper Sample (PDF)

Literature Review Research Paper Example

A literature review in a research paper is a comprehensive summary of the previous research on your topic. It studies sources like books, articles, journals, and papers on the relevant research problem to form the basis of the new research.

Writing this section of the research paper perfectly is as important as any part of it.

Literature Review in Research Sample (PDF)

Methods Section of Research Paper Example

The method section comes after the introduction of the research paper that presents the process of collecting data. Basically, in this section, a researcher presents the details of how your research was conducted.

Methods Section in Research Sample (PDF)

Research Paper Conclusion Example

The conclusion is the last part of your research paper that sums up the writerâs discussion for the audience and leaves an impression. This is how it should be drafted:

Research Paper Conclusion Sample (PDF)

Research Paper Examples for Different Fields

The research papers are not limited to a particular field. They can be written for any discipline or subject that needs a detailed study.

In the following section, various research paper examples are given to show how they are drafted for different subjects.

Science Research Paper Example

Are you a science student that has to conduct research? Here is an example for you to draft a compelling research paper for the field of science.

Science Research Paper Sample (PDF)

History Research Paper Example

Conducting research and drafting a paper is not only bound to science subjects. Other subjects like history and arts require a research paper to be written as well. Observe how research papers related to history are drafted.

History Research Paper Sample (PDF)

Psychology Research Paper Example

If you are a psychology student, look into the example provided in the research paper to help you draft yours professionally.

Psychology Research Paper Sample (PDF)

Research Paper Example for Different Levels

Writing a research paper is based on a list of elements. If the writer is not aware of the basic elements, the process of writing the paper will become daunting. Start writing your research paper taking the following steps:

Choose a topic
Form a strong thesis statement
Conduct research
Develop a research paper outline

Once you have a plan in your hand, the actual writing procedure will become a piece of cake for you.

No matter which level you are writing a research paper for, it has to be well structured and written to guarantee you better grades.

If you are a college or a high school student, the examples in the following section will be of great help.

Research Paper Outline (PDF)

Research Paper Example for College

Pay attention to the research paper example provided below. If you are a college student, this sample will help you understand how a winning paper is written.

College Research Paper Sample (PDF)

Research Paper Example for High School

Expert writers of CollegeEssay.org have provided an excellent example of a research paper for high school students. If you are struggling to draft an exceptional paper, go through the example provided.

High School Research Paper Sample (PDF)

Examples are essential when it comes to academic assignments. If you are a student and aim to achieve good grades in your assignments, it is suggested to get help from CollegeEssay.org .

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Professional writers have your back, whether you are looking for guidance in writing a lab report, college essay, or research paper.

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Research Paper Guide

Research Paper Example

Research Paper Examples - Free Sample Papers for Different Formats!

Research Paper Example for Different Formats

Following a specific formatting style is essential while writing a research paper . Knowing the conventions and guidelines for each format can help you in creating a perfect paper. Here we have gathered examples of research paper for most commonly applied citation styles :

Social Media and Social Media Marketing: A Literature Review

APA Research Paper Example

APA (American Psychological Association) style is commonly used in social sciences, psychology, and education. This format is recognized for its clear and concise writing, emphasis on proper citations, and orderly presentation of ideas.

Here are some research paper examples in APA style:

Research Paper Example APA 7th Edition

Research Paper Example MLA

MLA (Modern Language Association) style is frequently employed in humanities disciplines, including literature, languages, and cultural studies. An MLA research paper might explore literature analysis, linguistic studies, or historical research within the humanities.

Here is an example:

Found Voices: Carl Sagan

Research Paper Example Chicago

Chicago style is utilized in various fields like history, arts, and social sciences. Research papers in Chicago style could delve into historical events, artistic analyses, or social science inquiries.

Here is a research paper formatted in Chicago style:

Chicago Research Paper Sample

Research Paper Example Harvard

Harvard style is widely used in business, management, and some social sciences. Research papers in Harvard style might address business strategies, case studies, or social policies.

View this sample Harvard style paper here:

Harvard Research Paper Sample

Examples for Different Research Paper Parts

A research paper has different parts. Each part is important for the overall success of the paper. Chapters in a research paper must be written correctly, using a certain format and structure.

The following are examples of how different sections of the research paper can be written.

Research Proposal

The research proposal acts as a detailed plan or roadmap for your study, outlining the focus of your research and its significance. It's essential as it not only guides your research but also persuades others about the value of your study.

Example of Research Proposal

An abstract serves as a concise overview of your entire research paper. It provides a quick insight into the main elements of your study. It summarizes your research's purpose, methods, findings, and conclusions in a brief format.

Research Paper Example Abstract

Literature Review

A literature review summarizes the existing research on your study's topic, showcasing what has already been explored. This section adds credibility to your own research by analyzing and summarizing prior studies related to your topic.

Literature Review Research Paper Example

Methodology

The methodology section functions as a detailed explanation of how you conducted your research. This part covers the tools, techniques, and steps used to collect and analyze data for your study.

Methods Section of Research Paper Example

How to Write the Methods Section of a Research Paper

The conclusion summarizes your findings, their significance and the impact of your research. This section outlines the key takeaways and the broader implications of your study's results.

Research Paper Conclusion Example

Research Paper Examples for Different Fields

Research papers can be about any subject that needs a detailed study. The following examples show research papers for different subjects.

History Research Paper Sample

Preparing a history research paper involves investigating and presenting information about past events. This may include exploring perspectives, analyzing sources, and constructing a narrative that explains the significance of historical events.

View this history research paper sample:

Many Faces of Generalissimo Fransisco Franco

Sociology Research Paper Sample

In sociology research, statistics and data are harnessed to explore societal issues within a particular region or group. These findings are thoroughly analyzed to gain an understanding of the structure and dynamics present within these communities.

Here is a sample:

A Descriptive Statistical Analysis within the State of Virginia

Science Fair Research Paper Sample

A science research paper involves explaining a scientific experiment or project. It includes outlining the purpose, procedures, observations, and results of the experiment in a clear, logical manner.

Here are some examples:

Science Fair Paper Format

What Do I Need To Do For The Science Fair?

Psychology Research Paper Sample

Writing a psychology research paper involves studying human behavior and mental processes. This process includes conducting experiments, gathering data, and analyzing results to understand the human mind, emotions, and behavior.

Here is an example psychology paper:

The Effects of Food Deprivation on Concentration and Perseverance

Art History Research Paper Sample

Studying art history includes examining artworks, understanding their historical context, and learning about the artists. This helps analyze and interpret how art has evolved over various periods and regions.

Check out this sample paper analyzing European art and impacts:

European Art History: A Primer

Research Paper Example Outline

Before you plan on writing a well-researched paper, make a rough draft. An outline can be a great help when it comes to organizing vast amounts of research material for your paper.

Here is an outline of a research paper example:

Here is a downloadable sample of a standard research paper outline:

Research Paper Outline

Want to create the perfect outline for your paper? Check out this in-depth guide on creating a research paper outline for a structured paper!

Good Research Paper Examples for Students

Here are some more samples of research paper for students to learn from:

Fiscal Research Center - Action Plan

Qualitative Research Paper Example

Research Paper Example Introduction

How to Write a Research Paper Example

Research Paper Example for High School

Now that you have explored the research paper examples, you can start working on your research project. Hopefully, these examples will help you understand the writing process for a research paper.

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Our team is experienced in delivering perfectly formatted, 100% original research papers. So, whether you need help with a part of research or an entire paper, our experts are here to deliver.

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Research Paper Examples

Research paper examples are of great value for students who want to complete their assignments timely and efficiently. If you are a student in the university, your first stop in the quest for research paper examples will be the campus library where you can get to view the research sample papers of lecturers and other professionals in diverse fields plus those of fellow students who preceded you in the campus. Many college departments maintain libraries of previous student work, including large research papers, which current students can examine.

Embark on a journey of academic excellence with iResearchNet, your premier destination for research paper examples that illuminate the path to scholarly success. In the realm of academia, where the pursuit of knowledge is both a challenge and a privilege, the significance of having access to high-quality research paper examples cannot be overstated. These exemplars are not merely papers; they are beacons of insight, guiding students and scholars through the complex maze of academic writing and research methodologies.

At iResearchNet, we understand that the foundation of academic achievement lies in the quality of resources at one’s disposal. This is why we are dedicated to offering a comprehensive collection of research paper examples across a multitude of disciplines. Each example stands as a testament to rigorous research, clear writing, and the deep understanding necessary to advance in one’s academic and professional journey.

Access to superior research paper examples equips learners with the tools to develop their own ideas, arguments, and hypotheses, fostering a cycle of learning and discovery that transcends traditional boundaries. It is with this vision that iResearchNet commits to empowering students and researchers, providing them with the resources to not only meet but exceed the highest standards of academic excellence. Join us on this journey, and let iResearchNet be your guide to unlocking the full potential of your academic endeavors.

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Importance of Research Paper Examples

Research Paper Writing Services

A Sample Research Paper on Child Abuse

A research paper represents the pinnacle of academic investigation, a scholarly manuscript that encapsulates a detailed study, analysis, or argument based on extensive independent research. It is an embodiment of the researcher’s ability to synthesize a wealth of information, draw insightful conclusions, and contribute novel perspectives to the existing body of knowledge within a specific field. At its core, a research paper strives to push the boundaries of what is known, challenging existing theories and proposing new insights that could potentially reshape the understanding of a particular subject area.

The objective of writing a research paper is manifold, serving both educational and intellectual pursuits. Primarily, it aims to educate the author, providing a rigorous framework through which they engage deeply with a topic, hone their research and analytical skills, and learn the art of academic writing. Beyond personal growth, the research paper serves the broader academic community by contributing to the collective pool of knowledge, offering fresh perspectives, and stimulating further research. It is a medium through which scholars communicate ideas, findings, and theories, thereby fostering an ongoing dialogue that propels the advancement of science, humanities, and other fields of study.

Research papers can be categorized into various types, each with distinct objectives and methodologies. The most common types include:

Analytical Research Paper: This type focuses on analyzing different viewpoints represented in the scholarly literature or data. The author critically evaluates and interprets the information, aiming to provide a comprehensive understanding of the topic.
Argumentative or Persuasive Research Paper: Here, the author adopts a stance on a contentious issue and argues in favor of their position. The objective is to persuade the reader through evidence and logic that the author’s viewpoint is valid or preferable.
Experimental Research Paper: Often used in the sciences, this type documents the process, results, and implications of an experiment conducted by the author. It provides a detailed account of the methodology, data collected, analysis performed, and conclusions drawn.
Survey Research Paper: This involves collecting data from a set of respondents about their opinions, behaviors, or characteristics. The paper analyzes this data to draw conclusions about the population from which the sample was drawn.
Comparative Research Paper: This type involves comparing and contrasting different theories, policies, or phenomena. The aim is to highlight similarities and differences, thereby gaining a deeper understanding of the subjects under review.
Cause and Effect Research Paper: It explores the reasons behind specific actions, events, or conditions and the consequences that follow. The goal is to establish a causal relationship between variables.
Review Research Paper: This paper synthesizes existing research on a particular topic, offering a comprehensive analysis of the literature to identify trends, gaps, and consensus in the field.

Understanding the nuances and objectives of these various types of research papers is crucial for scholars and students alike, as it guides their approach to conducting and writing up their research. Each type demands a unique set of skills and perspectives, pushing the author to think critically and creatively about their subject matter. As the academic landscape continues to evolve, the research paper remains a fundamental tool for disseminating knowledge, encouraging innovation, and fostering a culture of inquiry and exploration.

Browse Sample Research Papers

iResearchNet prides itself on offering a wide array of research paper examples across various disciplines, meticulously curated to support students, educators, and researchers in their academic endeavors. Each example embodies the hallmarks of scholarly excellence—rigorous research, analytical depth, and clear, precise writing. Below, we explore the diverse range of research paper examples available through iResearchNet, designed to inspire and guide users in their quest for academic achievement.

Anthropology Research Paper Examples

Our anthropology research paper examples delve into the study of humanity, exploring cultural, social, biological, and linguistic variations among human populations. These papers offer insights into human behavior, traditions, and evolution, providing a comprehensive overview of anthropological research methods and theories.

Archaeology Research Paper
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Art Research Paper Examples

The art research paper examples feature analyses of artistic expressions across different cultures and historical periods. These papers cover a variety of topics, including art history, criticism, and theory, as well as the examination of specific artworks or movements.

Performing Arts Research Paper
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Cancer Research Paper Examples

Our cancer research paper examples focus on the latest findings in the field of oncology, discussing the biological mechanisms of cancer, advancements in diagnostic techniques, and innovative treatment strategies. These papers aim to contribute to the ongoing battle against cancer by sharing cutting-edge research.

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Communication Research Paper Examples

These examples explore the complexities of human communication, covering topics such as media studies, interpersonal communication, and public relations. The papers examine how communication processes affect individuals, societies, and cultures.

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Crime Research Paper Examples

The crime research paper examples provided by iResearchNet investigate various aspects of criminal behavior and the factors contributing to crime. These papers cover a range of topics, from theoretical analyses of criminality to empirical studies on crime prevention strategies.

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Criminal Justice Research Paper Examples

Our criminal justice research paper examples delve into the functioning of the criminal justice system, exploring issues related to law enforcement, the judiciary, and corrections. These papers critically examine policies, practices, and reforms within the criminal justice system.

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Criminal Law Research Paper Examples

These examples focus on the legal aspects of criminal behavior, discussing laws, regulations, and case law that govern criminal proceedings. The papers provide an in-depth analysis of criminal law principles, legal defenses, and the implications of legal decisions.

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Criminology Research Paper Examples

iResearchNet’s criminology research paper examples study the causes, prevention, and societal impacts of crime. These papers employ various theoretical frameworks to analyze crime trends and propose effective crime reduction strategies.

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Culture Research Paper Examples

The culture research paper examples examine the beliefs, practices, and artifacts that define different societies. These papers explore how culture shapes identities, influences behaviors, and impacts social interactions.

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Economics Research Paper Examples

Our economics research paper examples offer insights into the functioning of economies at both the micro and macro levels. Topics include economic theory, policy analysis, and the examination of economic indicators and trends.

Budget Research Paper
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Education Research Paper Examples

These examples address a wide range of issues in education, from teaching methods and curriculum design to educational policy and reform. The papers aim to enhance understanding and improve outcomes in educational settings.

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Health Research Paper Examples

The health research paper examples focus on public health issues, healthcare systems, and medical interventions. These papers contribute to the discourse on health promotion, disease prevention, and healthcare management.

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History Research Paper Examples

Our history research paper examples cover significant events, figures, and periods, offering critical analyses of historical narratives and their impact on present-day society.

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Each category of research paper examples provided by iResearchNet serves as a valuable resource for students and researchers seeking to deepen their understanding of a specific field. By offering a comprehensive collection of well-researched and thoughtfully written papers, iResearchNet aims to support academic growth and encourage scholarly inquiry across diverse disciplines.

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A research paper is an academic piece of writing, so you need to follow all the requirements and standards. Otherwise, it will be impossible to get the high results. To make it easier for you, we have analyzed the structure and peculiarities of a sample research paper on the topic ‘Child Abuse’.

The paper includes 7300+ words, a detailed outline, citations are in APA formatting style, and bibliography with 28 sources.

To write any paper you need to write a great outline. This is the key to a perfect paper. When you organize your paper, it is easier for you to present the ideas logically, without jumping from one thought to another.

In the outline, you need to name all the parts of your paper. That is to say, an introduction, main body, conclusion, bibliography, some papers require abstract and proposal as well.

A good outline will serve as a guide through your paper making it easier for the reader to follow your ideas.

