Multiple Linear Regression

Question 1

What are the hypotheses for multiple linear regression?

Answer 1

H0: There is no linear relationship between the predictors and the outcome
H1: At least one predictor is linearly related to the outcome

Question 2

What are the assumptions for multiple linear regression?

Answer 2

• Linearity: There is a linear relationship between the predictors and the outcome
• Independence: The residuals (errors) are independent
• Constant variance of residuals across all levels of predictors
• Normally distributed

Question 3

How do you interpret SPSS output for multiple regression?

Answer 3

• R squared and adjusted R squared indicate how well the model explains the variance in the dependent variable
• ANOVA F-Test: Tests the overall significance of he model
• Coefficients (B,Beta): Measure the impact of each predictor on the outcome
• P-Values: For each predictor, if p<0.05, the predictor significantly impacts the dependent variable