DATA ANALYSIS FOR SOCIAL SCIENCE

CODE AND DATASETS USED IN DSS

All code and datasets used in the book are available in the DSS folder here.

SELF-GRADED REVIEW EXERCISES

Interactive R tutorials for students to check their understanding of the material on their own after completing the readings and performing the analyses explained in the book — they are meant to supplement, not replace, the book. Each includes multiple-choice questions and hands-on coding exercises with instant feedback. At the end, students can generate a progress report of their work. Eventually, there will be a tutorial for each chapter in the book. Check again soon! (To access them, run the code in the linked R script in RStudio. Watch the walkthrough video.)

• Chapter 1. Introduction
• Chapter 2. Estimating Causal Effects with Randomized Experiments
• Chapter 3. Inferring Population Characteristics via Survey Research
• Chapter 4. Predicting Outcomes Using Linear Regression

INTERACTIVE GRAPHS

Dynamic graphs that students can interact with in real time, directly in their browser, designed to build intuition about key concepts in statistics.

• Random Treatment Assignment (Chapter 2)
• Random Sampling (Chapter 3)
• Mean and Standard Deviation (Chapter 3)
• Correlation Coefficient (Chapter 3)
• Intercept and Slope (Chapter 4)
• Least Squares Method (Chapter 4)

VIDEOS AND ADDITIONAL READINGS

• How to Use Posit Cloud for Data Analysis (Chapter 1, PDF)
• How to Run a Randomized Experiment (Chapter 2, video)