Manuel Hanna

Statistical Modeling

The main objective of this project is to build an accurate multiple linear regression model to predict a response variable (Y) based on 11 regressors (X1 to X11). The dataset used for this project contains 999 observations, and we will be experimenting with various modeling techniques, ranging from basic linear regression on subsets of the regressors to more complex models that incorporate transformations of the regressors, such as polynomial regression. Additionally, we will explore regularization methods like LASSO regression to further improve model performance.