I. Introduction

Ii. estimates of child abuse: methodological limitations, iii. child abuse and neglect: the legalities, iv. corporal punishment versus child abuse, v. child abuse victims: the patterns, vi. child abuse perpetrators: the patterns, vii. explanations for child abuse, viii. consequences of child abuse and neglect, ix. determining abuse: how to tell whether a child is abused or neglected, x. determining abuse: interviewing children, xi. how can society help abused children and abusive families, introduction.

An introduction should include a thesis statement and the main points that you will discuss in the paper.

A thesis statement is one sentence in which you need to show your point of view. You will then develop this point of view through the whole piece of work:

‘The impact of child abuse affects more than one’s childhood, as the psychological and physical injuries often extend well into adulthood.’

Child abuse is a very real and prominent social problem today. The impact of child abuse affects more than one’s childhood, as the psychological and physical injuries often extend well into adulthood. Most children are defenseless against abuse, are dependent on their caretakers, and are unable to protect themselves from these acts.

Childhood serves as the basis for growth, development, and socialization. Throughout adolescence, children are taught how to become productive and positive, functioning members of society. Much of the socializing of children, particularly in their very earliest years, comes at the hands of family members. Unfortunately, the messages conveyed to and the actions against children by their families are not always the positive building blocks for which one would hope.

In 2008, the Children’s Defense Fund reported that each day in America, 2,421 children are confirmed as abused or neglected, 4 children are killed by abuse or neglect, and 78 babies die before their first birthday. These daily estimates translate into tremendous national figures. In 2006, caseworkers substantiated an estimated 905,000 reports of child abuse or neglect. Of these, 64% suffered neglect, 16% were physically abused, 9% were sexually abused, 7% were emotionally or psychologically maltreated, and 2% were medically neglected. In addition, 15% of the victims experienced “other” types of maltreatment such as abandonment, threats of harm to the child, and congenital drug addiction (National Child Abuse and Neglect Data System, 2006). Obviously, this problem is a substantial one.

In the main body, you dwell upon the topic of your paper. You provide your ideas and support them with evidence. The evidence include all the data and material you have found, analyzed and systematized. You can support your point of view with different statistical data, with surveys, and the results of different experiments. Your task is to show that your idea is right, and make the reader interested in the topic.

In this example, a writer analyzes the issue of child abuse: different statistical data, controversies regarding the topic, examples of the problem and the consequences.

Several issues arise when considering the amount of child abuse that occurs annually in the United States. Child abuse is very hard to estimate because much (or most) of it is not reported. Children who are abused are unlikely to report their victimization because they may not know any better, they still love their abusers and do not want to see them taken away (or do not themselves want to be taken away from their abusers), they have been threatened into not reporting, or they do not know to whom they should report their victimizations. Still further, children may report their abuse only to find the person to whom they report does not believe them or take any action on their behalf. Continuing to muddy the waters, child abuse can be disguised as legitimate injury, particularly because young children are often somewhat uncoordinated and are still learning to accomplish physical tasks, may not know their physical limitations, and are often legitimately injured during regular play. In the end, children rarely report child abuse; most often it is an adult who makes a report based on suspicion (e.g., teacher, counselor, doctor, etc.).

Even when child abuse is reported, social service agents and investigators may not follow up or substantiate reports for a variety of reasons. Parents can pretend, lie, or cover up injuries or stories of how injuries occurred when social service agents come to investigate. Further, there is not always agreement about what should be counted as abuse by service providers and researchers. In addition, social service agencies/agents have huge caseloads and may only be able to deal with the most serious forms of child abuse, leaving the more “minor” forms of abuse unsupervised and unmanaged (and uncounted in the statistical totals).

While most laws about child abuse and neglect fall at the state levels, federal legislation provides a foundation for states by identifying a minimum set of acts and behaviors that define child abuse and neglect. The Federal Child Abuse Prevention and Treatment Act (CAPTA), which stems from the Keeping Children and Families Safe Act of 2003, defines child abuse and neglect as, at minimum, “(1) any recent act or failure to act on the part of a parent or caretaker which results in death, serious physical or emotional harm, sexual abuse, or exploitation; or (2) an act or failure to act which presents an imminent risk or serious harm.”

Using these minimum standards, each state is responsible for providing its own definition of maltreatment within civil and criminal statutes. When defining types of child abuse, many states incorporate similar elements and definitions into their legal statutes. For example, neglect is often defined as failure to provide for a child’s basic needs. Neglect can encompass physical elements (e.g., failure to provide necessary food or shelter, or lack of appropriate supervision), medical elements (e.g., failure to provide necessary medical or mental health treatment), educational elements (e.g., failure to educate a child or attend to special educational needs), and emotional elements (e.g., inattention to a child’s emotional needs, failure to provide psychological care, or permitting the child to use alcohol or other drugs). Failure to meet needs does not always mean a child is neglected, as situations such as poverty, cultural values, and community standards can influence the application of legal statutes. In addition, several states distinguish between failure to provide based on financial inability and failure to provide for no apparent financial reason.

Statutes on physical abuse typically include elements of physical injury (ranging from minor bruises to severe fractures or death) as a result of punching, beating, kicking, biting, shaking, throwing, stabbing, choking, hitting (with a hand, stick, strap, or other object), burning, or otherwise harming a child. Such injury is considered abuse regardless of the intention of the caretaker. In addition, many state statutes include allowing or encouraging another person to physically harm a child (such as noted above) as another form of physical abuse in and of itself. Sexual abuse usually includes activities by a parent or caretaker such as fondling a child’s genitals, penetration, incest, rape, sodomy, indecent exposure, and exploitation through prostitution or the production of pornographic materials.

Finally, emotional or psychological abuse typically is defined as a pattern of behavior that impairs a child’s emotional development or sense of self-worth. This may include constant criticism, threats, or rejection, as well as withholding love, support, or guidance. Emotional abuse is often the most difficult to prove and, therefore, child protective services may not be able to intervene without evidence of harm to the child. Some states suggest that harm may be evidenced by an observable or substantial change in behavior, emotional response, or cognition, or by anxiety, depression, withdrawal, or aggressive behavior. At a practical level, emotional abuse is almost always present when other types of abuse are identified.

Some states include an element of substance abuse in their statutes on child abuse. Circumstances that can be considered substance abuse include (a) the manufacture of a controlled substance in the presence of a child or on the premises occupied by a child (Colorado, Indiana, Iowa, Montana, South Dakota, Tennessee, and Virginia); (b) allowing a child to be present where the chemicals or equipment for the manufacture of controlled substances are used (Arizona, New Mexico); (c) selling, distributing, or giving drugs or alcohol to a child (Florida, Hawaii, Illinois, Minnesota, and Texas); (d) use of a controlled substance by a caregiver that impairs the caregiver’s ability to adequately care for the child (Kentucky, New York, Rhode Island, and Texas); and (e) exposure of the child to drug paraphernalia (North Dakota), the criminal sale or distribution of drugs (Montana, Virginia), or drug-related activity (District of Columbia).

One of the most difficult issues with which the U.S. legal system must contend is that of allowing parents the right to use corporal punishment when disciplining a child, while not letting them cross over the line into the realm of child abuse. Some parents may abuse their children under the guise of discipline, and many instances of child abuse arise from angry parents who go too far when disciplining their children with physical punishment. Generally, state statutes use terms such as “reasonable discipline of a minor,” “causes only temporary, short-term pain,” and may cause “the potential for bruising” but not “permanent damage, disability, disfigurement or injury” to the child as ways of indicating the types of discipline behaviors that are legal. However, corporal punishment that is “excessive,” “malicious,” “endangers the bodily safety of,” or is “an intentional infliction of injury” is not allowed under most state statutes (e.g., state of Florida child abuse statute).

Most research finds that the use of physical punishment (most often spanking) is not an effective method of discipline. The literature on this issue tends to find that spanking stops misbehavior, but no more effectively than other firm measures. Further, it seems to hinder rather than improve general compliance/obedience (particularly when the child is not in the presence of the punisher). Researchers have also explained why physical punishment is not any more effective at gaining child compliance than nonviolent forms of discipline. Some of the problems that arise when parents use spanking or other forms of physical punishment include the fact that spanking does not teach what children should do, nor does it provide them with alternative behavior options should the circumstance arise again. Spanking also undermines reasoning, explanation, or other forms of parental instruction because children cannot learn, reason, or problem solve well while experiencing threat, pain, fear, or anger. Further, the use of physical punishment is inconsistent with nonviolent principles, or parental modeling. In addition, the use of spanking chips away at the bonds of affection between parents and children, and tends to induce resentment and fear. Finally, it hinders the development of empathy and compassion in children, and they do not learn to take responsibility for their own behavior (Pitzer, 1997).

One of the biggest problems with the use of corporal punishment is that it can escalate into much more severe forms of violence. Usually, parents spank because they are angry (and somewhat out of control) and they can’t think of other ways to discipline. When parents are acting as a result of emotional triggers, the notion of discipline is lost while punishment and pain become the foci.

In 2006, of the children who were found to be victims of child abuse, nearly 75% of them were first-time victims (or had not come to the attention of authorities prior). A slight majority of child abuse victims were girls—51.5%, compared to 48% of abuse victims being boys. The younger the child, the more at risk he or she is for child abuse and neglect victimization. Specifically, the rate for infants (birth to 1 year old) was approximately 24 per 1,000 children of the same age group. The victimization rate for children 1–3 years old was 14 per 1,000 children of the same age group. The abuse rate for children aged 4– 7 years old declined further to 13 per 1,000 children of the same age group. African American, American Indian, and Alaska Native children, as well as children of multiple races, had the highest rates of victimization. White and Latino children had lower rates, and Asian children had the lowest rates of child abuse and neglect victimization. Regarding living arrangements, nearly 27% of victims were living with a single mother, 20% were living with married parents, while 22% were living with both parents but the marital status was unknown. (This reporting element had nearly 40% missing data, however.) Regarding disability, nearly 8% of child abuse victims had some degree of mental retardation, emotional disturbance, visual or hearing impairment, learning disability, physical disability, behavioral problems, or other medical problems. Unfortunately, data indicate that for many victims, the efforts of the child protection services system were not successful in preventing subsequent victimization. Children who had been prior victims of maltreatment were 96% more likely to experience another occurrence than those who were not prior victims. Further, child victims who were reported to have a disability were 52% more likely to experience recurrence than children without a disability. Finally, the oldest victims (16–21 years of age) were the least likely to experience a recurrence, and were 51% less likely to be victimized again than were infants (younger than age 1) (National Child Abuse and Neglect Data System, 2006).

Child fatalities are the most tragic consequence of maltreatment. Yet, each year, children die from abuse and neglect. In 2006, an estimated 1,530 children in the United States died due to abuse or neglect. The overall rate of child fatalities was 2 deaths per 100,000 children. More than 40% of child fatalities were attributed to neglect, but physical abuse also was a major contributor. Approximately 78% of the children who died due to child abuse and neglect were younger than 4 years old, and infant boys (younger than 1) had the highest rate of fatalities at 18.5 deaths per 100,000 boys of the same age in the national population. Infant girls had a rate of 14.7 deaths per 100,000 girls of the same age (National Child Abuse and Neglect Data System, 2006).

One question to be addressed regarding child fatalities is why infants have such a high rate of death when compared to toddlers and adolescents. Children under 1 year old pose an immense amount of responsibility for their caretakers: they are completely dependent and need constant attention. Children this age are needy, impulsive, and not amenable to verbal control or effective communication. This can easily overwhelm vulnerable parents. Another difficulty associated with infants is that they are physically weak and small. Injuries to infants can be fatal, while similar injuries to older children might not be. The most common cause of death in children less than 1 year is cerebral trauma (often the result of shaken-baby syndrome). Exasperated parents can deliver shakes or blows without realizing how little it takes to cause irreparable or fatal damage to an infant. Research informs us that two of the most common triggers for fatal child abuse are crying that will not cease and toileting accidents. Both of these circumstances are common in infants and toddlers whose only means of communication often is crying, and who are limited in mobility and cannot use the toilet. Finally, very young children cannot assist in injury diagnoses. Children who have been injured due to abuse or neglect often cannot communicate to medical professionals about where it hurts, how it hurts, and so forth. Also, nonfatal injuries can turn fatal in the absence of care by neglectful parents or parents who do not want medical professionals to possibly identify an injury as being the result of abuse.

Estimates reveal that nearly 80% of perpetrators of child abuse were parents of the victim. Other relatives accounted for nearly 7%, and unmarried partners of parents made up 4% of perpetrators. Of those perpetrators that were parents, over 90% were biological parents, 4% were stepparents, and 0.7% were adoptive parents. Of this group, approximately 58% of perpetrators were women and 42% were men. Women perpetrators are typically younger than men. The average age for women abusers was 31 years old, while for men the average was 34 years old. Forty percent of women who abused were younger than 30 years of age, compared with 33% of men being under 30. The racial distribution of perpetrators is similar to that of victims. Fifty-four percent were white, 21% were African American, and 20% were Hispanic/Latino (National Child Abuse and Neglect Data System, 2006).

There are many factors that are associated with child abuse. Some of the more common/well-accepted explanations are individual pathology, parent–child interaction, past abuse in the family (or social learning), situational factors, and cultural support for physical punishment along with a lack of cultural support for helping parents here in the United States.

The first explanation centers on the individual pathology of a parent or caretaker who is abusive. This theory focuses on the idea that people who abuse their children have something wrong with their individual personality or biological makeup. Such psychological pathologies may include having anger control problems; being depressed or having post-partum depression; having a low tolerance for frustration (e.g., children can be extremely frustrating: they don’t always listen; they constantly push the line of how far they can go; and once the line has been established, they are constantly treading on it to make sure it hasn’t moved. They are dependent and self-centered, so caretakers have very little privacy or time to themselves); being rigid (e.g., having no tolerance for differences—for example, what if your son wanted to play with dolls? A rigid father would not let him, laugh at him for wanting to, punish him when he does, etc.); having deficits in empathy (parents who cannot put themselves in the shoes of their children cannot fully understand what their children need emotionally); or being disorganized, inefficient, and ineffectual. (Parents who are unable to manage their own lives are unlikely to be successful at managing the lives of their children, and since many children want and need limits, these parents are unable to set them or adhere to them.)

Biological pathologies that may increase the likelihood of someone becoming a child abuser include having substance abuse or dependence problems, or having persistent or reoccurring physical health problems (especially health problems that can be extremely painful and can cause a person to become more self-absorbed, both qualities that can give rise to a lack of patience, lower frustration tolerance, and increased stress).

The second explanation for child abuse centers on the interaction between the parent and the child, noting that certain types of parents are more likely to abuse, and certain types of children are more likely to be abused, and when these less-skilled parents are coupled with these more difficult children, child abuse is the most likely to occur. Discussion here focuses on what makes a parent less skilled, and what makes a child more difficult. Characteristics of unskilled parents are likely to include such traits as only pointing out what children do wrong and never giving any encouragement for good behavior, and failing to be sensitive to the emotional needs of children. Less skilled parents tend to have unrealistic expectations of children. They may engage in role reversal— where the parents make the child take care of them—and view the parent’s happiness and well-being as the responsibility of the child. Some parents view the parental role as extremely stressful and experience little enjoyment from being a parent. Finally, less-skilled parents tend to have more negative perceptions regarding their child(ren). For example, perhaps the child has a different shade of skin than they expected and this may disappoint or anger them, they may feel the child is being manipulative (long before children have this capability), or they may view the child as the scapegoat for all the parents’ or family’s problems. Theoretically, parents with these characteristics would be more likely to abuse their children, but if they are coupled with having a difficult child, they would be especially likely to be abusive. So, what makes a child more difficult? Certainly, through no fault of their own, children may have characteristics that are associated with child care that is more demanding and difficult than in the “normal” or “average” situation. Such characteristics can include having physical and mental disabilities (autism, attention deficit hyperactivity disorder [ADHD], hyperactivity, etc.); the child may be colicky, frequently sick, be particularly needy, or cry more often. In addition, some babies are simply unhappier than other babies for reasons that cannot be known. Further, infants are difficult even in the best of circumstances. They are unable to communicate effectively, and they are completely dependent on their caretakers for everything, including eating, diaper changing, moving around, entertainment, and emotional bonding. Again, these types of children, being more difficult, are more likely to be victims of child abuse.

