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This assignment requires you to use Excel. Make sure you explain your answers and provide the regression output tables for questions 1 and 2.

Question 1

Shown below are rental and leasing revenue figures for office machinery and equipment in the United States over a seven-year period according to the U.S. Census Bureau. Use these data to run a linear regression and then forecast the rental and leasing revenue for the year 2012.

Year Rental and Leasing ($ millions)

2004 5,860

2005 6,632

2006 7,125

2007 6,000

2008 4,380

2009 3,326

2010 2,642

Question 2

Suppose a researcher gathered survey data from 19 employees and asked the employees to rate their job satisfaction on a scale from 0 to 100 (with 100 being perfectly satisfied). Suppose the following data represent the results of this survey. Assume that relationship with supervisor is rated on a scale from 0 to 50 (0 represents poor relationship and 50 represents an excellent relationship), overall quality of the work environment is rated on a scale from 0 to 100 (0 represents poor work environment and 100 rep resents an excellent work environment), and opportunities for advancement

is rated on a scale from 0 to 50 (0 represents no opportunities and 50 represents excellent opportunities).

Answer the following questions:

A) What is the regression formula?

B) How reliable do you think the estimates will be based on this formula? How can you tell?

C) Are there any variables that do not appear to be good predictors of Job satisfaction? How can

you tell?

D) If a new employee reports that her relationship with her supervisor is 40, finds the quality of the work environment to be scored at 75, works 60 hours per week and rates her opportunities for advancement to be at 30, what would you expect her job satisfaction score to be?

Job Relationship Overall Total hours

Satisfaction with quality worked

supervisor of work per

environment week

55 27 65 50

20 12 13 60

85 40 79 45

65 35 53 65

45 29 43 40

70 42 62 50

35 22 18 75

60 34 75 40

95 50 84 45

65 33 68 60

85 40 72 55

10 5 10 50

75 37 64 45

80 42 82 40

50 31 46 60

90 47 95 55

75 36 82 70

45 20 42 40

65 32 73 55

Last Column for this problem:

Opportunities

for

advancement

42

28

7

48

32

41

18

32

48

11

33

21

42

46

48

30

39

22

12

Question 3

Investment analysts generally believe the interest rate on bonds is inversely related to the prime interest rate for loans; that is, bonds perform well when lending rates are down and perform poorly when interest rates are up. Can the bond rate be predicted by the prime interest rate?

Use the following data to construct a scatter graph and then fit a regression line to the data. Report the regression formula and the r-squared value from the chart (right click on the line, select “Add Trendline” and select options to show these metrics).

Bond Rate Prime Interest Rate

5% 16%

12 6

9 8

15 4

7 7

Question 1

Shown below are rental and leasing revenue figures for office machinery and equipment in the United States over a seven-year period according to the U.S. Census Bureau. Use these data to run a linear regression and then forecast the rental and leasing revenue for the year 2012.

Year Rental and Leasing ($ millions)

2004 5,860

2005 6,632

2006 7,125

2007 6,000

2008 4,380

2009 3,326

2010 2,642

Question 2

Suppose a researcher gathered survey data from 19 employees and asked the employees to rate their job satisfaction on a scale from 0 to 100 (with 100 being perfectly satisfied). Suppose the following data represent the results of this survey. Assume that relationship with supervisor is rated on a scale from 0 to 50 (0 represents poor relationship and 50 represents an excellent relationship), overall quality of the work environment is rated on a scale from 0 to 100 (0 represents poor work environment and 100 rep resents an excellent work environment), and opportunities for advancement

is rated on a scale from 0 to 50 (0 represents no opportunities and 50 represents excellent opportunities).

Answer the following questions:

A) What is the regression formula?

B) How reliable do you think the estimates will be based on this formula? How can you tell?

C) Are there any variables that do not appear to be good predictors of Job satisfaction? How can

you tell?

D) If a new employee reports that her relationship with her supervisor is 40, finds the quality of the work environment to be scored at 75, works 60 hours per week and rates her opportunities for advancement to be at 30, what would you expect her job satisfaction score to be?

Job Relationship Overall Total hours

Satisfaction with quality worked

supervisor of work per

environment week

55 27 65 50

20 12 13 60

85 40 79 45

65 35 53 65

45 29 43 40

70 42 62 50

35 22 18 75

60 34 75 40

95 50 84 45

65 33 68 60

85 40 72 55

10 5 10 50

75 37 64 45

80 42 82 40

50 31 46 60

90 47 95 55

75 36 82 70

45 20 42 40

65 32 73 55

Last Column for this problem:

Opportunities

for

advancement

42

28

7

48

32

41

18

32

48

11

33

21

42

46

48

30

39

22

12

Question 3

Investment analysts generally believe the interest rate on bonds is inversely related to the prime interest rate for loans; that is, bonds perform well when lending rates are down and perform poorly when interest rates are up. Can the bond rate be predicted by the prime interest rate?

Use the following data to construct a scatter graph and then fit a regression line to the data. Report the regression formula and the r-squared value from the chart (right click on the line, select “Add Trendline” and select options to show these metrics).

Bond Rate Prime Interest Rate

5% 16%

12 6

9 8

15 4

7 7

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