6. The manager of the Petroco Service station wants to forecast the demand for unleaded gasoline next month so that the proper number of gallons can be ordered from the distributor. The owner has accumulated the following data on demand for unleaded gasoline from sales during the past 10 months:
Month Gasoline Demand (gal)
a. Compute an exponentially smoothed forecast, using on a value of .30.
b. Compute an adjusted exponentially smoothed forecast (with a =.30 and B =.20).
c. Compare the two forecast by using MAPD and indicate which seems to be more accurate.
5. The chairperson of the department of Management of State University wants to forecast the number of students who will enroll in production and operations management (POM) next semester, in order to determine how many sections to schedule. The chair has accumulated the following enrollment data for the past eight semesters:
Semester No. of students enrolled in POM
a. Compute the three-semester moving average forecast for semesters 4 through 9.
b. Compute the exponentially smoothed forecast (alpha = .20) for the enrollment data.
c. Compare the two forecasts by using MAD and indicate the more accurate of the two.
7. The victory plus mutual fund of growth stocks has had the following average monthly price for the past 10 months:
Month Fund Price
Compute the exponentially smoothed forecast with alpha=.40, the adjusted exponential smoothing forecast with alpha=.40 and beta=.30, and the linear trend line forecast. Compare the accuracy of the three forecasts, using cumulative error and MAD, and indicate which forecast appears to be most accurate.
1. The saki motorcycle dealer in Minneapolis wants to make an accurate forecast of demand for the Saki Super TXII motorcycle during the next month. Because the manufacturer is in Japan, it is difficult to send motorcycles back or reorder if the proper number is not ordered a month ahead. From sales records, the dealer has accumulated the following data for the past year:
Month Motorcyle Sales
a) Compute a 3-month moving average forecast of demand for April through January of the next year
b) Compute a 5-month moving average forecast for June through January
c) Compare the two forecasts computed in (a) and (b) using MAD. Which one should the dealer use for January of the next year?
A step by step explanation of exponentially smoothed, adjusted exponentially smoothed, linear trend line, and moving average forecasts, using real examples. Also different forecasts are compared using Mean Absolute Deviation (MAD) and Mean Absolute Percentage Deviation (MAPD).