The project involves sampling designs and summarizing data, maximum likelihood estimation of parameters, bootstrap, parametric and non-parametric inference, the analysis of variance, linear least squares, categorical data, elements of the decision theory and bayesian inference.

Creating predictive models to classify Trump's vote share and clustering counties based on demographics and economic variables. Report findings in PDF with detailed methodologies, model assessments, and R code for the project.