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 | Table of Contents Introduction. A 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. | Watch videos | Review terms 1. The Definition and 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. | Watch videos | Review terms 2. Measuring and 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. | Watch videos | Review terms 3. Creating and 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. | Watch videos | Review terms 4. Proposing Explanations, Framing Hypotheses, and 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. | Watch videos | Review terms 5. Graphing Relationships and 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. | Watch videos | Review terms 6. Research Design, Research Ethics, and 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. | Watch videos | Review terms 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. | Watch videos | Review terms 8. The 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. | Watch videos | Review terms 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. | Watch videos | Review terms 10. The Chi-Square Test and 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. | Watch videos | Review terms 11. Correlation and 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. | Watch videos | Review terms 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. | Watch videos | Review terms 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. | Watch videos | Review terms 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. | Watch videos | Review terms 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. | Watch videos | Review terms |
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