1,338 individual medical insurance records across 7 demographic and health-related categories. The data tracks personal attributes like age, BMI, and smoking status alongside total healthcare expenditure.
Use Cases
- Train a regression model to predict 'charges' using 'bmi' and 'smoker' status
- Perform a statistical analysis on the cost disparity between smokers and non-smokers using the 'charges' column
- Examine the relationship between 'age' and healthcare spending for individuals with high 'bmi' values
Strengths
- 1,338 rows of individual medical insurance data
- Features include 'age', 'sex', 'bmi', 'children', 'smoker', and 'region'
- Target variable 'charges' provides the total medical expenditure per record