Quantitative Social Science An Introduction

  quantitative social science an introduction: Quantitative Social Science Kosuke Imai, 2018-02-09 An introductory textbook on data analysis and statistics written especially for students in the social sciences and allied fields 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 Looking for a more accessible introduction? Consider Data Analysis for Social Science by Elena Llaudet and Kosuke Imai, which teaches from scratch and step-by-step the fundamentals of survey research, predictive models, and causal inference. It covers descriptive statistics, the difference-in-means estimator, simple linear regression, and multiple linear regression.
  quantitative social science an introduction: Quantitative Social Science Kosuke Imai, Nora Webb Williams, 2022-07-05 A tidyverse edition of the acclaimed textbook on data analysis and statistics for the social sciences and allied fields Quantitative analysis is an essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it. Quantitative Social Science is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, including business, economics, education, political science, psychology, sociology, public policy, and data science. Proven in classrooms around the world, this one-of-a-kind textbook engages directly with empirical analysis, showing students how to analyze and interpret data using the tidyverse family of R packages. Data sets taken directly from leading quantitative social science research illustrate how to use data analysis to answer important questions about society and human behavior. Emphasizes hands-on learning, not paper-and-pencil statistics Includes 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 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
  quantitative social science an introduction: Quantitative Social Science Data with R Brian J. Fogarty, 2018-11-24 Relevant, engaging, and packed with student-focused learning features, this book provides the basic step-by-step introduction to quantitative research and data every student needs.
  quantitative social science an introduction: Data Analysis for Social Science Elena Llaudet, Kosuke Imai, 2022-11-29 Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors--
  quantitative social science an introduction: Quantitative Methods for the Social Sciences Daniel Stockemer, 2018-11-19 This textbook offers an essential introduction to survey research and quantitative methods. Building on the premise that statistical methods need to be learned in a practical fashion, the book guides students through the various steps of the survey research process and helps to apply those steps toward a real example. In detail, the textbook introduces students to the four pillars of survey research and quantitative analysis: (1) the importance of survey research, (2) preparing a survey, (3) conducting a survey and (4) analyzing a survey. Students are shown how to create their own questionnaire based on some theoretically derived hypotheses to achieve empirical findings for a solid dataset. Lastly, they use said data to test their hypotheses in a bivariate and multivariate realm. The book explains the theory, rationale and mathematical foundations of these tests. In addition, it provides clear instructions on how to conduct the tests in SPSS and Stata. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research or quantitative methods classes in the social sciences.
  quantitative social science an introduction: The SAGE Handbook of Quantitative Methodology for the Social Sciences David Kaplan, 2004-06-21 Quantitative methodology is a highly specialized field, and as with any highly specialized field, working through idiosyncratic language can be very difficult made even more so when concepts are conveyed in the language of mathematics and statistics. The Sage Handbook of Quantitative Methodology for the Social Sciences was conceived as a way of introducing applied statisticians, empirical researchers, and graduate students to the broad array of state-of-the-art quantitative methodologies in the social sciences. The contributing authors of the Handbook were asked to write about their areas of expertise in a way that would convey to the reader the utility of their respective methodologies. Relevance to real-world problems in the social sciences is an essential ingredient of each chapter. The Handbook consists of six sections comprising twenty-five chapters, from topics in scaling and measurement, to advances in statistical modelling methodologies, and finally to broad philosophical themes that transcend many of the quantitative methodologies covered in this handbook.
  quantitative social science an introduction: Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences Michael J. Albers, 2017-04-03 Guides readers through the quantitative data analysis process including contextualizing data within a research situation, connecting data to the appropriate statistical tests, and drawing valid conclusions Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences presents a clear and accessible introduction to the basics of quantitative data analysis and focuses on how to use statistical tests as a key tool for analyzing research data. The book presents the entire data analysis process as a cyclical, multiphase process and addresses the processes of exploratory analysis, decision-making for performing parametric or nonparametric analysis, and practical significance determination. In addition, the author details how data analysis is used to reveal the underlying patterns and relationships between the variables and connects those trends to the data’s contextual situation. Filling the gap in quantitative data analysis literature, this book teaches the methods and thought processes behind data analysis, rather than how to perform the study itself or how to perform individual statistical tests. With a clear and conversational style, readers are provided with a better understanding of the overall structure and methodology behind performing a data analysis as well as the needed techniques to make informed, meaningful decisions during data analysis. The book features numerous data analysis examples in order to emphasize the decision and thought processes that are best followed, and self-contained sections throughout separate the statistical data analysis from the detailed discussion of the concepts allowing readers to reference a specific section of the book for immediate solutions to problems and/or applications. Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences also features coverage of the following: • The overall methodology and research mind-set for how to approach quantitative data analysis and how to use statistics tests as part of research data analysis • A comprehensive understanding of the data, its connection to a research situation, and the most appropriate statistical tests for the data • Numerous data analysis problems and worked-out examples to illustrate the decision and thought processes that reveal underlying patterns and trends • Detailed examples of the main concepts to aid readers in gaining the needed skills to perform a full analysis of research problems • A conversational tone to effectively introduce readers to the basics of how to perform data analysis as well as make meaningful decisions during data analysis Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences is an ideal textbook for upper-undergraduate and graduate-level research method courses in the behavioral and social sciences, statistics, and engineering. This book is also an appropriate reference for practitioners who require a review of quantitative research methods. Michael J. Albers, Ph.D., is Professor in the Department of English at East Carolina University. His research interests include information design with a focus on answering real-world questions, the presentation of complex information, and human–information interaction. Dr. Albers received his Ph.D. in Technical Communication and Rhetoric from Texas Tech University.
