Answer:
The correct answer is d. Data must be normally distributed for multiple regression.
Justification: In multiple regression, the assumption of normality applies to the residuals (the differences between observed and predicted values). The residuals should be approximately normally distributed for the regression analysis to be valid. However, it is not necessary for the independent variables (predictors) or the dependent variable to be normally distributed. The other points listed are true for conducting multiple regression: a. Multiple regression can be used to assess quadratic relationships, b. Multiple regression can be used to assess linear relationships, and e. Data should be free from outliers for a multiple regression to be reliable.