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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Below is a table containing data on product demand for the most recent five months along with the forecasts that had been made for those 5 previous months. Use the 3-period simple moving average method to forecast the number of sales to expect next month. Month Demand Forecast 1 308 341 388 343.3 3 344 364.7 4 400 346.7 341 377.3
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 108 80 108 115 105 114 125 120 Forecast Demand 100 100 97 101 104 104 108 107 November December For the given forecast, the tracking signal = MADS (round your response to two decimal places). 4
Apply 4-period SMA and 4-period WMA (0.1, 0.2, 0.3, 0.4) to the given data. Determine the MAD, MSE, and RSE for both method and provide the forecast for the next period using the method with better MSE. period demand period demand 120 1 13 131 2 124 14 132 3 122 15 133 4 123 16 130 132 125 17 128 18 134 7 129 19 134 8 127 20 133 129 21 131 10 128 22 135 11 130 23 137 12 132 24 138
The following data show the number of liters of gasoline sold by Mackrin's in Colorado for the past 12 weeks. Which forecasting model would you recommend to Mackrin's manager? Why? What demand forecast would you recommend for week 13? Week Actual Demand (1000 liters) Forecasting (1000 liters) FSMA /A-F/ FWMA /A-F/ FES, α=0.3 /A-F/ 1 17 2 21 17 4 3 19 18.2 0.8 4 23 19 4 18.44 4.56 5 18 21 3 20.8 2.8 19.81 1.81 6 16 20 4 20 4 19.3 3.3 7 20 19 1 18.3 2.3 18.31 1.69 8 18 18 0 18.7 0.7 18.82 0.82 9 22 18 4 18.2 4.2 18.6 3.4 10 20 20 0 19.8 0.2 19.62 0.38 11 15 20 5 20.2 5.2 19.73 4.73 12 22 19 3 18.2 3.8 18.3 3.7 13 19 19.5 19.41 MAD 2.67 2.9 2.7 MSE 10.22…
National Standard, Inc. sells radio frequency identification (RFID) tags. Monthly demand for a seven-month period is reported below: Sales (1000 units) Forecast Observation Month Yt Ft 1 February 19 2 March 18 3 April 15 4 May 20 5 June 18 6 July 22 7 August 20 8 September ? Use Excel to plot the data and forecast September sales using the following methods: The naïve forecast A three-month moving average Exponential smoothing with a smoothing coefficient of α = 0.2, assuming a February forecast of 19 A 3-month weighted moving average, with weights 0.60, 0.3, and 0.1. With 0.6 applied to the most recent past.
Please solve the attached question.
Consider the following from an estate agent’s business nationally: Month Houses Sold Jan 380 Feb 360 Mar 390 Apr 400 May 390 June 380 July 394 Aug 454 Sep 460 Oct 460 Nov 430 Dec 370 Calculate the three point moving averages (quarters) and seasonal variation for the above data Define moving averages and how they’re useful in forecasting (use Harvard referencing) At races, your horse, White Rum, has a probability of 1/20 of coming 1st, 1/10 of coming 2nd and a probability of ¼ in coming 3rd. First place pays $5,000 to the winner, second place $4,000 and third place $1,350. Hence, is it worth entering the race if it costs $1050? Your company plans to invest in a particular project. There is a 40% chance you will lose $3,000, a 45% chance you will break even, and a 15% chance you will make $5,500.…
A firm uses simple exponential smoothing with trend adjustment to forecast demand, "a = 0.6" and "B=0.6". The Forecast including Trend (FIT) for the 1st month of 2022 was 434 units whereas the actual demand turned out to be 488 units, the trend over that period was 26. Calculate the demand forecast including trend for the 2nd month.
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
Please help with the correct answers in details: 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 4 5 6 Value 19 12 17 10 18 15 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 = (b) mean squared error MSE = (c) mean absolute percentage error (Round your answer to two decimal places.) MAPE = % (d) What is the forecast for week 7?
Suppose you are working for a baking company in Bangladesh. What are the relevant factors you will consider for forecasting? What technique would you apply? How would you reduce forecast error in this case?The company must have to be any Bangladeshi banking company
Use exponential smoothing with trend adjustment to forecast demand for period 11. Let α = 0.5, � = 0.3, and let the initial trend value be 12 and the initial forecast be 200

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