It's a collection of iPython notebooks I created while taking a stats course. The professor taught the class using Minitab and SAS; however, I wanted to learn how to do the assignments in python. I knew this would be to my advantage later on when I started learning machine learning with scikit-learn.
Most of the problems come from Applied Linear Statistical Models, Fifth Edition by Kutner, Nachtsheim, Neter, and Li (2005).
- Linear regression with one predictor variable
- Regression and correlation analysis
- Multiple regression
- Quantitative and qualitative predictors
- Model selection, validation and diagnostics
- ANOVA diagnostics
- numpy
- scipy
- matplotlib
- pandas
- statsmodels
- sklearn
- seaborn
I also used Minitab and SAS for some work I didn't have time to figure out how to do in python.