IHP 525 Module Five Problem Set
1. Newborn weight. A study takes a SRS from a population of full-term infants. The standard
deviation of birth weights in this population is 2 pounds. Calculate 95% confidence intervals
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IHP 525 Module Five Problem Set
1. Newborn weight. A study takes a SRS from a population of full-term infants. The standard
deviation of birth weights in this population is 2 pounds. Calculate 95% confidence intervals for μ
for samples in which:
a) n = 81 and = 7.0 pounds
7.0±(1.96)(2/√81) = +7.0± (0.435)=( 6.6, 7.4)
b) n = 9 and = 7.0 pounds
7.0±(1.96)(2/√9) = +7.0± (1.31) = (5.7, 8.3)
c) Which sample provides the most precise estimate of the mean birth weight?
The first sample of n equals 81, and since this population has means that are
similar to eachother.
d) Interpret the CI you computed in part a).
We can be 95% confident that the birth weight in a population of full term
infants is between 6.6 and 7.4 pounds.
2. P-value and confidence interval. A two-sided test of H0: μ = 0 yields a P-value of 0.03. Will the
corresponding 95% confidence interval for μ include 0 in its midst? Will the 99% confidence
interval for μ include 0? Explain your reasoning in each instance.
a. In this case where the confidence interval is 95%, α= 0.05 > p = 0.03, the p-value
is considered less than alpha 0.05. Due ot this, we reject the null hypothesis so so
μ=0 is not included in the interval.
b. In the case where the confidence interval is 99%, α= 0.01 < p = 0.03, the p-value
is greater than the level of significance. Due to this, the p-value will not get
rejected and the 99% confidence interval for the mean(μ) will include a 0.
3. Menstrual cycle length. Menstrual cycle lengths (days) in an SRS of nine women are as follows:
{31, 28, 26, 24, 29, 33, 25, 26, 28}. Use this data to test whether mean menstrual cycle length
differs significantly from a lunar month using a one sample t-test. (A lunar month is 29.5 days.)
Assume that population values vary according to a Normal distribution. Use a two-sided
alternative. Show all hypothesis-testing steps.
Summary statistics:
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