Supplementary Materials for the book, Quantitative Social Science: An Introduction, published by Princeton University Press in 2017. It is also available for purchase at vendors like Amazon.

The book is based on the teaching philosophy summarized in the talk I gave at the Nuffield Foundation's Q-Step Programme in 2015: slides

This repository contains the data sets and R scripts for all of the chapters:

1. Introduction
2. Causality
3. Measurement
4. Prediction
5. Discovery
6. Probability
7. Uncertainty

In addition, the repository contains:

1. Errata
2. Sample course syllabi

The data and code in this repository are also available as an R package qss (see the package website). The code is in the form of vignettes. To install this package, use the following command:

install.packages("devtools") # if you have not installed devtools package already
devtools::install_github("kosukeimai/qss-package", build_vignettes = TRUE)

Once the qss package is installed, you can use the data and vignette:

library(qss)
data(package = "qss") # list all data sets
data(elections) # load the elections data
vignette(package = "qss") # list all vignettes
browseVignette("qss") # list vignettes and R code
vignette("causality", package = "qss") # show the vignette for the Causality chapter

1. swirl exercises qss-swirl
2. R package qss (the package website)
3. tidyverse code qss-tidy
4. R package qss.student for students
5. instructors' materials qss-inst (private repository)