okllsskh / ds-project

DSS

The DSS folder with all the files necessary to complete the exercises in the book

Students' and instructors' repository for Llaudet, Elena and Kosuke Imai. Data Analysis for Social Science, A Friendly and Practical Introduction (Princeton University Press, 2022)

This repository contains the R scripts (.R files) and datasets (.csv files) used in the book exercises.

• Chapter 1: Introduction

  • R Script: Introduction.R
  • Dataset: STAR.csv

• Chapter 2: Estimating Causal Effects with Randomized Experiments

  • Research Question: Do Small Classes Improve Student Performance?
  • Based on: Frederick Mosteller, "The Tennessee Study of Class Size in the Early School Grades," Future of Children 5, no. 2 (1995): 113-27.
  • R Script: Experimental.R
  • Dataset: STAR.csv

• Chapter 3: Inferring Population Characteristics via Survey Research

  • Research Question: Who Supported Brexit?
  • Based on: Sara B. Hobolt, "The Brexit Vote: A Divided Nation, a Divided Continent," Journal of European Public Policy 23, no. 9 (2016): 1259-77, and Sascha O. Becker, Thiemo Fetzer, and Dennis Novy, "Who Voted for Brexit? A Comprehensive District-Level Analysis," Economic Policy 32, no. 92 (2017): 601–50.
  • R Script: Population.R
  • Datasets: BES.csv, UK_districts.csv

• Chapter 4: Predicting Outcome Using Linear Regression

  • Goal: Predict GDP Growth Based on Night-Time Light Emissions
  • Based on: J. Vernon Henderson, Adam Storeygard, and David N. Weil, "Measuring Economic Growth from Outer Space," American Economic Review 102, no. 2 (2012): 994–1028.
  • R Script: Prediction.R
  • Dataset: countries.csv

• Chapter 5: Estimating Causal Effects with Observational Data

  • Research Question: What Was the Effect of Russian TV Propaganda on Ukrainians' 2014 Voting Behavior?
  • Based on: Leonid Peisakhin and Arturas Rozenas, "Electoral Effects of Biased Media: Russian Television in Ukraine," American Journal of Political Science 62, no. 3 (2018): 535–50.
  • R Script: Observational.R
  • Datasets: UA_survey.csv, UA_precincts.csv

• Chapter 6: Probability

  • Goal: Learn Basic Probability
  • R Script: Probability.R
  • Dataset: STAR.csv

• Chapter 7: Quantifying Uncertainty

  • Goal: Complete Some of the Analyses from Chapters 2 through 5 by Quantifying the Uncertainty in the Empirical Findings
  • R Script: Uncertainty.R
  • Datasets: BES.csv, STAR.csv, countries.csv, UA_survey.csv

We recommend downloading the whole folder and saving it directly on your Desktop.