OLS. R and Python. In this project, we study fundamental concepts of Supervised ML models, such as Regression Analysis: Coefficient of Model Adjustment (R²), Parameters Estimation ,Statistical Significance of the Model (F test, T test) ,Multiple Regression , Qualitative Explanatory Variables (X) , heteroscedasticity and etc.

Investigating the Impact of Smoking and Weight on Hypertension as part of the Biostatistics course at Ghent University

An interactive Shiny app to demonstrate the continuity in General Linear Models (GLM), created for Advanced Design and Data Analysis at the University of Melbourne.