Using a medical cost personal data set containing information on individual medical insurance prices, a linear model is constructed that, with certain knowledge about patients, can estimate the insurance cost of their treatment.
In this project, I have built a Ordinary Least Square (OLS) model to forecast insurance bill using Medical cost dataset. The dataset consists of age, sex, BMI(body mass index), children, smoker and region features, which are independent and charges as a dependent feature.
After performing EDA, model building and model validation, a detailed explanation based on the model's statistical parameters has also been provided at the end.
Have a look and enjoy!