social research methods qualitative and quantitative approaches 2014

• DOI: 10.2307/3211488
• Corpus ID: 145179283

Social Research Methods: Qualitative and Quantitative Approaches

• Y. Djamba , W. Neuman
• Published 1 July 2002
• Teaching Sociology

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Book review: social research methods: qualitative and quantitative approaches.

• Discipline of Psychology, School of Social Sciences, Indira Gandhi National Open University, New Delhi, India

A Book Review on Social Research Methods: Qualitative and Quantitative Approaches

William Lawrence Neuman (Essex: Pearson Education Limited), 2014, 594 pages, ISBN: 978-1-292-02023-5

“The Art and Science of Asking Questions is the Source of All Knowledge”—Thomas Berger

In an endeavor to bridge the gap between knowledge and applicability, Neuman (2014) presents a meticulous and comprehensive amalgamation of concepts and theories, defining qualitative and quantitative research methods in his book “Social Research Methods: Qualitative and Quantitative Approaches.” A professor of sociology at the University of Wisconsin-Whitewater, William Lawrence Neuman has gained immense experience and has worked rigorously in his subject matter. He has authored seven books, numerous book chapters, and articles in the field of social sciences.

The book reviewed at present is the seventh edition of the “Social research methods: Qualitative and Quantitative Approaches,” which was published by Pearson Education Limited in 2014. The book was written to help aspiring researchers gain an in-depth understanding of research and its purpose while stressing the essentials and theoretical considerations of conducting research. With a total of 15 chapters, the book elucidates various research methods, balancing between qualitative and quantitative approaches with an aim to emphasize the conceptual framework, applications, strategies, and the pros and cons of each approach, along with highlighting the benefits of using a combination of the two approaches.

The current edition is divided into five parts—foundations of research; planning and preparation for research; quantitative research methods—collection and analysis of data; qualitative research—methods of collecting data and analysis; and lastly “communicating the results of research with others.”

Part one of the book consists of five chapters, shedding light on the basics to provide an understanding of the and how of research and its importance; types of research; theoretical conceptualizations; methodology; and conducting a literature review and ethics in research. For example, in chapter one, the author explains the need to learn how to conduct research, followed by explaining the use, scope, and target audience for research in chapter two. Furthermore, in chapter four, in the most beautifully structured manner, the author has elaborated on the philosophical foundations and paradigms of research.

Part two describes the basics of the process of conducting research. Divided into three chapters explaining qualitative and quantitative research in terms of—research designs and its various strategies; measurement of data; and sampling. Research design issues, reliability and validity, and the types of scales and inventories used are also discussed in this section, providing an integrative and inclusive view of the research process.

In the third part, the types of research and their processes are elaborated for collection of data and analysis in quantitative research. Spread across four chapters, the topics covered under this section include experimental research; survey research; non-reactive research and secondary analysis; and quantitative analysis of data. Whereas, the fourth part is dedicated to qualitative research. Described in two chapters, this section focuses on field and focus group research and analyzing qualitative data.

Parts three and four of the book do justice to the concepts by providing thorough information about the procedure and methods of research. It covers the history, advantages, disadvantages, uses, requirements, as well as gives details about the types of variables and statistical and non-statistical techniques that can be applied. Each chapter is enriched with figures, diagrams, and maps which aid in enhancing conceptual clarity. For example, chapter ten includes information about the latest technological advances such as online surveys and computer-assisted data collection and chapter 14 includes detailed figures depicting qualitative data analysis techniques, with a figure for each like narrative analysis.

The last part of the book and the final chapter provides detailed information on writing and publishing research reports as well as talks about the politics in social research. This part covers everything from why a research report is required, to understanding the writing process, formulating a research proposal, to discussing the ethics, limitations, advantages, and difficulties faced in conducting and publishing research.

In terms of the structure of the book, each chapter begins with the title and key pointers of the topics to be discussed, along with a quote or a small paragraph, which in a theoretical yet poetic style serves as a brief introduction to the topic. Needless to say, each topic mentioned is covered scrupulously and thoroughly in a holistic manner and is explained in-depth, clearly divided point-wise and under sub-categories. This helps in reducing the burden of information overload and aids in maintaining the readers interest.

