Multiple independent variables usually indicate the potential for a(n):
A) testing effect.
B) main effect hypothesis.
C) interaction effect hypothesis.
D) carryover hypothesis.

Question

Quizplus · Accepted Answer

Multiple independent variables increase the likelihood of an interaction effect hypothesis, where the effect of one independent variable depends on the level of the other independent variable. This is in contrast to a main effect hypothesis, which would suggest that each independent variable has a significant effect on the dependent variable regardless of the level of the other independent variables. A testing effect refers to the possibility that simply being tested could affect the results, while a carryover hypothesis implies that the effects of one condition carry over into another condition.

Multiple Independent Variables Usually Indicate the Potential for A(n)