The Essentials of Political Analysis, 7th Edition

Table of Contents
Click chapter title for description and links to resources

Introduction. Scientific Approach to Politics

Students are introduced to the scientific approach in political analysis, focusing on evidence-based reasoning and critical inquiry. The course begins by discussing how scientific principles are applied to study political phenomena, setting the stage for the course. The Essentials preface and Companion introductions do not include exercises because this is typically an orientation week when students can drop/add classes.

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1. Definition & Measurement of Concepts

Students will learn how to define political concepts and operationalize them into measurable variables. Skills include formulating clear definitions and understanding the link between theoretical and empirical research using software to create operational definitions.

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2. Measuring & Describing Variables

This chapter covers descriptive statistics and levels of measurement. Students will practice summarizing data using means, medians, modes, and visualizations like bar charts and histograms, applying statistical software to describe datasets effectively.

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3. Creating & Transforming Variables

Students will learn how to create new variables and transform existing ones to fit research needs. Skills include calculating indices, recoding data, and applying transformations in statistical software to enhance data analysis.

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4. Proposing Explanations, Framing Hypotheses & Making Comparisons

This chapter emphasizes the development of testable hypotheses and the logic of comparisons. Students will practice crafting hypotheses and performing preliminary analyses to explore relationships using cross-tabulation tools in software.

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5. Graphing Relationships & Describing Patterns

Students will visualize data relationships using scatterplots and trendlines. Key skills include interpreting patterns (linear, curvilinear) and using graphing functions in statistical software to illustrate findings clearly.

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6. Research Design, Research Ethics & Evidence of Causation

This chapter focuses on designing ethical research and establishing causation. Students will learn about experimental and observational designs and use software to simulate experimental setups and analyze causal relationships.

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7. Making Controlled Comparisons

Students will explore techniques for controlling rival explanations and interpreting controlled comparisons. They will practice using statistical software to create and analyze control tables, identifying patterns and relationships.

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8. Foundations of Statistical Inference

This chapter introduces students to probability theory and confidence intervals. Students will calculate standard errors and use statistical software to compute and interpret confidence intervals for datasets.

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9. Hypothesis Tests with One or Two Samples

Students will learn hypothesis testing fundamentals, focusing on single and two-sample tests. They will practice performing t-tests in software to assess whether differences in means are statistically significant.

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10. Chi-Square Test & Analysis of Variance

This chapter covers analyzing relationships between categorical variables with chi-square tests and comparing group means using ANOVA. Students will apply these techniques to datasets using statistical software.

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11. Correlation & Bivariate Regression

Students will study linear relationships between two variables using correlation and regression analysis. Skills include interpreting Pearson’s r and running bivariate regressions in statistical software.

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12. Multiple Regression Analysis

This chapter expands to multiple regression models, emphasizing controlling for multiple variables. Students will practice building and interpreting regression models with multiple predictors in software.

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13. Analyzing Regression Residuals

Students will learn to diagnose and improve regression models by analyzing residuals. They will use software to identify outliers, test model assumptions, and refine their analyses.

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14. Logistic Regression Analysis

Students will explore logistic regression to analyze binary outcomes. Key skills include interpreting odds ratios and predicted probabilities, with hands-on software practice for real-world applications.

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15. Conducting Your Own Political Analysis

This chapter focuses on independent research projects. Students will apply the skills learned throughout the course to analyze a political question of their choice using software.

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Watch & Learn

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Teaching video by Philip Pollock & Barry Edwards for Essentials of Political Analysis, 7th Ed. (3:20).

Value of Experimental Research Designs

Ancillary Resources

Lecture Videos for Essentials: Compilations of streaming lecture videos for each chapter.
Practice Quizzes: Ten-question practice quizzes for each chapter.
Teaching Assistant Term Review: Watch five-minute review of key terms.
Sample Syllabi: from various instructors
Instructor's Solution Manual: Solutions to chapter exercises, available for Instructors from Sage Publications
Test Question Bank: for each chapter, available for Instructors from Sage Publications
Powerpoint Presentation Slides: for each chapter, available for Instructors from Sage Publications

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