The following data show the number of laptop computers sold each month at a retail store:
|
Month
|
Unit Sales
|
|
January
|
200
|
|
February
|
230
|
|
March
|
225
|
|
April
|
240
|
|
May
|
210
|
|
June
|
180
|
|
July
|
160
|
|
August
|
310
|
|
September
|
320
|
|
October
|
270
|
|
November
|
250
|
|
December
|
300
|
Use the above data:
a. Using the average demand for the year as the base, compute a seasonal index for each month.
b. Use regression to estimate the deseasonalized demand in each of the given months. Using these base values, compute a seasonal index for each month.
c. Are the seasonal indexes computed in parts a and b the same or different? Why?
d. Using the regression model and the seasonal indexes you computed in part b, compute a seasonally adjusted forecast for January, February, March, April, and May of the next year.