Develop a regression equation to forecast

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Reference no: EM13187127

1. Sales for the past 12 months at the Young Company are given here.

Month

Sales ($ millions)

January

20

February

24

March

27

April

31

May

37

June

47

July

53

August

62

September

54

October

36

November

32

December

29

a. Use a three-month moving average to forecast sales for January.

b. Use a four-month moving average to forecast sales for January.

c. Use a three-month weighted moving average to forecast sales for January.  Use weights of (3/6), (2/6) and (1/6), giving more weight to more recent data.

d. Use exponential smoothing with a = 0.6 to forecast sales for January. 

e. Using the mean absolute deviation as the performance criteria, pick the preferred forecast.  Begin the error measurement in May.

f. Using the mean squared error as the performance criteria, pick the preferred forecast.  Begin the error measurement in May.

2. SGC Milk Products manufacturers and distributes ice cream in upstate New York.  The company wants to expand operations by locating another plant in Vermont.  The size of the new plant will be a function of the expecteddemand for ice cream within the area served by the plant.  A market survey is currently underway to determine that demand.

SGC wants the estimate the relationship between the manufacturing cost per gallon and the number of gallons sold in a year to determine the demand for ice cream and, thus, the size of the new plant.  The following data have been collected:

Plant

Cost per 1000 gallons

Gallons sold (1000s)

1

1,015

416.9

2

973

472.5

3

1,046

250.0

4

1,006

372.1

5

1,058

238.1

6

1,068

258.6

7

967

597.0

8

997

444.0

9

1,044

263.2

10

1,008

372.0

a. Develop a regression equation to forecast the cost per gallon as a function of the number of gallons sold.

b. Suppose the market survey indicates a demand of 325,000 gallons in the Albany, NY area. Estimate the manufacturing cost per gallon for a plant producing 325,000 gallons per year.

3. Demand for oil changes at Lubes R Us have been as follows:

Month

Oil Changes

January

41

February

46

March

57

April

52

May

59

June

51

July

60

August

62

a. Use simple linear regression analysis to develop a forecasting model for monthly demand.  What is the forecast demand for September?

b. Use a three-month moving average to forecast demand for September.

c. Which forecast is best?  Why?

Reference no: EM13187127

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