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.
- Parallel Slopes
- Multiple Linear Regression
- Multiple Logistic Regression