The most noteworthy and distinguishing part of the book is the use of alternate means of representing and expressing information. Each topic is supported with various realistic examples, enriched with numerous figures, maps, diagrams, and is summarized in organized and structured tables for comparison and ease of understanding. The author has also included dialogue boxes in each chapter with short definitions of the topics in discussion. This is advantageous from a learning perspective as it provides a quick glimpse, simplifying the comprehension of concepts. It is these features that give the book an edge over other books of research.

The book also incorporates empirical evidence and statistical data in supporting its content and illustrations, making it more credible. The language used is simple and straightforward yet catchy in terms of grasping the reader's attention, making even complex theories and perspectives intelligible. At the end of each chapter, a list of key terms is provided, followed by a set of review questions. These questions are beneficial as a means of assessing conceptual clarity in addition to encouraging the reader to ruminate and indulge in lateral thinking over the subject matter.

Overall, the book is a valuable asset for the field of research. The confluence of theoretical concepts with realistic examples makes the book highly applicable and significant not just for students, but for anyone keen to venture into the realm of social research. Just like a building cannot withstand without a strong foundation, a researcher cannot exist without building and maintaining their repositories of knowledge. In conclusion, the book is a quintessential means of grasping and gaining mastery over research knowledge.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Neuman, W. L. (2014). Social Research Methods: Qualitative and Quantitative Approaches, 7th Edn . United Kingdom: Pearson Education Limited.

Google Scholar

Keywords: research, qualitative research, quantitative research, review, social sciences

Citation: Khosla I (2021) Book Review: Social Research Methods: Qualitative and Quantitative Approaches. Front. Psychol. 12:696828. doi: 10.3389/fpsyg.2021.696828

Received: 17 April 2021; Accepted: 30 April 2021; Published: 25 May 2021.

Edited and reviewed by: Laura Galiana , University of Valencia, Spain

Copyright © 2021 Khosla. 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) and the copyright owner(s) 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: Irene Khosla, irenekhosla96@gmail.com

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Book Review: Social Research Methods: Qualitative and Quantitative Approaches

William Lawrence Neuman, editor. Social Research Methods: Qualitative and Quantitative Approaches. 2014. Essex: Pearson Education Limited. 594 p. ISBN: 978-1-292-02023-5.

“The Art and Science of Asking Questions is the Source of All Knowledge”—Thomas Berger

In an endeavor to bridge the gap between knowledge and applicability, Neuman ( 2014 ) presents a meticulous and comprehensive amalgamation of concepts and theories, defining qualitative and quantitative research methods in his book “Social Research Methods: Qualitative and Quantitative Approaches.” A professor of sociology at the University of Wisconsin-Whitewater, William Lawrence Neuman has gained immense experience and has worked rigorously in his subject matter. He has authored seven books, numerous book chapters, and articles in the field of social sciences.

The book reviewed at present is the seventh edition of the “Social research methods: Qualitative and Quantitative Approaches,” which was published by Pearson Education Limited in 2014. The book was written to help aspiring researchers gain an in-depth understanding of research and its purpose while stressing the essentials and theoretical considerations of conducting research. With a total of 15 chapters, the book elucidates various research methods, balancing between qualitative and quantitative approaches with an aim to emphasize the conceptual framework, applications, strategies, and the pros and cons of each approach, along with highlighting the benefits of using a combination of the two approaches.

The current edition is divided into five parts—foundations of research; planning and preparation for research; quantitative research methods—collection and analysis of data; qualitative research—methods of collecting data and analysis; and lastly “communicating the results of research with others.”

Part one of the book consists of five chapters, shedding light on the basics to provide an understanding of the and how of research and its importance; types of research; theoretical conceptualizations; methodology; and conducting a literature review and ethics in research. For example, in chapter one, the author explains the need to learn how to conduct research, followed by explaining the use, scope, and target audience for research in chapter two. Furthermore, in chapter four, in the most beautifully structured manner, the author has elaborated on the philosophical foundations and paradigms of research.

Part two describes the basics of the process of conducting research. Divided into three chapters explaining qualitative and quantitative research in terms of—research designs and its various strategies; measurement of data; and sampling. Research design issues, reliability and validity, and the types of scales and inventories used are also discussed in this section, providing an integrative and inclusive view of the research process.

