An R Companion for The Fundamentals of Social Research

An R Companion for The Fundamentals of Social Research

An R Companion for The Fundamentals of Social Research

An R Companion for The Fundamentals of Social Research

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Overview

An R Companion for The Fundamentals of Social Research offers students the opportunity to delve into the world of R using real data sets and statistical analysis techniques directly from Paul M. Kellstedt, Guy D. Whitten, and Steven A. Tuch's new textbook. Workbook sections parallel chapters in the main text, giving students a chance to apply the lessons and techniques learned in each chapter in a statistical software setting. Detailed chapters teach students to reproduce results presented in the textbook, allowing them to become comfortable performing statistical analyses for evaluating causal claims through repeated practice. Step-by-step instructions for using R are provided, along with command lines and screenshots to demonstrate proper use of the software. Instructions for producing the figures and tables in the main text are integrated throughout the workbook. End-of-chapter exercises encourage students to formulate and evaluate their own hypotheses.

Product Details

ISBN-13: 9781009248914
Publisher: Cambridge University Press
Publication date: 09/08/2022
Pages: 100
Product dimensions: 6.93(w) x 9.96(h) x 0.24(d)

About the Author

Paul M. Kellstedt is a professor of political science at Texas A&M University.

Guy D. Whitten is a professor of political science and Director of the European Union Center at Texas A&M University.

Steven A. Tuch is a professor of sociology and public policy and public administration at George Washington University.

Table of Contents

List of figures; Preface; 1. The Scientific Study of Society; 2. The Art of Theory Building; 3. Evaluating Causal Relationships; 4. Research Design; 5. Survey Research; 6. Measuring Concepts of Interest; 7. Getting to Know Your Data; 8. Probability and Statistical Inference; 9. Bivariate Hypothesis Testing; 10. Two-variable Regression Models; 11. Multiple Regression; 12. Putting it all Together to Produce Effective Research; References; Index.
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