Question
Offered Price $15.00

MATHS - Compute MAD and MSE

Question # 00013114
Subject: Mathematics
Due on: 04/22/2014
Posted On: 04/22/2014 04:04 AM

Rating:
4.1/5
Expert tutors with experiences and qualities
Posted By
Best Tutors for school students, college students
Questions:
15717
Tutorials:
15365
Feedback Score:

Purchase it
Report this Question as Inappropriate
Question


This assignment requires you to use Excel. In question 3, you will use the regression tool from the analysis toolpack. 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

Template to answer

In the summary tables below, insert only the answers. You will show work after the summary section.
Question 1
MAD
MSE

Question 2
MAD for part a
MAD for part b
Recommended forecast method:
Question 3
R-squared for Linear model
R-squared for quadratic model
Regression formula for linear model
Regression formula for quadratic 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

Tags compute maths model forecasts data regreion orders develop factory forecast year years linear quadratic shown excel summary aignment united period 5year moving using tables errors states goods work compute formula rsquared datayear

Tutorials for this Question
Available for
$18.00

MATHS - Compute MAD and MSE SOlution

Tutorial # 00012670
Posted On: 04/22/2014 04:06 AM
Posted By:
Best Tutors for school students, college students expertden
Expert tutors with experiences and qualities
Questions:
15717
Tutorials:
15365
Feedback Score:
Report this Tutorial as Inappropriate
Tutorial Preview …Deviation x 202 x 191 202 xxx 11 3 xxx 192 xxx xx 4 xxx…
Attachments
MATHS_-_Compute_MAD_and_MSE_SOlution.xlsx (22.13 KB)
Preview: data xxx a xxxxxx model and xxxx try a xxxxxxxxx model xxx xxxx does xxxxxx model fit xxx data?Total Number xx New xxxxxxxxx xxx value xxx the linear xxxxx is 0 xxxxx indicating xxxx xxxx model xxxxxxxx 98 83% xx the variation xx the xxxxx xxxxxx of xxx orders The xxx value for xxx quadratic xxxxx xx 0 xxxxxx indicating that xxx quadratic model xxxxxxxx 98 xxx xx the xxxxxxxxx in the xxxxx number of xxx orders xxxxx xxx two xxxxxx.....
Purchase this Tutorial @ $18.00 *
* - Additional Paypal / Transaction Handling Fee (3.9% of Tutorial price + $0.30) applicable
Loading...