Applied Quantitative Analysis In Education And The Social Sciences

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.

This exciting collection is both useful and timely. It clearly lays out the problems, strategies and resources associated with the teaching of quantitative methods in modern universities. Addressing the perceived ′crisis of number′ in a practical and fresh way the book sets out dynamic new approaches to teaching quantitative methods. It offers historical, comparative, analytical reflection and empirical evidence concerning the crisis in contemporary social sciences. Experts from across the social sciences provide a wide range of authoritative insights as well as a number of useful illustrations of strategies and resources designed to help overcome this ′crisis of number′. Each chapter reflects the diversity of backgrounds and approaches within the social sciences making this an interdisciplinary, relevant addition to the subject. The book also: o focuses on innovations in how to teach quantitative research methods o reports on the latest ESRC research projects on teaching quantitative methods o locates itself within current debates about skills for employment. Clear, engaging and original this book will be essential reading for those interested in learning and teaching quantitative methods.

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.

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.

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.

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 statisticsIncludes data sets from actual research for students to test their skills onCovers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical toolsFeatures a wealth of supplementary exercises, including additional data analysis exercises and programming exercisesOffers a solid foundation for further studyComes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides

The Reviewer’s Guide to Quantitative Methods in the Social Sciences provides evaluators of research manuscripts and proposals in the social and behavioral sciences with the resources they need to read, understand, and assess quantitative work. 35 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 second edition of this valuable resource updates readers on each technique’s key principles, appropriate usage, underlying assumptions and limitations, providing reviewers with the information they need to offer constructive commentary on works they evaluate. Written by methodological and applied scholars, this volume is also an indispensable author’s reference for preparing sound research manuscripts and proposals.