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An SPSS Companion for the Third Edition of The Fundamentals of Political Science Research offers students a chance to delve into the world of SPSS using real political science 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 SPSS. 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 SPSS 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 SPSS 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.Read more
- Provides students with an introduction to using popular SPSS software program to assess causal relationships by conducting statistical analyses
- Parallels the main text, giving students a chance to apply the lessons and techniques learned in each chapter in a statistical software setting
- Teaches students to reproduce results presented in the main text, allowing them to become comfortable with data sets and techniques through repeated practice
- Includes step-by-step instructions for using SPSS, including command lines and screenshots to demonstrate proper use of the software
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- Date Published: April 2020
- format: Paperback
- isbn: 9781108447935
- length: 100 pages
- dimensions: 279 x 217 x 5 mm
- weight: 0.32kg
- availability: In stock
Table of Contents
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
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