Supplementary Materials for the book, Quantitative Social Science: An Introduction, published by Princeton University Press in 2017. See the book website. 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. Interactive Tutorials for QSS by Matt Blackwell
3. R package qss (the package website)
4. tidyverse code qss-tidy by Jeff Arnold
5. R package qss.student for students by Will Lowe
6. instructors' materials qss-inst
7. Lecture slides for QSS

The last two repositories are private. Instructors who wish access to these materials should either request access at the book website or email me.