Nonetheless, each of these types of parents and children alone cannot explain the abuse of children, but it is the interaction between them that becomes the key. Unskilled parents may produce children that are happy and not as needy, and even though they are unskilled, they do not abuse because the child takes less effort. At the same time, children who are more difficult may have parents who are skilled and are able to handle and manage the extra effort these children take with aplomb. However, risks for child abuse increase when unskilled parents must contend with difficult children.

Social learning or past abuse in the family is a third common explanation for child abuse. Here, the theory concentrates not only on what children learn when they see or experience violence in their homes, but additionally on what they do not learn as a result of these experiences. Social learning theory in the context of family violence stresses that if children are abused or see abuse (toward siblings or a parent), those interactions and violent family members become the representations and role models for their future familial interactions. In this way, what children learn is just as important as what they do not learn. Children who witness or experience violence may learn that this is the way parents deal with children, or that violence is an acceptable method of child rearing and discipline. They may think when they become parents that “violence worked on me when I was a child, and I turned out fine.” They may learn unhealthy relationship interaction patterns; children may witness the negative interactions of parents and they may learn the maladaptive or violent methods of expressing anger, reacting to stress, or coping with conflict.

What is equally as important, though, is that they are unlikely to learn more acceptable and nonviolent ways of rearing children, interacting with family members, and working out conflict. Here it may happen that an adult who was abused as a child would like to be nonviolent toward his or her own children, but when the chips are down and the child is misbehaving, this abused-child-turned-adult does not have a repertoire of nonviolent strategies to try. This parent is more likely to fall back on what he or she knows as methods of discipline.

Something important to note here is that not all abused children grow up to become abusive adults. Children who break the cycle were often able to establish and maintain one healthy emotional relationship with someone during their childhoods (or period of young adulthood). For instance, they may have received emotional support from a nonabusing parent, or they received social support and had a positive relationship with another adult during their childhood (e.g., teacher, coach, minister, neighbor, etc.). Abused children who participate in therapy during some period of their lives can often break the cycle of violence. In addition, adults who were abused but are able to form an emotionally supportive and satisfying relationship with a mate can make the transition to being nonviolent in their family interactions.

Moving on to a fourth familiar explanation for child abuse, there are some common situational factors that influence families and parents and increase the risks for child abuse. Typically, these are factors that increase family stress or social isolation. Specifically, such factors may include receiving public assistance or having low socioeconomic status (a combination of low income and low education). Other factors include having family members who are unemployed, underemployed (working in a job that requires lower qualifications than an individual possesses), or employed only part time. These financial difficulties cause great stress for families in meeting the needs of the individual members. Other stress-inducing familial characteristics are single-parent households and larger family size. Finally, social isolation can be devastating for families and family members. Having friends to talk to, who can be relied upon, and with whom kids can be dropped off occasionally is tremendously important for personal growth and satisfaction in life. In addition, social isolation and stress can cause individuals to be quick to lose their tempers, as well as cause people to be less rational in their decision making and to make mountains out of mole hills. These situations can lead families to be at greater risk for child abuse.

Finally, cultural views and supports (or lack thereof) can lead to greater amounts of child abuse in a society such as the United States. One such cultural view is that of societal support for physical punishment. This is problematic because there are similarities between the way criminals are dealt with and the way errant children are handled. The use of capital punishment is advocated for seriously violent criminals, and people are quick to use such idioms as “spare the rod and spoil the child” when it comes to the discipline or punishment of children. In fact, it was not until quite recently that parenting books began to encourage parents to use other strategies than spanking or other forms of corporal punishment in the discipline of their children. Only recently, the American Academy of Pediatrics has come out and recommended that parents do not spank or use other forms of violence on their children because of the deleterious effects such methods have on youngsters and their bonds with their parents. Nevertheless, regardless of recommendations, the culture of corporal punishment persists.

Another cultural view in the United States that can give rise to greater incidents of child abuse is the belief that after getting married, couples of course should want and have children. Culturally, Americans consider that children are a blessing, raising kids is the most wonderful thing a person can do, and everyone should have children. Along with this notion is the idea that motherhood is always wonderful; it is the most fulfilling thing a woman can do; and the bond between a mother and her child is strong, glorious, and automatic—all women love being mothers. Thus, culturally (and theoretically), society nearly insists that married couples have children and that they will love having children. But, after children are born, there is not much support for couples who have trouble adjusting to parenthood, or who do not absolutely love their new roles as parents. People look askance at parents who need help, and cannot believe parents who say anything negative about parenthood. As such, theoretically, society has set up a situation where couples are strongly encouraged to have kids, are told they will love kids, but then society turns a blind or disdainful eye when these same parents need emotional, financial, or other forms of help or support. It is these types of cultural viewpoints that increase the risks for child abuse in society.

The consequences of child abuse are tremendous and long lasting. Research has shown that the traumatic experience of childhood abuse is life changing. These costs may surface during adolescence, or they may not become evident until abused children have grown up and become abusing parents or abused spouses. Early identification and treatment is important to minimize these potential long-term effects. Whenever children say they have been abused, it is imperative that they be taken seriously and their abuse be reported. Suspicions of child abuse must be reported as well. If there is a possibility that a child is or has been abused, an investigation must be conducted.

Children who have been abused may exhibit traits such as the inability to love or have faith in others. This often translates into adults who are unable to establish lasting and stable personal relationships. These individuals have trouble with physical closeness and touching as well as emotional intimacy and trust. Further, these qualities tend to cause a fear of entering into new relationships, as well as the sabotaging of any current ones.

Psychologically, children who have been abused tend to have poor self-images or are passive, withdrawn, or clingy. They may be angry individuals who are filled with rage, anxiety, and a variety of fears. They are often aggressive, disruptive, and depressed. Many abused children have flashbacks and nightmares about the abuse they have experienced, and this may cause sleep problems as well as drug and alcohol problems. Posttraumatic stress disorder (PTSD) and antisocial personality disorder are both typical among maltreated children. Research has also shown that most abused children fail to reach “successful psychosocial functioning,” and are thus not resilient and do not resume a “normal life” after the abuse has ended.

Socially (and likely because of these psychological injuries), abused children have trouble in school, will have difficulty getting and remaining employed, and may commit a variety of illegal or socially inappropriate behaviors. Many studies have shown that victims of child abuse are likely to participate in high-risk behaviors such as alcohol or drug abuse, the use of tobacco, and high-risk sexual behaviors (e.g., unprotected sex, large numbers of sexual partners). Later in life, abused children are more likely to have been arrested and homeless. They are also less able to defend themselves in conflict situations and guard themselves against repeated victimizations.

Medically, abused children likely will experience health problems due to the high frequency of physical injuries they receive. In addition, abused children experience a great deal of emotional turmoil and stress, which can also have a significant impact on their physical condition. These health problems are likely to continue occurring into adulthood. Some of these longer-lasting health problems include headaches; eating problems; problems with toileting; and chronic pain in the back, stomach, chest, and genital areas. Some researchers have noted that abused children may experience neurological impairment and problems with intellectual functioning, while others have found a correlation between abuse and heart, lung, and liver disease, as well as cancer (Thomas, 2004).

Victims of sexual abuse show an alarming number of disturbances as adults. Some dislike and avoid sex, or experience sexual problems or disorders, while other victims appear to enjoy sexual activities that are self-defeating or maladaptive—normally called “dysfunctional sexual behavior”—and have many sexual partners.

Abused children also experience a wide variety of developmental delays. Many do not reach physical, cognitive, or emotional developmental milestones at the typical time, and some never accomplish what they are supposed to during childhood socialization. In the next section, these developmental delays are discussed as a means of identifying children who may be abused.

There are two primary ways of identifying children who are abused: spotting and evaluating physical injuries, and detecting and appraising developmental delays. Distinguishing physical injuries due to abuse can be difficult, particularly among younger children who are likely to get hurt or receive injuries while they are playing and learning to become ambulatory. Nonetheless, there are several types of wounds that children are unlikely to give themselves during their normal course of play and exploration. These less likely injuries may signal instances of child abuse.

While it is true that children are likely to get bruises, particularly when they are learning to walk or crawl, bruises on infants are not normal. Also, the back of the legs, upper arms, or on the chest, neck, head, or genitals are also locations where bruises are unlikely to occur during normal childhood activity. Further, bruises with clean patterns, like hand prints, buckle prints, or hangers (to name a few), are good examples of the types of bruises children do not give themselves.

Another area of physical injury where the source of the injury can be difficult to detect is fractures. Again, children fall out of trees, or crash their bikes, and can break limbs. These can be normal parts of growing up. However, fractures in infants less than 12 months old are particularly suspect, as infants are unlikely to be able to accomplish the types of movement necessary to actually break a leg or an arm. Further, multiple fractures, particularly more than one on a bone, should be examined more closely. Spiral or torsion fractures (when the bone is broken by twisting) are suspect because when children break their bones due to play injuries, the fractures are usually some other type (e.g., linear, oblique, compacted). In addition, when parents don’t know about the fracture(s) or how it occurred, abuse should be considered, because when children get these types of injuries, they need comfort and attention.

Head and internal injuries are also those that may signal abuse. Serious blows to the head cause internal head injuries, and this is very different from the injuries that result from bumping into things. Abused children are also likely to experience internal injuries like those to the abdomen, liver, kidney, and bladder. They may suffer a ruptured spleen, or intestinal perforation. These types of damages rarely happen by accident.

Burns are another type of physical injury that can happen by accident or by abuse. Nevertheless, there are ways to tell these types of burn injuries apart. The types of burns that should be examined and investigated are those where the burns are in particular locations. Burns to the bottom of the feet, genitals, abdomen, or other inaccessible spots should be closely considered. Burns of the whole hand or those to the buttocks are also unlikely to happen as a result of an accident.

Turning to the detection and appraisal of developmental delays, one can more readily assess possible abuse by considering what children of various ages should be able to accomplish, than by noting when children are delayed and how many milestones on which they are behind schedule. Importantly, a few delays in reaching milestones can be expected, since children develop individually and not always according to the norm. Nonetheless, when children are abused, their development is likely to be delayed in numerous areas and across many milestones.

As children develop and grow, they should be able to crawl, walk, run, talk, control going to the bathroom, write, set priorities, plan ahead, trust others, make friends, develop a good self-image, differentiate between feeling and behavior, and get their needs met in appropriate ways. As such, when children do not accomplish these feats, their circumstances should be examined.

Infants who are abused or neglected typically develop what is termed failure to thrive syndrome. This syndrome is characterized by slow, inadequate growth, or not “filling out” physically. They have a pale, colorless complexion and dull eyes. They are not likely to spend much time looking around, and nothing catches their eyes. They may show other signs of lack of nutrition such as cuts, bruises that do not heal in a timely way, and discolored fingernails. They are also not trusting and may not cry much, as they are not expecting to have their needs met. Older infants may not have developed any language skills, or these developments are quite slow. This includes both verbal and nonverbal means of communication.

Toddlers who are abused often become hypervigilant about their environments and others’ moods. They are more outwardly focused than a typical toddler (who is quite self-centered) and may be unable to separate themselves as individuals, or consider themselves as distinct beings. In this way, abused toddlers cannot focus on tasks at hand because they are too concerned about others’ reactions. They don’t play with toys, have no interest in exploration, and seem unable to enjoy life. They are likely to accept losses with little reaction, and may have age-inappropriate knowledge of sex and sexual relations. Finally, toddlers, whether they are abused or not, begin to mirror their parents’ behaviors. Thus, toddlers who are abused may mimic the abuse when they are playing with dolls or “playing house.”

Developmental delays can also be detected among abused young adolescents. Some signs include the failure to learn cause and effect, since their parents are so inconsistent. They have no energy for learning and have not developed beyond one- or two-word commands. They probably cannot follow complicated directions (such as two to three tasks per instruction), and they are unlikely to be able to think for themselves. Typically, they have learned that failure is totally unacceptable, but they are more concerned with the teacher’s mood than with learning and listening to instruction. Finally, they are apt to have been inadequately toilet trained and thus may be unable to control their bladders.

Older adolescents, because they are likely to have been abused for a longer period of time, continue to get further and further behind in their developmental achievements. Abused children this age become family nurturers. They take care of their parents and cater to their parents’ needs, rather than the other way around. In addition, they probably take care of any younger siblings and do the household chores. Because of these default responsibilities, they usually do not participate in school activities; they frequently miss days at school; and they have few, if any, friends. Because they have become so hypervigilant and have increasingly delayed development, they lose interest in and become disillusioned with education. They develop low self-esteem and little confidence, but seem old for their years. Children this age who are abused are still likely to be unable to control their bladders and may have frequent toileting accidents.

Other developmental delays can occur and be observed in abused and neglected children of any age. For example, malnutrition and withdrawal can be noticed in infants through teenagers. Maltreated children frequently have persistent or untreated illnesses, and these can become permanent disabilities if medical conditions go untreated for a long enough time. Another example can be the consequences of neurological damage. Beyond being a medical issue, this type of damage can cause problems with social behavior and impulse control, which, again, can be discerned in various ages of children.

Once child abuse is suspected, law enforcement officers, child protection workers, or various other practitioners may need to interview the child about the abuse or neglect he or she may have suffered. Interviewing children can be extremely difficult because children at various stages of development can remember only certain parts or aspects of the events in their lives. Also, interviewers must be careful that they do not put ideas or answers into the heads of the children they are interviewing. There are several general recommendations when interviewing children about the abuse they may have experienced. First, interviewers must acknowledge that even when children are abused, they likely still love their parents. They do not want to be taken away from their parents, nor do they want to see their parents get into trouble. Interviewers must not blame the parents or be judgmental about them or the child’s family. Beyond that, interviews should take place in a safe, neutral location. Interviewers can use dolls and role-play to help children express the types of abuse of which they may be victims.

Finally, interviewers must ask age-appropriate questions. For example, 3-year-olds can probably only answer questions about what happened and who was involved. Four- to five-year-olds can also discuss where the incidents occurred. Along with what, who, and where, 6- to 8-year-olds can talk about the element of time, or when the abuse occurred. Nine- to 10-year-olds are able to add commentary about the number of times the abuse occurred. Finally, 11-year-olds and older children can additionally inform interviewers about the circumstances of abusive instances.

A conclusion is not a summary of what a writer has already mentioned. On the contrary, it is the last point made. Taking every detail of the investigation, the researcher makes the concluding point. In this part of a paper, you need to put a full stop in your research. You need to persuade the reader in your opinion.

Never add any new information in the conclusion. You can present solutions to the problem and you dwell upon the results, but only if this information has been already mentioned in the main body.

Child advocates recommend a variety of strategies to aid families and children experiencing abuse. These recommendations tend to focus on societal efforts as well as more individual efforts. One common strategy advocated is the use of public service announcements that encourage individuals to report any suspected child abuse. Currently, many mandatory reporters (those required by law to report abuse such as teachers, doctors, and social service agency employees) and members of communities feel that child abuse should not be reported unless there is substantial evidence that abuse is indeed occurring. Child advocates stress that this notion should be changed, and that people should report child abuse even if it is only suspected. Public service announcements should stress that if people report suspected child abuse, the worst that can happen is that they might be wrong, but in the grander scheme of things that is really not so bad.

Child advocates also stress that greater interagency cooperation is needed. This cooperation should be evident between women’s shelters, child protection agencies, programs for at-risk children, medical agencies, and law enforcement officers. These agencies typically do not share information, and if they did, more instances of child abuse would come to the attention of various authorities and could be investigated and managed. Along these lines, child protection agencies and programs should receive more funding. When budgets are cut, social services are often the first things to go or to get less financial support. Child advocates insist that with more resources, child protection agencies could hire more workers, handle more cases, conduct more investigations, and follow up with more children and families.

