Ole J. Forsberg, PhD, is an Associate Professor of Mathematics-Statistics and the Associate Dean of Faculty Affairs at Knox College in Galesburg, IL. He received a PhD in Political Science from the University of Tennessee-Knoxville in 2006, concentrating in International Relations, War, and Terrorism. After finishing his dissertation, Forsberg began a deeper investigation of the statistical techniques he used there. As a result of the ensuing embarrassment, he began formal graduate statistical studies at the Johns Hopkins University (MSE, 2010) and concluded them with a PhD in Statistics from Oklahoma State University in 2014 (Go Pokes!). His statistics dissertation explored and applied 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 elections with the goal of drawing as much out of the available information as possible. . . whether this is in terms of understanding political polls, predicting election outcomes, or testing elections for unfairness.

• 1. Introduction to Polling. 2. Simple Random Sampling. 3. Interval Estimation. 4. Stratified Sampling. 5. The Bayesian Solution. 6. Aggregating Polls. 7. Going Beyond the Two-Race. 8. Testing Elections: Digit Tests. 9. Testing Elections: Regression Tests. 10. Election Polling Analysis: Brexit Vote, 2016. 11. Election Analysis: Collier County. 12. System Analysis: Sri Lanka since 1994. 13. An Afterword: Biases in Polling.

Ole J. Forsberg, PhD, is an Associate Professor of Mathematics-Statistics and the Associate Dean of Faculty Affairs at Knox College in Galesburg, IL. He received a PhD in Political Science from the University of Tennessee-Knoxville in 2006, concentrating in International Relations, War, and Terrorism. After finishing his dissertation, Forsberg began a deeper investigation of the statistical techniques he used there. As a result of the ensuing embarrassment, he began formal graduate statistical studies at the Johns Hopkins University (MSE, 2010) and concluded them with a PhD in Statistics from Oklahoma State University in 2014 (Go Pokes!). His statistics dissertation explored and applied 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 elections with the goal of drawing as much out of the available information as possible. . . whether this is in terms of understanding political polls, predicting election outcomes, or testing elections for unfairness.

• 1. Introduction to Polling. 2. Simple Random Sampling. 3. Interval Estimation. 4. Stratified Sampling. 5. The Bayesian Solution. 6. Aggregating Polls. 7. Going Beyond the Two-Race. 8. Testing Elections: Digit Tests. 9. Testing Elections: Regression Tests. 10. Election Polling Analysis: Brexit Vote, 2016. 11. Election Analysis: Collier County. 12. System Analysis: Sri Lanka since 1994. 13. An Afterword: Biases in Polling.

Ole J. Forsberg, PhD, is an Associate Professor of Mathematics-Statistics and the Associate Dean of Faculty Affairs at Knox College in Galesburg, IL. He received a PhD in Political Science from the University of Tennessee-Knoxville in 2006, concentrating in International Relations, War, and Terrorism. After finishing his dissertation, Forsberg began a deeper investigation of the statistical techniques he used there. As a result of the ensuing embarrassment, he began formal graduate statistical studies at the Johns Hopkins University (MSE, 2010) and concluded them with a PhD in Statistics from Oklahoma State University in 2014 (Go Pokes!). His statistics dissertation explored and applied 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 elections with the goal of drawing as much out of the available information as possible. . . whether this is in terms of understanding political polls, predicting election outcomes, or testing elections for unfairness.

• 1. Introduction to Polling. 2. Simple Random Sampling. 3. Interval Estimation. 4. Stratified Sampling. 5. The Bayesian Solution. 6. Aggregating Polls. 7. Going Beyond the Two-Race. 8. Testing Elections: Digit Tests. 9. Testing Elections: Regression Tests. 10. Election Polling Analysis: Brexit Vote, 2016. 11. Election Analysis: Collier County. 12. System Analysis: Sri Lanka since 1994. 13. An Afterword: Biases in Polling.