Linear Regression Quiz (Medium 2)

In linear regression, when we apply a log transformation to the response variable, what is a key impact on the model’s interpretation?

What is the primary purpose of using polynomial regression?

Which of the following best describes the concept of ‘interaction effects’ in linear regression? 

In linear regression, what does it imply if the confidence intervals for the coefficients are very wide? 

In linear regression, what is the consequence of ‘spatial autocorrelation’ in the residuals?

When modeling non-linear relationships in linear regression, which technique is commonly used?

How does a prediction interval in linear regression differ from a confidence interval?

How do you interpret a significant interaction term in a linear regression model?

In linear regression analysis, how does the role of the F-statistic compare to assessing the importance of individual variables?

What is the main limitation of using R-squared as the sole measure of goodness of fit in a linear regression model?

In linear regression, what is the implication of a high VIF (Variance Inflation Factor) value for a predictor variable?