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, Problem 51AP
A
Summary Introduction
To calculate: The computation of the forecast error for each month in which forecast is obtained.
Introduction:
B
Summary Introduction
To calculate: The absolute error, the squared error and the absolute percentage error in columns 5, 6 and 7 and using the results obtained the MAD, MSE and MAPE for the MA (3) forecasts for months through 24 are to be calculated.
Introduction: Forecasting is the main function of predicting the future using the information available for decision making. It is a mechanism for planning decisions based on the predicted information.
C
Summary Introduction
To determine: The method which was more accurate for these data.
Introduction: Forecasting is the main function of predicting the future using the information available for decision making. It is a mechanism for planning decisions based on the predicted information.
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Students have asked these similar questions
Amazon finds that sales in July are much greater relative to other months because of the Amazon Prime days in that month.
Assuming that an exponential smoothing model is used for forecasting sales, what should the company best do to make the forecast for the next month (Aug) more reflective of reality? Please pick from the provided options.
F t+1 = αDt + (1-α) Ft
increase value of alpha
decrease value of alpha
stay with the same alpha
decrease the expected forecast for the current month (Ft)
On hearing our forecast, our clients probe - how sure are we about the forecast? Which measure of errror (among those stated below) should we best use to respond?
a.
Root MSE (RMSE)
b.
Mean absolute percentage error (MAPE)
c.
Mean forecast error (Avg. error)
d.
Cumulative forecast error (CFE)
The Grand Bakery produces 60 special sourdough rolls every day. Any rolls that are not sold each day are given to the employees. They have collected sales data from the past week:
Day
Rolls sold
1
50
2
50
3
48
4
60
5
53
6
60
What is the value of F6 if they use a 3-day weighted moving average with W1 = 0.6, W2 = 0.2, and W3 = 0.2?
Using the data from above, calculate the forecast for period 7 using a four-period moving average:
A manager of a store that sells and installs spas wants to prepare a forecast for January, February, and March of next year. Her forecasts are a combination of trend and seasonality. She uses the following equation to estimate the trend component of monthly demand: Ft = 70 + 5t, where t = 0 in June of last year. Seasonal relatives are 1.10 for January, 1.02 for February, and .95 for March. What demands should she predict?
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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