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https://github.com/kosukeimai/qss

Supplementary Materials for ``Quantitative Social Science: An Introduction''
https://github.com/kosukeimai/qss

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Supplementary Materials for ``Quantitative Social Science: An Introduction''

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# QSS (Quantitative Social Science) [![Build Status](https://travis-ci.org/kosukeimai/qss.svg?branch=master)](https://travis-ci.org/kosukeimai/qss)

Supplementary Materials for the book,

**[Quantitative Social Science: An Introduction](http://press.princeton.edu/titles/11025.html)**,

published by Princeton University Press in 2017.  See the [book website](http://qss.princeton.press/).  It is

also available for purchase at vendors like

[Amazon](https://www.amazon.com/Quantitative-Social-Science-Kosuke-Imai/dp/0691175462). Also included are materials for **[Quantitative Social Science: An Introduction in tidyverse](https://qss.princeton.press/)**, published by Princeton University Press in 2022. All tidyverse versions contain "-tidy" in their file names. 



The book is based on the teaching philosophy summarized in the talk I

gave at the Nuffield Foundation's

[Q-Step Programme](http://www.nuffieldfoundation.org/q-step) in 2015: 

[slides](http://imai.princeton.edu/talk/files/Q-Step15.pdf) 



This repository contains the data sets and **R** scripts (available in .R, .Rmd, and .pdf formats) for all of the chapters:



1. [Introduction](INTRO)

2. [Causality](CAUSALITY)

3. [Measurement](MEASUREMENT)

4. [Prediction](PREDICTION)

5. [Discovery](DISCOVERY)

6. [Probability](PROBABILITY)

7. [Uncertainty](UNCERTAINTY)



In addition, the repository contains:



1. Errata ([QSS](errata/QSSerrata.pdf), [QSStidy](errata/QSS_tidy_errata.pdf))

2. [Sample course syllabi](syllabus)



## R package `qss`



The data and code in this repository are also available as an

[R package `qss`](https://github.com/kosukeimai/qss-package) 

(see [the package website](https://kosukeimai.github.io/qss-package/)). 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

    browseVignettes("qss") # list vignettes and R code

    vignette("causality", package = "qss") # show the vignette for the Causality chapter



## Related repositories



1. [swirl exercises `qss-swirl`](https://github.com/kosukeimai/qss-swirl)

2. [Interactive Tutorials for QSS by Matt Blackwell](https://github.com/mattblackwell/qsslearnr)

3. [R package `qss`](https://github.com/kosukeimai/qss-package) ([the package website](https://kosukeimai.github.io/qss-package/))

4. [tidyverse code `qss-tidy` by Jeff Arnold (the starting point for the QSS: tidyverse version of the book)](https://github.com/jrnold/qss-tidy) 

5. [R package `qss.student` for students by Will Lowe](https://conjugateprior.github.io/qss.student/) 

6. [python code `qsspy` by Jeffrey Allen](https://github.com/jeffallen13/qsspy) 

7. [instructors' materials `qss-inst`](https://github.com/kosukeimai/qss-inst)

8. [Lecture slides for QSS](https://github.com/kosukeimai/qss-lecture)



The last two repositories are private.  Instructors who wish access to these materials should either request access at the [book website](http://qss.princeton.press/) or email me.