There is a correlation between gender and the use of classes

3

[Q4] Conduct an “Independent Samples T Test for Means” to examine if the mean numbers
of visits are different between male and female (i.e., run an “Independent-Samples T Test
for Means” with “number of visits [visits]” as a Test Variable and “Gender [gender]” as a
Grouping Variable).
(Q4-1) Attach the SPSS output of the T-Test.

(Q4-2) What is the mean number of visits for the male
AFC members in the sample? 9.19
visits
(Q4-3) What is the mean number of visits for the female
AFC members in the sample?

[Q5] Conduct a “Multiple Regression” analysis to examine what are the important factors
that determine the total revenue. More specifically, consider the following equation:
[Revenue] = b0
4

+ b1 * [Age]
+ b2 * [Importance: General Health and Fitness]
+ b3 * [Importance: Social Aspects]
+ b4 * [Importance: Physical Enjoyment]
+ b5 * [Importance: Specific Medical Concerns]
+ b6 * [number of visits]
+ b7 * [Gender]
(Q5-1) Attach the SPSS output of the linear regression analysis.
Model Summary
Model
R
R Square
Adjusted R
Square
Std. Error of the
Estimate
1
.454
a
.206
.169
152.52081
a. Predictors: (Constant), Gender, number of visits, Age in Years,
Importance: General Health and Fitness, Importance: Social Aspects,
Importance: Specific Medical Concerns, Importance: Physical
Enjoyment
ANOVA
a
Model
Sum of Squares
df
Mean Square
F
Sig.