Describe the null hypothesis for the test of independence. List
the assumptions for the χ2 test of independence. What is
the major difference between the assumptions for this test and the
assumptions for the previous tests we have studied?
Explain the assumptions for using a two-independent sample
t test. Provide an example for when you could use a a
One-Sample t test. Provide an example for when a Two-Sample t
Test.
Describe the assumptions that should be met when deciding to use
the t-test (i.e., scale of measurement; assumptions about variances
of groups being compared; assumptions about group sizes; shapes of
distributions.)
Independent Samples T-Test by
Group (receiving intervention vs. control group on
waiting
list)
Independent Samples
T-Test
t
df
p
Uscreen
-7.495
98
< .001
Note.
Student's t-test.
Independent Samples T-Test by
Race (White vs. Black/Hispanic)
Independent Samples
T-Test
t
df
p
Uscreen
-2.473
98
0.015
Note.
Student's t-test.
Independent Samples T-Test by
Age (21-24 vs 25-30)
Independent Samples
T-Test
t
df
p
Uscreen
1.478
98
0.143
ᵃ
Note.
Student's t-test.
ᵃ Levene's test is significant
(p < .05), suggesting a...
Step 2 of hypothesis testing involves reviewing the assumptions
of 2 sample t-test. Discuss the three assumptions of the t-test.
Provide an example of the assumption that is not robust to
violations and a situation when the assumption is violated.
Explain why we must verify whether or not the assumptions of an
inferential statistical test are met before we calculate the
statistic. Specifically, what does a failure to meet the
assumptions mean in terms of the α level of our experiment? What
should we do if the assumptions are not met?