When two or more independent variables in a regression model are highly correlated, it's known as ________.
- Collinearity
- Interaction
- Multicollinearity
- Overfitting
This is known as multicollinearity. In regression analysis, multicollinearity refers to a situation where two or more independent variables are highly correlated. This can make it difficult to determine the effect of each individual variable on the dependent variable and can lead to unstable and unreliable estimates.
Loading...
Related Quiz
- What does a p-value represent in a t-test or Z-test?
- Why might the confidence interval for a proportion be skewed?
- If the Kruskal-Wallis H test is significant, it is often followed up with ________ to find which groups differ.
- The Wilcoxon Signed Rank Test requires the differences to be ________.
- The conditional probability of A given B is denoted as ________.