- Implement descriptive statistics, t-tests, chi-square tests, and ANOVA.
- Build linear and logistic regression models.
- Train decision trees and random forests using
caret. - Evaluate model performance with accuracy, RMSE, and cross-validation.
- Gain practical experience through hands-on projects with real datasets.
