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
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
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
B. Refer to Exhibit 8-2. The standard error of the mean is
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
B. Refer to Exhibit 9-4. The p-value is
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. s1 = s2 = 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
8. You are given the following information about y and x.
Dependent Variable Independent Variable
A. Refer to Exhibit 12-2. The least squares estimate of b1 equals
B. Refer to Exhibit 12-2. The least squares estimate of b0 equals
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
Sb1 = 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
10. A regression model between sales (Y in $1,000), unit price (X1 in dollars) and television advertisement (X2 in dollars) resulted in the following function:
= 7 - 3X1 + 5X2
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 X2 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