Question

In this section you will interpret output that is provided (you do NOT need to run anything for this scenario).

I am interested in testing whether the section of SOC390 that a participant was in (Variable name = Class; 1= Miller, 2 = Field, 3= Smith) influences their exam scores (Variable name = exam_scores). I also think that gender might also influence exam scores (Variable name = Gender; 0 = female, 1 = male). To test this, I conducted a two-way ANOVA. There is a lot of output associated with a two-way ANOVA – we are only going to focus on the output below.

Tests of Between-Subjects Effects
Dependent Variable:   Hypothetical exam scores (out of 100)
Source	Type III Sum of Squares	df	Mean Square	F	Sig.
Corrected Model	742.256a	5	148.451	2.783	.023
Intercept	477185.101	1	477185.101	8945.486	.000
Class	632.711	2	316.355	5.931	.004
gender	2.943	1	2.943	.055	.815
Class * gender	234.748	2	117.374	2.200	.118
Error	3947.432	74	53.344
Total	588655.000	80
Corrected Total	4689.688	79
a. R Squared = .158 (Adjusted R Squared = .101)

18. What are the two factors in this example? How many levels are on each factor?

[2 points]

           

19. What is the dependent variable? [2 points]

20. In the output above, there are two main effects and an interaction effect being tested. First: assuming α = .05, what are the conclusions for these tests (significant or not significant)? Second: For each, provide the F statistic including degrees of freedom and p-value. [6 points]

F_class(__________, ___________) = ________, p =___________             à Significant or not significant? Not significant

F_gender ( ________, _________) = _________, p =________            à Significant or not significant? Significant

F_classXgender(_______,_______) = ­­­­_________, p =        à Significant or not significant? Not significant

Answer 1