Content from the course "Principles and Applications in Statistical Analysis (52221)" at The Hebrew University of Jerusalem, in the Department of Statistics and Data Science.

This project develops a Bayesian data analysis to investigate and quantify how waste per capita is influenced by income and the adoption of Pay-As-You-Throw fee schemes, while accounting for inherently different socioeconomic contexts across Italy.

The Bayesian KMO index is a novel re-conceptualization of the Kaiser-Meyer-Olkin (KMO) index that enables researchers to incorporate prior information and make coherent probabilistic statements about the sampling adequacy of a data matrix.