Production and Operations Analysis, Seventh Edition
7th Edition
ISBN: 9781478623069
Author: Steven Nahmias, Tava Lennon Olsen
Publisher: Waveland Press, Inc.
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Chapter 2.9, Problem 36P
Summary Introduction
To calculate: MAD and MSE of actual given data and
Mean absolute deviation
MAD is calculated by the division of sum of absolute deviations and number of observations. Here, absolute deviations are calculated by deducting the forecasted data from the actual data.
Mean squared error
MSE is calculated by the division of sum of square of deviations and number of observations. Here, deviations are calculated by deducting estimated data from the actual data.
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Students have asked these similar questions
The number of cases of merlot wine sold by the Connor Owen winery in an eight-year period is as follows:
YEAR
CASES OFMERLOT WINE
1
286
2
372
3
414
4
472
5
374
6
516
7
426
8
392
Using an exponential smoothing model with an alpha value of 0.20, estimate the smoothed value calculated as of the end of year 8. Use the average demand for years 1 through 3 as your initial forecast for year 4, and then smooth the forecast forward to year 8.
The number of cases of merlot wine sold by the Connor Owen winery in an eight-year period is as follows:
YEAR
CASES OF MERLOT WINE
1
270
2
356
3
398
4
456
5
358
6
500
7
410
8
376
Using an exponential smoothing model with an alpha value of 0.20, estimate the smoothed value calculated as of the end of year 8. Use the average demand for years 1 through 3 as your initial forecast for year 4, and then smooth the forecast forward to year 8.
Note: Round your intermediate calculations and final answer to the nearest whole number.
National Standard, Inc. sells radio frequency identification (RFID) tags. Monthly demand for a seven-month period is reported below:
Sales (1000 units)
Forecast
Observation
Month
Yt
Ft
1
February
19
2
March
18
3
April
15
4
May
20
5
June
18
6
July
22
7
August
20
8
September
?
Use Excel to plot the data and forecast September sales using the following methods:
The naïve forecast
A three-month moving average
Exponential smoothing with a smoothing coefficient of α = 0.2, assuming a February forecast of 19
A 3-month weighted moving average, with weights 0.60, 0.3, and 0.1. With 0.6 applied to the most recent past.
Chapter 2 Solutions
Production and Operations Analysis, Seventh Edition
Ch. 2.4 - Prob. 1PCh. 2.4 - Prob. 2PCh. 2.4 - Prob. 3PCh. 2.4 - Prob. 4PCh. 2.4 - Prob. 5PCh. 2.4 - Prob. 6PCh. 2.4 - Prob. 7PCh. 2.4 - Prob. 8PCh. 2.4 - Prob. 9PCh. 2.6 - Prob. 10P
Ch. 2.6 - Prob. 11PCh. 2.6 - Prob. 12PCh. 2.6 - Prob. 13PCh. 2.6 - Prob. 14PCh. 2.6 - Prob. 15PCh. 2.7 - Prob. 16PCh. 2.7 - Prob. 17PCh. 2.7 - Prob. 18PCh. 2.7 - Prob. 19PCh. 2.7 - Prob. 20PCh. 2.7 - Prob. 21PCh. 2.7 - Prob. 22PCh. 2.7 - Prob. 23PCh. 2.7 - Prob. 24PCh. 2.7 - Prob. 25PCh. 2.7 - Prob. 26PCh. 2.7 - Prob. 27PCh. 2.8 - Prob. 28PCh. 2.8 - Prob. 29PCh. 2.8 - Prob. 30PCh. 2.8 - Prob. 31PCh. 2.8 - Prob. 32PCh. 2.9 - Prob. 33PCh. 2.9 - Prob. 34PCh. 2.9 - Prob. 35PCh. 2.9 - Prob. 36PCh. 2.9 - Prob. 37PCh. 2.10 - Prob. 38PCh. 2.10 - Prob. 42PCh. 2.10 - Prob. 43PCh. 2.10 - Prob. 44PCh. 2.10 - Prob. 45PCh. 2 - Prob. 47APCh. 2 - Prob. 48APCh. 2 - Prob. 49APCh. 2 - Prob. 50APCh. 2 - Prob. 51APCh. 2 - Prob. 52APCh. 2 - Prob. 53APCh. 2 - Prob. 54APCh. 2 - Prob. 55APCh. 2 - Prob. 56APCh. 2 - Prob. 57APCh. 2 - Prob. 58AP
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