Nonparametric analysis of 2020 US presidential elections. Repository for the code of "Nonparametric Statistics" course, 2020/21, Mathematical Engineering, Politecnico di Milano.
In this project, we analyze differences in performance metrics for collegiate basketball teams that have qualified for March Madness versus those that have not using a variety of Monte Carlo Simulation methods in R.
This was an experiment of a 2-sample permutation or randomization T-test with a small pre-and post-survey. The client had a small sample (n<30) and the experiment informed the research results.
This is the code of a group university project on insurance premiums I took part in. Nonparametric statistics has been used for the data analysis and a shiny app has been implemented to show health insurance premium predictions. I thank Anna Iob, Martina Garavaglia and Veronica Mazzola who have partecipated in the project realisation.
This is a project I did in the Spring of 2017 for the graduate course, Statistical Computing. In this project, I used a bootstrap approach to obtain a 90% confidence interval for an estimate of the coefficient variation