Question
In: Math
Demand data on "Service Orders" for a particular service enterprise for the previous 12 months is...
Demand data on "Service Orders" for a particular service enterprise for the previous 12 months is as follows: 550, 652, 673, 707, 725, 752, 780, 797, 815, 836, 850, and 872. Problem 3b) Use the following three methods and prepare three forecasting tables with errors for the given demand data. • a 3-month Weighted Moving Average with the weights 0.6, 0.3, and 0.1 with the maximum weight going for the most recent data point into the past • Exponential Smoothing with smoothing constant = 0.9 • Linear Trend Regression
Solutions
Expert Solution
a)
| Month | Service order | 3 month Weighted average |
| 1 | 550 | |
| 2 | 652 | |
| 3 | 673 | |
| 4 | 707 | 654.4 |
| 5 | 725 | 691.3 |
| 6 | 752 | 714.4 |
| 7 | 780 | 739.4 |
| 8 | 797 | 766.1 |
| 9 | 815 | 787.4 |
| 10 | 836 | 806.1 |
| 11 | 850 | 825.8 |
| 12 | 872 | 842.3 |
b) Exponential smoothing method
| Month | Service order | Exponential smoothing |
| 1 | 550 | 550 |
| 2 | 652 | 550 |
| 3 | 673 | 641.8 |
| 4 | 707 | 669.88 |
| 5 | 725 | 703.288 |
| 6 | 752 | 722.8288 |
| 7 | 780 | 749.08288 |
| 8 | 797 | 776.908288 |
| 9 | 815 | 794.990829 |
| 10 | 836 | 812.999083 |
| 11 | 850 | 833.699908 |
| 12 | 872 | 848.369991 |
c) Linear trend
Sum of X = 78
Sum of Y = 9009
Mean X = 6.5
Mean Y = 750.75
Sum of squares (SSX) = 143
Sum of products (SP) = 2997.5
Regression Equation = ŷ = bX + a
b = SP/SSX = 2997.5/143 =
20.96154
a = MY - bMX = 750.75 -
(20.96*6.5) = 614.5
ŷ = 20.96154X + 614.5
| Month | Service order | Linear trend |
| 1 | 550 | 635.46154 |
| 2 | 652 | 656.42308 |
| 3 | 673 | 677.38462 |
| 4 | 707 | 698.34616 |
| 5 | 725 | 719.3077 |
| 6 | 752 | 740.26924 |
| 7 | 780 | 761.23078 |
| 8 | 797 | 782.19232 |
| 9 | 815 | 803.15386 |
| 10 | 836 | 824.1154 |
| 11 | 850 | 845.07694 |
| 12 | 872 | 866.03848 |
milcah answered 1 year agoRelated Solutions
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The time series showing the sales of a particular product over
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Construct a spreadsheet to answer the following
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Use a=0.2 to compute the exponential smoothing forecasts for the
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Month
Time-Series
Value
Forecast
1
105
2
130
3
125
4
100
5
90
6
120
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150
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135
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95
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75
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100
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The following time series shows the sales of a particular product over the past 12 months....
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product over the past 12 months.
Month
Sales
1
105
2
135
3
120
4
105
5
90
6
120
7
145
8
140
9
100
10
80
11
100
12
110
(a)
Construct a time series plot.
(b)
Use α = 0.3 to compute the exponential smoothing
forecasts for the time series. (Round your answers to two decimal
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Month t
Time Series Value
Yt
Forecast
Ft
1
105...
The following time series shows the sales of a particular product over the past 12 months....
The following time series shows the sales of a particular
product over the past 12 months.
Month
Sales
1
105
2
135
3
120
4
105
5
90
6
120
7
145
8
140
9
100
10
80
11
100
12
110
(a)
Construct a time series plot.
A time series plot contains a series of 12 points connected by
line segments. The horizontal axis ranges from 0 to 13 and is
labeled: Month. The vertical axis ranges from 0...
The following time series shows the sales of a particular product over the past 12 months....
The following time series shows the sales of a
particular product over the past 12 months. can be found in the
below excel file.
https://drive.google.com/file/d/1gIpr0IBYUGgCIRSO7g3mqZ84F89vJU_P/view?usp=sharing
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Squared Error (MSE)?
(Round your answer to 2 decimal places. Negative values
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(Round your answer to 2 decimal places. Negative values
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The following time series shows the sales of a particular product over the past 12 months....
The following time series shows the sales of a particular
product over the past 12 months.
Month
Sales
1
105
2
135
3
120
4
105
5
90
6
120
7
145
8
140
9
100
10
80
11
100
12
110
Use α = 0.5 to compute the exponential smoothing
forecasts for the time series. (Round your answers to two decimal
places.)
Month t
Time Series Value
Yt
Forecast
Ft
1
105
2
135
3
120
4
105
5...
The following time series shows the sales of a particular product over the past 12 months....
The following time series shows the sales of a particular
product over the past 12 months.
Month
Sales
1
105
2
135
3
120
4
105
5
90
6
120
7
145
8
140
9
100
10
80
11
100
12
110
(b)
Use α = 0.4 to compute the exponential smoothing
forecasts for the time series. (Round your answers to two decimal
places.)
Month t
Time Series Value
Yt
Forecast
Ft
1
105
2
135
3
120
4
105...
The following time series shows the sales of a particular product over the past 12 months....
The following time series shows the sales of a
particular product over the past 12 months. can be found in the
below excel file.
https://drive.google.com/file/d/1gIpr0IBYUGgCIRSO7g3mqZ84F89vJU_P/view?usp=sharing
1. Using the three-month moving average, what is the Mean
Squared Error (MSE)?
(Round your answer to 2 decimal places. Negative values
should be indicated by a minus sign.)
2. Using the three-month moving average, what is the
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(Round your answer to 2 decimal places. Negative values
should be indicated by...
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228
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185
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206
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243
197
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194
224
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209
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243
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206
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156
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149
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191
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159
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