Question 1
A store managers wishes to forecast the weekly number of television sets sold. Calculate the error for each of the following forecasts, the MAD and the MSE. Be sure to show the entire table in the work area of the template.
Period Value Forecast Error
202 — —
191 202
173 192
169 181
171 174
175 172
182 174
196 179
204 189
219 198
11 227 211
Question 2
The data below shows the number of goods manufactured in one year.
($ billion).
Calculate forecasts for years 6 through 13 using a 5-year moving average.
Then, calculate forecasts for years 6 through 13 using a 5-year weighted moving average. Weight the most recent year by 6, the previous year by 4, the year before that by 2, and the other years by 1. Be sure to show the entire table in the work area of the template.
Answer the following questions:
What is the forecast for year 13 based on the 5-year moving average?
What is the forecast for year 13 based on the 5-year weighted moving average?
What is the MAD for the moving average forecast?
What is the MAD for the weighted moving average forecast?
Which forecasting model that you calculated is better? Why?
Year Factory orders
1 2,512.70
2 2,739.20
3 2,874.90
4 2,934.10
5 2,865.70
6 2,978.50
7 3,092.40
8 3,052.60
9 3,145.20
10 3,114.10
11 3,257.40
12 3,654.00
13
Question 3
The “Economic Report to the President of the United States” included data on the amounts of manufacturers’ new and unfilled orders in millions of dollars. Shown here are the figures for new orders over a 21-year period.
Use the charting tool in Excel to develop a regression model to fit the trend effects for the data. Use a linear model and then try a polynomial (order 2) model. Make sure the charts show the line formula and the r-squared value. Include both charts in your report. Then, answer the following question:
● How well does either model fit the data? Which model should be used for forecasting? Explain using the relevant metrics.
Year Total Number of New Orders
1 55,022
2 55,921
3 64,182
4 76,003
5 87,327
6 85,139
7 99,513
8 115,109
9 116,251
10 121,547
11 123,321
12 141,200
13 162,140
14 168,420
15 171,250
16 176,355
17 195,204
18 209,389
19 237,025
20 272,544
21 293,475