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The Reviewer S Guide To Quantitative Methods In The Social Sciences

Author: Gregory R. Hancock
Publisher: Routledge
ISBN: 1135172994
Size: 80.56 MB
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The Reviewer’s Guide is designed for reviewers of research manuscripts and proposals in the social and behavioral sciences, and beyond. Its uniquely structured chapters address traditional and emerging quantitative methods of data analysis.

The Reviewer S Guide To Quantitative Methods In The Social Sciences

Author: Greg Hancock
Publisher: Routledge
ISBN: 1135172986
Size: 28.35 MB
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The Reviewer’s Guide to Quantitative Methods in the Social Sciences is designed for evaluators of research manuscripts and proposals in the social and behavioral sciences, and beyond. Its thirty-one uniquely structured chapters cover both traditional and emerging methods of quantitative data analysis, which neither junior nor veteran reviewers can be expected to know in detail. The book updates readers on each technique’s key principles, appropriate usage, underlying assumptions, and limitations. It thereby assists reviewers to offer constructive commentary on works they evaluate, and also serves as an indispensable author’s reference for preparing sound research manuscripts and proposals. Key features include: The chapters cover virtually all of the popular classic and emerging quantitative techniques, thus helping reviewers to evaluate a manuscript’s methodological approach and its data analysis. In addition, the volume serves as an indispensable reference tool for those designing their own research. For ease of use, all chapters follow the same structure: the opening page of each chapter defines and explains the purpose of that statistical method the next one or two pages provide a table listing various criteria that should be considered when evaluating and applying that methodological approach to data analysis the remainder of each chapter contains numbered sections corresponding to the numbered criteria listed in the opening table. Each section explains the role and importance of that particular criterion. Chapters are written by methodological and applied scholars who are expert in the particular quantitative method being reviewed.

The Reviewer S Guide To Quantitative Methods In The Social Sciences

Author: Gregory R. Hancock
Publisher: Routledge
ISBN: 0203861558
Size: 26.63 MB
Format: PDF, ePub, Mobi
View: 6883
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The Reviewer’s Guide to Quantitative Methods in the Social Sciences is designed for evaluators of research manuscripts and proposals in the social and behavioral sciences, and beyond. Its thirty-one uniquely structured chapters cover both traditional and emerging methods of quantitative data analysis, which neither junior nor veteran reviewers can be expected to know in detail. The book updates readers on each technique’s key principles, appropriate usage, underlying assumptions, and limitations. It thereby assists reviewers to offer constructive commentary on works they evaluate, and also serves as an indispensable author’s reference for preparing sound research manuscripts and proposals. Key features include: The chapters cover virtually all of the popular classic and emerging quantitative techniques, thus helping reviewers to evaluate a manuscript’s methodological approach and its data analysis. In addition, the volume serves as an indispensable reference tool for those designing their own research. For ease of use, all chapters follow the same structure: the opening page of each chapter defines and explains the purpose of that statistical method the next one or two pages provide a table listing various criteria that should be considered when evaluating and applying that methodological approach to data analysis the remainder of each chapter contains numbered sections corresponding to the numbered criteria listed in the opening table. Each section explains the role and importance of that particular criterion. Chapters are written by methodological and applied scholars who are expert in the particular quantitative method being reviewed.

Doing Survey Research

Author: Peter M. Nardi
Publisher: Routledge
ISBN: 1351697242
Size: 37.22 MB
Format: PDF, Kindle
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Each day we are faced with continuing claims made by media pundits, politicians, teachers, and friends, often quoting research. Consider also the numerous comments and posts on Internet blogs, Twitter, and Facebook that illustrate the confusion between opinion and factual data. How do we learn to interpret the research we hear about and read, to distinguish opinions from scientific facts, and to use this knowledge to conduct our own studies to answer the questions faced in everyday situations? Understanding the components that go into scientific research and learning how to do research, make decisions about which statistics to use, and analyze statistical findings are goals for everyone in today's research-oriented world. Questions about the reliability and validity of data from a study or public opinion poll come up routinely and need critical review. This book contributes to achieving these objectives. Doing Survey Research is intended for people who want to learn how to conduct quantitative studies for a project in an undergraduate course, a graduate-level thesis, or a survey that an employer may want completed. This brief, practical textbook prepares beginners to conduct their own survey research and write up the results, as well as read and interpret other people's research. It combines survey design with data analysis and interpretation. And it is for those who need to understand and critically interpret survey research found in scholarly journals, reports distributed in the workplace, and social scientific findings presented online in the media, on a blog, or in social media postings. Essential new updates to this edition include coverage of Big Data, Meta-Analysis, and A/B testing methodology—methods used by scholars as well as businesses like Netflix and Amazon. New to this Fourth Edition Each chapter and its exercises feature updated data and illustrations from current academic and popular articles relevant to today’s web-oriented students, including studies focused on topics related to social media. Update web site http://doingsurveyresearch.wordpress.com/ New Coverage of Big Data (used by popular web sites like Amazon and Netflix) and the ethical issues which emerge not only about privacy, but also how it relates to the methods discussed in this book about sampling, probability, and research design. New coverage of meta-data, and the increasingly popular method in many professional and other settings.