  quantitative social science an introduction: Doing Quantitative Research in the Social Sciences Thomas R Black, 1999-03-30 This original textbook provides a comprehensive and integrated approach to using quantitative methods in the social sciences. Thomas R Black guides the student and researcher through the minefield of potential problems that may be confronted, and it is this emphasis on the practical that distinguishes his book from others which focus exclusively on either research design and measurement or statistical methods. Focusing on the design and execution of research, key topics such as planning, sampling, the design of measuring instruments, choice of statistical text and interpretation of results are examined within the context of the research process. In a lively and accessible style, the student is introduced to researc design issues alongside statistical procedures and encouraged to develop analytical and decision-making skills.
  quantitative social science an introduction: Introduction to Social Research Keith F Punch, 2005-03-15 `This book offers an excellent description of quantitative and qualitative design and analysis taught in the context of three inquiry pathways: knowledge development, social inquiry, and social research. Furthermore, it provides an excellent overview of both quantitative and qualitative methods with regard to their different epistemologies, methods and techniques. Additionally, Punch provides (a) information guiding students in the use of computers for quantitative and qualitative analysis and (b) a wide range of illustrative examples to give the book a practical flavour.... I would not hesitate to recommend it to my undergraduate students' - Forum: Qualitative Social Research (www.qualitative-research.net) `A carefully crafted introduction to social research methodology. The author guides the reader through the research process in a comprehensive and logical way which is particularly helpful for the new researcher. A great resource for anyone involved in social research - novice or experienced' - Dr Mary Kellett, Open University Building on the success of An Introduction to Social Research, this Second Edition has been fully revised and updated to provide a broader coverage of a range of methodological approaches for third year and postgraduate students across the social sciences. New features include: - Wider coverage of qualitative research methods, including sections on action research and discourse analysis. - More pedagogical features such as student exercises and illustrative examples to ensure this is a practical, student-friendly guide. - More in-depth examination of the ethical issues involved in social research. A comprehensive and accessible introduction to qualitative, quantitative and mixed empirical methods, An Introduction to Social Research is an ideal starting point for all students and researchers in the social sciences.
  quantitative social science an introduction: Introduction to Quantitative Research Methods Mark Balnaves, Peter Caputi, 2001-04-10 Introduction to Quantitative Research Methods is a student-friendly introduction to quantitative research methods and basic statistics. It uses a detective theme throughout the text to show how quantitative methods have been used to solve real-life problems. The book focuses on principles and techniques that are appropriate to introductory level courses in media, psychology and sociology. Examples and illustrations are drawn from historical and contemporary research in the social sciences. The original CD-ROM accompanying the book and its content are no longer available.
  quantitative social science an introduction: Quantitative Corpus Linguistics with R Stefan Th. Gries, 2009-03-04 The first textbook of its kind, Quantitative Corpus Linguistics with R demonstrates how to use the open source programming language R for corpus linguistic analyses. Computational and corpus linguists doing corpus work will find that R provides an enormous range of functions that currently require several programs to achieve – searching and processing corpora, arranging and outputting the results of corpus searches, statistical evaluation, and graphing.
  quantitative social science an introduction: Relating Statistics and Experimental Design Irwin P. Levin, 1999-02 This handy guide gives the novice researcher a clear description of the standard tools of the trade. Unlike some texts which focus on either design or statistics, this book covers the fundamentals of design, together with experiments and observational methods. There is an exposition of major tests of significance with formulas plus easy verbal interpretations, and boxes embedded in the text contain prototypic applications.
  quantitative social science an introduction: Applied Quantitative Analysis in Education and the Social Sciences Yaacov Petscher, Christopher Schatschneider, Donald L. Compton, 2013-03-05 To say that complex data analyses are ubiquitous in the education and social sciences might be an understatement. Funding agencies and peer-review journals alike require that researchers use the most appropriate models and methods for explaining phenomena. Univariate and multivariate data structures often require the application of more rigorous methods than basic correlational or analysis of variance models. Additionally, though a vast set of resources may exist on how to run analysis, difficulties may be encountered when explicit direction is not provided as to how one should run a model and interpret results. The mission of this book is to expose the reader to advanced quantitative methods as it pertains to individual level analysis, multilevel analysis, item-level analysis, and covariance structure analysis. Each chapter is self-contained and follows a common format so that readers can run the analysis and correctly interpret the output for reporting.
  quantitative social science an introduction: Processing Data Linda Brookover Bourque, Virginia Clark, 1992-06-06 This volume highlights the theory that decisions made during the design of a data collection instrument influence the kind of data and the format of the data that are available for analysis. Opening with a discussion on the selection of the data collection technique(s) and how this impacts on data processing and the data for later analysis, the book covers key issues such as: should you create your own instrument for a questionnaire? how do you test a questionnaire? what are the characteristics of good data processing? how to deal with missing data? how to scale an evaluation and create subfiles for analysis? In addition, each major section concludes with examples and when appropriate, directs the reader to commonly available computer software that can aid in data processing.
  quantitative social science an introduction: Multi-Method Social Science Jason Seawright, 2016-09-08 This book provides the first systematic guide to designing multi-method research, considering a wide range of statistical and qualitative tools.
  quantitative social science an introduction: Data Visualization Kieran Healy, 2018-12-18 An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions
