Gb513: business analytics unit 5

This Assignment requires you to use Excel. Make sure to use the Unit 5 Assignment template located in Doc Sharing when you turn in your answers.

Submit your Assignment to the Unit 5 Dropbox.

Question 1

Determine the error for each of the following forecasts. Then, calculate 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). 

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

Then, 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.

Answer the following questions:

a) What is the forecast for year 13 based on the 5-year moving average?

b) What is the forecast for year 13 based on the 5-year weighted moving average?

c) What is the MAD for the moving average forecast?

d) What is the MAD for the weighted moving average forecast?

e) Which forecasting model is better?

 

Year Factory

Orders 

($ billion)

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 3,111.10

9 3,222.20

10 3,555.00

11 4,221.50

12 4,551.20

13 4,137.00

 

Question 3

The “Economic Report to the President of the United States” included data on theamounts of manufacturers’ new and unfilled orders in millions of dollars. Shownhere are the figures for new orders over a 21-year period. 

Use the Charting tool in Excel to developa regression model to fit the trend effects for these data.

Use a linear model andthen 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

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