In this workbook, using the medical insurance cost dataset, and the OLS.from_formula() function from statsmodels.api module, two models that attempt to predict annual insurance costs will be developed.

A significant portion of the implementation workflow will be focusing on data exploration and analyses- from which an understanding of the dataset will be derived, and possible new features for model improvement will be ascertained.

The conclusion of the implementation workflow will be focused on the suitability of the models for prediction based on the criterion of successfully meeting key linear regression assumptions.