  quantitative social science an introduction: A Gentle Introduction to Effective Computing in Quantitative Research Harry J. Paarsch, Konstantin Golyaev, 2016-05-06 A practical guide to using modern software effectively in quantitative research in the social and natural sciences. This book offers a practical guide to the computational methods at the heart of most modern quantitative research. It will be essential reading for research assistants needing hands-on experience; students entering PhD programs in business, economics, and other social or natural sciences; and those seeking quantitative jobs in industry. No background in computer science is assumed; a learner need only have a computer with access to the Internet. Using the example as its principal pedagogical device, the book offers tried-and-true prototypes that illustrate many important computational tasks required in quantitative research. The best way to use the book is to read it at the computer keyboard and learn by doing. The book begins by introducing basic skills: how to use the operating system, how to organize data, and how to complete simple programming tasks. For its demonstrations, the book uses a UNIX-based operating system and a set of free software tools: the scripting language Python for programming tasks; the database management system SQLite; and the freely available R for statistical computing and graphics. The book goes on to describe particular tasks: analyzing data, implementing commonly used numerical and simulation methods, and creating extensions to Python to reduce cycle time. Finally, the book describes the use of LaTeX, a document markup language and preparation system.
  quantitative social science an introduction: Social Science Research Anol Bhattacherjee, 2012-04-01 This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.
  quantitative social science an introduction: Introduction to the Comparative Method With Boolean Algebra Daniele Caramani, 2009 Utilizing a systematic, broad approach, Introduction to the Comparative Method With Boolean Algebra gives readers the logical foundations of comparison with guided applications and is the ultimate comparative method text covering each of the current and most important issues in the field. Author Daniele Caramani discusses the elements of scientific research, including Mill's methods, Boolean algebra, classification and typologization, and necessary and sufficient conditions, and how these apply to concrete research in the social sciences. This text is indispensable for upper-level undergraduate and graduate students as well as researchers interested in methodology, behavioral and social sciences, history, and logic.--BOOK JACKET.
  quantitative social science an introduction: Applied Meta-Analysis for Social Science Research Noel A. Card, 2015-10-06 Offering pragmatic guidance for planning and conducting a meta-analytic review, this book is written in an engaging, nontechnical style that makes it ideal for graduate course use or self-study. The author shows how to identify questions that can be answered using meta-analysis, retrieve both published and unpublished studies, create a coding manual, use traditional and unique effect size indices, and write a meta-analytic review. An ongoing example illustrates meta-analytic techniques. In addition to the fundamentals, the book discusses more advanced topics, such as artifact correction, random- and mixed-effects models, structural equation representations, and multivariate procedures. User-friendly features include annotated equations; discussions of alternative approaches; and Practical Matters sections that give advice on topics not often discussed in other books, such as linking meta-analytic results with theory and the utility of meta-analysis software programs. ÿ
  quantitative social science an introduction: Introduction to Webometrics Michael Thelwall, 2022-05-31 Webometrics is concerned with measuring aspects of the web: web sites, web pages, parts of web pages, words in web pages, hyperlinks, web search engine results. The importance of the web itself as a communication medium and for hosting an increasingly wide array of documents, from journal articles to holiday brochures, needs no introduction. Given this huge and easily accessible source of information, there are limitless possibilities for measuring or counting on a huge scale (e.g., the number of web sites, the number of web pages, the number of blogs) or on a smaller scale (e.g., the number of web sites in Ireland, the number of web pages in the CNN web site, the number of blogs mentioning Barack Obama before the 2008 presidential campaign). This book argues that it can be useful for social scientists to measure aspects of the web and explains how this can be achieved on both a small and large scale. The book is intended for social scientists with research topics that are wholly or partly online (e.g., social networks, news, political communication) and social scientists with offline research topics with an online reflection, even if this is not a core component (e.g., diaspora communities, consumer culture, linguistic change). The book is also intended for library and information science students in the belief that the knowledge and techniques described will be useful for them to guide and aid other social scientists in their research. In addition, the techniques and issues are all directly relevant to library and information science research problems. Table of Contents: Introduction / Web Impact Assessment / Link Analysis / Blog Searching / Automatic Search Engine Searches: LexiURL Searcher / Web Crawling: SocSciBot / Search Engines and Data Reliability / Tracking User Actions Online / Advaned Techniques / Summary and Future Directions
  quantitative social science an introduction: Introduction to Time Series Analysis Mark Pickup, 2014-10-15 Introducing time series methods and their application in social science research, this practical guide to time series models is the first in the field written for a non-econometrics audience. Giving readers the tools they need to apply models to their own research, Introduction to Time Series Analysis, by Mark Pickup, demonstrates the use of—and the assumptions underlying—common models of time series data including finite distributed lag; autoregressive distributed lag; moving average; differenced data; and GARCH, ARMA, ARIMA, and error correction models. “This volume does an excellent job of introducing modern time series analysis to social scientists who are already familiar with basic statistics and the general linear model.” —William G. Jacoby, Michigan State University
  quantitative social science an introduction: A Tale of Two Cultures Gary Goertz, James Mahoney, 2012-09-09 Some in the social sciences argue that the same logic applies to both qualitative and quantitative methods. In A Tale of Two Cultures, Gary Goertz and James Mahoney demonstrate that these two paradigms constitute different cultures, each internally coherent yet marked by contrasting norms, practices, and toolkits. They identify and discuss major differences between these two traditions that touch nearly every aspect of social science research, including design, goals, causal effects and models, concepts and measurement, data analysis, and case selection. Although focused on the differences between qualitative and quantitative research, Goertz and Mahoney also seek to promote toleration, exchange, and learning by enabling scholars to think beyond their own culture and see an alternative scientific worldview. This book is written in an easily accessible style and features a host of real-world examples to illustrate methodological points.
