The essentials of political analysis
著者
書誌事項
The essentials of political analysis
CQ Press, Sage, c2012
4th ed
- : pbk
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注記
Includes index
内容説明・目次
内容説明
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'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.
目次
Introduction
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
Correlation
Bivariate Regression
R-Square
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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