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?