  quantitative social science an introduction: Quantitative Methods in the Humanities Claire Lemercier, Claire Zalc, 2019 This timely and lucid guide is intended for students and scholars working on all historical periods and topics in the humanities and social sciences--especially for those who do not think of themselves as experts in quantification, big data, or digital humanities. The authors reveal quantification to be a powerful and versatile tool, applicable to a myriad of materials from the past. Their book, accessible to complete beginners, offers detailed advice and practical tips on how to build a dataset from historical sources and how to categorize it according to specific research questions. Drawing on examples from works in social, political, economic, and cultural history, the book guides readers through a wide range of methods, including sampling, cross-tabulations, statistical tests, regression, factor analysis, network analysis, sequence analysis, event history analysis, geographical information systems, text analysis, and visualization. The requirements, advantages, and pitfalls of these techniques are presented in layperson's terms, avoiding mathematical terminology. Conceived primarily for historians, the book will prove invaluable to other humanists, as well as to social scientists looking for a nontechnical introduction to quantitative methods. Covering the most recent techniques, in addition to others not often enough discussed, the book will also have much to offer to the most seasoned practitioners of quantification.
  quantitative social science an introduction: Quantitative Data Analysis Using Spss: An Introduction For Health And Social Sciences Greasley, Pete, 2007-12-01 Designed for the complete novice, this title guides you through a sample analysis of survey data and shows you step-by-step how to use SPSS to complete it.
  quantitative social science an introduction: Social Science Methodology John Gerring, 2011-12-15 John Gerring's exceptional textbook has been thoroughly revised in this second edition. It offers a one-volume introduction to social science methodology relevant to the disciplines of anthropology, economics, history, political science, psychology and sociology. This new edition has been extensively developed with the introduction of new material and a thorough treatment of essential elements such as conceptualization, measurement, causality and research design. It is written for students, long-time practitioners and methodologists and covers both qualitative and quantitative methods. It synthesizes the vast and diverse field of methodology in a way that is clear, concise and comprehensive. While offering a handy overview of the subject, the book is also an argument about how we should conceptualize methodological problems. Thinking about methodology through this lens provides a new framework for understanding work in the social sciences.
  quantitative social science an introduction: The SAGE Encyclopedia of Social Science Research Methods Michael Lewis-Beck, Alan E Bryman, Tim Futing Liao, 2004 Featuring over 900 entries, this resource covers all disciplines within the social sciences with both concise definitions & in-depth essays.
  quantitative social science an introduction: Thinking Clearly with Data Ethan Bueno de Mesquita, Anthony Fowler, 2021-11-16 An engaging introduction to data science that emphasizes critical thinking over statistical techniques An introduction to data science or statistics shouldn’t involve proving complex theorems or memorizing obscure terms and formulas, but that is exactly what most introductory quantitative textbooks emphasize. In contrast, Thinking Clearly with Data focuses, first and foremost, on critical thinking and conceptual understanding in order to teach students how to be better consumers and analysts of the kinds of quantitative information and arguments that they will encounter throughout their lives. Among much else, the book teaches how to assess whether an observed relationship in data reflects a genuine relationship in the world and, if so, whether it is causal; how to make the most informative comparisons for answering questions; what questions to ask others who are making arguments using quantitative evidence; which statistics are particularly informative or misleading; how quantitative evidence should and shouldn’t influence decision-making; and how to make better decisions by using moral values as well as data. Filled with real-world examples, the book shows how its thinking tools apply to problems in a wide variety of subjects, including elections, civil conflict, crime, terrorism, financial crises, health care, sports, music, and space travel. Above all else, Thinking Clearly with Data demonstrates why, despite the many benefits of our data-driven age, data can never be a substitute for thinking. An ideal textbook for introductory quantitative methods courses in data science, statistics, political science, economics, psychology, sociology, public policy, and other fields Introduces the basic toolkit of data analysis—including sampling, hypothesis testing, Bayesian inference, regression, experiments, instrumental variables, differences in differences, and regression discontinuity Uses real-world examples and data from a wide variety of subjects Includes practice questions and data exercises
  quantitative social science an introduction: Analyzing Quantitative Data Debra Wetcher-Hendricks, 2014-08-21 A user-friendly, hands-on guide to recognizing and conducting proper research techniques in data collection Offering a unique approach to numerical research methods, Analyzing Quantitative Data: An Introduction for Social Researchers presents readers with the necessary statistical applications for carrying out the key phases of conducting and evaluating a research project. The book guides readers through the steps of data analysis, from organizing raw data to utilizing descriptive statistics and tests of significance, drawing valid conclusions, and writing research reports. The author successfully provides a presentation that is accessible and hands-on rather than heavily theoretical, outlining the key quantitative processes and the use of software to successfully draw valid conclusions from gathered data. In its discussion of methods for organizing data, the book includes suggestions for coding and entry into spreadsheets or databases while also introducing commonly used descriptive statistics and clarifying their roles in data analysis. Next, inferential statistics is explored in-depth with explanations of and instructions for performing chi-square tests, t-tests, analyses of variance, correlation and regression analyses, and a number of advanced statistical procedures. Each chapter contains explanations of when to use the tests described, relevant formulas, and sample computations. The book concludes with guidance on extracting meaningful conclusions from statistical tests and writing research reports that describe procedures and analyses. Throughout the book, Statistical Resources for SPSS® sections provide fundamental instruction for using SPSS® to obtain the results presented. Where necessary, the author provides basic theoretical explanations for distributions and background information regarding formulas. Each chapter concludes with practice problems, and a related website features derivations of the book's formulas along with additional resources for performing the discussed processes. Analyzing Quantitative Data is an excellent book for social sciences courses on data analysis and research methods at the upper-undergraduate and graduate levels. It also serves as a valuable reference for applied statisticians and practitioners working in the fields of education, medicine, business and public service who analyze, interpret, and evaluate data in their daily work.
  quantitative social science an introduction: Quantitative Tourism Industry Analysis Tadayuki Hara, 2008-09-10 Quantitative Tourism Industry Analysis is the first book to deal with the input-output, social accounting matrix in a way which readers from a non-economics or non-mathematical background can follow, in order to understand how useful their application would be for tourism industry analysis. It acquaints readers with useful applications of economic modelling without the unnecessary burden of higher algebra, so that they will understand concepts of the economics measurement system, Tourism Satellite Accounts (TSA) methodology. Quantitative Tourism Industry Analysis offers a new set of economic tools for tourism policy analysis, ideal for those with a non-mathematical background.
