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**1.** A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is 0.22 ounces. The point estimate of the mean content of the bottles is

a. 0.22

b. 4

c. 121

d. 0.02

**2.** There are 6 children in a family. The number of children defines a population. The number of simple random samples of size 2 (without replacement) that are possible equals

a. 12

b. 15

c. 3

d. 16

** **

**3. **A random sample of 81 automobiles traveling on an interstate showed an average speed of 60 mph and a standard deviation of 13.5 mph. Assume the distribution of speeds of all the cars is normal.

A. Refer to Exhibit 8-2. If we are interested in determining an interval estimate for m at 86.9% confidence, the Z value to use is

a. 1.96

b. 1.31

c. 1.51

d. 2.00

B. Refer to Exhibit 8-2. The standard error of the mean is

a. 13.5

b. 9

c. 2.26

d. 1.5

**4**. The manager of a grocery store has taken a random sample of 100 customers. The average length of time it took the customers in the sample to check out was 3.1 minutes with a standard deviation of 0.5 minutes. We want to test to determine whether or not the mean waiting time of all customers is significantly more than 3 minutes.

A. Refer to Exhibit 9-4. The standardized test statistic is

a. 1.96

b. 1.64

c. 2.00

d. 0.056

B. Refer to Exhibit 9-4. The p-value is

a. 0.025

b. 0.0456

c. 0.05

d. 0.0228

**5.** Which of the following statements is **not** a required assumption for developing an interval estimate of the difference between two sample means when the samples are small?

a. Both populations have normal distributions.

b. s_{1} = s_{2} = 1

c. Independent random samples are selected from the two populations.

d. The variances of the two populations are equal.

**6.** If two independent large samples are taken from two populations, the sampling distribution of the difference between the two sample proportions

a. can be approximated by a Poisson distribution

b. will have a standard error of proportion of one

c. can be approximated by a normal distribution

d. will have a proportion of 50%

**7**. Two independent large samples are taken from two populations. The standard error of the difference between the two proportions is determined to be 0.04. At 95% confidence the margin of error is

a. 1.96

b. 1.645

c. 4%

d. 0.0784

**8. **You are given the following information about y and x.

**y** **x**

**Dependent Variable** **Independent Variable**

5 1

4 2

3 3

2 4

1 5

A. Refer to Exhibit 12-2. The least squares estimate of b_{1} equals

a. 1

b. -1

c. 6

d. 5

B. Refer to Exhibit 12-2. The least squares estimate of b_{0} equals

a. 1

b. -1

c. 6

d. 5

**9. **Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained.

= 12 + 1.8 x

n = 17

SSR = 225

SSE = 75

S_{b1} = 0.2683

A. Refer to Exhibit 12-4. Based on the above estimated regression equation, if advertising is $3,000, then the point estimate for sales (in dollars) is

a. $66,000

b. $5,412

c. $66

d. $17,400

**10. **A regression model between sales (Y in $1,000), unit price (X_{1} in dollars) and television advertisement (X_{2} in dollars) resulted in the following function:

= 7 - 3X_{1} + 5X_{2}

For this model SSR = 3500, SSE = 1500, and the sample size is 18.

A. Refer to Exhibit 13**-**2. The coefficient of the unit price indicates that if the unit price is

a. increased by $1 (holding advertising constant), sales are expected to increase by $3

b. decreased by $1 (holding advertising constant), sales are expected to decrease by $3

c. increased by $1 (holding advertising constant), sales are expected to increase by $4,000

d. increased by $1 (holding advertising constant), sales are expected to decrease by $3,000

B. Refer to Exhibit 13**-**2. The coefficient of X_{2} indicates that if television advertising is increased by $1 (holding the unit price constant), sales are expected to

a. increase by $5

b. increase by $12,000

c. increase by $5,000

d. decrease by $2,000

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