Production and Operations Analysis, Seventh Edition
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 2.7, Problem 20P
Summary Introduction

To determine: The three month and six month moving average forecasts in advance the month of for July till December and the effect on the forecasts due to increase inN from 3 to 6.

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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The problem is based on the following data given. Observations of the demand for a certain part stocked at a parts supply depot during the calendar year 2013 were ( as shown ). Compute the one-step-ahead three-month and six-month moving-average forecasts for July through December. What effect does increasing N from 3 to 6 have on the forecasts?
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 = Day: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Number sold: 31 32 35 38 38 42 42 43 41 44 46 46 49 55 52
Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be related to the number of television appearances by the popular group Maroon 5 during the previous month. Gershon has collected the data shown in the following table: D₁ Maroon 5 TV Appearances Demand for Guitars 3 4 4 6 6 5 9 8 6 9 6 8 This exercise contains only parts b, c, and d. b) Using the least-squares regression method, the equation for forecasting is (round your responses to four decimal places): Y = + x
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