Question 1
A study was conducted on 8 pairs on twins. In each pair:
- twin 1 regularly exercised
- twin 2 was not involved in any sport activities.
The stress level for each study participant was recorded as a score
from 0 to 100.
1 |
75.25909 |
57.82698 |
2 |
43.47533 |
100.00000 |
3 |
76.59599 |
80.90780 |
4 |
75.44859 |
34.02972 |
5 |
58.29283 |
23.57029 |
6 |
19.20100 |
49.31615 |
7 |
31.42866 |
49.02355 |
8 |
44.10559 |
45.65467 |
- You want to test if sport decreases the average stress level. State
null and alternative hypotheses. What type of test is appropriate in
this scenario?
- Restate the hypotheses in terms of \(p\), the probability to observe positive
difference between stress levels of twins (twin 1 - twin 2).
- What would be the test statistic for this test?
- What would be the null distribution? Draw the null
distribution.
- What is the observed value of test statistic?
- Find the p-value.
- What conclusion can we draw at significance level 0.1?
Question 2
A study was conducted on 50 male and 50 female first-year students at
U of T.
The stress level for each study participant was recorded as a score
from 0 to 100 and the summary statistics were computed.
mean(male)
## [1] 50.47862
sd(male)
## [1] 18.32589
mean(female)
## [1] 58.15811
sd(female)
## [1] 23.72332
- You want to test if average stress level is different for male and
female students. What test will you use? State null and alternative
hypotheses in terms of the male and female population averages.
- Well, compute degrees of freedom for this test :(
- Compute the \(t_{df}^{\alpha/2}\)
quantile for 90% confidence interval.
- Compute 90% confidence interval for the difference in population
means.
- What conclusion can we draw from the confidence interval?
- Now find the upper 90% CI for the difference in population
means.
- What alternative hypothesis corresponds to this CI? What conclusion
can we draw from this CI?
- Suppose that we know that the population variances for male and
female stress levels are equal, i.e. \(\sigma^2_{male} = \sigma^2_{female}\). How
can you use the summary statistics to approximate the values of the
population variances?
- Find test statistic \(t_{obs}\) for
the case when \(\sigma^2_{male} =
\sigma^2_{female}\).
- Suppose you want to check that female students are more stressed
than male students for the case when \(\sigma^2_{male} = \sigma^2_{female}\). What
would be the p-value?
- What conclusion can you make for the hypothesis from 10 at
significance level \(\alpha =
0.05\)?
Question 3
A study was conducted on 50 male and 50 female first-year students at
U of T.
Each study participant was asked if they feel stressed. The following
results were received:
- You want to test if proportions of stressed male and female students
are different. What test will you use? State null and alternative
hypotheses.
- Find the value of observed statistic.
- Find the p-value.
- Can we conclude that female students stress out more often at
significance level 0.05?