The following are monthly actual and forecast demand levels for May through December for units of a product manufactured by the Deborah Bishop Company in Des Moines:MonthMayJuneJulyAugustSeptemberOctoberFor the given forecast, the tracking signal ==MADS (round your response to two decimal places).NovemberDecemberActual Demand100801/10115105110125120Forecast Demand10010499101104104105109

A tracking signal is a tool utilized in statistics and management science to observe forecasts and…

Answered: The following are monthly actual and…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...

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The following represents the actual demand and two different sets of forecasts using different methods. Compute the MAD for each forecasting method and determine the best method for this set of data. Year-Qtr Actual demand Forecast methos 1 MAD1 (A-F) Forecast Method 2 MAD2 (A-F) 2020-3 98 97 89 2020-4 108 110 106 2021-1 83 68 70 2021-2 100 101 102 2021-3 95 86 87 2021-4 90 94 92 2022-1 71 68 72 2022-2 104 105 106 2022-3 84 91 88 2022-4 80 93 91 2023-1 78 68 70 2023-2 120 118 122
Sales for the past 6 months at Dalworth Company are given in the following table: O Month July August September October What is the Mean Absolute Deviation (MAD) for August through December forecasts produced by using exponential smoothing with a = 0.9? (Note: Do not round the forecasts, and choose the closest answer.) Multiple Choice O November December O 15.28 9.04 8.75 Sales 52 61 53 35 31 28 31.59
The following are monthly actual and forecast demand levels for May through December for units of a product manufactured by the Deborah Bishop Company in Des Moines: Month May June July August September October Actual Demand 105 82 110 112 108 106 130 120 Forecast Demand 100 108 97 98 108 102 105 107 November December For the given forecast, the tracking signal = MADS (round your response to two decimal places).
Month Demand Forecast Error 1 20 2 18 3 21 4 25 5 24 6 27 7 22 8 30 9 23 10 20 11 29 12 22 Mean Abs Error Problem 6: The demand manager of Maverick Jeans is responsible for ensuring sufficient warehouse space for the finished jeans that come from the production plants. It has occasionally been necessary to rent public warehouse space, something that Maverick would like to avoid. In order to estimate the space requirements the demand manager is evaluating moving-average forecasts. The demand (in 1,000 case units) for the last fiscal year is shown below. Bias MAD (mean error) Month 1 2 3 4 5 6 7 8 9 10 11 12 Demand 20 18 21 25 24 27 22 30 23 20 29 22 Use a three-month moving average to estimate the month-in- advance forecast of demand for months 4-12. Calculate the Bias and MAD. (Note: Adjust all cell values to two decimal points.)
The following data are for calculator sales in units at an electronics store over the past nine weeks: Week Sales Week Sales 45 6 53 50 7 59 44 8 59 51 64 57 Use trend projection with regression to forecast sales for weeks 10 - 13. What are the error measures (CFE, MSE, G. 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 MAPE 6.72 2.75 2.1 4.1 % Find the coefficient of determination (). The coefficient of determination ? = (Enter your response rounded to two decimal places.)
Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table: Year Year Forecast (000) 1 2 4.00 7.00 1 5.00 3 5.00 Registrations (000) a) Calculate the forecasted registrations for years 2 through 12 using exponential smoothing, with a smoothing constant (a) of 0.40 and a starting forecast of 5.00 for year 1 (round your responses to one decimal place): 2 3 4.6 5.56 4 4.00 4 5.34 11 9 10 7 8 6 5 9.00 9.00 6.00 10.00 13.00 14.00 12.00 5 4.80 6 7 6.48 7.49 8 6.89 9 8.14 10 10.08 11 11.64 12 11.79 b) Mean absolute deviation based on the forecast developed using the exponential smoothing method (with a smoothing constant (a) = 0.40 and a starting forecast of F₁ = 5.00) is response to one decimal place). registrations (round your
Use regression or simple exponential smoothing with the following data. For exponential smoothing, assume the forecast for year 1 was the same as the actual and use an alpha of 0.7. (use excel to show formauls used) Year Sales 1 290 2 340 3 400 4 410 5 400 1. What is the tracking signal for the forecast?
The following data are for calculator sales in units at an electronics store over the past nine weeks: Week 1 2 3 4 5 Obtain the error measures. (Enter your responses rounded to two decimal places.) CFE MSE Sales Find the coefficient of determination (²). The coefficient of determination r² = 0. (Enter your response rounded to two decimal places.) 44459 46 51 58 Use trend projection with regression to forecast sales for weeks 10-13. What are the error measures (CFE, MSE, 6, MAD, and MAPE) for this forecasting procedure? How about r²? Obtain the trend projection with regression forecast for weeks 10-13. (Enter your responses rounded to two decimal places.) Forecast, Ft Period 10 11 12 13 Week 6 69809 7 Sales 54 63 53 61 MAD U MAPE %
Here are the actual tabulated demands for an item for a nine-month period (January through September). Your supervisor wants to test two forecasting methods to see which method was better over this period. MONTH ACTUAL January 120 February 145 March 146 April 171 May 154 June 182 July 138 August 135 September 146 a. Forecast April through September using a three-month moving average. b. Use simple exponential smoothing with an alpha of 0.20 to estimate April through September, using the average of January through March as the initial forecast for April. c-1. Calculate MAD for Three-month moving average and Exponential smoothing. c-2. Use MAD to decide which method produced the better forecast over the six-month period.
Centerville Bikes and Stuff (CBS) sells motorcycles and accessories. The number of helmets sold by CBS per week for the past six weeks follows. Week 1 2 3 Value 17 12 17 (a) mean absolute error MAE = (b) mean squared error MSE = Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. 4 % 5 6 (d) What is the forecast for week 7? 10 16 15 (c) mean absolute percentage error (Round your answer to two decimal places.) MAPE =
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The manager of the Petroco Service Station wants to forecast the demand for unleaded gasoline next month so that the proper number of gallons can be ordered from the distributor. The owner has accumulated the following data on demand for unleaded gasoline from sales during the past 10 months. Compute an exponentially smoothed forecast with an a value of .30. According to the result from Excel and/or POM-QM, the forecast for the month of January would be (type number only, two decimals) Month October November December January February March April May June July 733.25 Gasoline Demanded (gal.) 800 725 630 500 645 690 730 810 1,200 980

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