Hours of sleep: The table below provides
information about hours of sleep.
- Calculate statistical power for a one-tailed test (a =
0.05, or 5%) aimed at determining if those in the sample sleep
fewer hours, on average, than those in the population.
- Recalculate statistical power with alpha of 0.01, or 1%.
Explain why changing alpha affects power. Explain why we should not
use a larger alpha to increase power.
- Without performing any computations, describe how statistical
power is affected by performing a two-tailed test for this example.
Why are two-tailed tests recommended over one-tailed tests?
- The easiest way to affect the outcome of a hypothesis test is
to increase sample size. Similarly, true results may sometimes be
missed because a sufficient sample was not used in the research.
Perform the hypothesis test on these data with a sample of 37. Then
perform the same hypothesis test but assume that the mean was based
on only 4 infants.
- The easiest way to increase statistical power is to increase
sample size. Similarly, statistical power decreases with a smaller
sample size. For these data, compute the statistical power of the
one-tailed statistical test with alpha of 0.05 when N is
4. How does that value compare to when N was 37?
Mean of population 1 (from which the sample comes)
|
14.9 hours of sleep
|
Sample size
|
37 infants
|
Mean of population 2
|
16 hours of sleep
|
Standard deviation of the population
|
1.7 hours of sleep
|
Standard error
|
|