Intermediate Regression with statsmodels in Python

Description

In this course, you will :

• Extend your linear regression knowledge to parallel slopes regression, which uses one numerical and one categorical explanatory variable. This is the first step in overcoming multiple linear regression.
• Investigate the impact of explanatory variable interactions. Taking interactions into account allows for more realistic models with higher predictive power.
• See how modelling and linear regression make it simple to work with variables that have more than two explanatory variables.
• Expand your logistic regression knowledge to include multiple explanatory variables.
• Before implementing your own logistic regression algorithm, learn about logistic distribution, which underpins this type of regression.

Syllabus :

• Parallel Slopes
• Interactions
• Multiple Linear Regression
• Multiple Logistic Regression