Continuing, more educational efforts must be initiated about issues such as punishment and discipline styles and strategies; having greater respect for children; as well as informing the community about what child abuse is, and how to recognize it. In addition, Americans must alter the cultural orientation about child bearing and child rearing. Couples who wish to remain child-free must be allowed to do so without disdain. And, it must be acknowledged that raising children is very difficult, is not always gloriously wonderful, and that parents who seek help should be lauded and not criticized. These kinds of efforts can help more children to be raised in nonviolent, emotionally satisfying families, and thus become better adults.

Bibliography

When you write a paper, make sure you are aware of all the formatting requirements. Incorrect formatting can lower your mark, so do not underestimate the importance of this part.

Organizing your bibliography is quite a tedious and time-consuming task. Still, you need to do it flawlessly. For this reason, analyze all the standards you need to meet or ask professionals to help you with it. All the comas, colons, brackets etc. matter. They truly do.

Bibliography:

American Academy of Pediatrics: https://www.aap.org/
Bancroft, L., & Silverman, J. G. (2002). The batterer as parent. Thousand Oaks, CA: Sage.
Child Abuse Prevention and Treatment Act, 42 U.S.C.A. § 5106g (1998).
Childhelp: Child Abuse Statistics: https://www.childhelp.org/child-abuse-statistics/
Children’s Defense Fund: https://www.childrensdefense.org/
Child Stats.gov: https://www.childstats.gov/
Child Welfare League of America: https://www.cwla.org/
Crosson-Tower, C. (2008). Understanding child abuse and neglect (7th ed.). Boston: Allyn & Bacon.
DeBecker, G. (1999). Protecting the gift: Keeping children and teenagers safe (and parents sane). New York: Bantam Dell.
Family Research Laboratory at the University of New Hampshire: https://cola.unh.edu/family-research-laboratory
Guterman, N. B. (2001). Stopping child maltreatment before it starts: Emerging horizons in early home visitation services. Thousand Oaks, CA: Sage.
Herman, J. L. (2000). Father-daughter incest. Cambridge, MA: Harvard University Press.
Medline Plus, Child Abuse: https://medlineplus.gov/childabuse.html
Myers, J. E. B. (Ed.). (1994). The backlash: Child protection under fire. Newbury Park, CA: Sage.
National Center for Missing and Exploited Children: https://www.missingkids.org/home
National Child Abuse and Neglect Data System. (2006). Child maltreatment 2006: Reports from the states to the National Child Abuse and Neglect Data System. Washington, DC: U.S. Department of Health and Human Services, Administration for Children and Families.
New York University Silver School of Social Work: https://socialwork.nyu.edu/
Pitzer, R. L. (1997). Corporal punishment in the discipline of children in the home: Research update for practitioners. Paper presented at the National Council on Family Relations Annual Conference, Washington, DC.
RAND, Child Abuse and Neglect: https://www.rand.org/topics/child-abuse-and-neglect.html
Richards, C. E. (2001). The loss of innocents: Child killers and their victims. Wilmington, DE: Scholarly Resources.
Straus, M. A. (2001). Beating the devil out of them: Corporal punishment in American families and its effects on children. Edison, NJ: Transaction.
Thomas, P. M. (2004). Protection, dissociation, and internal roles: Modeling and treating the effects of child abuse. Review of General Psychology, 7(15).
U.S. Department of Health and Human Services, Administration for Children and Families: https://www.acf.hhs.gov/

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Methodology

Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question using empirical data. Creating a research design means making decisions about:

Your overall aims and approach
The type of research design you’ll use
Your sampling methods or criteria for selecting subjects
Your data collection methods
The procedures you’ll follow to collect data
Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

How much time do you have to collect data and write up the research?
Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Prevent plagiarism, run a free check.

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

How many participants do you need for an adequate sample size?
What inclusion and exclusion criteria will you use to identify eligible participants?
How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

The distribution of the data (e.g., the frequency of each score on a test)
The central tendency of the data (e.g., the mean to describe the average score)
The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

Make estimates about the population based on your sample data.
Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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Examples of Simple Experiments in Scientific Research

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Adah Chung is a fact checker, writer, researcher, and occupational therapist.

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A simple experiment is used by researchers to determine if changes in one variable lead to changes in another variable — in other words, to establish cause-and-effect.

For example, in a simple experiment looking at the effectiveness of a new medication, study participants would be randomly assigned to one of two groups: one of these would be the control group and receive no treatment, while the other group would be the experimental group that receives the treatment being studied.

The Elements of a Simple Experiment

A simple experiment is composed of several key elements:

The Experimental Hypothesis: This is a statement that predicts the treatment will cause an effect. It will always be phrased as a cause-and-effect statement. For example, researchers might phrase a hypothesis as: "Administration of Medicine A will result in a reduction of symptoms of Disease B."
The Null Hypothesis: This is a hypothesis stating the experimental treatment will have no effect on the participants or dependent variables. It's important to note that failing to find an effect of the treatment does not mean there is no effect. The treatment might impact another variable the researchers are not measuring in the current experiment.
The Independent Variable : The treatment variable being manipulated by the experimenter.
The Dependent Variable : The response the researchers are measuring.
The Control Group: The group of randomly assigned individuals who do not receive the treatment. The measurements taken from the control group will be compared to those in the experimental group to determine if the treatment had an effect.
The Experimental Group: This group of randomly assigned individuals who will receive the treatment being tested.

Determining the Results of a Simple Experiment

Once the data from the simple experiment is gathered, researchers compare the results of the experimental group to those of the control group to determine if the treatment had an effect. Due to the omnipresent possibility of errors, it's not possible to be 100 percent sure of the relationship between two variables. There can always be be unknown variables influencing the outcome of the experiment.

Despite this challenge, there are ways to determine if there most likely is a meaningful relationship between the variables. To do this, scientists use inferential statistics—a branch of science that deals with drawing inferences about a population based on measurements taken from a representative sample of that population.

The key to determining if a treatment had an effect is to measure the statistical significance. Statistical significance shows that the relationship between the variables is probably not due to mere chance and that a real relationship most likely exists between the two variables.

Statistical significance is often represented like this:

p < 0.05

A p-value of less than .05 indicates that the results likely are due to chance and that the probability of obtaining these results would be less than 5%.

There are a number of different means of measuring statistical significance. The one used will depend on the type of research design that was used for the experiment.

Skelly AC. Probability, proof, and clinical significance . Evid Based Spine Care J . 2011;2(4):9-11. doi:10.1055/s-0031-1274751

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Home » Basic Research – Types, Methods and Examples

Basic Research – Types, Methods and Examples

Table of Contents

Basic Research

Definition:

Basic Research, also known as Fundamental or Pure Research , is scientific research that aims to increase knowledge and understanding about the natural world without necessarily having any practical or immediate applications. It is driven by curiosity and the desire to explore new frontiers of knowledge rather than by the need to solve a specific problem or to develop a new product.

Types of Basic Research

Types of Basic Research are as follows:

Experimental Research

This type of research involves manipulating one or more variables to observe their effect on a particular phenomenon. It aims to test hypotheses and establish cause-and-effect relationships.

Observational Research

This type of research involves observing and documenting natural phenomena without manipulating any variables. It aims to describe and understand the behavior of the observed system.

Theoretical Research

This type of research involves developing and testing theories and models to explain natural phenomena. It aims to provide a framework for understanding and predicting observations and experiments.

Descriptive Research

This type of research involves describing and cataloging natural phenomena without attempting to explain or understand them. It aims to provide a comprehensive and accurate picture of the observed system.

Comparative Research

This type of research involves comparing different systems or phenomena to identify similarities and differences. It aims to understand the underlying principles that govern different natural phenomena.

Historical Research

This type of research involves studying past events, developments, and discoveries to understand how science has evolved over time. It aims to provide insights into the factors that have influenced scientific progress and the role of basic research in shaping our understanding of the world.

Data Collection Methods

Some common data collection methods used in basic research include:

Observation : This involves watching and recording natural phenomena in a systematic and structured way. Observations can be made in a laboratory setting or in the field and can be qualitative or quantitative.
Surveys and questionnaires: These are tools for collecting data from a large number of individuals about their attitudes, beliefs, behaviors, and experiences. Surveys and questionnaires can be administered in person, by mail, or online.
Interviews : Interviews involve asking questions to a person or a group of people to gather information about their experiences, opinions, and perspectives. Interviews can be structured, semi-structured, or unstructured.
Experiments : Experiments involve manipulating one or more variables and observing their effect on a particular phenomenon. Experiments can be conducted in a laboratory or in the field and can be controlled or naturalistic.
Case studies : Case studies involve in-depth analysis of a particular individual, group, or phenomenon. Case studies can provide rich and detailed information about complex phenomena.
Archival research : Archival research involves analyzing existing data, documents, and records to answer research questions. Archival research can be used to study historical events, trends, and developments.
Simulation : Simulation involves creating a computer model of a particular phenomenon to study its behavior and predict its future outcomes. Simulation can be used to study complex systems that are difficult to study in the real world.

Data Analysis Methods

Some common data analysis methods used in basic research include:

Descriptive statistics: This involves summarizing and describing data using measures such as mean, median, mode, and standard deviation. Descriptive statistics provide a simple and easy way to understand the basic properties of the data.
Inferential statistics : This involves making inferences about a population based on data collected from a sample. Inferential statistics can be used to test hypotheses, estimate parameters, and quantify uncertainty.
Qualitative analysis : This involves analyzing data that are not numerical in nature, such as text, images, or audio recordings. Qualitative analysis can involve coding, categorizing, and interpreting data to identify themes, patterns, and relationships.
Content analysis: This involves analyzing the content of text, images, or audio recordings to identify specific words, phrases, or themes. Content analysis can be used to study communication, media, and discourse.
Multivariate analysis: This involves analyzing data that have multiple variables or factors. Multivariate analysis can be used to identify patterns and relationships among variables, cluster similar observations, and reduce the dimensionality of the data.
Network analysis: This involves analyzing the structure and dynamics of networks, such as social networks, communication networks, or ecological networks. Network analysis can be used to study the relationships and interactions among individuals, groups, or entities.
Machine learning : This involves using algorithms and models to analyze and make predictions based on data. Machine learning can be used to identify patterns, classify observations, and make predictions based on complex data sets.

Basic Research Methodology

Basic research methodology refers to the approach, techniques, and procedures used to conduct basic research. The following are some common steps involved in basic research methodology:

Formulating research questions or hypotheses : This involves identifying the research problem and formulating specific questions or hypotheses that can guide the research.
Reviewing the literature: This involves reviewing and synthesizing existing research on the topic of interest to identify gaps, controversies, and areas for further investigation.
Designing the study: This involves designing a study that is appropriate for the research question or hypothesis. The study design can involve experiments, observations, surveys, case studies, or other methods.
Collecting data: This involves collecting data using appropriate methods and instruments, such as observation, surveys, experiments, or interviews.
Analyzing data: This involves analyzing the collected data using appropriate methods, such as descriptive or inferential statistics, qualitative analysis, or content analysis.
Interpreting results : This involves interpreting the results of the data analysis in light of the research question or hypothesis and the existing literature.
Drawing conclusions: This involves drawing conclusions based on the interpretation of the results and assessing their implications for the research question or hypothesis.
Communicating findings : This involves communicating the research findings in the form of research reports, journal articles, conference presentations, or other forms of dissemination.

Applications of Basic Research

Some applications of basic research include:

Medical breakthroughs : Basic research in fields such as biology, chemistry, and physics has led to important medical breakthroughs, including the discovery of antibiotics, vaccines, and new drugs.
Technology advancements: Basic research in fields such as computer science, physics, and engineering has led to advancements in technology, such as the development of the internet, smartphones, and other electronic devices.
Environmental solutions: Basic research in fields such as ecology, geology, and meteorology has led to the development of solutions to environmental problems, such as climate change, air pollution, and water contamination.
Economic growth: Basic research can stimulate economic growth by creating new industries and markets based on scientific discoveries and technological advancements.
National security: Basic research in fields such as physics, chemistry, and biology has led to the development of new technologies for national security, including encryption, radar, and stealth technology.

Examples of Basic Research

Here are some examples of basic research:

Astronomy : Astronomers conduct basic research to understand the fundamental principles that govern the universe, such as the laws of gravity, the behavior of stars and galaxies, and the origins of the universe.
Genetics : Geneticists conduct basic research to understand the genetic basis of various traits, diseases, and disorders. This research can lead to the development of new treatments and therapies for genetic diseases.
Physics : Physicists conduct basic research to understand the fundamental principles of matter and energy, such as quantum mechanics, particle physics, and cosmology. This research can lead to new technologies and advancements in fields such as medicine and engineering.
Neuroscience: Neuroscientists conduct basic research to understand the structure and function of the brain, including how it processes information and controls behavior. This research can lead to new treatments and therapies for neurological disorders and brain injuries.
Mathematics : Mathematicians conduct basic research to develop and explore new mathematical theories, such as number theory, topology, and geometry. This research can lead to new applications in fields such as computer science, physics, and engineering.
Chemistry : Chemists conduct basic research to understand the fundamental properties of matter and how it interacts with other substances. This research can lead to the development of new materials, drugs, and technologies.

Purpose of Basic Research

The purpose of basic research, also known as fundamental or pure research, is to expand knowledge in a particular field or discipline without any specific practical application in mind. The primary goal of basic research is to advance our understanding of the natural world and to uncover fundamental principles and relationships that underlie complex phenomena.

Basic research is often exploratory in nature, with researchers seeking to answer fundamental questions about how the world works. The research may involve conducting experiments, collecting and analyzing data, or developing new theories and hypotheses. Basic research often requires a high degree of creativity, innovation, and intellectual curiosity, as well as a willingness to take risks and pursue unconventional lines of inquiry.

Although basic research is not conducted with a specific practical outcome in mind, it can lead to significant practical applications in various fields. Many of the major scientific discoveries and technological advancements of the past century have been rooted in basic research, from the discovery of antibiotics to the development of the internet.

In summary, the purpose of basic research is to expand knowledge and understanding in a particular field or discipline, with the goal of uncovering fundamental principles and relationships that can help us better understand the natural world. While the practical applications of basic research may not always be immediately apparent, it has led to significant scientific and technological advancements that have benefited society in numerous ways.

When to use Basic Research

Basic research is generally conducted when scientists and researchers are seeking to expand knowledge and understanding in a particular field or discipline. It is particularly useful when there are gaps in our understanding of fundamental principles and relationships that underlie complex phenomena. Here are some situations where basic research might be particularly useful:

Exploring new fields: Basic research can be particularly valuable when researchers are exploring new fields or areas of inquiry where little is known. By conducting basic research, scientists can establish a foundation of knowledge that can be built upon in future studies.
Testing new theories: Basic research can be useful when researchers are testing new theories or hypotheses that have not been tested before. This can help scientists to gain a better understanding of how the world works and to identify areas where further research is needed.
Developing new technologies : Basic research can be important for developing new technologies and innovations. By conducting basic research, scientists can uncover new materials, properties, and relationships that can be used to develop new products or technologies.
Investigating complex phenomena : Basic research can be particularly valuable when investigating complex phenomena that are not yet well understood. By conducting basic research, scientists can gain a better understanding of the underlying principles and relationships that govern complex systems.
Advancing scientific knowledge: Basic research is important for advancing scientific knowledge in general. By conducting basic research, scientists can uncover new principles and relationships that can be applied across multiple fields of study.

