Elections are random events. From individuals deciding whether to vote, to people deciding for whom to vote, to election authorities deciding what to count, the outcomes of competitive democratic elections are rarely known until election day...or beyond. Understanding Elections through Statistics: Polling, Prediction, and Testing explores this random phenomenon from two points of view: predicting the election outcome using opinion polls and testing the election outcome using government-reported data.
Written for those with only a brief introduction to statistics, this book takes you on a statistical journey from how polls are taken to how they can-and should-be used to estimate current popular opinion. Once an understanding of the election process is built, we turn toward testing elections for evidence of unfairness. While holding elections has become the de facto proof of government legitimacy, those electoral processes may hide a dirty little secret of the government illicitly ensuring a favorable election outcome.
This book includes these features designed to make your statistical journey more enjoyable:
- Vignettes of elections, including maps, to provide concrete bases for the material
- In-chapter cues to help one avoid the heavy math-or to focus on it
- End-of-chapter problems designed to review and extend that which was covered in the chapter
- Many opportunities to turn the power of the R statistical environment to the enclosed election data files, as well as to those you find interesting
From these features, it is clear the audience for this book is quite diverse. This text provides mathematics for those interested in mathematics, but also offers detours for those who just want a good read and a deeper understanding of elections.
Ole J. Forsberg holds PhDs in both political science and statistics. He currently teaches mathematics and statistics in the Department of Mathematics at Knox College in Galesburg, IL.
Ole J. Forsberg, BS, MAT, MA, MSE, PhDd, is an Assistant Professor of Mathematics-Statistics at Knox College in Galesburg, IL. He received a PhD in Political Science at the University of Tennessee-Knoxville in 2006, concentrating in International Relations, War, and Terrorism. After finishing his dissertation, Dr Forsberg began a deeper investigation of the statistical techniques he used. As a result of that embarrassment, Dr Forsberg began statistical studies at the Johns Hopkins University (MSE, 2010) and concluded them with a PhD in Statistics from Oklahoma State University in 2014. His dissertation explored and applied applications of statistical techniques to testing elections for violations of the "free and fair" democratic claim. His research agenda lies in extending and applying statistical methods to modeling elections and testing the results for evidence of bias in election results.
1. Polling 101
2. Polling 399
3. Combining Polls
4. In-Depth Analysis: Brexit 2016
5. Digit Tests
6. Differential Invalidation
7. Considering Geography
8. In-Depth Analysis: Sri Lanka since 1994
"This unique book, by an author who is both a Statistician and Political Scientist, discusses the statistical theory of two important aspects of elections. The first half is an in-depth introduction to the classical statistical theory of polling, including estimators, confidence intervals, and stratified sampling. It comes complete with snippets of R code and many concrete examples, including two cases that challenged pollsters: the 2016 US presidential election and the 2016 Brexit vote. The second half concerns statistical methods for after the fact detection of fraudulent elections. It includes an in-depth treatment of methods based on the Benford distribution, but also methods based on classical regression analysis. Again numerous pieces of R code and concrete examples are provided."
- E. Arthur Robinson, Jr., Professor of Mathematics, George Washington University