  quantitative social science an introduction: Applied Social Science Methodology John Gerring, Dino Christenson, 2017-04-27 An innovative textbook introducing a variety of social science methodologies applicable to a range of social and political science disciplines.
  quantitative social science an introduction: Best Practices in Quantitative Methods Jason W. Osborne, 2008 The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the best choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.
  quantitative social science an introduction: Doing Quantitative Research in Education with SPSS Daniel Muijs, 2010-12-31 This accessible and authoritative introduction is essential for education students and researchers needing to use quantitative methods for the first time. Using datasets from real-life educational research and avoiding the use of mathematical formulae, the author guides students through the essential techniques that they will need to know, explaining each procedure using the latest version of SPSS. The datasets can also be downloaded from the book′s website, enabling students to practice the techniques for themselves. This revised and updated second edition now also includes more advanced methods such as log linear analysis, logistic regression, and canonical correlation. Written specifically for those with no prior experience of quantitative research, this book is ideal for education students and researchers in this field.
  quantitative social science an introduction: Applying Social Statistics Jay Alan Weinstein, 2010-01-15 While Applying Social Statistics is 'about' social statistics and includes all of the topics generally covered in similar texts, it is first and foremost a book about how sociologists use statistics. Its emphasis is on statistical reasoning in sociology and on showing how these principles can be applied to numerous problems in a wide variety of contexts; to answer effectively the question 'what's it for.' A main learning objective is to help students understand how and why social statistics is used. Yet, Weinstein's style and substance recognize that it is of equal-or even greater-importance that they begin to learn how to apply these principles and techniques themselves.
  quantitative social science an introduction: Missing Data Patrick E. McKnight, Katherine M. McKnight, Souraya Sidani, Aurelio José Figueredo, 2007-03-28 While most books on missing data focus on applying sophisticated statistical techniques to deal with the problem after it has occurred, this volume provides a methodology for the control and prevention of missing data. In clear, nontechnical language, the authors help the reader understand the different types of missing data and their implications for the reliability, validity, and generalizability of a study’s conclusions. They provide practical recommendations for designing studies that decrease the likelihood of missing data, and for addressing this important issue when reporting study results. When statistical remedies are needed--such as deletion procedures, augmentation methods, and single imputation and multiple imputation procedures--the book also explains how to make sound decisions about their use. Patrick E. McKnight's website offers a periodically updated annotated bibliography on missing data and links to other Web resources that address missing data.
  quantitative social science an introduction: Advances in Social Science Research Using R Hrishikesh D. Vinod, 2009-12-24 Quantitative social science research has been expanding due to the ava- ability of computers and data over the past few decades. Yet the textbooks and supplements for researchers do not adequately highlight the revolution created by the R software [2] and graphics system. R is fast becoming the l- gua franca of quantitative research with some 2000 free specialized packages, where the latest versions can be downloaded in seconds. Many packages such as “car” [1] developed by social scientists are popular among all scientists. An early 2009 article [3] in the New York Times notes that statisticians, engineers and scientists without computer programming skills ?nd R “easy to use.” A common language R can readily promote deeper mutual respect and understanding of unique problems facing quantitative work in various social sciences. Often the solutions developed in one ?eld can be extended and used in many ?elds. This book promotes just such exchange of ideas across many social sciences. Since Springer has played a leadership role in promoting R, we are fortunate to have Springer publish this book. A Conference on Quantitative Social Science Research Using R was held in New York City at the Lincoln Center campus of Fordham University, June 18–19, 2009. This book contains selected papers presented at the conference, representing the “Proceedings” of the conference.
  quantitative social science an introduction: Social Research Methods H. Russell Bernard, 2013 Bernard does an excellent job of not only showing how to practice research, but also provides a detailed discussion of broader historical and philosophical contexts that are important for understanding research.
  quantitative social science an introduction: Measurement Theory and Applications for the Social Sciences Deborah L. Bandalos, 2018-01-31 Which types of validity evidence should be considered when determining whether a scale is appropriate for a given measurement situation? What about reliability evidence? Using clear explanations illustrated by examples from across the social and behavioral sciences, this engaging text prepares students to make effective decisions about the selection, administration, scoring, interpretation, and development of measurement instruments. Coverage includes the essential measurement topics of scale development, item writing and analysis, and reliability and validity, as well as more advanced topics such as exploratory and confirmatory factor analysis, item response theory, diagnostic classification models, test bias and fairness, standard setting, and equating. End-of-chapter exercises (with answers) emphasize both computations and conceptual understanding to encourage readers to think critically about the material. ÿ
  quantitative social science an introduction: Quantitative Geography Richard Harris, 2016-09-13 Numerical data are everywhere. Charts and statistics appear not just in geography journals but also in the media, in public policy, and in business and commerce too. To engage with quantitative geography, we must engage with the quantitative methods used to collect, analyse, present and interpret these data. Quantitative Geography: The Basics is the perfect introduction for undergraduates beginning any quantitative methods course. Written in short, user-friendly chapters with full-colour diagrams, the book guides the reader through a wide range of topics from the basic to the more advanced, including: Statistics Maths Graphics Models Mapping and GIS R Closely aligned with the Q-Step quantitative social science programme, Quantitative Geography: The Basics is the ideal starting point for understanding and exploring this fundamental area of Geography.
  quantitative social science an introduction: Quantitative Methods in Social Science Research Stephen Gorard, 2003-10-01 This clever scheme builds on Gorard's previous book, Quantitative Methods in Educational Research. He has revised the original book in the light of experience and feedback, and has reworked it so that it includes more social science examples. Four chapters are entirely new.
BSc in Quantitative Social Analysis - HKUST
School of Humanities and Social Science - BSc in Quantitative Social Analysis ... COMP 1021 Introduction to Computer Science 3 COMP 1022P Introduction to Computing with Java 3 COMP 1942 Exploring and Visualizing Data 3 2021-22 QSA (4Y) (2021-22 intake) Page 1.