Characteristics of Basic Research

Here are some of the main characteristics of basic research:

Focus on fundamental knowledge : Basic research is focused on expanding our understanding of the natural world and uncovering fundamental principles and relationships that underlie complex phenomena. The primary goal of basic research is to advance knowledge without any specific practical application in mind.
Exploratory in nature: Basic research is often exploratory in nature, with researchers seeking to answer fundamental questions about how the world works. The research may involve conducting experiments, collecting and analyzing data, or developing new theories and hypotheses.
Long-term focus: Basic research is often focused on long-term outcomes rather than immediate practical applications. The insights and discoveries generated by basic research may take years or even decades to translate into practical applications.
High degree of creativity and innovation : Basic research often requires a high degree of creativity, innovation, and intellectual curiosity. Researchers must be willing to take risks and pursue unconventional lines of inquiry.
Emphasis on scientific rigor: Basic research is conducted using the scientific method, which emphasizes the importance of rigorous experimental design, data collection and analysis, and peer review.
Interdisciplinary: Basic research is often interdisciplinary, drawing on multiple fields of study to address complex research questions. Basic research can be conducted in fields ranging from physics and chemistry to biology and psychology.
Open-ended : Basic research is open-ended, meaning that it does not have a specific end goal in mind. Researchers may follow unexpected paths or uncover new lines of inquiry that they had not anticipated.

Advantages of Basic Research

Here are some of the main advantages of basic research:

Advancing scientific knowledge: Basic research is essential for expanding our understanding of the natural world and uncovering fundamental principles and relationships that underlie complex phenomena. This knowledge can be applied across multiple fields of study and can lead to significant scientific and technological advancements.
Fostering innovation: Basic research often requires a high degree of creativity, innovation, and intellectual curiosity. By encouraging scientists to pursue unconventional lines of inquiry and take risks, basic research can lead to breakthrough discoveries and innovations.
Stimulating economic growth : Basic research can lead to the development of new technologies and products that can stimulate economic growth and create new industries. Many of the major scientific and technological advancements of the past century have been rooted in basic research.
Improving health and well-being: Basic research can lead to the development of new drugs, therapies, and medical treatments that can improve health and well-being. For example, many of the major advances in medical science, such as the development of antibiotics and vaccines, were rooted in basic research.
Training the next generation of scientists : Basic research is essential for training the next generation of scientists and researchers. By providing opportunities for young scientists to engage in research and gain hands-on experience, basic research helps to develop the skills and expertise needed to advance scientific knowledge in the future.
Encouraging interdisciplinary collaboration : Basic research often requires collaboration between scientists from different fields of study. By fostering interdisciplinary collaboration, basic research can lead to new insights and discoveries that would not be possible through single-discipline research alone.

Limitations of Basic Research

Here are some of the main limitations of basic research:

Lack of immediate practical applications : Basic research is often focused on long-term outcomes rather than immediate practical applications. The insights and discoveries generated by basic research may take years or even decades to translate into practical applications.
High cost and time requirements: Basic research can be expensive and time-consuming, as it often requires sophisticated equipment, specialized facilities, and large research teams. Funding for basic research can be limited, making it difficult to sustain long-term projects.
Ethical concerns : Basic research may involve working with animal models or human subjects, raising ethical concerns around the use of animals or the safety and well-being of human participants.
Uncertainty around outcomes: Basic research is often open-ended, meaning that it does not have a specific end goal in mind. This uncertainty can make it difficult to justify funding for basic research, as it is difficult to predict what outcomes the research will produce.
Difficulty in communicating results : Basic research can produce complex and technical findings that may be difficult to communicate to the general public or policymakers. This can make it challenging to generate public support for basic research or to translate basic research findings into policy or practical applications.

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25 Basic Research Examples

basic research examples and definition, explained below

Basic research is research that focuses on expanding human knowledge, without obvious practical applications.

For a scholarly definition, we can turn to Grimsgaard (2023):

“Basic research, also called pure, theoretical or fundamental research, tends to focus more on ‘big picture’ topics, such as increasing the scientific knowledge base around a particular topic.”

It is contrasted with applied research , which “seeks to solve real world problems” (Lehmann, 2023).

Generally, basis research has no clear economic or market value, meaning it tends to take place in universities rather than private organizations. Nevertheless, this blue-skies basic research can lead to enormous technological breakthroughs that forms the foundation for future applied research .

Basic Research Examples

Physics: Understanding the properties of neutrinos.
Medicine: Investigating the role of gut microbiota in mental health.
Anthropology: Studying the social structures of ancient civilizations.
Biology: Exploring the mechanism of CRISPR-Cas9 gene editing.
Psychology: Understanding the cognitive development in infants.
Chemistry: Researching new catalytic processes for organic synthesis.
Astronomy: Investigating the life cycle of stars.
Sociology: Exploring the impacts of social media on society.
Ecology: Studying the biodiversity in rainforests.
Computer Science: Developing new algorithms for machine learning.
Mathematics: Exploring new approaches to number theory.
Economics: Investigating the causes and effects of inflation.
Linguistics: Researching the evolution of languages over time.
Political Science: Studying the effects of political campaigns on voter behavior.
Geology: Investigating the formation of mountain ranges.
Architecture: Studying ancient building techniques and materials.
Education: Researching the impact of remote learning on academic performance.
History: Investigating trade routes in the medieval period.
Literature: Analyzing symbolism in 19th-century novels.
Philosophy: Exploring concepts of justice in different cultures.
Environmental Science: Studying the impact of plastics on marine life.
Genetics: Investigating the role of specific genes in aging.
Engineering: Researching materials for improving battery technology.
Art History: Investigating the influence of politics on Renaissance art.
Agricultural Science: Studying the impact of pest management practices on crop yield.

Case Studies

1. understanding the structure of the atom.

The study of atomic structure began in the early 1800s, with John Dalton’s atomic theory suggesting that atoms were indivisible and indestructible. However, it was not until the 20th century that Ernest Rutherford’s gold foil experiment led to the discovery of the nucleus and the proposal of the planetary model of the atom, which was further refined by Niels Bohr and eventually led to the quantum mechanical model, showing that electrons move in orbital shells around the nucleus.

Research Context:

Topic: Investigating the structure and behavior of atoms.
Purpose: Understand the fundamental particles (protons, neutrons, and electrons) and forces that govern atomic behavior.
Methodology: Utilize particle accelerators, theoretical models, and experimental physics.
Significance: Fundamental understanding of atomic structures has paved the way for numerous technological and scientific breakthroughs, such as the development of nuclear energy and advancements in chemistry and materials science.

Outcomes and Further Developments:

Discovery and exploration of subatomic particles like quarks.
Development of quantum mechanics and quantum field theory.
Subsequent advancements in various scientific fields, such as nuclear physics, chemistry, and nanotechnology.

2. Researching the Human Genome

The Human Genome Project, an international research effort that began in 1990, aimed to sequence and map all of the genes – collectively known as the genome – of humans. Completed in 2003, it represented a monumental achievement in science, providing researchers with powerful tools to understand the genetic factors in human disease, paving the way for new strategies for diagnosis, treatment, and prevention.

Topic: Investigating the structure, function, and mapping of the human genome.
Purpose: Understand the genetic makeup of humans, identify genes, and learn how they work.
Methodology: Techniques like DNA sequencing, genetic mapping, and computational biology.
Significance: Foundational for various advancements in genetics, medicine, and biology, providing insights into diseases, development, and evolution.
Completion of the Human Genome Project, which mapped the entire human genome.
Advancements in personalized medicine, genetic testing, and gene therapy.
Development of CRISPR technology, enabling precise genetic editing.

Basic Research vs Applied Research

Basic research focuses on expanding knowledge and understanding fundamental concepts without immediate practical application, while applied research focuses on solving specific, practical problems using the knowledge gained from basic research (Akcigit, Hanley & Serrano-Velarde, 2021).

A simple comparison of definitions is below:

Basic research seeks to gain greater knowledge or understanding of the fundamental aspects of phenomena.
Applied research seeks to solve practical problems the researcher or their stakeholders are facing.

A researcher might choose basic research over applied if their primary motivation is to expand the boundaries of human knowledge and contribute to academic theories, whilst they might favor applied research if they are more interested in achieving immediate solutions, innovations, or enhancements impacting real-world scenarios (Akcigit, Hanley & Serrano-Velarde, 2021; Baetu, 2016).

To learn more about applied research, check out my article on applied research.

Basic Research: Disappearing in 21st Century Universities?

In the 1980s, universities increasingly came under pressure to prove their specific financial value to society. This has only intensified over the decades. So, whereas once universities were preoccupied with basic research, there’s been a big push toward academic-industry collaborations where research demonstrates its economic value, rather than its cultural or intellectual value, to society. This may, on the one hand, help make universities relevant to today’s world. But on the other hand, it may interfere with the blue skies research that could identify and solve the bigger, less financially pressing, questions and problems of our ages (Bentley, Gulbrandsen & Kyvik, 2015).

Pros and Cons of Basic Research

The primary advantage of basic research is that it generates knowledge and understanding of fundamental principles that can later serve as a foundation for technological advancement or social betterment.

It can lead to groundbreaking discoveries, stimulate creativity, and drive scientific innovation by satisfying human curiosity (Akcigit, Hanley & Serrano-Velarde, 2021; Baetu, 2016).

It is also often the catalyst for training the next generation of scientists and researchers.

However, basic research can be time-consuming, expensive, and its outcomes may not always be directly observable or immediately beneficial.

This is why it’s often left to government-funded research institutes and universities to conduct this sort of research. As Binswanger (2014) argues, “basic research constitutes, for the most part, a common good which cannot be sold profitably on markets.

Furthermore, its value is often underestimated because the applications are not immediately apparent or tangible.

Below is a summary of some advantages and disadvantages of basic research:

Abeysekera, A. (2019). Basic research and applied research. Journal of the National Science Foundation of Sri Lanka , 47 (3).

Akcigit, U., Hanley, D., & Serrano-Velarde, N. (2021). Back to basics: Basic research spillovers, innovation policy, and growth. The Review of Economic Studies , 88 (1), 1-43.

Baetu, T. M. (2016). The ‘big picture’: the problem of extrapolation in basic research. The British Journal for the Philosophy of Science.

Bentley, P. J., Gulbrandsen, M., & Kyvik, S. (2015). The relationship between basic and applied research in universities. Higher Education , 70 , 689-709. ( Source )

Binswanger, M. (2014). How nonsense became excellence: forcing professors to publish. In Welpe, I. M., Wollersheim, J., Osterloh, M., & Ringelhan, S. (Eds.), Incentives and Performance: Governance of Research Organizations . Springer International Publishing.

Grimsgaard, W. (2023). Design and strategy: a step by step guide . New York: Taylor & Francis.

Lehmann, W. (2023). Social Media Theory and Communications Practice . London: Taylor & Francis.

Wiid, J., & Diggines, C. (2009). Marketing Research . Juta.

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Basic Research: What it is with examples

In building knowledge, there are many stages and methodologies to generate insights that contribute to its understanding and advancement; basic research and applied research are usually the most effective on this path.

Understanding research allows us to understand all the properties of a specific science or phenomenon at a fundamental level. Some examples are branches such as sociology, humanities, and other scientific fields; below, we will tell you everything you need to know about this type of research and its possible applications.

What is Basic Research?

Basic Research is a type of research used in the scientific field to understand and extend our knowledge about a specific phenomenon or field. It is also accepted as pure investigation or fundamental research .

This type of research contributes to the intellectual body of knowledge. Basic research is concerned with the generalization of a theory in a branch of knowledge; its purpose is usually to generate data that confirm or refute the initial thesis of the study.

It can also be called foundational research; many things get built on this foundation, and more practical applications are made.

Basic Research vs. Applied Research

Basic Research finds its counterpart and complement in applied research. They are two handy research methods when generating and giving a utility to the generated data. There are very marked differences, and understanding them will allow you to understand the path followed to create new knowledge.

The most important difference between basic research and applied research lies in the objective of each. It seeks to expand the information and understanding of the object of study, while applied research aims to provide a solution to the problem studied.

The relationship between these two types of research is usually very close since the methodologies used are often quite similar; the significant change is found in the initial and final point of the investigation.

Basic Research Examples

There can be many examples of basic research; here are some of them:

A study of how stress affects labor productivity.
Studying the best factors of pricing strategies.
Understand the client’s level of satisfaction before certain interactions with the company providing solutions.
The understanding of the leadership style of a particular company.

Advantages & Disadvantages

Basic research is critical for expanding the pool of knowledge in any discipline. The introductory course usually does not have a strict period, and the researcher’s concern commonly guides them. The conclusion of the fundamental course is generally applicable in a wide range of cases and plots.

At the same time, the basic study has disadvantages as well. The findings of this type of study have limited or no constructive conclusions. In another sense, fundamental studies do not resolve complex and definite business problems, but it does help you understand them better.

Taking actions and decisions based on the results of this type of research will increase the impact these insights may have on the problem studied if that is the purpose.

LEARN ABOUT: Theoretical Research

How to do basic research?

This process follows the same steps as a standard research methodology. The most crucial point is to define a thesis or theory that involves a perfectly defined case study; this can be a phenomenon or a research problem observed in a particular place.

There are many types of research, such as longitudinal studies , observational research , and exploratory studies. So the first thing you should do is determine if you can obtain the desired result with research or if it is better to opt for another type of research.

Once you have determined your research methodology, the data collection process begins, also depending on your type of study; sometimes, you can collect the data passively through observation or experimentation. On other occasions, intervene directly and collect quantitative information with tools such as surveys.

Platforms like QuestionPro will help you have a wide range of functions and tools to carry out your research; its survey software has helped students and professionals obtain all the information necessary to generate high-value insights.

In addition, it has a data analysis suite with which you can analyze all this information using all kinds of reports for a more straightforward interpretation of the final results.

QuestionPro is much more than survey software ; we have a solution for each specific problem and industry. We also offer data management platforms such as our research data repository called Insights Hub.

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The Essential Guide to Doing Your Research Project

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v.25(8); 2020 Dec

Purposive sampling: complex or simple? Research case examples

Steve campbell.

Professor of Clinical Redesign, Nursing, Associate Head Research, School of Nursing, University of Tasmania, College of Health and Medicine, Australia

Melanie Greenwood

Associate Professor, Director Post Graduate Courses, School of Nursing, University of Tasmania, College of Health and Medicine, Australia

Sarah Prior

Lecturer, Tasmanian School of Medicine, University of Tasmania, College of Health and Medicine, Australia

Toniele Shearer

Lecturer, PhD Candidate, School of Nursing, University of Tasmania, College of Health and Medicine, Australia

Kerrie Walkem

Sarah young.

Professor of Health Care Improvement, School of Nursing, University of Tasmania, College of Health and Medicine, School of Health Science, Australia

Danielle Bywaters

PhD Candidate, School of Nursing, University of Tasmania, College of Health and Medicine, Australia

Purposive sampling has a long developmental history and there are as many views that it is simple and straightforward as there are about its complexity. The reason for purposive sampling is the better matching of the sample to the aims and objectives of the research, thus improving the rigour of the study and trustworthiness of the data and results. Four aspects to this concept have previously been described: credibility, transferability, dependability and confirmability.

The aim of this paper is to outline the nature and intent of purposive sampling, presenting three different case studies as examples of its application in different contexts.

Presenting individual case studies has highlighted how purposive sampling can be integrated into varying contexts dependent on study design. The sampling strategies clearly situate each study in terms of trustworthiness for data collection and analysis. The selected approach to purposive sampling used in each case aligns to the research methodology, aims and objectives, thus addressing each of the aspects of rigour.

Conclusions

Making explicit the approach used for participant sampling provides improved methodological rigour as judged by the four aspects of trustworthiness. The cases presented provide a guide for novice researchers of how rigour may be addressed in qualitative research.

