Question
In: Math
Using the demand data supplied in the below table, please calculate the following from your company's forecasting perspective.
Using the demand data supplied in the below table, please calculate the following from your company's forecasting perspective. Please use Excel to calculate your forecasting answers, so behind the cells in Excel, there has to be formulas for answering the below questions. Your company wants to forecast the demand for their product, based on the data below
a) Calculate the simple four-week moving average for weeks 5 through 12
b) Calculate the weighted three-week moving average using weights of 0.40, 0.40, and 0.20 for weeks 4 through 12
c) Calculate the exponential smoothing forecast for weeks 2 through 12 using an initial forecast of 4400 units and an alpha of 0.30
d) Calculate the exponential smoothing forecast plus trend for week2 through 12 using an alpha of 0.10, delta of 0.20, a previous forecast including trend of 4600 units, a previous trend of 120 units
e) Calculate the MAD and MAPE for all four of the forecasting models. Which forecast method do you recommend and why?
| Week | Demand |
|---|---|
| 1 | 4500 |
| 2 | 4750 |
| 3 | 5400 |
| 4 | 5800 |
| 5 | 6250 |
| 6 | 6500 |
| 7 | 7000 |
| 8 | 7500 |
| 9 | 7920 |
| 10 | 8200 |
| 11 | 8500 |
| 12 | 8800 |
Solutions
milcah answered 3 years agoRelated Solutions
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Date
Price
Dividend
Jan 1
$31.53
−
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$0.22
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$0.18
Aug 13
$31.78
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Nov 12
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$0.22
Dec 31
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Please Show Work
Week Number
10
11
12
13
14
15
16
17
18
Weight
0
0
0
5%
10%
10%
20%
25%
30%
Cases Shipped
2,500
2,650
2,325
2,200
2,700
2,750
2,900
2,850
2,925
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Price, dollars per pound
Quantity, thousand pounds per day
1.90
1.5
1.35
2.2
1.25
4.4
1.20
5.9
0.95
6.5
0.85
7.0
0.73
8.8
Using the Excel trendline option to estimate a linear demand
function, the linear demand function is
Qequals=12.53 minus 6.25 p12.53−6.25p.
Suppose the quantity in the first row of the table were
22
instead of 1.5.
The linear demand function would now be
Qequals=nothingminus−nothingp....
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Using the data from table below fit a fourth-order polynomial to
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Year Built
SalePrice
1885
122500
1890
240000
1900
150000
1910
125500
1912
159900
1915
149500
1920
100000
1921...
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Point
Price
In Dollars
Quantity...
Using the table below calculate the missing values.
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