What are the types of linear regression?

Linear regression is a statistical technique used to model the relationship between a dependent variable and one or more independent variables. There are several types of linear regression methods that can be employed based on the nature of the data and the research question. Simple linear regression involves a single independent variable, while multiple linear regression incorporates multiple independent variables. Polynomial regression allows for non-linear relationships by including polynomial terms in the model equation. Ridge regression and lasso regression are techniques used to prevent overfitting in cases where there are high multicollinearity and many independent variables. Stepwise regression is a method that automatically selects the most significant independent variables to include in the model. Overall, the types of linear regression vary to accommodate different data structures and research objectives.

This mind map was published on 26 October 2023 and has been viewed 104 times.