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E-grāmata: SPSS Companion for the Third Edition of The Fundamentals of Political Science Research

(Texas A & M University), (Texas A & M University)
  • Formāts: PDF+DRM
  • Izdošanas datums: 23-Apr-2020
  • Izdevniecība: Cambridge University Press
  • Valoda: eng
  • ISBN-13: 9781108637343
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SPSS Companion for the Third Edition of The Fundamentals of Political Science ResearchPalielināt
  • Formāts: PDF+DRM
  • Izdošanas datums: 23-Apr-2020
  • Izdevniecība: Cambridge University Press
  • Valoda: eng
  • ISBN-13: 9781108637343
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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. Kellstedtand 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"--

Papildus informācija

Teaches students how to use SPSS to conduct the statistical analyses most commonly used in political science.
Preface xi
List of Figures
xiii
1 The Scientific Study of Politics
1(10)
1.1 Overview
1(1)
1.2 "A Workbook? Why Is There a Workbook?"
1(1)
1.3 Getting Started with SPSS
2(8)
1.3.1 Launching SPSS
2(2)
1.3.2 Getting SPSS to Do Things by Using Pull-Down Menus
4(3)
1.3.3 Initially Examining Data in SPSS
7(2)
1.3.4 Saving Output and Exiting the Program
9(1)
1.4 Exercises
10(1)
2 The Art of Theory Building
11(12)
2.1 Overview
11(1)
2.2 Examining Variation Across Time and Across Space
11(7)
2.2.1 Producing a Bar Graph for Examining Cross-Section Variation
11(5)
2.2.2 Producing a Connected Plot for Examining Time-Series Variation
16(2)
2.3 Using Google Scholar to Search the Literature Effectively
18(3)
2.4 Wrapping Up
21(1)
2.5 Exercises
21(2)
3 Evaluating Causal Relationships
23(3)
3.1 Overview
23(1)
3.2 Exercises
23(3)
4 Research Design
26(3)
4.1 Overview
26(1)
4.2 Exercises
26(3)
5 Measuring Concepts of Interest
29(3)
5.1 Overview
29(1)
5.2 Exercises
29(3)
6 Getting to Know Your Data
32(8)
6.1 Overview
32(1)
6.2 Describing Categorical and Ordinal Variables
32(3)
6.3 Describing Continuous Variables
35(3)
6.4 Putting Statistical Output into Tables, Documents, and Presentations
38(1)
6.5 Exercises
39(1)
7 Probability and Statistical Inference
40(6)
7.1 Overview
40(1)
7.2 Dice Rolling in Excel
40(5)
7.3 Exercises
45(1)
8 Bivariate Hypothesis Testing
46(9)
8.1 Overview
46(1)
8.2 Tabular Analysis
46(4)
8.2.1 Generating Test Statistics
48(1)
8.2.2 Putting Tabular Results into Papers
49(1)
8.3 Difference of Means
50(1)
8.3.1 Examining Differences Graphically
50(1)
8.3.2 Generating Test Statistics
50(1)
8.4 Correlation Coefficients
51(3)
8.4.1 Producing Scatter Plots
52(1)
8.4.2 Generating Correlation Coefficients and Test Statistics
52(2)
8.5 Exercises
54(1)
9 Two-Variable Regression Models
55(4)
9.1 Overview
55(1)
9.2 Estimating a Two-Variable Regression
55(2)
9.3 Graphing a Two-Variable Regression
57(1)
9.4 Exercises
58(1)
10 Multiple Regression: the Basics
59(5)
10.1 Overview
59(1)
10.2 Estimating a Multiple Regression
59(1)
10.3 From Regression Output to Table - Making Only One Type of Comparison
60(3)
10.3.1 Comparing Models with the Same Sample of Data, but Different Specifications
61(2)
10.3.2 Comparing Models with the Same Specification, but Different Samples of Data
63(1)
10.4 Standardized Coefficients
63(1)
10.5 Exercises
63(1)
11 Multiple Regression Model Specification
64(9)
11.1 Overview
64(1)
11.2 Dummy Variables
64(3)
11.2.1 Creating a Dummy Variable in SPSS
64(2)
11.2.2 Estimating a Multiple Regression Model with a Single Dummy Independent Variable
66(1)
11.2.3 Estimating a Multiple Regression Model with Multiple Dummy Independent Variables
67(1)
11.3 Dummy Variables in Interactions
67(2)
11.4 Post-Estimation Diagnostics in SPSS for OLS
69(2)
11.4.1 Identifying Outliers and Influential Cases in OLS
70(1)
11.4.2 Detecting Multicollinearity in OLS
71(1)
11.5 Exercises
71(2)
12 Limited Dependent Variables and Time-Series Data
73(12)
12.1 Overview
73(1)
12.2 Models with Dummy Dependent Variables
73(4)
12.3 Being Careful with Time-Series Data
77(6)
12.3.1 Setting Up a Time-Series Data Set in SPSS
78(2)
12.3.2 Lag and Difference Operators in SPSS
80(1)
12.3.3 Performing Time-Series Regression Analyses in SPSS
81(2)
12.4 Exercises
83(2)
Bibliography 85(2)
Index 87
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. Guy D. Whitten is Cullen-McFadden Professor of Political Science, as well as Director of the European Union Center, at Texas A & M University. He has published a variety of articles in leading peer-reviewed journals. He is on the editorial boards of Electoral Studies and Political Science Research and Methods.
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