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 2.6, Problem 12P

a.

Summary Introduction

To determine: The one step ahead forecasts for periods 3 through 12.

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.

b.

Summary Introduction

To determine:The forecast errors for the periods 3 through 12.

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 MAD, MSE and MAPE for the forecast errors calculated for periods 3 through 12.

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 monthly market shares of General Electric Company for 12 consecutive months follow. A. Construct a time series plot. What type of pattern exists in the data? B. Develop three-month and four-month moving averages for this time series. Does the three-month or the four-month moving average provide the better forecasts based on MSE? Explain your reasoning. C. Using your results in (B), compute MAD, MAPE, and Tracking Signal (TS). Which method provides better forecast? Explain your reasoning. Assume TS limit of ±4. D. Apply exponential smoothing to the data. Compute MSE, MAPE, MAD, and TS. Use a = 0.3. How does exponential smoothing compare with four-month moving average? Assume TS limit of ±4. Month 1 2 3 4 5 6 7 8 9 10 11 12 Market Shares 23.39 23.56 23.02 23.03 23.60 23.37 23.21 23.40 23.31 23.94 23.39 23.50
) Consider the following time series data: Week 1     2    3   4    5    6 Value 18  13  16  11 17 14 i)Construct a time series plot. What type of pattern exist in the data? ii)Develop a three – week moving average for the time series. Compute MSE and a forecast cast for week 7. Use alpha = 0.2 to compute the exponential smoothing value for the time series. Compute MSE and a forecast for week 7. IV)Compare the three -week moving average forecast with exponential smoothing forecast using alpha = 0.2. Which appears to provide the better forecast based on MSE? Explain V)Use trial and error to find a value of the exponential smoothing. Coefficient Alpha that result in a smaller MSE than what you calculated for alpha = 0.2.
The following data are for calculator sales in units at an electronics store over the past nine weeks: Week Sales Week Sales 1 45 53 2 50 7 59 3 44 8. 59 4 51 9 64 5 57 Use trend projection with regression to forecast sales for weeks 10 - 13. What are the error measures (CFE, MSE, o, MAD, and MAPE) for this forecasting procedure? How about ? Obtain the trend projection with regression forecast for weeks 10 – 13. (Enter your responses rounded to two decimal places.) Period Forecast, F, 10 64.81 11 67.06 12 69.31 13 71.56 Obtain the error measures. (Enter your responses rounded to two decimal places.) CFE MSE MAD МАРЕ
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