Operations Management: Processes and Supply Chains (11th Edition)
Operations Management: Processes and Supply Chains (11th Edition)
11th Edition
ISBN: 9780133872132
Author: Lee J. Krajewski, Manoj K. Malhotra, Larry P. Ritzman
Publisher: PEARSON
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Chapter 8, Problem 9P

Consider the sales data for Computer Success given in Problem 7.

  1. Use a 3-month weighted moving average to forecast the sales for the months April through December. Use weights of ( 4 / 8 ) , ( 3 / 8 ) , and ( 1 / 8 ) , giving more weight to more recent data.
  2. Use exponential smoothing with α = 0.6 to forecast the sales for the months April through December. Assume that the initial forecast for January was $3,200. Start error measurement in April.
  3. Compare the performance of the two methods by using the mean absolute deviation as the performance criterion, with error measurement beginning in April. Which method would you recommend?
  4. Compare the performance of the two methods by using the mean absolute percent error as the performance criterion, with error measurement beginning in April. Which method would you recommend?
  5. Compare the performance of the two methods by using the mean squared error as time performance criterion, with error measurement beginning in April. Which beginning would you recommend?

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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
The following data are for calculator sales in units at an electronicsstore over the past 9 weeks:Week    Sales           Week                    Sales1            46                   6                       582             49                 7                        623             43                  8                        564            50                   9                        635            53Use trend projection with regression to forecast sales for weeks 10–13. What are the error measures (CFE, MSE, s, MAD, and MAPE) for this forecasting procedure? How about r2?
The monthly sales for Yazici Batteries, Inc., were as follows: Month Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Sales 20 21 16 14 11 16 17 19 22 20 20 24 This exercise contains only parts b and c. b) The forecast for the next month (Jan) using the naive method = sales (round your response to a whole number). The forecast for the next period (Jan) using a 3-month moving average approach = sales (round your response to two decimal places). The forecast for the next period (Jan) using a 6-month weighted average with weights of 0.10, 0.10, 0.10, 0.20, 0.20, and 0.30, where the heaviest weights are applied to the most recent month = sales (round your response to one decimal place). sales (round your response Using exponential smoothing with a = 0.30 and a September forecast of 18.00, the forecast for the next period (Jan) = to two decimal places). Using a method of trend projection, the forecast for the month (Jan) = sales (round your response to two decimal places). c) The method…

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Operations Management: Processes and Supply Chains (11th Edition)

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