For each of the following scenarios, simply state WHICH technique would be the most appropriate method to analyze the results.

a. Sam wants to know if students spend more time studying for midterms or for finals. She asks 30 people how many hours they studied for each exam, and records their responses. She expects that students spend more time studying for finals.
b. Michael thinks that people who travel more report higher quality of life. To test this, Michael studies a group of 20 people across many years. He gets them to rate their quality of life (on a scale from 1-10) before they’ve travelled at all, again after they’ve taken their first trip abroad and again after their third trip abroad. Michael compares the data at the three time points to see if his hypothesis is correct.
c. Meredith wants to know if a new medication affects sleep. So, she takes a sample of 81 people and has them all take the medication for a week. During that time, those 81 people record the number of hours they slept. If you are given M = 42, µ = 45 and σ = 8, how can you determine whether the medication affects the number of hours people sleep.
d. In the previous question, if you were given the standard deviation for the group of 81 people only, instead of σ, what would you do to answer the same question?

There have 30 overviews paired here and we'd like to analyze the mean studying time in the middle and final periods. It will employ a paired t-test. The difference (d) = mid - final

Hypotheses:

[tex]H_o: \mu_d \geq 0\\\\H_a: \mu_d < 0[/tex]

For point b:

More than three variables should be examined here because ANOVA is employed in one method.

For point c:

This one Z test is used since we have the standard difference in population.

Hypotheses:

[tex]H_o:\mu = 45\\\\ H_a:\mu\neq 45[/tex]

For point d:

Since not knowing the sample standard deviation, we will use an individual sample t-test.

Hypotheses:

[tex]H_o: \mu = 45\\\\ H_a: \mu \neq 45[/tex]