Introduction to Quantitative Social Science Kosuke Imai Harvard ...
Introduction to Quantitative Social Science Kosuke Imai Harvard University / University of Tokyo Summer 2022 Intro. to Quantitative Social Science Electoral Polls and Prediciton Todai (Summer 2022)1/24. 2008USPresidentialElection Ahistoricelection firstAfrican-Americanpresident

Quantitative Social Science: An Introduction - WPMU DEV
Quantitative Social Science: An Introduction Kosuke Imai Harvard University November13,2020 1/6

Kosuke Imai - Harvard University
Institute for Quantitative Social Science Phone: 617-384-6778 Harvard University Email: Imai@Harvard.Edu Cambridge, MA 02138 URL: https://imai.fas.harvard.edu ... Kosuke. (2017). Quantitative Social Science: An Introduction. Princeton Univer-sity Press. Translated into Japanese (2018), Chinese (2020), and Korean (2021). 3 April 2024. Kosuke ...

Introduct Ion to Social - SAGE Publications Ltd
the way of doing empirical social science research, was challenged. This challenge accompanied a major growth of interest in using qualitative methods, and this in turn produced a split in the field, between quantitative and qualitative researchers. A prolonged quantitative–qualitative debate ensued, sometimes described as the ‘paradigm ...

POL345/SOC305: Introduction to Quantitative Social Science
This course will teach students how to address these and other social science questions by analyzing quantitative data. The course introduces basic principles of statistical inference and programming skills for data analysis. The goal is to provide students with the foundation necessary to analyze

Introduction to Quantitative Social Science Kosuke Imai Harvard ...
Intro. to Quantitative Social Science Observational Studies Todai (Summer 2022)9/13 Before-and-afterComparison State-specificconfoundersforcross-sectioncomparison

An Introduction to Social Sciences - RAIJMR
Introduction "Social science" is commonly used as an umbrella term to refer to anthropology, archaeology, criminology, economics, education, linguistics, law, communication studies, history, political ... The development of social science subfields became very quantitative in methodology. The interdisciplinary and cross-disciplinary nature of ...

Quantitative Methods in Social Science - The University of …
Quantitative Methods in Social Science About Quantitative Methods in Social Sciences What are quantitative methods? Quantitative methods encompass a range of data skills, from simple statistical analysis to more advanced predictive modelling. The idea behind many quantitative approaches is to understand how and why something has happened and ...

Quantitative Social Science: An Introduction - Chapter one Introduction
Quantitative social science is an interdisciplinary field encompassing a large number of disciplines, including economics, education, political science, public policy, psy- ... how to best utilize the book and presents a brief introduction to R, a popular open-source statistical programming environment. R is freely available for download

SOSC5090: Quantitative Methods to Social Science I - HKUST
Note: QSS stands for Quantitative Social Sciences: An Introduction and JW stands for Introductory Econometrics: A Modern Approach. Ch stands for chapters and Ap stands for Appendix. 1. Week 1: Motivation, Overview and a brief introduction to R (QSS Ch1, JW Ap A) 2. Week 2-3: Causality (QSS Ch2) a. An example of randomized trials b ...

Quantitative Social Science: An Introduction - Chapter 1 Introduction
Introduction In God we trust; all others must bring data. —William Edwards Deming Quantitative social science is an interdisciplinary field encompassing a large number of disciplines, including economics, education, political science, public policy, psy-chology, and sociology. In quantitative social science research, scholars analyze data

Camparison between Qualitative and Quantitative Research
Keyword: Investigation, Methodology, Quantitative, Qualitative, Social Science INTRODUCTION There are different attitudes toward social science possess which facilities new concepts to address subjects inherent in the study of human beings; it …

Introduction to Social Science Methods: An Overview of Quantitative …
Research Design n Identify the problem to be studied n Transform problem into a testable hypothesis/hypotheses n à An idea that will be tested through systematic investigation n Identify the population you need to examine in order to test your hypothesis/hypotheses n Identify the sample you can reasonably access to gather data n Determine the appropriate method for …

PO11Q-15 Introduction to Quantitative Political Analysis I
PO11Q-15 Introduction to Quantitative Political Analysis I 24/25 Department Politics & International Studies Level Undergraduate Level 1 Module leader Florian Reiche Credit value 15 ... Causation and Explanation in Social Science. In R. Goodin (Ed.), The Oxford Handbook of Political Science. Oxford University Press.

