Answered: Two different forecasting techniques…

Two different forecasting techniques (F1 and F2) were used to forecast demand for cases of bottled water. Actual demand and the two sets of forecasts are as follows:

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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Following are two weekly forecasts made by two different methods for the number of gallons of gasoline, in thousands, demanded at a local gasoline station. Also shown are actual demand levels, in thousands of gallons: Week Forecast Method 1 Actual Demand 1 0.95 0.72 2 1.08 0.98 3 0.92 1.07 4 1.17 1.04 Week Forecast Method 2 Actual Demand 1 0.80 0.72 2 1.21 0.98 3 0.88 1.07 4 1.17 1.04 Part 2 The MAD for Method 1 = enter your response here thousand gallons (round your response to three decimal places).
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
Sales of tablet computers at Marika Gonzalez's electronics store in Washington, D.C., over the past 10 weeks are shown in the table below: Week Demand 1 20 2 20 Week 1 Demand 20 Forecast 20.0 3 29 4 37 4 37 5 24 2 3 29 20 6 30 7 8 37 24 a) The forecast for weeks 2 through 10 using exponential smoothing with a = 0.55 and a week 1 initial forecast of 20.0 are (round your responses to two decimal places): 5 6 30 24 7 37 9 24 8 24 10 28 9 24 10 28
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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.
Two independent methods of forecasting based on judgment and experience have been prepared each month for the past 10 months. The forecasts and actual sales are as follows:
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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
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The following table gives the number of pints of type A blood used at Woodlawn Hospital in the past 6 weeks: Week Of August 31 September 7 September 14 September 21 September 28 October 5 - a) The forecasted demand for the week of October 12 using a 3-week moving average = pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.10, 0.30, and 0.60, using 0.60 for the most recent week, the forecasted demand for the week of October 12 = pints (round your response to two decimal places and remember to use the weights in appropriate order the largest weight applies to most recent period and smallest weight applies to oldest period.) Week Of c) If the forecasted demand for the week of August 31 is 360 and a = 0.20, using exponential smoothing, develop the forecast for each of the weeks with the known demand and the forecast for the week of October 12 (round your responses to two decimal places). August 31 September 7 September 14…