Data Applications in Public Administration

Using R to Learn Concepts and Skills

Alex Combs

Last updated on 31 July 2023

Preface

This is a collection of lecture and presentation notes intended as a resource for students enrolled in my sections of PADP 7120: Data Applications in Public Administration. Distributing this resource beyond those enrolled in PADP 7120 is discouraged. This resource is not peer-reviewed. All opinions and errors are my own. I do not benefit monetarily from this resource in any way.

The objective of this resource is to help students in PADP 7120 become as competitive as possible in their desired job markets via competency in statistics and statistical programming software. It aims to teach students key concepts in statistics and applications of those concepts using R with a level of theoretical and technical detail that is appropriate for those pursing a Masters in Public Administration.

Style and Structure

Rather than provide thorough coverage of complex theory, I take some liberty to present stylized facts for the benefit of the reader. When using R, it is often the case that multiple options exist to achieve a desired result. I provide what I consider or understand to be the best option.

Chapters are organized along two tracks. The first track covers statistical concepts and is self-contained. The second track applies the concepts in the first track using R. The chapters in the applied track are referred to as R Chapters, each of which corresponds to a chapter in the first track. For example, the R Data chapter corresponds to the Data chapter in the first track.

The conceptual track is divided into four sections:

1. Data and description
2. Regression models
3. Inference
4. Advanced topics

Examples and exercises are presented using R. Students who intend to use a personal computer to complete exercises in the R chapters need to download and install the following software:

• R
• RStudio

Supplemental Resources

Students may desire alternative coverage of the topics covered in this course. Below is a list of free texts and websites that teach statistics and/or R.

• Traditional statistics texts
  • OpenIntro Statistics by David Diez, Mine Cetinkaya-Rundel, and Christopher Barr
  • Quantitative Research Methods for Political Science, Public Policy and Public Administration (With Applications in R) - 3rd Edition by Hank Jenkins-Smith and Joseph Ripberger
• R-centric statistics texts
  • Statistical Inference via Data Science by Chester Ismay and Albert Y. Kim
  • R for Data Science by Garrett Grolemund and Hadley Wickham
  • Data Visualization: A practical introduction by Kieran Healy
  • Forecasting: Principles and Practice by Rob J. Hyndman and George Athanasopoulos
• Other R resources
  • R Markdown from RStudio
  • R Markdown: The Definitive Guide by Yihui Xie, J.J. Allaire, and Garrett Grolemund
  • Pimp my RMD by Yan Holtz
  • Data Carpentry: R for Social Scientists

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Data Applications in Public Administration by Alex Combs is licensed under CC BY-NC-ND 4.0