In the third part, the types of research and their processes are elaborated for collection of data and analysis in quantitative research. Spread across four chapters, the topics covered under this section include experimental research; survey research; non-reactive research and secondary analysis; and quantitative analysis of data. Whereas, the fourth part is dedicated to qualitative research. Described in two chapters, this section focuses on field and focus group research and analyzing qualitative data.

Parts three and four of the book do justice to the concepts by providing thorough information about the procedure and methods of research. It covers the history, advantages, disadvantages, uses, requirements, as well as gives details about the types of variables and statistical and non-statistical techniques that can be applied. Each chapter is enriched with figures, diagrams, and maps which aid in enhancing conceptual clarity. For example, chapter ten includes information about the latest technological advances such as online surveys and computer-assisted data collection and chapter 14 includes detailed figures depicting qualitative data analysis techniques, with a figure for each like narrative analysis.

The last part of the book and the final chapter provides detailed information on writing and publishing research reports as well as talks about the politics in social research. This part covers everything from why a research report is required, to understanding the writing process, formulating a research proposal, to discussing the ethics, limitations, advantages, and difficulties faced in conducting and publishing research.

In terms of the structure of the book, each chapter begins with the title and key pointers of the topics to be discussed, along with a quote or a small paragraph, which in a theoretical yet poetic style serves as a brief introduction to the topic. Needless to say, each topic mentioned is covered scrupulously and thoroughly in a holistic manner and is explained in-depth, clearly divided point-wise and under sub-categories. This helps in reducing the burden of information overload and aids in maintaining the readers interest.

The most noteworthy and distinguishing part of the book is the use of alternate means of representing and expressing information. Each topic is supported with various realistic examples, enriched with numerous figures, maps, diagrams, and is summarized in organized and structured tables for comparison and ease of understanding. The author has also included dialogue boxes in each chapter with short definitions of the topics in discussion. This is advantageous from a learning perspective as it provides a quick glimpse, simplifying the comprehension of concepts. It is these features that give the book an edge over other books of research.

The book also incorporates empirical evidence and statistical data in supporting its content and illustrations, making it more credible. The language used is simple and straightforward yet catchy in terms of grasping the reader's attention, making even complex theories and perspectives intelligible. At the end of each chapter, a list of key terms is provided, followed by a set of review questions. These questions are beneficial as a means of assessing conceptual clarity in addition to encouraging the reader to ruminate and indulge in lateral thinking over the subject matter.

Overall, the book is a valuable asset for the field of research. The confluence of theoretical concepts with realistic examples makes the book highly applicable and significant not just for students, but for anyone keen to venture into the realm of social research. Just like a building cannot withstand without a strong foundation, a researcher cannot exist without building and maintaining their repositories of knowledge. In conclusion, the book is a quintessential means of grasping and gaining mastery over research knowledge.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

• Neuman W. L. (2014). Social Research Methods: Qualitative and Quantitative Approaches, 7th Edn . United Kingdom: Pearson Education Limited. [ Google Scholar ]

