An SPSS Companion for The Fundamentals of Social Research [Paperback]

Teaches students how to use SPSS to conduct the statistical analyses most commonly used in political science.This workbook teaches students how to use the popular SPSS statistical software program to assess causal relationships using real data. It parallels the main Kellstedt/Whitten/Tuch text, which allows students to apply the lessons and techniques they learn in each chapter in a statistical software setting.This workbook teaches students how to use the popular SPSS statistical software program to assess causal relationships using real data. It parallels the main Kellstedt/Whitten/Tuch text, which allows students to apply the lessons and techniques they learn in each chapter in a statistical software setting.An SPSS Companion for The Fundamentals of Social Research offers students the opportunity to delve into the world of SPSS 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 SPSS 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.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 lӤ