Question: 1) If you have five predictor variables in a multiple regression approximately how large of a sample would you need? 2) What does the multicollinearity

1) If you have five predictor variables in a multiple regression approximately how large of a sample would you need?

2) What does the multicollinearity assumption mean?

3) What are some advantages of multiple regression compared to bivariate regression?

4) R2 is:

A) indicates the slope of the regression line.

B) The proportion of variance in the outcome accounted for by the predictor variable or variables.

C) The proportion of variance in the predictor accounted for by the outcome variable.

D) Tells you if there is a significant difference between variables.

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