1. A teacher is experimenting with computer-based instruction. In which situation could the teacher use a hypothesis test for a difference in two population means?

A) She gives each student a pretest. Then she teaches a lesson using a computer program. Afterwards, she gives each student a posttest. The teacher wants to see if the difference in scores will show an improvement.

B) She randomly divides the class into two groups. One group receives computer-based instruction. The other group receives traditional instruction without computers. After instruction, each student has to solve a single problem. The teachers wants to compare the proportion of each group who can solve the problem.

C) She gives each student a pretest. She then randomly divides the class into two groups. One group receives computer-based instruction. The other group receives traditional instruction without computers. After instruction, each student takes a post-test. The teacher compares the improvement in scores (post-test minus pretest) in the two groups.

D) The teacher uses a combination of traditional methods and computer-based instruction. She asks students if they liked computer-based instruction better. She wants to determine if the majority prefer the computer-based instruction.

2. In a study of the impact of smoking on birth weight, researchers analyze birth weights (in grams) for babies born to 189 women who gave birth in 1989 at a hospital in Massachusetts. In the group 74 were categorized as "smokers" and 115 as "nonsmokers." The difference in mean birth weights (nonsmokers minus smokers) is 281.7 grams with a margin of error of 205.2 grams with 95% confidence.

A) We are 95% confident that smoking causes lower birth weights by an average of between 76.5 grams to 486.9 grams.

B) There is a 95% chance that if a woman smokes during pregnancy her baby will weigh between 76.5 grams to 486.9 grams less than if she did not smoke.

C) Good job. Smoking is associated with lower birth weights. When smokers are compared to nonsmokers, we are 95% confident that the mean weight of babies born to nonsmokers will be between 76.5 grams to 486.9 grams more than the mean birth weight of babies born to smokers.

D) With such a large margin of error, this study does not suggest that there is a difference in mean birth weights when we compare smokers to nonsmokers.

3. A random sample of 500 StatCrunchU students contains 309 female and 191 males. We analyze responses to the question, "What is the total amount (in dollars) of your student loans to date?"

Two sample T confidence interval: 1: Mean of Loans where Gender="Female" 2: Mean of Loans where Gender="Male" 12: Difference between two means (without pooled variances)

95% confidence interval results:

Difference	Sample Diff.	Std. Err.	DF	L. Limit	U. Limit
12	1271.695	526.63081	435.7666	236.64284	2306.7472

What can we conclude from the 95% confidence interval? Select all that apply.

A) According to this confidence interval, it is possible that there are no gender differences in student loan debt.

B) We are 95% confident that at StatCrunchU female students carry anywhere from an average of $236.64 to $2,306.74 more in student loan debt than male students.

C) We are 95% confident that at StatCrunchU male students carry anywhere from an average of $236.64 to $2,306.74 more in student loan debt than female students.

D) We are 95% confident that at StatCrunchU female students carry anywhere from an average of $236.64 less to $2,306.74 more in student loan debt than male students.

E) We are 95% confident that the mean gender difference in student loan debt in the samples is $1,271.70.

F) We cannot draw a conclusion because conditions for the T-model are not met.

4. To study the impact of industrial waste on fish, a researcher compares the mercury levels in 15 fish caught near industrial sites to the levels in 15 of the same type of fish caught away from industrial sites. Suppose the researcher correctly conducted a test of significance. The test showed no statistically significant difference in average mercury level for the two groups of fish.

What conclusion can the researcher draw from these results?

A) The researcher must not be interpreting the results correctly; there should be a significant difference.

B) The sample size may be too small to detect a statistically significant difference.

C) It must be true that the industrial waste does not cause higher levels of mercury in fish.

5. Suppose that a biologist is concerned about the effects of a nearby construction site on the nesting behavior of an endangered bird. In this fictional study, nesting behavior is measured by counting the number of trips to the nest per hour for an individual bird.

The biologist compares a random sample of 16 birds near the construction site to a random sample of 16 birds in an undisturbed location.

For both groups, dot plots of these counts are fairly symmetric without strong skew.

The biologist conducts a two-sample t-test to determine whether this sample provides significant evidence that birds near a construction site make fewer trips to the nest per hour. The biologist uses a 5% significance level. The test statistic is t = 1.81 with a P-value 0.04.

Which of the following is an appropriate conclusion?

A) The samples provide statistically significant evidence that birds near a construction site make fewer trips to the nest per hour.

B) The biologist cannot use the t-test in this case because the sample sizes are too small.

C) The samples do not provide statistically significant evidence that birds near a construction site make less trips to the nest per hour.