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 35P
1
Summary Introduction
To calculate: Seasonal factors, intercept and slope for year 2 and 3.
Seasonal factors
Seasonal factors help in analyzing a serious of data and they identify all the changes of regular and recurring nature.
2
Summary Introduction
To calculate: The slope, intercept and seasonal factor for quarter 1 of year 4 by using the given value of a, ß and γ.
Demand
Demand forecasting is a process in which past data is used to estimate the expected demand of some future period.
3
Summary Introduction
To calculate: Estimated demand for quarters 2,3 and 4 of year 4.
Demand forecasting
Demand forecasting is a process in which past data is used to estimate the expected demand of some future period.
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a. Identify and give a brief explanation of the:i. Dependent variableii. Independent variable
b. Use simple linear regression to forecast annual demand for months 9 and 10 by using thetabular method to:i. Derive the values for the intercept and slope. ii. Derive the linear regression equation.iii. Plot the linear regression line. iv. Develop a forecast of the clinic attendance for months 9 and 10.
4. The yearly demand for units manufactured by the Orion Company Limited has been as follows:Year Units Year Units1 520 5 8602 830 6 9403 520 7 9904 750 8 850Required:i. Prepare a forecast for year 5 through 8 by using a three-year simple moving average.What is the forecast for year 9?ii. Calculate the Cumulative Frequency Error (CFE), Mean Absolute Deviation (MAD),Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE) as at the endof year 8.
A pharmacist has been monitoring sales of a certain over-the-counter pain reliever. Daily sales during the last 15 days were
a. Assume the data refer to demand rather than sales. Using trend-adjusted exponential smoothing with an initial forecast of 46 for Day 8, an initial trend estimate of 2, and α = β = .3, develop demand forecasts for Days 9 through 16. Then compute the resultant MSE using the error values from Days 8 through 15. (Round your intermediate period-by-period forecast and error values to 3 decimal places. Round your final MSE answer to 3 decimal places.)
MSE =
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Number sold:
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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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