BiteSizedChunks.comLearn one small thing at a time.

Course contentsShow

634Categorical Variables in Regression
635Dummy Variable Encoding Basics
636The Reference Category
637Interpreting Dummy Variable Coefficients
638One-Hot Encoding Overview
639The Dummy Variable Trap
640Encoding in Python with pandas
641Handling High-Cardinality Categoricals
642What is a Reference Category?
643Interpreting Coefficients Relative to Reference
644Choosing a Reference Category
645Changing the Reference Category
646Reference Categories in Statistical Software
647Impact on Model Results and Reporting
648What are Interaction Terms?
649Interpreting Models Without Interactions
650Creating Interaction Terms
651Interpreting Continuous × Continuous Interactions
652Interpreting Categorical × Continuous Interactions
653Interpreting Categorical × Categorical Interactions
654Testing Interaction Significance
655Visualizing Interactions
656Centering Variables in Interactions
657What Are Polynomial Features?
658Creating Polynomial Terms
659Interpreting Polynomial Regression Coefficients
660Choosing the Polynomial Degree
661Centering Predictors for Polynomials
662Polynomial Features vs Splines
663Common Pitfalls with Polynomial Features

634Categorical Variables in Regression
635Dummy Variable Encoding Basics
636The Reference Category
637Interpreting Dummy Variable Coefficients
638One-Hot Encoding Overview
639The Dummy Variable Trap
640Encoding in Python with pandas
641Handling High-Cardinality Categoricals
642What is a Reference Category?
643Interpreting Coefficients Relative to Reference
644Choosing a Reference Category
645Changing the Reference Category
646Reference Categories in Statistical Software
647Impact on Model Results and Reporting
648What are Interaction Terms?
649Interpreting Models Without Interactions
650Creating Interaction Terms
651Interpreting Continuous × Continuous Interactions
652Interpreting Categorical × Continuous Interactions
653Interpreting Categorical × Categorical Interactions
654Testing Interaction Significance
655Visualizing Interactions
656Centering Variables in Interactions
657What Are Polynomial Features?
658Creating Polynomial Terms
659Interpreting Polynomial Regression Coefficients
660Choosing the Polynomial Degree
661Centering Predictors for Polynomials
662Polynomial Features vs Splines
663Common Pitfalls with Polynomial Features

← Data Science

Lesson 651 of 2,145·17. Categorical Predictors and InteractionsPro lesson

Interpreting Continuous × Continuous Interactions

Understand how to interpret coefficients when both predictors in an interaction are continuous variables.

This lesson is for subscribers

You've completed the free preview. Subscribe to unlock every lesson in every course.

See pricing Back to course