The essentials of political analysis

著者

書誌事項

The essentials of political analysis

Phillip H. Pollock III, Barry C. Edwards

CQ Press, an imprint of Sage, c2020

6th ed

  • : pbk

大学図書館所蔵 件 / 全2件

この図書・雑誌をさがす

注記

Previous edition: 2016

Includes bibliographical references and index

内容説明・目次

内容説明

"Pollock and Edwards explain the nuts-and-bolts of research design and data analysis in a clear and concise style. The Essential of Political Analysis is an intuitive introduction to complex material, replete with examples from the political science literature that add relevance to statistical concepts. This text offers students an excellent balance between the technical and the practical." -Francis Neely, San Francisco State University Gain the skills you need to conduct political analysis and critically assess statistical research. In this Sixth Edition of The Essentials of Political Science, bestselling authors Philip H. Pollock III and Barry C. Edwards build students' analytic abilities and develop their statistical reasoning with new data, fresh exercises, and accessible examples. This brief, accessible guide walks students through the essentials-measuring concepts, formulating and testing hypotheses, describing variables-while using key terms, chapter-opening objectives, over 80 tables and figures, and practical exercises to get them using and applying their new skills. Using SPSS, STATA or R? Discounted package deals available with Philip H. Pollock's companion workbooks. . Give your students the SAGE edge! SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review, study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.

目次

Tables, Figures, and Boxes Preface Acknowledgments About the Authors Introduction Facts and Values in Perspective The Scientific Approach What This Book Is About Conclusion Key Terms Notes CHAPTER 1 * The Definition and Measurement of Concepts Learning Objectives Conceptual Definitions Operational Definitions Measurement Error Reliability and Validity Working with Datasets, Codebooks, and Software Summary Key Terms Exercises Notes CHAPTER 2 * Measuring and Describing Variables Learning Objectives Essential Features Levels of Measurement Describing Variables Transforming Variables Summary Key Terms Exercises Notes CHAPTER 3 * Proposing Explanations, Framing Hypotheses, and Making Comparisons Learning Objectives "All Models Are Wrong, But Some Are Useful" Proposing Explanations Framing Hypotheses Common Mistakes in Hypothesis Writing Making Comparisons Graphing Relationships and Describing Patterns Summary Key Terms Exercises Notes CHAPTER 4 * Research Design, Research Ethics, and Evidence of Causation Learning Objectives Establishing Causation Experimental Designs Selecting Cases for Analysis Conducting Research Ethically Summary Key Terms Exercises Notes CHAPTER 5 * Making Controlled Comparisons Learning Objectives The Logic of Controlled Comparisons Essential Terms and Concepts Effect of Partisanship on Gun Control Vote, Controlling for Gender: An Illustrative Example Controlled Mean Comparisons Identifying Patterns Advanced Methods of Making Controlled Comparisons Summary Key Terms Exercises Notes CHAPTER 6 * Foundations of Statistical Inference Learning Objectives Population Parameters and Sample Statistics The Central Limit Theorem and the Normal Distribution Quantifying Standard Errors Confidence Intervals Sample Size and the Margin of Error of a Poll Inferences with Small Batches: The Student's t-Distribution Summary Key Terms Exercises Notes CHAPTER 7 * Tests of Significance and Measures of Association Learning Objectives Statistical Significance and Null Hypothesis Testing One-Sample Significance Tests Two-Sample Significance Tests The Chi-square Test Measures of Association Criticisms of Null Hypothesis Testing Summary Key Terms Exercises Notes CHAPTER 8 * Correlation and Linear Regression Learning Objectives Correlation Bivariate Regression Educational Attainment and Voter Turnout in States Example R-square Multiple Regression Some Practical Issues: Multicollinearity, Parsimony, and Missing Data Analyzing Residuals to Evaluate Linear Regression Models Summary Key Terms Exercises Notes CHAPTER 9 * Logistic Regression Learning Objectives The Logistic Regression Approach Logistic Regression Approach to Vote Choice in the 2016 Presidential Election Finding the Best Fit: Maximum Likelihood Estimation Logistic Regression with Multiple Independent Variables Graphing Predicted Probabilities with Multiple Independent Variables Summary Key Terms Exercises Notes CHAPTER 10 * Conducting Your Own Political Analysis Picking a Good Topic Getting Focused and Staying Motivated Reviewing Prior Literature Collecting Data Writing It Up Maintain a Scientific Mindset Key Terms Exercises Notes Index

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