Multiple Choice
Before running a multiple regression, it is smart to look at the distribution of each variable. We do this because
A) we want to see that the distributions are not very badly skewed.
B) we want to look for extreme scores.
C) we want to pick up obvious coding errors.
D) all of the above
Correct Answer:
Verified
Correct Answer:
Verified
Q14: If we have three predictors and they
Q15: Stepwise regression procedures capitalize on chance.
Q16: In multiple regression an outlier is one
Q17: Multiple regression allows you to examine the
Q18: If we want to compare the contribution
Q20: In the previous question, a student who
Q21: In multiple regression the intercept is usually
Q22: Individual predictors cannot be individually associated with
Q23: Any association that was significant as a
Q24: Are the set of predictors significantly associated