Introduction

Novice nurse researchers tend to see purposive sampling as either simple or too difficult ( Tuckett, 2004 ) and may therefore default to using a convenience sample for the wrong reasons. Attempting to ensure that nursing research has the right sample is crucial to good processes. This paper came out of the ongoing work of a research group, made up largely of nurses, at the University of Tasmania. The group ranged in experience from PhD students and early career researchers to experienced full professors and the research ranged similarly from PhD studies to funded research. A number of the group were using purposive sampling techniques under different circumstances and with different challenges. The lessons learnt by the individuals and by the group as a whole are interweaved into this paper and the case studies using purposive sampling are used to exemplify the different uses of purposive sampling, and the way in which each context has been handled.

Purposive sampling

In terms of sampling, the strategy for participant selection should be integrated into the overall logic of any study ( Punch, 2004 ) and the rationale for sample selection needs to be aligned from an ontological, epistemological and axiological perspective with the overarching aims of the study. In a qualitative study, a relatively small and purposively selected sample may be employed ( Miles and Huberman, 1994 ), with the aim of increasing the depth (as opposed to breadth) of understanding ( Palinkas et al., 2015 ). Purposive sampling is ‘used to select respondents that are most likely to yield appropriate and useful information’ ( Kelly, 2010 : 317) and is a way of identifying and selecting cases that will use limited research resources effectively ( Palinkas et al., 2015 ).

Purposive sampling strategies move away from any random form of sampling and are strategies to make sure that specific kinds of cases of those that could possibly be included are part of the final sample in the research study. The reasons for adopting a purposive strategy are based on the assumption that, given the aims and objectives of the study, specific kinds of people may hold different and important views about the ideas and issues at question and therefore need to be included in the sample ( Mason, 2002 ; Robinson, 2014 ; Trost, 1986 ).

With respect to research involving multiple cases, the most popular forms of purposive sampling are stratified, cell, quota and theoretical sampling. The different nature of these approaches is described in brief below.

Stratified sampling selects specific kinds or groups of participants that need to be part of the final sample. The sample is then stratified by the characteristic of the participant or group, with a specific number allocated to each stratification. (The number allocated to each category is also clearly important, particularly when allocation to separate groups is different.) Categories might be age, size of family, IQ, etc. However, and importantly, there needs to be a clear reason linked to the aims and objectives of the study to show why each group is different. Moreover, in terms of interviews, they must have something to add to the study.

Cell sampling is similar to stratified sampling but differs in that the categories for stratification are discrete, and in cell sampling they can overlap like a Venn diagram ( Miles and Huberman, 1994 ). For example, in a study of children with chronic disease, one cell might be obese children and the other might be children with diabetes and the overlap will be obese children with diabetes.

In quota sampling, there is greater flexibility – rather than fixed numbers of cases being required with particular criteria, quota sampling specifies categories and the minimum number needed for each one ( Mason, 2002 ). As the study proceeds, numbers in each area are monitored for fulfilment of the quota. For example, in a study, again of children with chronic illness, there might be quota for kinds of chronic illness and for kinds of family. The research team would specify a minimum for each of the quota. (A minimum of five children each with diabetes, leukaemia, arthritis, etc., and for the kind of family, 10 from a nuclear family, 15 from a reconstituted family, etc.) The use of minimum quota makes sure that key participants are part of the final sample. It is argued that this approach is also more flexible in shaping the final sample and easier, in recruitment terms, compared with stratified and cell sampling ( Robinson, 2014 ).

Theoretical sampling is different by being part of the collection and analysis of the data, following provisional sampling and analysis of some data ( Coyne, 1997 ; Robinson, 2014 ; Strauss, 1987 ). Theoretical sampling originally came from Grounded Theory but is applied to other methods as well ( Mason, 2002 ). The process involves either identifying cases from new groups, which might amount to being a comparison or a contrast with other groups, or reshaping the sample into a new set of criteria as a result of the analysis, and in so doing replacing the original sampling strategy chosen a-priori ( Draucker et al., 2007 ; Robinson, 2014 ).

This paper now introduces three different research studies in which the processes and challenges of purposive sampling are taken up in each instance.

Research study 1: Co-led redesign of stroke services in North West Tasmania

This example relates to the redesign of stroke services and is reported at the point when all patient interviews have been collected. Co-led redesign initiatives in healthcare service provision rely on experience-based feedback from patients and their families as well as sourcing information from healthcare staff and data collected specifically for the purpose of a service redesign (Prior and Campbell, 2018). The stroke service co-led redesign project utilised a purposive sampling method developed by Reed et al. (1996) based on stakeholder sampling ( Ovretveit, 1998 ), termed the Matrix sampling method. Matrix sampling empowers the stakeholders, allowing them to select categories of participants who they determine to be representative of the service users, essentially creating a trustworthy sample. For example, the stroke patient interviews consisted of 50% of patients over age 65 and 50% of those aged 65 or under. The stakeholder group identified that these two groups of patients require differing types of acute and rehabilitative stroke care in some instances and placed a high level of importance on being able to achieve the levels of care required for different age groups. The stakeholders included senior medical and nursing management, medical consultants, nursing unit managers, the director of allied health and the research team. The research team is then able to perform the interviews with selected patients on behalf of the stakeholders and report the findings to the group via thematic analysis.

Matrix sampling strengthens qualitative research by providing a structured and purposive method for nominating participants. It creates maximum variability based on stakeholder knowledge of the population and the intended research outcomes. Previously utilised in healthcare redesign research in the United Kingdom ( Campbell et al., 2004 ) as part of a patient journey approach, Matrix sampling is a cost-effective and time-efficient method allowing the stakeholders a level of control over the selected sample. This method of sampling was selected to capture a relevant participant group, representing stroke patients in North West Tasmania. A number of clinical and demographic variables were considered when determining the appropriate stroke patient participants, influenced by the local population and a quantitative data analysis determining the numbers and types of stroke patients admitted. Exclusion criteria were set prior to the sampling process; these included mini strokes (transient ischaemic attacks), patients who were living in a nursing home at the time of their stroke and deceased patients. As with other purposive sampling methods, Matrix sampling utilises the specific characteristic of stroke to provide a potential pool of participants. Other characteristics of importance noted during the participant selection phase for this project included the number of risk factors associated with each stroke patient, mode of arrival to the hospital, whether the patient was transferred into or out of a specific hospital and the type of stroke for which the patient was admitted (haemorrhagic or ischaemic). These specific criteria, determined by the stakeholders, allowed the research team to find candidates for the interviews to represent the patient group who could provide the most appropriate input into stroke service redesign for this particular population area.

Although this sampling method fulfils the needs of the stakeholders by allowing them to make the decisions over the sample population, there are also some weaknesses or disadvantages to the Matrix sampling method. If it is not possible to recruit participants to a selected criterion, gaps appear in the data. In the project it was noted that one particular criterion, patients who were transferred between hospitals, was more difficult to ‘fill’ due to smaller numbers of admitted patients fitting this description, purely due to the population being sampled. The dependability of the data, then, can be difficult to control; however, to overcome this issue, discussions with the stakeholder group suggested other recruitment methods, such as clinicians identifying patients and requesting consent. If these patients were unable to be identified, the group was satisfied that all was done to ensure the stakeholder view was utilised to the best abilities of the research team and the results delivered still reflected a representative population.

The Matrix sampling method is an easily transferable approach for qualitative research, which allows the input of the stakeholder(s) to determine the output of the research through the provision of local information and knowledge. Matrix sampling is a form of stratified sampling, but it is also quota driven. It is a form of stakeholder sampling where the views of the stakeholders are paramount, as they have to be reassured of the adequacy of the sampling so they regard the evidence as adequate and credible.

Research study 2: Child and family health nurses and safety and wellbeing of young children

This example is from a PhD study (Young, 2020 [unpublished thesis]) focusing on the response of child and family health (CFH) nurses to concerns around the safety and wellbeing of young children aged from birth to 5 years within the family, using Interpretive Description (ID) as the methodological approach. The setting in which the study is situated is that of a CFH nursing service provided by an Australian state-wide health department.

ID methodology, developed by Thorne et al. (1997) , is a way of generating increased understanding of clinical phenomena that are complex and experiential. ID studies generate an ID of the themes and patterns captured within subjective perceptions around a phenomena of clinical interest ( Thorne et al., 2004 ) and produce practice-relevant knowledge that can be immediately applied in the clinical context ( Thorne, 2016 ; Hunt, 2009 ). When using ID methodology, researchers identify who should be included in the study, so the eventual findings allow better understanding of the phenomenon of interest ( Hunt, 2009 ; Thorne, 2016 ). Purposive sampling is an accepted and often used initial sampling strategy in ID methodology as it allows settings and people to be recruited based on their expected contribution to the study ( Schensul, 2011 ) and by virtue of some angle of the phenomenon that they might help us better understand ( Hunt, 2009 ; Thorne, 2016 ). Participants are those who are most likely to have in-depth knowledge and experience of the phenomenon being studied. With this in mind, the inclusion criteria developed for this study were that participants must be nurses currently employed as CFH nurses with a minimum of 2 years recent (within the last 5 years) experience working in this specialist area of nursing. This was to help to ensure the opinions obtained were those of experienced CFH nurses with exposure to relevant practice experiences in a range of situations. Excluded from the study were those nurses who did not have at least 2 years recent post-graduate experience as a CFH nurse.

In developing the sample subset, an awareness was maintained of how this might either privilege or silence particular angles or perspectives and thus impact the eventual findings of the study and its credibility ( Thorne, 2016 ). To enhance credibility, care was taken to clearly, transparently and explicitly describe the logic used in selecting the sample subset ( Robinson, 2014 ; Thorne, 2016 ). Furthermore, a critical awareness of the nature of the selected sample and how this might impact on any findings generated was maintained throughout the study to help ensure claims beyond the sample subset were not made ( Robinson, 2014 ; Thorne, 2016 ).

Transferability was enhanced by the way in which study participants were clearly identified in terms of inclusion and exclusion criteria and demographic information. This helps others to determine whether the findings are applicable to other situations and population groups ( Shenton, 2004 ; Amankwaa, 2016 ). A sample that is fully contextualised helps prevent unwarranted generalisation ( Robinson, 2014 ). Dependability was enhanced by the description of participants using clear inclusion and exclusion criteria ( Shenton, 2014 ). In addition, a well-accepted sampling strategy appropriate to an ID study was used ( Thorne, 2016 ). Confirmability was enhanced by the provision of a rationale for the choice of inclusion and exclusion criteria, so that the integrity of the process could be determined by others ( Shenton, 2014 ).

Research study 3: How can mental wellbeing for new mothers be achieved?

This example is from a PhD study (Young, 2020 [unpublished thesis]) about women's experiences after childbirth, where recruitment is about to commence. This research aims to determine what influences mothers’ mental wellbeing in the year after the birth of a first baby and asks, ‘how can mental wellbeing for new mothers be achieved?’ Narrative inquiry involving three or four in-depth interviews with ∼10 women will be used to answer this question. The interviews will be conducted longitudinally over a period of 9–12 months and will aim to capture a rich, deep picture of the first year after childbirth. It is hoped that the major influences impacting mental wellbeing will be identified.

To determine which women to include in this study, purposive sampling will be employed. Specific inclusion and exclusion criteria will be indicated, making the inclusion of participants in this study non-probabilistic, and indeed purposive, in nature. Women will be recruited for involvement from the antenatal clinic at the local public hospital by way of response to a posted flyer. Although there is an element of convenience sampling involved in this process, the very specific nature of the criteria for involvement make this design purposive. Inclusion criteria will include considerations such as first-time mothers only, singleton pregnancy, maternal age over 18 years and gestational due date within a specified timeframe to facilitate the longitudinal interview schedule. Exclusion criteria will include anyone who has had a previous mental health issue or a pregnancy-related health complication (e.g., gestational diabetes, placenta praevia, known foetal issues, etc.).

The trustworthiness and rigour of the data will be enhanced by the purposive sampling design. In terms of credibility, this method of sampling supports the likelihood that ‘member checking’ may occur, which will increase the credibility of the findings ( Guba, 1981 ). Because women will self-select for participation in the study, this degree of interest and investment increases the likelihood of their willingness to remain involved for the duration of the research.

Both the transferability and dependability of the data will be enhanced by the specific nature of the inclusion and exclusion criteria laid out for this research. Transferability will be affected because these detailed criteria will allow readers to develop a clear picture of participants involved. Guba notes the importance of ‘full description of all the contextual factors impinging on the inquiry’ (1981: 70) and the participants themselves can be considered a ‘contextual factor’ in the research. In a similar vein, the detailed nature of the criteria will form part of the audit trail that contributes to dependability in a study ( Baillie, 2015 ; Guba, 1981 ). A risk to trustworthiness in interview-based research is the role of the interviewer themselves and the influence of their own beliefs and perspectives ( Haga et al., 2012 ; Shenton, 2004 ).

When determining the sample size for a study of this nature, several factors are considered. Morse notes that the scope of the study, the nature of the topic, the quality of the data, the study design and the use of shadowed data all require consideration (2000). Relatedly, Morse (2000 : 4) emphasises that ‘the quality of data and the number of interviews per participant determine the amount of useable data obtained. There is an inverse relationship between the amount of useable data obtained from each participant and the number of participants’. This is an important consideration with a longitudinal study where, for example, four interviews with 10 participants would amass data very quickly. With these considerations in mind, a sample size of 10 participants will be the aim.

Implications for research in nursing and health

The sample, particularly for qualitative research, is often not analysed by the nursing reader of practice papers ( Gelling et al., 2014 ). The sample itself, the context and the process are all important issues to consider when reading a paper and considering its impact, particularly when making potential policy changes. Therefore, novice nursing researchers need to ensure the sampling process fits the needs of the study and be clear about the actual process that ensued. For instance: does the sample in the nursing research strategy match the patients who are being considered? The context of sampling in nursing research, as in all research, is a key issue.

Each of these research studies has considered purposive sampling in very different contexts. However, all of them, although purposive, have a convenience element to them given the voluntary nature of all consent processes, where the researcher is at the mercy of the pool of potential participants. However, the voluntary nature of the participation means the researchers can characterise them as fitting not only the inclusion criteria of the study, but also being interested in the topic and motivated to take part out of this interest and their potential to contribute to development of knowledge in this arena.

The Co-Led Stroke Redesign sampling process was about interviewing a representative sample that was persuasive enough to inform change of practice in the stakeholders. The CFH nurse study is the simplest of the designs cited in this paper and has power in this simplicity. However, the analysis of the data is already showing important differences in the nature of the sample. The identification of the right mothers to gain their views of motherhood shows the lengths researchers can go to when considering complex forms of purposive sampling, only to discard them for a simpler process. However, this process of considering options is important in developing high-quality research designs rather than settling for standard approaches.

A continued narrative for all of the research studies that have been exemplified in this paper was whether being purposive in some more complex manner was actually necessary. The only clarity was that all studies were purposive with the intent of recruiting participants who could inform the researchers' aims and objectives. The argument was that the reader of the research would be able to make the judgements about the relevance of the research, if the nature of the sample was transparent. This is another example of the context of research being all important in qualitative research. In combination, the case studies highlight important elements researchers should consider when using purposive sampling techniques to address the four elements of trustworthiness for the research design.

Key points for policy, practice and/or research

Novice nurse researchers need to ensure purposive sampling is used where appropriate and not default to a convenience sample.
The context of the data collection is an important consideration in purposive sampling for trustworthiness of data in nursing research.
Nurse researchers adopt theoretical positions that are reflected in purposive sampling techniques and assist policy makers to understand the relevance of the research.
The voluntary nature of nursing research supports the purposive sampling approach, it does not mitigate against it.

Acknowledgements

The authors thank the Patient Involvement Group, School of Health Sciences, University of Tasmania.

Steve Campbell joined the University of Tasmania in January 2013 as the Head of Nursing and Midwifery and then Head of the School of Health Sciences until 2016. With the reestablishment of the School of Nursing in 2019, Steve is now the Research Director/Associate Head of Research for the school and Professor of Clinical Redesign, Nursing.

