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Question 15 of 40 (Please answer all 6 questions or none at all.) Question 16 of

ID: 3248925 • Letter: Q

Question

Question 15 of 40 (Please answer all 6 questions or none at all.)

Question 16 of 40

Question 17 of 40

Question 18 of 40

Question 19 of 40

Question 20 of 40

A study was conducted to compare the average time spent in the lab each week versus course grade for computer programming students. The results are recorded in the table below. Find the value of the linear correlation coefficient r.

Number of hours spent in lab Grade (percent)  
10 96
11 51
16 62
9 58
7 89
15 81
16 46
10 51

Question 15 of 40 (Please answer all 6 questions or none at all.)

1.0 Points TABLE 13-2

A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below:
City Price ($) Sales River City 1.30 100 Hudson 1.60 90 Ellsworth 1.80 90 Prescott 2.00 40 Rock Elm 2.40 38 Stillwater 2.90 32

Referring to Table 13-2, what is the percentage of the total variation in candy bar sales explained by the regression model? A. 78.39% B. 88.54% C. 48.19% D. 100% Reset Selection

Question 16 of 40

1.0 Points TABLE 13-2

A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below:
City Price ($) Sales River City 1.30 100 Hudson 1.60 90 Ellsworth 1.80 90 Prescott 2.00 40 Rock Elm 2.40 38 Stillwater 2.90 32

Referring to Table 13-2, what is )2 for these data? A. 1.66 B. 25.66 C. 2.54 D. 0 Reset Selection

Question 17 of 40

1.0 Points TABLE 13-2

A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below:
City Price ($) Sales River City 1.30 100 Hudson 1.60 90 Ellsworth 1.80 90 Prescott 2.00 40 Rock Elm 2.40 38 Stillwater 2.90 32

Referring to Table 13-2, if the price of the candy bar is set at $2, the predicted sales will be A. 30. B. 65. C. 90. D. 100. Reset Selection

Question 18 of 40

1.0 Points TABLE 14-1

A manager of a product sales group believes the number of sales made by an employee (Y) depends on how many years that employee has been with the company (X1) and how he/she scored on a business aptitude test (X2). A random sample of 8 employees provides the following:
Employee Y X1 X2 1 100 10 7 2 90 3 10 3 80 8 9 4 70 5 4 5 60 5 8 6 50 7 5 7 40 1 4 8 30 1 1

Referring to Table 14-1, if an employee who had been with the company 5 years scored a 9 on the aptitude test, what would his estimated expected sales be? A. 79.09 B. 17.98 C. 60.88 D. 55.62 Reset Selection

Question 19 of 40

1.0 Points TABLE 14-2

A professor of industrial relations believes that an individual's wage rate at a factory (Y) depends on his performance rating (X1) and the number of economics courses the employee successfully completed in college (X2). The professor randomly selects 6 workers and collects the following information:
Employee Y ($) X1 X2 1 10 3 0 2 12 1 5 3 15 8 1 4 17 5 8 5 20 7 12 6 25 10 9

Referring to Table 14-2, suppose an employee had never taken an economics course and managed to score a 5 on his performance rating. What is his estimated expected wage rate? A. 25.11 B. 12.20 C. 17.23 D. 10.90 Reset Selection

Question 20 of 40

1.0 Points

A study was conducted to compare the average time spent in the lab each week versus course grade for computer programming students. The results are recorded in the table below. Find the value of the linear correlation coefficient r.

Number of hours spent in lab Grade (percent)  
10 96
11 51
16 62
9 58
7 89
15 81
16 46
10 51

A. -0.335 B. 0.017 C. -0.284 D. 0.462

Explanation / Answer

Q . 15 We got regression output from excel

Here R2 = 0.7839 = 78.39%

The correct option is A. 78.39%

17. Here intercept = a = 161.39 , slope = b = -48.19

Hence the regression equation is

y = 161.39 - 48.19 *x

We have x = 2

y = 161.39 - 48.19 * 2

= 65.01

predicted sales will be B. 65.

18 . We got regression output from excel

Here intercept = a = 21.29 slope of x1 = 3.10 , slope x2 = 4.70

The regression equation will be

y = 21.29 + 3.10 * x1 + 4.70 * x2

We have x1 = 5, x2 = 9

y = 21.29 + 3.10 * 5 + 4.70 * 9

y = 79.09

The correct option A. 79.09 .

19. Here x1 = 5, x2 = 0

y = 21.29 + 3.10 * 5 + 4.70 *0

= 36.79

20 . We use excel formula

'=correl( x, y )'

so we get,

r = -0.335

The correct option is

A. -0.335

SUMMARY OUTPUT Regression Statistics Multiple R 0.885404 R Square 0.783941 Adjusted R Square 0.729926 Standard Error 16.29861 Observations 6 ANOVA df SS MS F Significance F Regression 1 3855.422 3855.422 14.51346 0.018946 Residual 4 1062.578 265.6446 Total 5 4918 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 161.3855 26.16069 6.16901 0.003506 88.75183 234.0193 Price -48.1928 12.65017 -3.80965 0.018946 -83.3153 -13.0703
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