Quantitative Social Science

Author: Kosuke Imai
Publisher: Princeton University Press
ISBN: 1400885256
Size: 10.90 MB
Format: PDF, Kindle
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Quantitative analysis is an increasingly essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it—or if they do, they usually end up in statistics classes that offer few insights into their field. This textbook is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, such as economics, sociology, public policy, and data science. Quantitative Social Science engages directly with empirical analysis, showing students how to analyze data using the R programming language and to interpret the results—it encourages hands-on learning, not paper-and-pencil statistics. More than forty data sets taken directly from leading quantitative social science research illustrate how data analysis can be used to answer important questions about society and human behavior. Proven in the classroom, this one-of-a-kind textbook features numerous additional data analysis exercises and interactive R programming exercises, and also comes with supplementary teaching materials for instructors. Written especially for students in the social sciences and allied fields, including economics, sociology, public policy, and data science Provides hands-on instruction using R programming, not paper-and-pencil statistics Includes more than forty data sets from actual research for students to test their skills on Covers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools Features a wealth of supplementary exercises, including additional data analysis exercises and interactive programming exercises Offers a solid foundation for further study Comes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides

Handbook Of Research Methods

Author: Natalie L. Sproull
Publisher: Scarecrow Press
ISBN: 9780810844865
Size: 25.58 MB
Format: PDF, Docs
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Designed for researchers, managers, and administrators who make research-based decisions, as well as students of the social sciences and business. The entire research process, from variables to final report, is covered step by step.

The Sage Handbook Of Quantitative Methodology For The Social Sciences

Author: David Kaplan
Publisher: SAGE Publications
ISBN: 1483365875
Size: 18.12 MB
Format: PDF, Mobi
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The SAGE Handbook of Quantitative Methodology for the Social Sciences is the definitive reference for teachers, students, and researchers of quantitative methods in the social sciences, as it provides a comprehensive overview of the major techniques used in the field. The contributors, top methodologists and researchers, have written about their areas of expertise in ways that convey the utility of their respective techniques, but, where appropriate, they also offer a fair critique of these techniques. Relevance to real-world problems in the social sciences is an essential ingredient of each chapter and makes this an invaluable resource.

Handbook Of Ethics In Quantitative Methodology

Author: A. T. Panter
Publisher: Routledge
ISBN: 1136888721
Size: 74.48 MB
Format: PDF
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This comprehensive Handbook is the first to provide a practical, interdisciplinary review of ethical issues as they relate to quantitative methodology including how to present evidence for reliability and validity, what comprises an adequate tested population, and what constitutes scientific knowledge for eliminating biases. The book uses an ethical framework that emphasizes the human cost of quantitative decision making to help researchers understand the specific implications of their choices. The order of the Handbook chapters parallels the chronology of the research process: determining the research design and data collection; data analysis; and communicating findings. Each chapter: Explores the ethics of a particular topic Identifies prevailing methodological issues Reviews strategies and approaches for handling such issues and their ethical implications Provides one or more case examples Outlines plausible approaches to the issue including best-practice solutions. Part 1 presents ethical frameworks that cross-cut design, analysis, and modeling in the behavioral sciences. Part 2 focuses on ideas for disseminating ethical training in statistics courses. Part 3 considers the ethical aspects of selecting measurement instruments and sample size planning and explores issues related to high stakes testing, the defensibility of experimental vs. quasi-experimental research designs, and ethics in program evaluation. Decision points that shape a researchers’ approach to data analysis are examined in Part 4 – when and why analysts need to account for how the sample was selected, how to evaluate tradeoffs of hypothesis-testing vs. estimation, and how to handle missing data. Ethical issues that arise when using techniques such as factor analysis or multilevel modeling and when making causal inferences are also explored. The book concludes with ethical aspects of reporting meta-analyses, of cross-disciplinary statistical reform, and of the publication process. This Handbook appeals to researchers and practitioners in psychology, human development, family studies, health, education, sociology, social work, political science, and business/marketing. This book is also a valuable supplement for quantitative methods courses required of all graduate students in these fields.

Big Data And Social Science

Author: Ian Foster
Publisher: CRC Press
ISBN: 1498751431
Size: 61.73 MB
Format: PDF, Docs
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Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.