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• Each chapter begins with an Introduction and ends with Conclusion, Key Terms, Review Questions and Notes. Preface. I. FOUNDATIONS.
• 1. Science and Research. Alternatives to Social Research. How Science Works. Qualitative and Quantitative Social Research. Steps of the Research Process. Why Conduct Social Research.
• 2. Dimensions of Research. Dimensions of Research. Audience for and Use of Research The Purpose of research The Time Dimension in Research Data Collection Techniques Used.
• 3. Theory and Research. What Is Theory? Social Theory versus Ideology. The Parts of Theory. Aspects of Theory. The Dynamic Duo.
• 4. The Meanings of Methodology. The Three Approaches. Positivist Social Science. Interpretative Social Science. Critical Social Science. Feminist and Postmodern Research.
• 5. The Literature Review and Ethical Concerns. The Literature Review. Ethics in Social Research. II. PLANNING AND PREPARATION.
• 6. Qualitative and Quantitative Research Designs. Triangulation. Qualitative and Quantitative Orientations Toward Research. Qualitative Design Issues. Quantitative Design Issues.
• 7. Qualitative and Quantitative Measurement. Why Measure? Qualitative and Quantitative Measurement. Parts of the Measurement Process. Reliability and Validity. A Guide to Quantitative Measurement. Index Construction. Scales.
• 8. Qualitative and Quantitative Sampling. Nonprobability Sampling. Probability Sampling. III. QUANTITATIVE DATA COLLECTION AND ANALYSIS.
• 9. Experimental Research. Random Assignment. Experimental Design Logic. Internal and External Validity. Practical Considerations. Results of Experimental Research: Making Comparisons. A Word on Ethics.
• 10. Survey Research. The Logic of Survey Research. Constructing the Questionnaire. Types of Surveys: Advantages and Disadvantages. Interviewing. Computer-Assisted Pilot-Testing and Web Surveys The Ethical Survey.
• 11. Nonreactive Research and Secondary Analysis. Nonreactive Measurement. Content Analysis. Existing Statistics/Documents and Secondary Analysis. Issues of Inference and Theory Testing.
• 12. Analysis of Quantitative Data. Dealing with Data. Results with One Variable. Results with Two Variables. More than Two Variables. Inferential Statistics. IV. QUALITATIVE DATA COLLECTION AND ANALYSIS.
• 13. Field Research. The Logic of Field Research. Choosing a Site and Gaining Access. Relations in the Field. Observing and Collecting Data. The Field Research Interview. Leaving the Field. Ethical Dilemmas of Field Research.
• 14. Historical-Comparative Research. The Logic of Historical Comparative Research. Steps in a Historical-Comparative Research Project. Data and Evidence in Historical Context. Comparative Research. Equivalence in Historical Comparative Research.
• 15. Analysis of Qualitative Data. Comparing Methods of Data Analysis. Coding and Concept Formation. Analytic Strategies for Qualitative Data. What Is Not Seen. Other Tools. V. COMMUNICATING WITH OTHERS.
• 16. Writing the Research Report and the Politics of Social Research. Introduction. The Research Report. The Politics of Social Research. Objectivity and Value Freedom. Conclusion. Appendices. Appendix A: American Sociological Association Code of Ethics. Appendix B: Table of Randomly Selected Five Digit Numbers. Appendix C: Sample of Data Archives and Resources. Appendix D: Measurement Theory. Appendix E: Evaluation Research. Glossary. Bibliography. Name Index. Subject Index. Scholarly Journals in the Social Sciences in English.
• (source: Nielsen Book Data)

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Home » Descriptive Research Design – Types, Methods and Examples

Descriptive Research Design – Types, Methods and Examples

Table of Contents

Descriptive Research Design

Definition:

Descriptive research design is a type of research methodology that aims to describe or document the characteristics, behaviors, attitudes, opinions, or perceptions of a group or population being studied.

Descriptive research design does not attempt to establish cause-and-effect relationships between variables or make predictions about future outcomes. Instead, it focuses on providing a detailed and accurate representation of the data collected, which can be useful for generating hypotheses, exploring trends, and identifying patterns in the data.

Types of Descriptive Research Design

Types of Descriptive Research Design are as follows:

Cross-sectional Study

This involves collecting data at a single point in time from a sample or population to describe their characteristics or behaviors. For example, a researcher may conduct a cross-sectional study to investigate the prevalence of certain health conditions among a population, or to describe the attitudes and beliefs of a particular group.

Longitudinal Study

This involves collecting data over an extended period of time, often through repeated observations or surveys of the same group or population. Longitudinal studies can be used to track changes in attitudes, behaviors, or outcomes over time, or to investigate the effects of interventions or treatments.

This involves an in-depth examination of a single individual, group, or situation to gain a detailed understanding of its characteristics or dynamics. Case studies are often used in psychology, sociology, and business to explore complex phenomena or to generate hypotheses for further research.

Survey Research

This involves collecting data from a sample or population through standardized questionnaires or interviews. Surveys can be used to describe attitudes, opinions, behaviors, or demographic characteristics of a group, and can be conducted in person, by phone, or online.

Observational Research

This involves observing and documenting the behavior or interactions of individuals or groups in a natural or controlled setting. Observational studies can be used to describe social, cultural, or environmental phenomena, or to investigate the effects of interventions or treatments.

Correlational Research

This involves examining the relationships between two or more variables to describe their patterns or associations. Correlational studies can be used to identify potential causal relationships or to explore the strength and direction of relationships between variables.

Data Analysis Methods

Descriptive research design data analysis methods depend on the type of data collected and the research question being addressed. Here are some common methods of data analysis for descriptive research:

Descriptive Statistics

This method involves analyzing data to summarize and describe the key features of a sample or population. Descriptive statistics can include measures of central tendency (e.g., mean, median, mode) and measures of variability (e.g., range, standard deviation).

