Introduction
This project comprehensively analyzes three distinct datasets: FEV.csv, BreastCancer.csv, and a contingency table related to salt intake and blood pressure studies. The analyses include statistical hypothesis testing, logistic regression, random forest classification, and chi-square tests to understand relationships and predict outcomes based on the provided data.
The original project was done in R as part of the Exam for MA335 submitted at the University of Essex. This is the well-written Python version with detailed explanations.