Description of this paper

GB513: Business Analytics Unit 5

Description

solution


Question

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 the amounts of manufacturers’ new and unlled orders in millions of dollars. Shown here are the gures for new orders over a 21-year period.

 

Use the Charting tool in Excel to develop a regression model to t the trend effects for these 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 t 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

 

 

Paper#78911 | Written in 19-Dec-2015

Price : $60
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