1 INTRODUCTION 1.1 Overview of the Book 1.2 How to Use This Book 1.3 Introduction to R and the tidyverse 1.4 Summary 1.5 Exercises 2 CAUSALITY 2.1 Racial Discrimination in the Labor Market 2.2 Subsetting Data in R 2.3 Causal Effects and the Counterfactual 2.4 Randomized Controlled Trials 2.5 Observational Studies 2.6 Descriptive Statistics for a Single Variable 2.7 Summary 2.8 Exercises 3 MEASUREMENT 3.1 Measuring Civilian Victimization during Wartime 3.2 Handling Missing Data in R 3.3 Visualizing the Univariate Distribution 3.4 Survey Sampling 3.5 Measuring Political Polarization 3.6 Summarizing Bivariate Relationships 3.7 Quantile-Quantile Plot 3.8 Clustering 3.9 Summary 3.10 Exercises 4 PREDICTION 4.1 Predicting Election Outcomes 4.2 Linear Regression 4.3 Regressing and Causation 4.4 Randomized Experiments 4.5 Summary 4.6 Exercises 5 DISCOVERY 5.1 Textual Data 5.2 Network Data 5.3 Spatial Data 5.4 Summary 5.5 Exercises 6 PROBABILITY 6.1 Probability 6.2 Conditional Probability 6.3 Random Variables and Probability Distributions 6.4 Large Sample Theorems 6.5 Summary 6.6 Execises 7 UNCERTAINTY 7.1 Estimation 7.2 Hypothesis Testing 7.3 Linear Regression Model with Uncertainty 7.4 Summary 7.5 Exercises 8 NEXT