The limitations of quantitative social science for informing …
Quantitative social science (QSS) has the potential to make an important contribution to public policy. However it also has a number of limitations, many of which are unknown or ... Introduction QSS has a major role in the policy-making process worldwide (see Johnson and Antill [2011] and Parsons et al [2014] for recent examples from the UK ...

How to Teach Quantitative Methods to Social Science
The Textbook — Quantitative Social Science: An Introduction Combines three essential components: 1 social science research 2 methodological concepts 3 computer programming (using R and RStudio) Teachesdata analysisbefore statistics: 1 Introduction 2 Causality 3 Measurement 4 Prediction 5 Discovery 6 Probability 7 Uncertainty 8 Next Contains about 50 …

Quantitative Social Science An Introduction In Tidyverse
Quantitative Social Science Kosuke Imai,Lori D. Bougher,2021-03-16 Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017.

PUBL0055: Introduction to Quantitative Methods
• This is a course on applied quantitative research methods • Focus on the developing intuition about quantitative methods • Focus on using these methods to answer social science questions • This course is different to other similar courses • Stronger focus …

PART I. MODELS AND METHODS IN THE SOCIAL SCIENCES
The seven parts of this book cover different examples of quantitative reasoning in social science applications, along with interspersed discussions on the role of quantitative theories and methods in understanding the social world. We are trying to show how researchers in different social sciences think about and use quanti-tative ideas.

BSc in Quantitative Social Analysis - HKUST
School of Humanities and Social Science - BSc in Quantitative Social Analysis COMP Note: COMP 1021 OR COMP 1022P 3 COMP 1021 Introduction to Computer Science 3 COMP 1022P Introduction to Computing with Java 3 Elective(s) Minimum credit(s) required SOSC Social Science Electives (8 courses from the specified elective 24 list.

Research Methods for the Social Sciences: An Introduction
13 Feb 2020 · 1.5 Research Paradigms in Social Science. 1.5 Research Paradigms in Social Science. 1.5 Research Paradigms in Social Science. 1.6 Inductive Approaches to Research. 1.6 Inductive Approaches to Research

A Practical Introduction to Regression Discontinuity Designs: …
quantitative-and-computational-methods-social-science ∗ Department of Operations Research and Financial Engineering, Princeton University. † Department of Political Science, University of Pennsylvania.

Political Science 2580 INTRODUCTION TO QUANTITATIVE …
Imai, K. (2017). Quantitative Social Science: An Introduction. Princeton, NJ: Princeton University Press The primary textbook on which the course is structured. Most chapters are spread over multiple weeks. You should read this text with your laptop and R Studio open. Execute the code in the main text and ideally try to complete the assignments and

Quantitative Methods For The Social Sciences A
Quantitative Social Science: An Introduction - Chapter one … Quantitative social science is an interdisciplinary field encompassing a large number of disciplines, including economics, education, political science, public policy, psy-chology, and … Quantitative Analysis Statistics Notes Quantitative Social Science is a practical ...

PART I DOING SOCIAL RESEARCH - SAGE Publications Ltd
• theories and findings from social science. Because social science is a very ‘reflexive’ activity, new findings often lead to new ideas about how to go about researching the social world. • practical constraints on conducting actual research. Whatever the philosophical position we might start from, or the social science idea that ...

COURSE OUTLINE - NTU Singapore
HA2027 Introduction to Quantitative Social Sciences . Pre-requisites : Nil . No. of AUs. : 3 . Contact Hours : 39 . Course Aims . This course sets a basic foundation of students’ quantitative skills to analyze various social science phenomena. Intended Learning Outcomes (ILO) By the end of this course, you should be able to: 1.

PO91Q-20 Fundamentals in Quantitative Research Methods
Quantitative Social Science Data with R: An Introduction. Sage GILL J. 2006. Essential Mathematics for Political and Social Research. Cambridge University Press [a mathematics refresher] • IMAI K. 2017. Quantitative Social Science: …

SO5041 Quantitative Research Methods
•Quantitative social science data collection, especially the survey ... •Introduction to quantitative method – use number to represent information, simple descriptive statistics & presentations. Use Stata to enter & report data •Samples, surveys and probability – the theory of how a …

BSc in Quantitative Social Analysis - ugadmin.hkust.edu.hk
School of Humanities and Social Science - BSc in Quantitative Social Analysis (For students admitted in 2019-20 under the 4-year degree) In addition to the requirements of their major programs, students are required to complete the University ... COMP 1021 Introduction to Computer Science 3

Interpretive Quantitative Methods for the Social Sciences
Introduction Methodological disputes between what we now call positivist and interpretive research strategies are as old as social science itself, if not older. ... Rightly or wrongly, quantitative social science has long been identified with self-consciously positivist approaches to the philosophy, rhetoric and methodology of research. Bryman

HPSC0140 Social Research Methods and Data Analysis in STS
social science more generally, comprising both qualitative and quantitative methods. It will cover research design; qualitative and quantitative methods; research management and ethics; and the epistemology of social research. The course is strongly recommended for any students

POLI 311: Introduction to Quantitative Political Science
academics in political science across the world, as well as the open source and data science community. 3. Gain real world skills that will help you obtain jobs in careers of the future. 3 Textbook The textbook for this course will be: Kosuke Imai, Quantitative Social Science: An Introduction (Princeton University Press, 2018).

