10. Hypothesis Testing for Two Samples

When comparing two independent samples with unknown and unequal variances, which of the following statements is NOT true?

Suppose two independent random samples are taken from two normal populations with unknown and unequal variances. Which statistical test is most appropriate for testing whether the population means are equal?

When dealing with two independent means where the population variances are unknown and assumed to be unequal, which statistical test is most appropriate to compare the means?

Performing a Wilcoxon Test In Exercises 3–8,

a. identify the claim and state H0 and Ha.

b. decide whether to use a Wilcoxon signed-rank test or a Wilcoxon rank sum test

c. find the critical value(s).

d. find the test statistic.

e. decide whether to reject or fail to reject the null hypothesis.

[APPLET] Earnings by Degree A college administrator claims that there is a difference in the earnings of people with bachelor’s degrees and those with advanced degrees. The table shows the earnings (in thousands of dollars) of a random sample of 11 people with bachelor’s degrees and 10 people with advanced degrees. At α = 0.01, is there enough evidence to support the administrator’s claim? (Adapted from U.S. Census Bureau)

Bachelor’s: 50, 63, 93, 69, 67, 99, 82, 67, 50, 74, 71

Advanced: 138, 88, 99, 113, 104, 102, 116, 84, 114, 96

Researchers are comparing the average number of hours worked per week by employees at two different companies. Below are the results from two independent random samples. Assuming population standard deviations are unknown and unequal, calculate the $t$-score for the difference in means, but do not find a $P$-value or state a conclusion.

Company A: $n_1=25$; ${\bar{x}}_1=22.4$ hours; $s_1=3.2$ hours

Company B: $n_2=16$ ${\bar{x}}_2=21.1$ hours; $s_1=2.9$ hours

A researcher is comparing average number of hours spelt per night by college students who work part-time versus those who don't. From survey data, they calculate ${\bar{x}}_1=6.82$ hours and $x_{\bar{2}}=6.57$ hours with a margin of error of 0.41. Should they reject or fail to reject the claim that there is no difference in hours slept between the two groups?

Randomization with Commute Times Given the two samples of commute times (minutes) shown here, which of the following are randomizations of them?

[Image]

a. Boston: 10 10 60. New York: 5 20 25 30 45.

b. Boston: 10 10 60 20 25. New York: 5 30 45.

c. Boston: 5 10 25 25 60. New York: 5 30 30 60.

d. Boston: 10 10 60. New York: 5 20 25 30 45.

e. Boston: 10 10 10 10 10. New York: 60 60 60.

Finding Critical Values Assume that we have two treatments (A and B) that produce quantitative results, and we have only two observations for treatment A and two observations for treatment B. We cannot use the Wilcoxon signed-ranks test given in this section because both sample sizes do not exceed 10.

a. Complete the accompanying table by listing the five rows corresponding to the other five possible outcomes, and enter the corresponding rank sums for treatment A.

Comparing Two Means Treating the data as samples from larger populations, test the claim that there is a significant difference between the mean of presidents and the mean of popes.

Explain how to perform a two-sample z-test for the difference between two population means using independent samples with and known.

Describe another way you can perform a hypothesis test for the difference between the means of two populations using independent samples with and known that does not use rejection regions.

Independent and Dependent Samples In Exercises 5–8, classify the two samples as independent or dependent and justify your answer.

Sample 1: The commute times of 10 workers when they use their own vehicles

Sample 2: The commute times of the same 10 workers when they use public transportation

In Exercises 11–14, test the claim about the difference between two population means and at the level of significance . Assume the samples are random and independent, and the populations are normally distributed.

Claim: μ1<μ2; α=0.05

Population statistics:σ1=75 and σ2=105

Sample Statistics: x̅1=2435, n1=35, x̅2=2432, n2=90

In Exercises 11–14, test the claim about the difference between two population means and at the level of significance . Assume the samples are random and independent, and the populations are normally distributed.

Claim: μ1<μ2; α=0.03

Population statistics:σ1=136 and σ2=215

Sample Statistics: x̅1=5004, n1=144, x̅2=4895, n2=156

Testing the Difference Between Two Means In Exercises 15–24, (a) identify the claim and state Ho and Ha, (b) find the critical value(s) and identify the rejection region(s), (c) find the standardized test statistic z, (d) decide whether to reject or fail to reject the null hypothesis, and (e) interpret the decision in the context of the original claim. Assume the samples are random and independent, and the populations are normally distributed.

Braking Distances To compare the dry braking distances from 60 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 16 compact SUVs and 11 midsize SUVs. The mean braking distance for the compact SUVs is 131.8 feet. Assume the population standard deviation is 5.5 feet. The mean braking distance for the midsize SUVs is 132.8 feet. Assume the population standard deviation is 6.7 feet. At α=0.10 , can the engineer support the claim that the mean braking distances are different for the two categories of SUVs? (Adapted from Consumer Reports)