Question

In: Statistics and Probability

This week we are learning about the Independent Samples T-Test (a.k.a., between-subjects research design), which tests...

This week we are learning about the Independent Samples T-Test (a.k.a., between-subjects research design), which tests for mean differences between two independent groups. For this discussion, your task is to describe two examplesof a research question that could be tested with an independent samples t-test. In addition, describe what you believe the outcome would be if the study were to be conducted. Or, if you happen to know of actual research that has tested this question, provide a link for others to check it out. To clarify, you are not actually going to conduct this research. All you need to do is describe the research question and what you hypothesize the outcome to be.

Solutions

Expert Solution

David Anderson has been working as a lecturer at Michigan State University for the last three
years. He teaches two large sections of introductory accounting every semester. While he uses
the same lecture notes in both sections, his students in the first section outperform those in the
second section. David decides to carry out a formal test to validate his hunch regarding the
difference in average scores. In a random sample of 18 students in the first section, he computes
a mean and standard deviation of 77.4 and 10.8, respectively. In the second section, a random
sample of 14 students results in a mean of 74.1 and a standard deviation of 12.2.

sample mean s n
1 77.4 10.8 18
2 74.1 12.2 14
df 30
sp 11.4277
TS 0.8104
alpha 0.01
critical value 2.4573
Decision fail to reject

Formulas

sample mean s n
1 77.4 10.8 18
2 74.1 12.2 14
df =D2+D3-2
sp =SQRT(((D2-1)*C2^2+(D3-1)*C3^2)/C5)
TS =(B2-B3)/(C6*SQRT(1/D2+1/D3))
alpha 0.01
critical value =T.INV(1-C10,C5)
Decision fail to reject

a)
Ho: μ1 = μ2
Ha: μ1 > μ2

b)
TS = 0.8104
c)
critical value = 2.4573
Rejection region is TS larger than 2.4573
Since TS does not lie in rejection region
Therefore, we fail to reject the null hypothesis
There is not enough evidence to conclude that students in the first section outperform those
in the second section.


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