Introduction to Quantitative Methods for the Social Sciences
Introduction to Quantitative Methods for the Social Sciences Beatrice Magistro Winter, 2019 E-mail: beatrice.magistro@utoronto.ca Web: ... Quantitative Social Science: An Introduction. Princeton University Press. Hadley Wickham, Garrett Groleman. 2017. R For Data Science: Import, Tidy, Transform, Vi-

Introduction to Social Science Methods: An Overview of Quantitative …
Introduction to Social Science Methods: An Overview of Quantitative and Qualitative Methods D-Lab Nora Broege Carmen Brick ... Quantitative methods are mostly used to justify the hypotheses and draw a general conclusion on selected hypotheses ! Statistics, tables and graphs, are often used to present the ...

Using social media for social research: An introduction - GOV.UK
An introduction Social Media Research Group May 2016. Contents ... Social media research varies from other forms of online research, such as internet-based surveys or webpage reviewing, due to the social nature of the data being extracted from purpose-built platforms. As with any new form of research, several methodological points

Introduction to Quantitative Data Analysis in the Behavioral and Social …
Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences Michael J. Albers East Carolina University. This edition first published 2017 2017 John Wiley & Sons, Inc. ... Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences ...

The Great Regression. Machine Learning, Econometrics, and the …
and the Future of Quantitative Social Sciences Julien Boelaert, Étienne Ollion To cite this version: Julien Boelaert, Étienne Ollion. The Great Regression. Machine Learning, Econometrics, and the Future of Quantitative Social Sciences. Revue française de sociologie, 2018, 2018/3 (59), pp.475-506. 10.3917/rfs.593.0475. hal-01841413

Quantitative Social-Scientific His tory - CORE
used such implicitly quantitative phrases as "more," "less," "most." But the rapid de­ velopment in social science theory and statistical methods in the postwar era and the continuing revolution in data-processing technology have given a qualitatively different cast to quantitative history in the last two decades. 2.

Instructor HAN Li Mr. CHEN Ziyang - HKUST
Note: QSS stands for Quantitative Social Sciences: An Introduction and JW stands for Introductory Econometrics: A Modern Approach. Ch stands for chapters and Ap stands for Appendix. 1. Week 1: Motivation, Overview and a brief introduction to R (QSS Ch1, JW Ap A) 2. Week 2-3: Causality (QSS Ch2) a. An example of randomized trials b ...

Glossary for Quantitative Research in Social Science
Social Science Social Science science and computer science methods to model and analyze the data. Within computational social science, researchers are analyzing large data sets to answer social science questions. They use both data Confidence interval Social Science value lies A confidence interval is a range of values we are fairly sure our true .

Introduction to Quantitative Methods - European University …
Introduction to Quantitative Methods Instructors: Elias Dinas (elias.dinas@eui.eu), Political Science ... Quantitative Social Science: An Introduction. Princeton. 4. Wooldridge, Jeffrey M (2015). Introductory econometrics: A modern approach, ... Quantitative Data Analysis: Doing Social Research to Test Ideas. Jossey-Bass. Author: Juho ...

MEASURING UP: INTERNATIONAL CASE STUDIES ON THE …
1 Introduction 10 2 Teaching quantitative skills in university social science: The challenge 12 3 The case study research: Leading universities 18 ... Columbia University, MA in quantitative methods in the social sciences 50 Glossary 52 References 55. 4 Measuring up: International case studies on the teaching of quantitative methods in the ...

POL345/SOC305: Introduction to Quantitative Social Science
This course will teach students how to address these and other social science questions by analyzing quantitative data. The course introduces basic principles of statistical inference and programming skills for data analysis. The goal is to provide students with the foundation necessary to analyze

Quantitative analysis in social sciences: An brief introduction
In this paper, I present an introduction to quantitative research methods in social sciences. The paper is intended for non-Economics undergraduate students, development researchers and practitioners who although unfamiliar with statistical techniques, are interested in quantitative methods to study social phenomena.

SOSC1200: Quantitative Social Analysis - HKUST
2.Identify the di erences in norms and practices between the major social science disciplines with respect to the application of quantitative techniques. 3.Identify exemplary studies that have advanced our current understanding of important social phenomena using quantitative techniques. 4.Apply their understanding of best practices in ...

Quantitative and Computational Social Science 2024/25
Quantitative Social Science (QSS), Global Human Development (GHD), Complex Systems and Computational Social Science (CSCS) and Quantitative and Computational Social Science (QCSS). The QSS and CSCS programmes are now being phased out, having been replaced by the QCSS programme.

BSc in Quantitative Social Analysis - HKUST
School of Humanities and Social Science - BSc in Quantitative Social Analysis (For students admitted in 2020-21 under the 4-year degree) ... COMP 1021 Introduction to Computer Science 3 COMP 1022P Introduction to Computing with Java 3 COMP 1942 Exploring and Visualizing Data 3 Elective(s) Minimum credit(s)

A Practical Introduction to Regression Discontinuity Designs: …
22 Nov 2019 · 1 Introduction 1 Introduction An important goal in the social sciences is to understand the causal e ect of a treatment on outcomes of interest. As social scientists, we are interested in questions as varied as the

BSc in Quantitative Social Analysis - HKUST
School of Humanities and Social Science - BSc in Quantitative Social Analysis (For students admitted in 2021-22 under the 4-year degree) In addition to the requirements of their major programs, students are required to complete the University ... SOSC 3720 Introduction to Social Network Analysis 3 2023-24 QSA (4Y) (2021-22 intake) Page 2.