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Ace Linear Regression Practical Exam
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Module 6
Advanced Modeling: Interactions & Transformations
1
Understanding Interaction Effects in Regression Models
Interpret the coefficients in a model with an interaction term, explaining how the effect of one predictor depends on the level of another.
2
Conditional Slopes in Interaction Models
Calculate the slope of one predictor for different fixed values of another predictor in an interaction model.
Log Transformations for Linearity and Homoscedasticity
Explain when to use a log transformation on the response or predictor variables to address violations of linearity or homoscedasticity.
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Interpreting Multiple & Categorical Predictors
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Advanced Diagnostics: Problematic Data