Paul M. Kellstedt

R Companion for the Third Edition of The Fundamentals of Political Science Research (eBook, PDF)

• Format: PDF

Produktbeschreibung

An R Companion for the Third Edition of The Fundamentals of Political Science Research offers students a chance to delve into the world of R using real political data sets and statistical analysis techniques directly from Paul M. Kellstedt and Guy D. Whitten's best-selling textbook. Built in parallel with the main text, this workbook teaches students to apply the techniques they learn in each chapter by reproducing the analyses and results from each lesson using R. Students will also learn to create all of the tables and figures found in the textbook, leading to an even greater mastery of the core material. This accessible, informative, and engaging companion walks through the use of R step-by-step, using command lines and screenshots to demonstrate proper use of the software. With the help of these guides, students will become comfortable creating, editing, and using data sets in R to produce original statistical analyses for evaluating causal claims. End-of-chapter exercises encourage this innovation by asking students to formulate and evaluate their own hypotheses.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 10. Juni 2021
• Englisch
• ISBN-13: 9781108617796
• Artikelnr.: 66178600

Autorenporträt

Paul M. Kellstedt is Professor of Political Science at Texas A&M University. He is the author of The Mass Media and the Dynamics of American Racial Attitudes (Cambridge, 2003), winner of Harvard University's John F. Kennedy School of Government's 2004 Goldsmith Book Prize. In addition, he has published numerous articles in a variety of leading journals. He is the Editor-in-chief of Political Science Research and Methods, the flagship journal of the European Political Science Association.

Inhaltsangabe

List of figures
Preface
1. The scientific study of politics
2. The art of theory building
3. Evaluating causal relationships
4. Research design
5. Measuring concepts of interest
6. Getting to know your data
7. Probability and statistical inference
8. Bivariate hypothesis testing
9. Two-variable regression models
10. Multiple regression: the basics
11. Multiple regression model specification
12. Limited dependent variables and time-series data
Bibliography
Index.