The purpose of this project was to perform a multiple linear regression analysis on a dataset centered around medical costs. The endgame was to build a model that can accurately predict charge costs based on certain attributes (age, sex, smoking status, region, etc.). EDA and pre-processing take place first to refine dataset in preparation for the analysis, which helps to deliver the most accurate regression model possible for the analysis. Find link here.