Cross-tabulation

This method involves analyzing data by creating a table that shows the frequency of two or more variables together. Cross-tabulation can help identify patterns or relationships between variables.

Content Analysis

This method involves analyzing qualitative data (e.g., text, images, audio) to identify themes, patterns, or trends. Content analysis can be used to describe the characteristics of a sample or population, or to identify factors that influence attitudes or behaviors.

Qualitative Coding

This method involves analyzing qualitative data by assigning codes to segments of data based on their meaning or content. Qualitative coding can be used to identify common themes, patterns, or categories within the data.

Visualization

This method involves creating graphs or charts to represent data visually. Visualization can help identify patterns or relationships between variables and make it easier to communicate findings to others.

Comparative Analysis

This method involves comparing data across different groups or time periods to identify similarities and differences. Comparative analysis can help describe changes in attitudes or behaviors over time or differences between subgroups within a population.

Applications of Descriptive Research Design

Descriptive research design has numerous applications in various fields. Some of the common applications of descriptive research design are:

• Market research: Descriptive research design is widely used in market research to understand consumer preferences, behavior, and attitudes. This helps companies to develop new products and services, improve marketing strategies, and increase customer satisfaction.
• Health research: Descriptive research design is used in health research to describe the prevalence and distribution of a disease or health condition in a population. This helps healthcare providers to develop prevention and treatment strategies.
• Educational research: Descriptive research design is used in educational research to describe the performance of students, schools, or educational programs. This helps educators to improve teaching methods and develop effective educational programs.
• Social science research: Descriptive research design is used in social science research to describe social phenomena such as cultural norms, values, and beliefs. This helps researchers to understand social behavior and develop effective policies.
• Public opinion research: Descriptive research design is used in public opinion research to understand the opinions and attitudes of the general public on various issues. This helps policymakers to develop effective policies that are aligned with public opinion.
• Environmental research: Descriptive research design is used in environmental research to describe the environmental conditions of a particular region or ecosystem. This helps policymakers and environmentalists to develop effective conservation and preservation strategies.

Descriptive Research Design Examples

Here are some real-time examples of descriptive research designs:

• A restaurant chain wants to understand the demographics and attitudes of its customers. They conduct a survey asking customers about their age, gender, income, frequency of visits, favorite menu items, and overall satisfaction. The survey data is analyzed using descriptive statistics and cross-tabulation to describe the characteristics of their customer base.
• A medical researcher wants to describe the prevalence and risk factors of a particular disease in a population. They conduct a cross-sectional study in which they collect data from a sample of individuals using a standardized questionnaire. The data is analyzed using descriptive statistics and cross-tabulation to identify patterns in the prevalence and risk factors of the disease.
• An education researcher wants to describe the learning outcomes of students in a particular school district. They collect test scores from a representative sample of students in the district and use descriptive statistics to calculate the mean, median, and standard deviation of the scores. They also create visualizations such as histograms and box plots to show the distribution of scores.
• A marketing team wants to understand the attitudes and behaviors of consumers towards a new product. They conduct a series of focus groups and use qualitative coding to identify common themes and patterns in the data. They also create visualizations such as word clouds to show the most frequently mentioned topics.
• An environmental scientist wants to describe the biodiversity of a particular ecosystem. They conduct an observational study in which they collect data on the species and abundance of plants and animals in the ecosystem. The data is analyzed using descriptive statistics to describe the diversity and richness of the ecosystem.

How to Conduct Descriptive Research Design

To conduct a descriptive research design, you can follow these general steps:

• Define your research question: Clearly define the research question or problem that you want to address. Your research question should be specific and focused to guide your data collection and analysis.
• Choose your research method: Select the most appropriate research method for your research question. As discussed earlier, common research methods for descriptive research include surveys, case studies, observational studies, cross-sectional studies, and longitudinal studies.
• Design your study: Plan the details of your study, including the sampling strategy, data collection methods, and data analysis plan. Determine the sample size and sampling method, decide on the data collection tools (such as questionnaires, interviews, or observations), and outline your data analysis plan.
• Collect data: Collect data from your sample or population using the data collection tools you have chosen. Ensure that you follow ethical guidelines for research and obtain informed consent from participants.
• Analyze data: Use appropriate statistical or qualitative analysis methods to analyze your data. As discussed earlier, common data analysis methods for descriptive research include descriptive statistics, cross-tabulation, content analysis, qualitative coding, visualization, and comparative analysis.
• I nterpret results: Interpret your findings in light of your research question and objectives. Identify patterns, trends, and relationships in the data, and describe the characteristics of your sample or population.
• Draw conclusions and report results: Draw conclusions based on your analysis and interpretation of the data. Report your results in a clear and concise manner, using appropriate tables, graphs, or figures to present your findings. Ensure that your report follows accepted research standards and guidelines.

