After using your forecasting model for six months, you decide to test it using MAD and a tracking signal. Here are the forecast andactual demands for the six-month period:PERIODMayJuneJulyAugustSeptemberOctoberPeriodFORECAST450500550615635710a. Find the tracking signal. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.)MayJuneJulyAugustSeptemberOctoberACTUAL495545395460675625Tracking Signal1.002.00(0.80)(2.20)(2.38)(3.50)

Formula: Tracking Signal = RSFE / Mean Absolute Deviation (MAD) RSFE = Cumulative deviation…

Answered: After using your forecasting model for…

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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Consider the following yearly demand values for a particular product. Year Demand 1 360 389 3 410 4 381 368 374 (a) Produce forecast for year 4,5,6, and 7 by using 3-week moving average. (b) Produce forecast for year 4,5,6, and 7 by using 3-week weighted moving average where weights are as follows; wt–3 = .1, wt-2 = .3, and wt-1 = .6. (c) Produce forecast for year 4,5,6, and 7 by using exponential smoothing with a = .2. Please assume that the forecast for the first year is 360.
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
The Yummy Ice Cream Company projects the demand for ice cream by using first-order exponential smoothing. Last week the forecast was 100,000 gallons of ice cream, and 90,000 gallons was actually sold. Using alpha=.1, prepare a forecast for next week. Calculate the forecast using Alpha=.2 and Alpha=.3 for this problem. Which values of Alpha gave the best forecast, assuming actual demand for next week ends up being 95,000 gallons?
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.
Here are the actual tabulated demands for an item for a nine-month period (January through September). Your supervisor wants to test two moving average forecasting methods to see which one was better over this period. Month Actual Demand Jan 120 Feb 140 March 160 April 180 May 170 June 190 July 150 August 160 September 170 a. Forecast April through September using a three-month moving average and calculate MAD for the forecasts. b. Forecast May through September using a four-month moving average and calculate MAD for the forecasts.
Since the beginning of the year, the purchase manager at a department store has been recording sales data to be used to compute 4-period moving averages to forecast sales for an upcoming month. Sales data for the months of January through September are reported in the table below. Month January February March April May June July August September Sales 21 20 39 22 29 14 42 28 27 Computed forecast values are not rounded. Compute the four-period moving average forecast for October. value as a whole number by rounding. Specify the Compute the mean absolute deviation (MAD) for the four-period moving average forecasts. Specify the MAD as a whole number by rounding. Compute the mean squared error (MSE) for the four-period moving average forecasts. Specify the MSE as a whole number by rounding. Compute the mean absolute percentage error (MAPE) for the four-period moving average forecasts. Specify the MAPE as a whole number by rounding. CHECK ANSWER
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 =
The number of cases of merlot wine sold by the Connor Owen winery in an eight-year period is as follows: YEAR CASES OFMERLOT WINE 2005 321 2006 407 2007 449 2008 507 2009 409 2010 551 2011 461 2012 427 Using an exponential smoothing model with an alpha value of 0.30, estimate the smoothed value calculated as of the end of 2012. Use the average demand for 2005 through 2007 as your initial forecast for 2008, and then smooth the forecast forward to 2012.
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 Value 17 14 15 3 (b) mean squared error MSE = % 4 Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. (a) mean absolute error MAE = 5 6 (d) What is the forecast for week 7? 12 16 15 (c) mean absolute percentage error (Round your answer to two decimal places.) MAPE =
You have the data on the application during the 8 consecutive year period below Wanted / Find the forecast demand for the year 2008 using the simple moving average method and on a 4-period basis the years 2000 2001 2002 2003 2004 2005 2006 2007 2008 Order quantity 24 48 50 68 60 66 70 90
b. Compute 2s control limits for each forecast. (Do not round your intermediate calculations. Round your answers to 2 decimal places.) Forecast Method 1 Method 2 Control Limits
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 18 13 (a) Construct a time series plot. 20T 18 16- 14- Time Series Value O Week 1 2 3 4 5 6 What type of pattern exists in the data? O The data appear to follow a cyclical pattern. O The data appear to follow a trend pattern. 8 6 O The data appear to follow a seasonal pattern. O The data appear to follow a horizontal pattern. Week 1 2 0 1 3 4 5 6 18 13 15 12 (b) Develop the three-week moving average for this time series. (Round your answers to two decimal places.) Time Series Value 16 14 18 + 2 13 15 4 5 6 15 12 16 3 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? 12 16 4 14 Week (c) Use a = 0.2 to compute the exponential smoothing values for the time series. Time Series Value 5 14 Forecast 6 Forecast 7 20 18 16 14 12 WE 10 2 + 7 @o 20 18 0 1 2 3 4 Week 5 6 00 0 1 2 3 4 5 Week 6 7…

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