Predicting Insurance Costs

In this project, you'll assume the role of a data analyst for a hospital administration working to predict patient medical insurance costs. Using a dataset of patient demographic and health information, you'll apply your skills in data exploration, linear regression modeling, model evaluation, and results interpretation to develop a predictive model. This hands-on project allows you to showcase your ability to leverage Python and linear regression to solve a real-world challenge. You'll work through the entire data science pipeline from data loading and exploratory analysis to model fitting, diagnostics, and extracting insights. The final model could help hospitals forecast costs and allocate resources more effectively. Objective: Develop a linear regression model to predict patient medical insurance costs based on demographic and health data, and interpret the model results to provide actionable insights.