The Essentials of Political Analysis

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  • Edition: 4th
  • Format: Paperback
  • Copyright: 2011-07-19
  • Publisher: Cq Pr
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Political science students need to get comfortable using the tools of political analysis. For stats-phobic undergrads, the research methods course need not need be nerve wracking, especially with Pollock#x19;s bestselling text to help them along the way. His brief, accessible guide walks students through the basics-measuring concepts, formulating and testing hypotheses, describing variables-while using key terms, chapter-opening objectives, 80 tables and figures, and class-tested exercises to get them using and applying their new skills. The new fourth edition features enhanced treatment of research design and logic controlled comparison and illustrates complex relationships with more accessible examples. A completely revised rubric further helps students identify these complex relationships in their own research.

Author Biography

Philip H. Pollock III is 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.

Table of Contents

The Definition and Measurement of Concepts
Conceptual Definitions
Operational Definitions
Measuring and Describing Variables
Measuring Variables
Describing Variables
Proposing Explanations, Framing Hypotheses, and Making Comparisons
Proposing Explanations
Framing Hypotheses
Making Comparisons
Graphing Relationships and Describing Patterns
The ‚«£How Else?‚«† Question: Making Controlled Comparisons
Experimental Studies
Observational Studies
Three Scenarios: X Y, Controlling for Z
Sampling and Inference
Cross-Tabulation Analysis
Graphing Controlled Comparisons
Foundations of Statistical Inference
Population Parameters and Sample Statistics
Random Sampling
The Standard Error of a Sample Mean
Inference Using the Normal Distribution
Inference Using the Students' T-Distribution
What About Sample Proportions?
Tests of Significance and Measures of Association
Statistical Significance
Measures of Association
Correlation and Linear Regression
Bivariate Regression
Dummy Variable Regression
Logistic Regression
The Logistic Regression Approach
Finding the Best Fit: Maximum Likelihood Estimation
Logistic Regression with Multiple Independent Variables
Working with Probabilities
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