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Discuss-the-model-fit

1. The management of Wheeler Company has decided to develop cost formulas for its major overhead activities. Wheeler uses a highly automated manufacturing process, and power costs are a significant manufacturing cost. They have debated whether the power cost should be treated as fixed, variable, or both. Using the following data you are charged to settle this issue and determine the best cost formula for Wheeler.

Quarter

Machine Hrs.

Power Cost

1

20000

26000

2

25000

38000

3

30000

42500

4

22000

37000

5

21000

34000

6

18000

29000

7

24000

36000

8

28000

40000

  1. Find the estimated fixed cost associated with the machine hours.
  1. Find the estimated variable cost associated with the machine hours.
  1. Discuss your confidence in the use of these estimates.
  1. Would you recommend using this cost function? Explain.
  1. You are asked to predict orders for the next two periods. You have information

available for the overtime hours used for each month.

Month

Orders

Overtime

1

53

22

2

56

23

3

61

25

4

63

31

5

67

21

6

74

22

7

73

20

8

77

29

9

84

23

10

87

12

11

88

22

12

94

26

13

92

16

14

99

17

  1. Find the best method to predict orders.
  1. Discuss the model fit.
  1. Predict the orders for the next two periods.
  1. Would you recommend using this model? Explain.

3. The data below are weekly figures from Herbert Hooley’s Happy House (except for the quarterly error figures). They sell radios, TVs, and VCRs in their electronics department. He needs you to help him with a few things, which he will indicate to you.

Profit

Revenue

Radios

TVs

VCRs

Quarter

Errors

6318.96

8395.91

36

65

48

4721.57

6300.28

26

48

39

5049.16

6747.55

33

51

40

2000 – 3

32

5249.44

7028.56

29

53

45

4

46

5290.08

7116.41

32

52

49

2001 – 1

19

5924.41

7951.00

41

58

52

2

23

5251.97

7031.09

36

52

44

3

34

4805.72

6462.88

31

47

44

4

49

5278.60

7162.42

46

49

51

2002 – 1

22

5301.77

7136.35

43

51

46

2

20

6121.98

8249.84

45

59

56

3

31

5416.63

7244.79

29

55

46

4

51

6552.89

8718.21

43

67

48

2003 – 1

16

6352.93

8494.02

46

63

51

2

26

6693.01

8881.75

55

68

43

3

37

5761.97

7669.10

48

58

39

4

48

5419.50

7265.38

33

54

47

2004 -1

22

5474.64

7302.97

35

55

44

2

24

4650.87

6335.89

41

42

49

4781.91

6438.23

48

45

39

  1. “Doug, I could surely use some help. I would like to find a useful profit formula for my department. Please let me know if it is a good model, and if there are any potential issues I should consider.” Note that the numbers of radios, TVs, and VCRs represent the number held on hand for the week. Please find the best model for Herb.
  1. Discuss the model.
  1. Are there other issues to consider here? Explain.
  1. What is your recommendation regarding use of this model? Explain.

Model 1

Model 2

Model 3

X-variables

6

4

3

R2

.9344

.9277

.8761

Adjusted R2

.9058

.9133

.8497

MSE

5867.53

5746.09

5844.78

  • Model 1 performs the best in all areas.
  • Model 3 performs better than Model 2.
  • We would most likely prefer Model 1.
  • We would most likely prefer Model 2.
  • We would most likely prefer Model 3.
    • The table below features three forecasting models used on the same set of data.

Model 1

Model 2

Model 3

Type

Exponential Smoothing

Regression

Seasonal & Trend

MSE

8755.3

4876.2

5945.8

Based solely on the information in this output, which of the following si the best answer?

  1. The data set contains no trend or seasonality.
  2. The data set contains trend but no seasonality.
  3. The data set contains seasonality but no trend.
  4. The data set probably contains cyclicality.
  5. The data set contains both trend and seasonality.
 
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