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Question 1

Determine the error for each of the following forecasts. Compute MAD and MSE.

Period Value Forecast Error

1 202 — —

2 191 202

3 173 192

4 169 181

5 171 174

6 175 172

7 182 174

8 196 179

9 204 189

10 219 198

11 227 211

Question 2

The U.S. Census Bureau publishes data on factory orders for all manufacturing, durable goods, and nondurable goods industries. Shown here are factory orders in the United States over a 13-year period ($ billion).

a. Use these data to develop forecasts for the years 6 through 13 using a 5-year moving average.

b. Use these data to develop forecasts for the 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.

c. Compute the errors of the forecasts in parts (a) and (b) and then the MAD. Which forecast is better?

Year Factory Orders ($ billion)

1 2,512.7

2 2,739.2

3 2,874.9

4 2,934.1

5 2,865.7

6 2,978.5

7 3,092.4

8 3,356.8

9 3,607.6

10 3,749.3

11 3,952.0

12 3,949.0

13 4,137.0

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 Excel to develop a regression model to fit the trend effects for these data. Use a linear model and then try a quadratic model. How well does either model fit the data?

Year Total Number of New Orders

1 55,022

2 55,921

3 64,1 82

4 76,003

5 87,327

6 85,139

7 99,513

8 115,109

9 131,629

10 147,604

11 156,359

12 168,025

13 162,140

14 175,451

15 192,879

16 195,706

17 195,204

18 209,389

19 227,025

Question 1

Determine the error for each of the following forecasts. Compute MAD and MSE.

Period Value Forecast Error

1 202 — —

2 191 202

3 173 192

4 169 181

5 171 174

6 175 172

7 182 174

8 196 179

9 204 189

10 219 198

11 227 211

Question 2

The U.S. Census Bureau publishes data on factory orders for all manufacturing, durable goods, and nondurable goods industries. Shown here are factory orders in the United States over a 13-year period ($ billion).

a. Use these data to develop forecasts for the years 6 through 13 using a 5-year moving average.

b. Use these data to develop forecasts for the 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.

c. Compute the errors of the forecasts in parts (a) and (b) and then the MAD. Which forecast is better?

Year Factory Orders ($ billion)

1 2,512.7

2 2,739.2

3 2,874.9

4 2,934.1

5 2,865.7

6 2,978.5

7 3,092.4

8 3,356.8

9 3,607.6

10 3,749.3

11 3,952.0

12 3,949.0

13 4,137.0

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 Excel to develop a regression model to fit the trend effects for these data. Use a linear model and then try a quadratic model. How well does either model fit the data?

Year Total Number of New Orders

1 55,022

2 55,921

3 64,1 82

4 76,003

5 87,327

6 85,139

7 99,513

8 115,109

9 131,629

10 147,604

11 156,359

12 168,025

13 162,140

14 175,451

15 192,879

16 195,706

17 195,204

18 209,389

19 227,025

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