When to Use Descriptive Research Design

Descriptive research design is used in situations where the researcher wants to describe a population or phenomenon in detail. It is used to gather information about the current status or condition of a group or phenomenon without making any causal inferences. Descriptive research design is useful in the following situations:

• Exploratory research: Descriptive research design is often used in exploratory research to gain an initial understanding of a phenomenon or population.
• Identifying trends: Descriptive research design can be used to identify trends or patterns in a population, such as changes in consumer behavior or attitudes over time.
• Market research: Descriptive research design is commonly used in market research to understand consumer preferences, behavior, and attitudes.
• Health research: Descriptive research design is useful in health research to describe the prevalence and distribution of a disease or health condition in a population.
• Social science research: Descriptive research design is used in social science research to describe social phenomena such as cultural norms, values, and beliefs.
• Educational research: Descriptive research design is used in educational research to describe the performance of students, schools, or educational programs.

Purpose of Descriptive Research Design

The main purpose of descriptive research design is to describe and measure the characteristics of a population or phenomenon in a systematic and objective manner. It involves collecting data that describe the current status or condition of the population or phenomenon of interest, without manipulating or altering any variables.

The purpose of descriptive research design can be summarized as follows:

• To provide an accurate description of a population or phenomenon: Descriptive research design aims to provide a comprehensive and accurate description of a population or phenomenon of interest. This can help researchers to develop a better understanding of the characteristics of the population or phenomenon.
• To identify trends and patterns: Descriptive research design can help researchers to identify trends and patterns in the data, such as changes in behavior or attitudes over time. This can be useful for making predictions and developing strategies.
• To generate hypotheses: Descriptive research design can be used to generate hypotheses or research questions that can be tested in future studies. For example, if a descriptive study finds a correlation between two variables, this could lead to the development of a hypothesis about the causal relationship between the variables.
• To establish a baseline: Descriptive research design can establish a baseline or starting point for future research. This can be useful for comparing data from different time periods or populations.

Characteristics of Descriptive Research Design

Descriptive research design has several key characteristics that distinguish it from other research designs. Some of the main characteristics of descriptive research design are:

• Objective : Descriptive research design is objective in nature, which means that it focuses on collecting factual and accurate data without any personal bias. The researcher aims to report the data objectively without any personal interpretation.
• Non-experimental: Descriptive research design is non-experimental, which means that the researcher does not manipulate any variables. The researcher simply observes and records the behavior or characteristics of the population or phenomenon of interest.
• Quantitative : Descriptive research design is quantitative in nature, which means that it involves collecting numerical data that can be analyzed using statistical techniques. This helps to provide a more precise and accurate description of the population or phenomenon.
• Cross-sectional: Descriptive research design is often cross-sectional, which means that the data is collected at a single point in time. This can be useful for understanding the current state of the population or phenomenon, but it may not provide information about changes over time.
• Large sample size: Descriptive research design typically involves a large sample size, which helps to ensure that the data is representative of the population of interest. A large sample size also helps to increase the reliability and validity of the data.
• Systematic and structured: Descriptive research design involves a systematic and structured approach to data collection, which helps to ensure that the data is accurate and reliable. This involves using standardized procedures for data collection, such as surveys, questionnaires, or observation checklists.