Melanie Greenwood is an Associate Professor within the School of Nursing at the University of Tasmania and leads the school’s extensive postgraduate framework. She has over 20 years’ critical care nursing expertise in researching into recognition and response to deteriorating patients with a quality and safety in healthcare focus.

Sarah Prior is an academic with the School of Medicine, coordinating the postgraduate, workplace integrated healthcare quality and safety courses. Sarah’s research interests include patient involvement, co-design, rural health service delivery and health service improvement.

Toniele Shearer has worked as a critical care nurse in Australia for around 17 years in the Intensive Care/Coronary Care setting. Toniele teaches in both postgraduate and undergraduate programs offered in the School of Nursing at the University of Tasmania. She is also a PhD candidate.

Kerrie Walkem is a lecturer in the School of Nursing. She coordinates and teaches the postgraduate child and family health nursing stream, as well as other related nursing units across the postgraduate and undergraduate areas. She is also a PhD candidate.

Sarah Young is a PhD candidate with the University of Tasmania’s School of Nursing. Her PhD thesis aims to contribute to the development of a picture of women's experiences after having their first baby.

Danielle Bywaters is a nursing lecturer in the School of Nursing and a photographer who is currently a PhD Candidate. Her PhD study is interdisciplinary and uses a visual method to explore communication in nursing.

Kim Walker is a nurse and a former Professor of Healthcare Improvement, a position he held between the University of Tasmania (nursing discipline) and St Vincent’s Private hospital in Sydney.

Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article..

Ethical approval: This paper is a methodological paper, therefore ethics approval was not needed.

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs: Steve Campbell https://orcid.org/0000-0003-4830-8488 Melanie Greenwood https://orcid.org/0000-0001-5840-0750 Sarah Prior

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ORIGINAL RESEARCH article

The causal relationship between obesity, obstructive sleep apnea and atrial fibrillation: a study based on mediated mendelian randomization provisionally accepted.

1 Department of Cardiology, Second Hospital of Anhui Medical University, China

The final, formatted version of the article will be published soon.

This study employed a two-sample and multivariate Mendelian randomization (MR) approach to evaluate the mediating role of obstructive sleep apnea (OSA) in the link between obesity and atrial fibrillation (AF). The findings revealed that obesity heightened the risk of OSA, and OSA substantially increased the risk of AF. The mediated MR analysis demonstrated that OSA plays a part in the causal relationship between obesity and AF, with approximately 6.4% of the AF risk being mediated by OSA. This investigation utilized GWAS data on AF and OSA, and obesity data from the Finngen database. The methodologies employed included inverse variance weighted meta-analysis, MR-Egger regression, weighted median, simple model, and weighted model. Additionally, sensitivity analyses were conducted to evaluate heterogeneity and potential bias. This study underscores the potential of MR as a novel approach to explore biomedical causality. The outcomes of this study enhance comprehension of the correlation between obesity, OSA, and AF and offer new insights for the prevention and treatment of AF.

Keywords: Obesity, obstructive sleep apnea, AF, mediated Mendelian randomization, causal relationship

Received: 24 Mar 2024; Accepted: 08 Apr 2024.

Copyright: © 2024 Li, Rong, Gao and Cheng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mx. Wei Cheng, Department of Cardiology, Second Hospital of Anhui Medical University, Hefei, Anhui Province, China

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Tyler A. Cochran ORCID: orcid.org/0000-0003-1745-8467 1 ,
Mohammad Yahyavi 6 ,
Xian P. Yang ORCID: orcid.org/0000-0002-5019-374X 1 ,
Luis Balicas ORCID: orcid.org/0000-0002-5209-0293 7 ,
Guoqing Chang ORCID: orcid.org/0000-0003-1180-3127 6 ,
Weisheng Zhao ORCID: orcid.org/0000-0001-8088-0404 5 ,
Titus Neupert 8 &
M. Zahid Hasan ORCID: orcid.org/0000-0001-9730-3128 1 , 9 , 10

Nature ( 2024 ) Cite this article

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Electronic properties and materials
Topological insulators

Topology 1 , 2 , 3 and interactions are foundational concepts in the modern understanding of quantum matter. Their nexus yields three important research directions: (1) the competition between distinct interactions, as in several intertwined phases, (2) the interplay between interactions and topology that drives the phenomena in twisted layered materials and topological magnets, and (3) the coalescence of several topological orders to generate distinct novel phases. The first two examples have grown into major areas of research, although the last example remains mostly unexplored, mainly because of the lack of a material platform for experimental studies. Here, using tunnelling microscopy, photoemission spectroscopy and a theoretical analysis, we unveil a ‘hybrid’ topological phase of matter in the simple elemental-solid arsenic. Through a unique bulk-surface-edge correspondence, we uncover that arsenic features a conjoined strong and higher-order topology that stabilizes a hybrid topological phase. Although momentum-space spectroscopy measurements show signs of topological surface states, real-space microscopy measurements unravel a unique geometry of topologically induced step-edge conduction channels revealed on various natural nanostructures on the surface. Using theoretical models, we show that the existence of gapless step-edge states in arsenic relies on the simultaneous presence of both a non-trivial strong Z 2 invariant and a non-trivial higher-order topological invariant, which provide experimental evidence for hybrid topology. Our study highlights pathways for exploring the interplay of different band topologies and harnessing the associated topological conduction channels in engineered quantum or nano-devices.

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Acknowledgements

M.Z.H. group acknowledges primary support from the US Department of Energy (DOE), Office of Science, National Quantum Information Science Research Centers, Quantum Science Center (at Oak Ridge National Laboratory) and Princeton University, support from the Gordon and Betty Moore Foundation for scanning tunneling microscopy instrumentation and theoretical work (Grant No. GBMF9461) and support from the DOE under the Basic Energy Sciences (DOE-BES) programme for theoretical work and photoemission spectroscopy (Grant No. DOE/BES DE-FG-02-05ER46200). R.I. acknowledges support from the Foundation for Polish Science through the international research agendas programme co-financed by the European Union within the smart growth operational programme and the National Science Foundation (NSF; Grant No. OIA-2229498), University of Alabama at Birmingham (UAB) internal startup funds, and a UAB Faculty Development Grant Program, Office of the Provost. L.B. is supported by the DOE-BES (Award No. DE-SC0002613). The National High Magnetic Field Laboratory acknowledges support from the NSF (Cooperative Agreement Grant No. DMR-1644779) and the state of Florida. T.N. acknowledges support from the Swiss National Science Foundation through a consolidator grant (Grant No. TMCG-2_213805). Z.M. and W.Z. acknowledge support from the National Natural Science Foundation of China (Grant No. 62150410438), the Beihang Hefei Innovation Research Institute (Project No. BHKX-19-02) for growth and beamline 13U of the National Synchrotron Radiation Laboratory for the ARPES experiments. Work at Nanyang Technological University was supported by the National Research Foundation, Singapore, under its Fellowship Award (NRF-NRFF13-2021-0010), the Agency for Science, Technology and Research (A*STAR) under its Manufacturing, Trade and Connectivity (MTC) Individual Research Grant (IRG) (Grant No. M23M6c0100), and the Nanyang Assistant Professorship grant (NTU-SUG).

Author information

These authors contributed equally: Md Shafayat Hossain, Frank Schindler, Rajibul Islam, Zahir Muhammad, Yu-Xiao Jiang, Zi-Jia Cheng

Authors and Affiliations

Laboratory for Topological Quantum Matter and Advanced Spectroscopy (B7), Department of Physics, Princeton University, Princeton, NJ, USA

Md Shafayat Hossain, Yu-Xiao Jiang, Zi-Jia Cheng, Qi Zhang, Maksim Litskevich, Jia-Xin Yin, Tyler A. Cochran, Xian P. Yang & M. Zahid Hasan

Blackett Laboratory, Imperial College London, London, UK

Frank Schindler

International Research Centre MagTop, Institute of Physics, Polish Academy of Sciences, Warsaw, Poland

Rajibul Islam

Department of Physics, University of Alabama at Birmingham, Birmingham, AL, USA

Hefei Innovation Research Institute, School of Integrated Circuit Science and Engineering, Beihang University, Hefei, P.R. China

Zahir Muhammad & Weisheng Zhao

Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore, Singapore

Tao Hou, Hongyu Chen, Mohammad Yahyavi & Guoqing Chang

National High Magnetic Field Laboratory, and Physics Department, Florida State University, Tallahassee, FL, USA

Brian Casas & Luis Balicas

Department of Physics, University of Zurich, Zurich, Switzerland

Titus Neupert

Princeton Institute for Science and Technology of Materials, Princeton University, Princeton, NJ, USA

M. Zahid Hasan

Quantum Science Center (QSC, ORNL), Oak Ridge, TN, USA

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Contributions

M.S.H. conceived the project. The STM experiments were performed by M.S.H. and Y.X.J. in consultation with M.Z.H. F.S. performed the tight-binding calculations. R.I. performed the first-principles calculations. The crystals were grown by Z.M. and W.Z. The ARPES measurements were performed by Z.J.C. and Z.M. The Landau-level calculations were performed by T.H. and M.Y. under the supervision of G.C. The quasiparticle interference calculations were carried out by H.C. under the supervision of G.C. M.S.H., F.S., R.I., T.N., L.B. and M.Z.H. developed the figures and wrote the paper. M.Z.H. supervised the project. All authors discussed the results and participated in the making the interpretation and drawing the conclusion.

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Correspondence to Md Shafayat Hossain , Frank Schindler or M. Zahid Hasan .

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Extended data figures and tables

Extended data fig. 1 first-principles calculations and angle-resolved photoemission spectroscopy determination of the electronic band structures..

a , First Brillouin zone and the projected surface along (111). Note that L is part of a group of three inequivalent L -points that are related by C 3 rotation symmetry around the z -axis. In the caption of Fig. 4 and the Supplementary Information, these are referred to as L , L ′, and L ″. b , Electronic band structure of bulk α-As calculated using density functional theory over the whole bulk Brillouin zone, taking into consideration the presence of spin-orbit coupling. The bands crossing the Fermi energy are highlighted in magenta (valence band) and cyan (conduction band). c , Left: Calculated surface bands connecting the conduction and valence bands with Rashba-like features. These bands, depicted using bright orange curves, are projected on the (111) surface (also shown in Fig. 1g ). Right: Calculated spin texture of the Rashba-like surface bands. d - f , Angle-resolved photoemission spectroscopy energy-momentum cuts encompassing high symmetry points- \(T\) (panel d ), \(\varGamma \) (panel e ), and \({L}_{3}\) (panel f )- of the bulk Brillouin zone. The directions are marked in panel a with dashed blue lines. The cuts are measured with a linear -horizontal polarized light with the photon energies of 67 eV (panel d ), 40 eV (panel e ), and 97 eV (panel f ), respectively. The right panels in d - f show the corresponding band structures obtained via first-principles calculations. The bulk bands obtained from photoemission spectroscopy qualitatively match the first-principles results. g , Constant energy contour of the photon energy dependence measurement at the Fermi energy. The size of the electron pocket near \(\varGamma \) does not depend on the photon energy, which confirms its surface-state nature. h , Energy-momentum cut (left) and its second derivative (right) taken along \(\bar{\varGamma }-\bar{M}\) direction of the surface Brillouin zone, obtained from photoemission spectroscopy on the cleaved (111) surface ( ab plane). The spectra were acquired using 22 eV, linear-horizontally polarized light. The topological surface state is marked by the white arrow. The small Rashba splitting is visualized in the second derivative plot (also shown in Fig. 1f ). i , Extracted dispersion of the Rashba-split surface states, shown using red and blue points. Red and blue curves denote parabolic fits to the photoemission data. These photoemission spectroscopy results are consistent with the first-principles calculations presented in panel c .

Extended Data Fig. 2 Fermi surface of α-As obtained via first-principles calculations and photoemission spectroscopy.

a and b , Three-dimensional Fermi surface of α-As featuring a hole-like ( α ) pocket shown in magenta and an electron-like ( β ) pocket shown in cyan, originating from the magenta and cyan bands in Extended Data Fig. 1b , respectively. c , Fermi surface projected on the (111) surface obtained using first-principles tight-binding calculations. It exhibits two additional Fermi pockets centered at k = 0, due to the Rashba-like surface states. d , Fermi surface map taken on the As (111) surface. The map is obtained using 20 eV photon energy and with linear-horizontally polarized light. Photoemission data also show ring-shaped Fermi pockets centering at k = 0 in addition to the three-dimensional bulk state.

Extended Data Fig. 3 Quasiparticle interference signature of the surface state.

a , Large-scale spectroscopic maps (left) and the corresponding Fourier transform at different tip-sample biases; the respective topography is also shown. Clear quasiparticle interference patterns are seen at all the bias voltages. b , Calculated quasiparticle interference patterns. The joint density of states method, which takes into account all possible scattering vectors, has been employed for the calculation. c , Experimental quasiparticle interference spectrum (energy resolution ≃ 25 meV which is determined by the number of bias points in the tunneling spectrum at each spatial point; q resolution = 0.0015 Å −1 which comes from the dimensions of the scanned area) taken along a high-symmetry direction, marked with an arrow in panel a , right column. The spectrum demonstrates several interference branches. The parabolic-shaped branch, which is the most prominent scattering branch in the quasiparticle interference spectrum, originates from \(\sim -230\pm 15\) meV. This energy position matches the location of the surface band bottom in the photoemission spectroscopy (Fig. 1f ) and the first-principles calculation results (Fig. 1g ). (A quantitative comparison between the three sets of data is provided in Supplementary Table 1 ). Therefore, it is most likely that this quasiparticle interference branch stems from the surface state. Tunneling junction set-up for d I /d V maps: V set = 200 mV, I set = 1 nA, V mod = 5 mV. d , Calculated quasiparticle interference spectrum, showing a clear parabolic-shaped scattering branch, which is in excellent agreement with the experimental result presented in panel c .

Extended Data Fig. 4 Landau level spectroscopy of α-As.

a , d I /d V line map (top) and its derivative (bottom) under B = 8 T applied perpendicularly to the cleaved surface. The intense modulation in differential conductance is due to Landau quantization. b , Averaged d I /d V spectra at B = 0 T, and 8 T taken from the same region clarifying that the d I /d V modulation is due to Landau quantization. c , Derivative (to remove the slowly varying background) of the 8 T data and its Fourier transform (inset) showing two (close-by) peaks, suggesting two sets of Landau fans. d , Field-dependent differential conductance data obtained from a line cut of the Landau fan (shown in Fig. 1h ) at the Fermi energy. e , Fourier transform of panel d data (after replotting the data as a function of \(\frac{1}{B}\) ). Fourier transform magnitude as a function of cyclotron frequency reveals two well-developed peaks at 175 T and 187 T. The two peaks correspond to the Fermi surface areas (in units of cyclotron frequency) of the two Fermi pockets stemming from the Rashba-split surface state. f , Schematic illustration of the Fermi surface stemming from the Rashba bands (see Extended Data Fig. 1c for numerically computed bands). Left: Schematic energy-momentum plot of the parabolic Rashba bands. A cut at the Fermi energy yields two concentric, ring-shaped Fermi pockets. Right: Schematic Fermi surface plot containing the two concentric ring-shaped pockets (see Extended Data Fig. 2c for numerically computed Fermi surfaces). The experimentally obtained 175 T and 187 T peaks (panel e ) represent the area of the inner and outer ring-shaped Fermi pockets, respectively. Tunneling junction set-up: V set = 50 mV, I set = 0.5 nA, V mod = 0.5 mV.

Extended Data Fig. 5 Line spectroscopy with high spatial and energy resolutions and the corresponding Fourier transform taken along a bilayer step edge.

This bilayer step edge, whose orientation is identical to that of the step edges displayed in Fig. 3a and d , manifests a step edge state. a , Intensity plot revealing pronounced quantum interference patterns. The green dotted line on the topographic image (shown at the top) indicates the location where the d I /d V line spectroscopy is performed. The direction of the scan is marked by an arrow. b , Corresponding one-dimensional Fourier transform, highlighting a clear edge state dispersion. Tunneling junction set-up: V set = 100 mV, I set = 0.5 nA, V mod = 0.5 mV.

