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This course trains students to use statistical models
for forecasting societal, mainly political, outcomes
The students learn how to use Machine Learning and
Data Mining algorithms to explore topics such as
measuring the extent of partisan polarization,
predicting electoral outcomes, predicting local
violence, analyzing the trend of interstate war, and
forecasting civil war. Subjects to be covered include
understanding the differences and similarities
between Correlation Analysis, Causal Inference, and
Forecasting Principles; Naive Bayes; k-Nearest
Neighbors (KNN); Regularized Linear Regression
(Lasso, Ridge, eNet); forecasting using Maximum
Likelihood Estimation (MLE); Trees methods;
Clustering; and Dimension Reduction.
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