Advantages of Descriptive Research Design

Descriptive research design has several advantages that make it a popular choice for researchers. Some of the main advantages of descriptive research design are:

• Provides an accurate description: Descriptive research design is focused on accurately describing the characteristics of a population or phenomenon. This can help researchers to develop a better understanding of the subject of interest.
• Easy to conduct: Descriptive research design is relatively easy to conduct and requires minimal resources compared to other research designs. It can be conducted quickly and efficiently, and data can be collected through surveys, questionnaires, or observations.
• Useful for generating hypotheses: Descriptive research design can be used to generate hypotheses or research questions that can be tested in future studies. For example, if a descriptive study finds a correlation between two variables, this could lead to the development of a hypothesis about the causal relationship between the variables.
• Large sample size : Descriptive research design typically involves a large sample size, which helps to ensure that the data is representative of the population of interest. A large sample size also helps to increase the reliability and validity of the data.
• Can be used to monitor changes : Descriptive research design can be used to monitor changes over time in a population or phenomenon. This can be useful for identifying trends and patterns, and for making predictions about future behavior or attitudes.
• Can be used in a variety of fields : Descriptive research design can be used in a variety of fields, including social sciences, healthcare, business, and education.

Limitation of Descriptive Research Design

Descriptive research design also has some limitations that researchers should consider before using this design. Some of the main limitations of descriptive research design are:

• Cannot establish cause and effect: Descriptive research design cannot establish cause and effect relationships between variables. It only provides a description of the characteristics of the population or phenomenon of interest.
• Limited generalizability: The results of a descriptive study may not be generalizable to other populations or situations. This is because descriptive research design often involves a specific sample or situation, which may not be representative of the broader population.
• Potential for bias: Descriptive research design can be subject to bias, particularly if the researcher is not objective in their data collection or interpretation. This can lead to inaccurate or incomplete descriptions of the population or phenomenon of interest.
• Limited depth: Descriptive research design may provide a superficial description of the population or phenomenon of interest. It does not delve into the underlying causes or mechanisms behind the observed behavior or characteristics.
• Limited utility for theory development: Descriptive research design may not be useful for developing theories about the relationship between variables. It only provides a description of the variables themselves.
• Relies on self-report data: Descriptive research design often relies on self-report data, such as surveys or questionnaires. This type of data may be subject to biases, such as social desirability bias or recall bias.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Social Research Methods: Qualitative and Quantitative Approaches Second Edition

• ISBN-10 1412978548
• ISBN-13 978-1412978545
• Edition Second
• Publisher SAGE Publications, Inc
• Publication date March 2, 2012
• Language English
• Dimensions 7.5 x 1.5 x 10.25 inches
• Print length 824 pages
• See all details

Editorial Reviews

′There is considerable detail on the history and philosophical foundations of social and behavioural research, ranging from the ‘what’ to the ‘how-to’ of social research.

To make sure the message of each chapter is clearly communicated [Bernard] employs a wealth of examples and reading lists. He also provides the reader with a description of key concepts employed in each chapter.′

About the Author

H. Russell Bernard is Professor of Anthropology, Emeritus at the University of Florida. He served as editor of the American Anthropologist and Human Organization . He is co-founder (with Pertti Pelto and Stephen Borgatti) of the Cultural Anthropology Methods journal (1989), which became Field Methods in 1999. The five editions of his methods text Research Methods in Anthropology (AltaMira 2006) and his general research methods text Social Research Methods (Sage 2012), have been used by tens of thousands of students. Bernard co-founded (with Pelto) and co-directed (with Pelto and Borgatti) the National Science Foundation′s Institute on Research Methods in Cultural Anthropology and has done fieldwork in Greece, Mexico, and the U.S.A. His publications include (with Jesús Salinas Pedraza) Native Ethnography: A Otomí Indian Describes His Culture (Sage, 1989). Bernard is known as well for his work, with Peter Killworth, Eugene Johnsen, Christopher McCarty, and Gene A. Shelley, on network analysis, including work on the network scale-up method for estimating hard-to-count populations. In 2010, Bernard was elected to the National Academy of Sciences.

Product details

• Publisher ‏ : ‎ SAGE Publications, Inc; Second edition (March 2, 2012)
• Language ‏ : ‎ English
• Hardcover ‏ : ‎ 824 pages
• ISBN-10 ‏ : ‎ 1412978548
• ISBN-13 ‏ : ‎ 978-1412978545
• Item Weight ‏ : ‎ 3.13 pounds
• Dimensions ‏ : ‎ 7.5 x 1.5 x 10.25 inches
• #314 in Social Sciences Methodology
• #684 in Social Sciences Research
• #4,851 in Social Sciences (Books)

About the author

H. russell bernard.

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