# Unit 5 [GB513 : Business Analytics ] Assignment - 41233

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Unit 5 [GB513 : Business Analytics ] Assignment
This assignment requires you to use Excel. Make sure to use the Assignment 5 template found in your online course when you turn in your answers.
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
20 240,758
21 243,643
Submit your Assignment to the Unit 5 Dropbox.
Content
Points
Possible
Points
Earned
Provide error for each forecast by computing Mean Absolute Deviation (MAD) for Q1
5
Provide error for each forecast by computing Mean Square Error (MSE) for Q1
5
Used data in Q2 (a) to develop forecasts for the years 6 through 13 using a 5-year moving average
3
Used data in Q2 (b) to develop forecasts for the years 6 through 13 using a 5-year weighted moving average
3
In the summary tables below, insert only the answers. You will show work after the summary section.
Question 1
MSE
Question 2
Recommended forecast method:
Question 3
R-squared for Linear model
Regression formula for linear model
Work
Show all your work for the questions below.
Question 1
Show the errors you calculated
Question 2
Show the two forecasts and the errors
Question 3
Show the regression output tables

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