I will attempt to link to my GitHub Repo for this project here. I’m new to this.
https://github.com/SRB75/CC-US-Medical-Insurance-Analysis
This was a fun project. I enjoyed every step.
Big Decisions made:
- I opted to use linear regression to relate BMI to Insurance Costs (similar to the Reggie’s Linear Regression Project)
- I decided to normalize BMI and Insurance Costs to Z-scores before analyzing because neither variable would natively include a zero, or anything close.
- I decided to test the variable globally, and also by gender
- I wanted to display my results graphically. I don’t have that skill yet, so I leaned on ChatGPT to help me with Seaborn and Matplotlib to get this step done.
Do you agree with my conclusions? I added a conclusions and future consideration section to my Jupyter Notebook, and I’m open to your critiques.