1.A numerical measure of linear association between two variables is the _____. A. correlation coefficient
2. A population has a mean of 80 and a standard deviation of 7. A sample of 49 observations will be taken. The probability that the mean from that sample will be larger than 82 is _____. A. 0228
3. A regression model between sales (y in $1000s), unit price (x1 in dollars) and television advertisement (x2 in dollars) resulted in the following function:
y^ = 7 – 3×1 + 5×2
For this model, SSR = 3500, SSE = 1500, and the sample size is 18.
Refer to Exhibit 15-2. 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 $5000
4. A regression model between sales (y in $1000s), unit price (x1 in dollars) and television advertisement (x2 in dollars) resulted in the following function:
y^ = 7 – 3×1 + 5×2
For this model, SSR = 3500, SSE = 1500, and the sample size is 18.
Refer to Exhibit 15-2. The coefficient of the unit price indicates that if the unit price is _____. A. increased by $1 (holding advertising constant), sales are expected to decrease by $3000
5. Assume z is a standard normal random variable. What is the value of z if the area between -z and zis .754? A. 1.16
6. Exhibit 15-8
The following estimated regression model was developed relating yearly income (y in $1000s) of 30 individuals with their age (x1) and their term-3 gender (x2) (0 if male and 1 if female).
y^= 30 + 0.7×1 + 3×2
Also provided are SST = 1200 and SSE = 384.
Refer to Exhibit 15-8. From the above function, it can be said that the expected yearly income for _____. A. female is $3,000 more than males
7. Exhibit 5-7A sample of 2,500 people was asked how many cups of coffee they drink in the morning. You are given the following sample information.
Cups of Coffee ; Frequency
0 ; 700
1 ; 900
2 ; 600
3 ; 300
; 2,500
Refer to Exhibit 5-7. The variance of the number of cups of coffee is _____. A. .96
8. Exhibit 5-7A sample of 2,500 people was asked how many cups of coffee they drink in the morning. You are given the following sample information.
Cups of Coffee ; Frequency
0 ; 700
1 ; 900
2 ; 600
3 ; 300
2,500
Refer to Exhibit 5-7. The expected number of cups of coffee is _____. A. 1.2
9. Exhibit 6-3The weight of football players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds.
Refer to Exhibit 6-3. What is the minimum weight of the middle 95% of the players? A. 151
10. Exhibit 6-3The weight of football players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds.
Refer to Exhibit 6-3. The probability of a player weighing less than 250 pounds is _____. A. 9772
11. Exhibit 7-3The following information was collected from a simple random sample of a population.
16 ; 19 ; 18 ; 17 ; 20 ; 18
Refer to Exhibit 7-3. The point estimate of the mean of the population is _____. A. 18.0
12. Exhibit 7-4A 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.
Refer to Exhibit 7-4. The point estimate of the mean content of all bottles is _____. A. 4
13. Exhibit 7-4A 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.
Refer to Exhibit 7-4. The standard error of the mean equals _____. A. 0200
14. For any continuous random variable, the probability that the random variable takes on exactly a specific value is _____. A. 0
15. If a qualitative variable has k levels, the number of dummy variables required is _____. A. k− 1
16. Random samples of size 49 are taken from a population that has 200 elements, a mean of 180, and a variance of 196. The distribution of the population is unknown. The mean and the standard error of the distribution of sample means are _____. A. 180 and 2
17. The difference between the observed value of the dependent variable and the value predicted by using the estimated regression equation is the _____. A. residual
18. The expected value of a random variable is the _____. A. mean value
19. The probability distribution of all possible values of the sample mean is called the ____. A. sampling distribution of the sample mean
20. The weight of football players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds.
Refer to Exhibit 6-3. What percent of players weigh between 180 and 220 pounds? A. None of the answers is correct
21. When the population has a normal distribution, the sampling distribution of is normally distributed _____. A. for any sample size
22. Which of the following is NOT a characteristic of the normal probability distribution? A. The graph of the curve is the shape of a rectangle.
23. Exhibit 7-4A 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.
Refer to Exhibit 7-4. In this problem, the .22 is _____. A. a parameter
24. As the sample size increases, the variability among the sample means _____. A. decreases
25. Exhibit 15-8
The following estimated regression model was developed relating yearly income (y in $1000s) of 30 individuals with their age (x1) and their gender (x2) (0 if male and 1 if female).
y^= 30 + 0.7×1 + 3×2
Also provided are SST = 1200 and SSE = 384.
Refer to Exhibit 15-8. The multiple coefficient of determination is _____ A. 68
26. The following estimated regression model was developed relating yearly income (y in $1000s) of 30 individuals with their age (x1) and their gender (x2) (0 if male and 1 if female).
y^ = 30 + 0.7×1 + 3×2
Also provided are SST = 1200 and SSE = 384.
Refer to Exhibit 15-8. The yearly income of a 24-year-old male individual is _____. A. $46,800
27. A marketing manager instructs his team to make 80 telephone calls to attempt to sell an insurance policy. The random variable in this experiment is the number of sales made. This random variable is a _____. A. discrete random variable
28. If r = 0.48 for data set A and r = -0.48 for data set B, which of the following is true? A. The two data sets have the same level of correlation.
29. Exhibit 6-3The weight of football players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds.
Refer to Exhibit 6-3. The probability of a player weighing more than 241.25 pounds is _____. A. 0495
30. Regression analysis is a statistical procedure for developing a mathematical equation that describes how _____. A. one dependent and one or more independent variables are related
Other Links:
See other websites for quiz:
Check on QUIZLET