1. The president of a university claimed that the entering class this year appeared to be larger than the entering class from previous years but their mean SAT score is lower than previous years. He took a sample of 20 of this year's entering students and found that their mean SAT score is 1,501 with a standard deviation of 53. The university's record indicates that the mean SAT score for entering students from previous years is 1,520. He wants to find out if his claim is supported by the evidence at a 5% level of significance. What is the population the president is interested in?

A. the SAT scores of all students entering universities in the U.S. this year

B. all entering students to all universities in the U.S this year

C. all SAT test centers in the U.S. this year

D. all entering students to his university this year

2. A drug company is considering marketing a new local anesthetic. The effective time of the anesthetic the drug company is currently producing has a normal distribution with an mean of 7.4 minutes with a standard deviation of 1.2 minutes. The chemistry of the new anesthetic is such that the effective time should be normally distributed with the same standard deviation, but the mean effective time may be lower. If it is lower, the drug company will market the new anesthetic; otherwise, they will continue to produce the older one. A sample of size 36 results in a sample mean of 7.1. A hypothesis test will be done to help make the decision. What are the appropriate hypotheses?

A. H0: >7.4

versus

H1: 7.4

B.

H0: =7.4

versus

H1: 7.4

C.

H0: 7.4

versus

H1: >7.4

D.

H0: 7.4

versus

H1: <7.4

3. For a given level of significance (), if the sample size n is increased, what can be said about the probability of a Type II error ()?

A. The probability of a Type II error () will increase.

B. The probability of a Type II error () will remain the same.

C. The probability of a Type II error () will decrease.

D.The probability of a Type II error () cannot be determined.

4. Microsoft Excel was used on a set of data involving the number of defective items found in a random sample of 46 cases of light bulbs produced during a morning shift at a plant. A manager wants to know if the mean number of defective bulbs per case is greater than 20 during the morning shift. She will make her decision using a test with a level of significance of 0.10. This information was extracted from the Microsoft Excel output for the sample of 46 cases.

n=46;

Arithmetic

Mean=28.00;

Standard

Deviation=25.92;

Standard

Error=3.82;

Null Hypothesis:

20;

=0.10;

df=45;

T Test

Statistic=2.09;

One-Tail Test Upper Critical

Value=1.3006;

p-value=0.021;

Decision=Reject.

What is the parameter the manager is interested in?

A.the mean number of defective light bulbs per case produced at the plant

B.the mean number of defective light bulbs per case produced during the morning shift

C.the mean number of defective light bulbs per case among the 46 cases

D.the proportion of cases with defective light bulbs produced at the plant

5. The quality control engineer for a furniture manufacturer is interested in the mean amount of force necessary to produce cracks in stressed oak furniture. She performs a two-tail test of the null hypothesis that the mean for the stressed oak furniture is 650. The calculated value of the Z test statistic is a positive number that leads to a p-value of 0.080 for the test. Suppose the engineer had decided that the alternative hypothesis to test was that the mean was less than 650. What would be the p-value of this one-tail test?

A.0.040

B. 0.160

C.0.840

D.0.960