Extended Data Fig. 6 Orientation-dependence of the monolayer step edge states.

a, b , Topographic images, height profiles, and the corresponding differential conductance maps around two monolayer step edges (1 and 2 as marked). The color-coded arrows in the topographies and the height profiles indicate the directions from the bottom to the top terraces. Depending on this direction, one monolayer step edge (monolayer step edge 2) exhibits a step edge state while the other monolayer step edge (monolayer step edge 1) does not. c , Differential spectra, taken at the monolayer step edge 1 (orange), monolayer step edge 2 (green), and away from the step edges (violet), revealing striking differences between the two step edges. Orange and green dots in the topographic images in panels a and b denote the respective positions on the monolayer step edges 1 and 2 where the differential spectra are taken. While the monolayer step edge 2 exhibits a pronounced step edge state, the monolayer step edge 1 features a largely suppressed differential conductance within the soft gap. Note that the monolayer step edge 2 has the same orientation as the monolayer step edge in Fig. 2a , and thereby both exhibit the same electronic structure. On the other hand, resembling the two bilayer step edges shown in Fig. 3a,b , the two monolayer step edges also show a dramatic contrast—one step edge exhibits a pronounced step edge state while the other step edge along the same crystallographic axis, but with a different orientation, does not. Here, however, the orientation favoring a step edge state is opposite to that of the bilayer case (Fig. 3a,b ). Tunneling junction set-up for the differential spectra: V set = 100 mV, I set = 0.5 nA, V mod = 0.5 mV. Tunneling junction set-up for d I /d V maps: V set = 100 mV, I set = 0.5 nA, V mod = 1 mV.

Extended Data Fig. 7 Low-energy spectra of the tight binding model in absence of first-order topology.

Here we delineate the step edge dispersion in a tight-binding system that differs from α-As in that it only has a double band inversion at the Γ point of the bulk Brillouin zone, and not an extra single band inversion at each of the three L , L ′, L ″ points as is the case for α-As. Correspondingly, the model only has nontrivial higher-order topology, but no first-order topology. As derived in our Supplementary Information, such a situation implies a gapped step edge dispersion, however, the gapped modes are precursors of hinge modes localized near the step edges. This situation is schematically depicted in Fig. 4c . a , Monolayer step edge geometry. We preserve periodic boundary conditions in the a 1 -direction (the out-of-plane direction, with lattice spacing a 1 ), so that k 1 is a conserved crystal momentum. There are two step edges, one of type A and one of type B (see Supplementary Information), on each of the top and bottom surfaces. This is the minimal configuration of step edges that preserves inversion symmetry as well as periodic boundary conditions along the a 2 -direction. b , Monolayer step edge dispersion with k 1 using the lattice shown in panel a . We only show the momentum range k 1 ∈ [0, π] because the spectrum in the range k 1 ∈ [π, 2π] is related by time-reversal symmetry. There is no nontrivial spectral flow (the spectrum is gapped). c , Local density of states (LDOS) for the A step edge. The LDOS is large for the low-energy bands closest to the gap, implying that they are well-localized at the step edge. d , Local density of states for the B step edge. This LDOS is small, implying that there are no low-energy states at the step edge. e , Bilayer step edge geometry. f , Bilayer step edge dispersion. There is still a gap, but the low-energy bands are slightly different from the monolayer case. g , Local density of states for the A step edge. The LDOS is again large for the low-energy bands, implying that they are well-localized at the same step edge as for the monolayer. h , Local density of states for the B step edge. Like the monolayer case, there are no step edge states close to the Fermi level.

Extended Data Fig. 8 Step edge states at the monolayer step edges along the b -axis and rotated by 120 o with respect to it.

a , Topographic image of two monolayer step edges along the b -axis and rotated by 120 o with respect to it. The orientation of the two step edges is opposite to those of the two monolayer step edges in Fig. 3d . Here the crystal side lies between the two step edges contrary to Fig. 3d , where the crystal side extends away from the pit. b , Height profile taken perpendicular to the b -axis direction. The corresponding location is marked on the topographic image in panel a with a green line; the direction of the scan is marked with an arrow. c , Differential conductance maps at different bias voltages, taken in the region shown in panel a. The two monolayer step edges, along the b -axis and rotated by 120 o with respect to it, harbor step edge states that are manifested via an enhanced differential conductance. This behavior is in stark contrast to the monolayer step edges along the same directions, but with opposite orientations (Fig. 3d ). Such an orientation dependence is consistent with our other data on different step edges along different crystallographic directions and with different orientations and layer thicknesses. Tunneling junction set-up for the differential spectra: V set = 100 mV, I set = 0.5 nA, V mod = 0.5 mV. Tunneling junction set-up for d I /d V maps: V set = 100 mV, I set = 0.5 nA, V mod = 1 mV.

Extended Data Fig. 9 Orientation-dependence of the three-, four-, and six-layer-thick step edge states.

Topographic images, height profiles, and the corresponding differential conductance maps at V = −5 mV around two tri-layer ( a and b ), four-layer ( c and d ), and six-layer ( e and f ) step edges. The color-coded arrows in the topographies and the height profiles indicate the directions from the bottom to the top terraces. Depending on this direction and the layer thickness, certain step edge orientations (such as tri-layer step edge 2, four-layer step edge 1, and six-layer step edge 1) exhibit step edge states, while other orientations (like tri-layer step edge 1, four-layer step edge 2, and six-layer step edge 2) do not. g-i , Differential spectra, taken at the two tri-layer (panel g ), four-layer (panel h ), and six-layer (panel i ) step edges, revealing striking differences between the two step edge orientations. Consistent with the orientation dependence of the monolayer step edges in Extended Data Fig. 6 , and opposite to that of the bilayer step edges in Fig. 3a,b , the tri-layer step edge 2 (green curve in panel g ; d I /d V map in panel b ) shows a pronounced step edge state, while the tri-layer step edge 1 (orange curve in panel g ; d I /d V map in panel a ) exhibits largely suppressed differential conductance within the soft gap of the surface. Interestingly, this orientation dependence switches for the four-layer step edge, where the four-layer step edge 2 (green curve in panel h ; d I /d V map in panel d ) lacks a step edge state, while the four-layer step edge 1 (orange curve in panel h; d I /d V map in panel c ) carries a strong step edge state. This observation is consistent with the even-odd effect observed between the step-edge preferred orientations in mono and bilayer step edges. The six-layer step edge displays a similar geometry dependence as the four-layer step edge, with the six-layer step edge 2 (green curve in panel i ; d I /d V map in panel f ) lacking a step edge state, while the six-layer step edge 1 (orange curve in panel i ; d I /d V map in panel e ) exhibits a pronounced step edge state. Tunneling junction set-up for the differential spectra: V set = 100 mV, I set = 0.5 nA, V mod = 0.5 mV. Tunneling junction set-up for d I /d V maps: V set = 100 mV, I set = 0.5 nA, V mod = 1 mV.

Extended Data Fig. 10 Atomic structure for two different geometric orientations of the mono and bilayer step edges, highlighting the asymmetry between them.

a , Side view (along the bc plane) of the two monolayer step edges. b and c , Atomically resolved topographic images of the corresponding monolayer step edges along the a -direction. d , Side view (along the bc plane) of the two bilayer step edges. e and f , Atomically resolved topographic images ( V gap = 100 mV, I t = 3 nA) of the corresponding bilayer step edges along the a direction. Notably, there is an asymmetry between the two orientations in both monolayer and bilayer step edges, with one orientation featuring a sharper step edge. Interestingly, this preferred orientation alternates between the mono and bilayer cases, in accordance with the even-odd effect observed in the step edge states, where the step edge state appears to favor the smoother edge. We note that visualizing atoms directly at the step edge poses challenges due to the abrupt change in height at that location and the small inter-atomic distance ( \(\simeq \) 3.7 Å) in α-As. As a result, the atom arrays at the step edge may not be as clearly visualized in our scanning tunneling microscopy compared to those located away from the step edge. g , Extended scanning tunneling microscopy data: Topography (bottom) and the corresponding d I /d V maps ( V = −5 mV) acquired at B = 0 T and 2 T. At B = 2 T, the spectral weight at the step edge is suppressed. Such a suppression highlights the impact of time-reversal symmetry breaking on the step edge state. Tunneling junction set-up: V set = 100 mV, I set = 0.5 nA, V mod = 1 mV.

Supplementary information

Supplementary information.

This Supplementary Information file contains the following sections: (I) Theory of step edge states in α-As; (II) Tight-binding model with hybrid topology; (III) Lattice-based model of step edge states in the context of quasiparticle interference at step edges; (IV) First-principles calculations showing band hybridization leading to gapless edge states in α-As; and Supplementary References.

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Methodology

Sampling Methods | Types, Techniques & Examples

Sampling Methods | Types, Techniques & Examples

Published on September 19, 2019 by Shona McCombes . Revised on June 22, 2023.

When you conduct research about a group of people, it’s rarely possible to collect data from every person in that group. Instead, you select a sample . The sample is the group of individuals who will actually participate in the research.

To draw valid conclusions from your results, you have to carefully decide how you will select a sample that is representative of the group as a whole. This is called a sampling method . There are two primary types of sampling methods that you can use in your research:

Probability sampling involves random selection, allowing you to make strong statistical inferences about the whole group.
Non-probability sampling involves non-random selection based on convenience or other criteria, allowing you to easily collect data.

You should clearly explain how you selected your sample in the methodology section of your paper or thesis, as well as how you approached minimizing research bias in your work.

Population vs. sample, probability sampling methods, non-probability sampling methods, other interesting articles, frequently asked questions about sampling.

First, you need to understand the difference between a population and a sample , and identify the target population of your research.

The population is the entire group that you want to draw conclusions about.
The sample is the specific group of individuals that you will collect data from.

The population can be defined in terms of geographical location, age, income, or many other characteristics.

It is important to carefully define your target population according to the purpose and practicalities of your project.

If the population is very large, demographically mixed, and geographically dispersed, it might be difficult to gain access to a representative sample. A lack of a representative sample affects the validity of your results, and can lead to several research biases , particularly sampling bias .

Sampling frame

The sampling frame is the actual list of individuals that the sample will be drawn from. Ideally, it should include the entire target population (and nobody who is not part of that population).

Sample size

The number of individuals you should include in your sample depends on various factors, including the size and variability of the population and your research design. There are different sample size calculators and formulas depending on what you want to achieve with statistical analysis .

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Probability sampling means that every member of the population has a chance of being selected. It is mainly used in quantitative research . If you want to produce results that are representative of the whole population, probability sampling techniques are the most valid choice.

There are four main types of probability sample.

1. Simple random sampling

In a simple random sample, every member of the population has an equal chance of being selected. Your sampling frame should include the whole population.

To conduct this type of sampling, you can use tools like random number generators or other techniques that are based entirely on chance.

2. Systematic sampling

Systematic sampling is similar to simple random sampling, but it is usually slightly easier to conduct. Every member of the population is listed with a number, but instead of randomly generating numbers, individuals are chosen at regular intervals.

If you use this technique, it is important to make sure that there is no hidden pattern in the list that might skew the sample. For example, if the HR database groups employees by team, and team members are listed in order of seniority, there is a risk that your interval might skip over people in junior roles, resulting in a sample that is skewed towards senior employees.

3. Stratified sampling

Stratified sampling involves dividing the population into subpopulations that may differ in important ways. It allows you draw more precise conclusions by ensuring that every subgroup is properly represented in the sample.

To use this sampling method, you divide the population into subgroups (called strata) based on the relevant characteristic (e.g., gender identity, age range, income bracket, job role).

Based on the overall proportions of the population, you calculate how many people should be sampled from each subgroup. Then you use random or systematic sampling to select a sample from each subgroup.

4. Cluster sampling

Cluster sampling also involves dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample. Instead of sampling individuals from each subgroup, you randomly select entire subgroups.

If it is practically possible, you might include every individual from each sampled cluster. If the clusters themselves are large, you can also sample individuals from within each cluster using one of the techniques above. This is called multistage sampling .

This method is good for dealing with large and dispersed populations, but there is more risk of error in the sample, as there could be substantial differences between clusters. It’s difficult to guarantee that the sampled clusters are really representative of the whole population.

In a non-probability sample, individuals are selected based on non-random criteria, and not every individual has a chance of being included.

This type of sample is easier and cheaper to access, but it has a higher risk of sampling bias . That means the inferences you can make about the population are weaker than with probability samples, and your conclusions may be more limited. If you use a non-probability sample, you should still aim to make it as representative of the population as possible.

Non-probability sampling techniques are often used in exploratory and qualitative research . In these types of research, the aim is not to test a hypothesis about a broad population, but to develop an initial understanding of a small or under-researched population.

1. Convenience sampling

A convenience sample simply includes the individuals who happen to be most accessible to the researcher.

This is an easy and inexpensive way to gather initial data, but there is no way to tell if the sample is representative of the population, so it can’t produce generalizable results. Convenience samples are at risk for both sampling bias and selection bias .

2. Voluntary response sampling

Similar to a convenience sample, a voluntary response sample is mainly based on ease of access. Instead of the researcher choosing participants and directly contacting them, people volunteer themselves (e.g. by responding to a public online survey).

Voluntary response samples are always at least somewhat biased , as some people will inherently be more likely to volunteer than others, leading to self-selection bias .

3. Purposive sampling

This type of sampling, also known as judgement sampling, involves the researcher using their expertise to select a sample that is most useful to the purposes of the research.

It is often used in qualitative research , where the researcher wants to gain detailed knowledge about a specific phenomenon rather than make statistical inferences, or where the population is very small and specific. An effective purposive sample must have clear criteria and rationale for inclusion. Always make sure to describe your inclusion and exclusion criteria and beware of observer bias affecting your arguments.

4. Snowball sampling

If the population is hard to access, snowball sampling can be used to recruit participants via other participants. The number of people you have access to “snowballs” as you get in contact with more people. The downside here is also representativeness, as you have no way of knowing how representative your sample is due to the reliance on participants recruiting others. This can lead to sampling bias .

5. Quota sampling

Quota sampling relies on the non-random selection of a predetermined number or proportion of units. This is called a quota.

You first divide the population into mutually exclusive subgroups (called strata) and then recruit sample units until you reach your quota. These units share specific characteristics, determined by you prior to forming your strata. The aim of quota sampling is to control what or who makes up your sample.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Student’s t -distribution
Normal distribution
Null and Alternative Hypotheses
Chi square tests
Confidence interval
Quartiles & Quantiles
Cluster sampling
Stratified sampling
Data cleansing
Reproducibility vs Replicability
Peer review
Prospective cohort study

Research bias

Implicit bias
Cognitive bias
Placebo effect
Hawthorne effect
Hindsight bias
Affect heuristic
Social desirability bias

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Samples are used to make inferences about populations . Samples are easier to collect data from because they are practical, cost-effective, convenient, and manageable.

Probability sampling means that every member of the target population has a known chance of being included in the sample.

Probability sampling methods include simple random sampling , systematic sampling , stratified sampling , and cluster sampling .

In non-probability sampling , the sample is selected based on non-random criteria, and not every member of the population has a chance of being included.

Common non-probability sampling methods include convenience sampling , voluntary response sampling, purposive sampling , snowball sampling, and quota sampling .

In multistage sampling , or multistage cluster sampling, you draw a sample from a population using smaller and smaller groups at each stage.

This method is often used to collect data from a large, geographically spread group of people in national surveys, for example. You take advantage of hierarchical groupings (e.g., from state to city to neighborhood) to create a sample that’s less expensive and time-consuming to collect data from.

Sampling bias occurs when some members of a population are systematically more likely to be selected in a sample than others.

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