Building Statistical Models in Python: Develop useful models for regression, classification, time series, and survival analysis

Table of Contents

1. Sampling and Generalization
2. Distributions of Data
3. Hypothesis Testing
4. Parametric Tests
5. Non-Parametric Tests
6. Linear Regression
7. More Discussion on Model Selection & Regularization
8. Logistic Regression
9. Discriminant Analysis
10. Introduction to Time Series
11. ARIMA Models
12. Multivariate Time Series Methods
13. Time to Event variables - An introduction
14. Models with Survival Responses