The Essentials of Political Analysis

Table of Contents:
List of Tables List of Boxes Preface Acknowledgments About the Authors Chapter 1 The Definition and Measurement of Concepts 1.1 Conceptual Definitions 1.2 Operational Definitions 1.3 Measurement Error 1.4 Reliability and Validity 1.5 Working With Datasets, Codebooks, and Software Summary Key Terms Exercises Chapter 2 Measuring and Describing Variables 2.1 Essential Features 2.2 Levels of Measurement 2.3 Central Tendency and Dispersion of Variables 2.4 Describing Nominal-Level Variables 2.5 Describing Ordinal-Level Variables 2.6 Describing Interval-Level Variables Summary Key Terms Exercises Chapter 3 Creating and Transforming Variables 3.1 Transforming Interval-Level Variables With Math Functions 3.2 Sometimes, Less Is More: Simplifying Variables 3.3 Managing Data and Metadata 3.4 Additive Indexes and Measurement Scales 3.5 Advanced Data Transformation Methods Summary Key Terms Exercises Chapter 4 Proposing Explanations, Framing Hypotheses, and Making Comparisons 4.1 “All Models Are Wrong, but Some Are Useful” 4.2 Proposing Explanations 4.3 Framing Hypotheses 4.4 Making Comparisons Summary Key Terms Exercises Chapter 5 Graphing Relationships and Describing Patterns 5.1 Historic Examples of Data Visualization 5.2 Levels of Measurement and Choice of Graph Types 5.3 Visualizing Relationships With Categorical Variables 5.4 Describing Patterns 5.5 Graphing Relationship Between Interval-Level Variables 5.6 Challenges of Visualizing Data Summary Key Terms Exercises Chapter 6 Research Design, Research Ethics, and Evidence of Causation 6.1 Establishing Causation 6.2 Experimental Designs 6.3 Selecting Cases for Analysis 6.4 Conducting Research Ethically Summary Key Terms Exercises Chapter 7 Making Controlled Comparisons 7.1 The Logic of Controlled Comparisons 7.2 Essential Terms and Concepts 7.3 Effect of Partisanship on Gun Control Vote, Controlling for Gender: An Illustrative Example 7.4 Controlled Mean Comparisons 7.5 Identifying Patterns 7.6 Advanced Methods of Making Controlled Comparisons Summary Key Terms Exercises Chapter 8 Foundations of Statistical Inference 8.1 Population Parameters and Sample Statistics 8.2 The Central Limit Theorem and the Normal Distribution 8.3 Quantifying Standard Errors 8.4 Confidence Intervals 8.5 Sample Size and the Margin of Error of a Poll 8.6 Inferences With Small Batches: The Student’s t-Distribution Summary Key Terms Exercises Chapter 9 Hypothesis Tests With One or Two Samples 9.1 Statistical Significance and Null Hypothesis Testing 9.2 One-Sample Significance Tests 9.3 Two-Sample Significance Tests 9.4 Criticisms of Null Hypothesis Testing Summary Key Terms Exercises Chapter 10 Chi-Square Test and Analysis of Variance 10.1 Null Hypothesis Tests With More than Two Groups 10.2 The Chi-Square Test of Independence 10.3 Measures of Association 10.4 Analysis of Variance (ANOVA) Summary Key Terms Exercises Chapter 11 Correlation and Bivariate Regression 11.1 Correlation 11.2 Bivariate Regression 11.3 Educational Attainment and Voter Turnout in States Example 11.4 R-Square and Adjusted R-Square 11.5 All Models Are Still Wrong, but Some Are Useful Summary Key Terms Exercises Chapter 12 Multiple Regression 12.1 Multiple Regression Equation 12.2 Educational Attainment and Voter Turnout in States Revisited 12.3 Regression With Multiple Dummy Variables 12.4 Interaction Effects in Multiple Regression 12.5 Some Practical Issues in Multiple Regression Analysis Summary Key Terms Exercises Chapter 13 Analyzing Regression Residuals 13.1 What Are Regression Residuals? 13.2 Assumptions About Regression Residuals 13.3 Diagnostic Graphs of Regression Residuals 13.4 Testing Assumptions About Regression Residuals 13.5 What If Assumptions Are Violated? Summary Key Terms Exercises Chapter 14 Logistic Regression 14.1 The Logistic Regression Approach 14.2 Logistic Regression Analysis of Vote Choice in the 2020 Presidential Election 14.3 Finding the Best Fit: Maximum Likelihood Estimation 14.4 Logistic Regression With Multiple Independent Variables 14.5 Graphing Predicted Probabilities With Multiple Independent Variables Summary Key Terms Exercises Chapter 15 Conducting Your Own Political Analysis 15.1 Picking a Good Topic 15.2 Getting Focused and Staying Motivated 15.3 Reviewing Prior Literature 15.4 Collecting Data 15.5 Writing It Up 15.6 Maintain a Scientific Mindset Summary Key Terms Exercises Glossary Endnotes Index

About the Author :
Philip H. Pollock III is a professor of political science at the University of Central Florida. He has taught courses in research methods at the undergraduate and graduate levels for more than thirty years. His main research interests are American public opinion, voting behavior, techniques of quantitative analysis, and the scholarship of teaching and learning. His recent research has been on the effectiveness of Internet-based instruction. Pollock’s research has appeared in the American Journal of Political Science, Social Science Quarterly, and the British Journal of Political Science. Recent scholarly publications include articles in Political Research Quarterly, the Journal of Political Science Education, and PS: Political Science and Politics. Barry C. Edwards writes textbooks and works for Fair Trial Analysis, LLC, a company that conducts research on juries and jurors for civil and criminal litigation. He received his B.A. from Stanford University, a J.D. from New York University, and a Ph.D. from the University of Georgia. He taught survey design and analysis, research methods, and prelaw courses at the University of Central Florida and continues to teach occasional courses for the University of Georgia. His political science interests include American politics, public law, and research methods. He founded the Political Science Data Group and created the PoliSciData.com website. His research has been published in American Politics Research, Congress & the Presidency, Election Law Journal, Emory Law Journal, Georgia Bar Journal, Harvard Negotiation Law Review, Journal of Politics, NYU Journal of Legislation and Public Policy, Political Research Quarterly, Presidential Studies Quarterly, Public Management Review, State Politics and Policy Quarterly, and UCLA Criminal Justice Law Review.

Review :
An approachable and lucidly written text that provides students with the essential knowledge and tools for conducting empirical political science research. An excellent introduction on how to carry out social scientific research. Highly recommended for undergraduate courses on research design and the basics of statistical analysis. An excellent textbook to use for scope and methods and undergraduate statistics courses. A great book that introduces students to the basic elements of research, data, and data analysis. Students don′t necessarily need to start the class with a working knowledge of statistics to be successful. A well-written undergraduate methods textbook that even the most apprehensive student can understand. Foundations of statistics for poli sci major in plain language with easy to comprehend exercises. Straightforward with good resources. This is a thorough and understandable introduction to research methods that can easily be adapted to your classroom preferences and needs.