The following is the actual sales for Manama Company for a particular good:tSales17531The company wants to determine how accurate their forecasting model, so they asked their modeling expert to build a trend model. He found the model toforecast sales can be expressed by the following model: Ft-5+241Calculate the amount of error occurred by applying the model is:Hint: Use MSE(Round your answer to 2 decimal places)1234182530

Answered: The following is the actual sales 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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I The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week Of August 31 September 7 September 14 September 21 September 28 October 5 Pints Used 345 389 412 383 366 371 a) The forecasted demand for the week of October 12 using a 3-week moving average = 373.33 pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.10, 0.35, and 0.55, using 0.55 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 recent period and smallest weight applies to oldest period.) the largest weight applies to most
A large cement manufacturer uses exponential smoothing to forecast demand for a piece of pollution-control equipment. It appears that an increasing trend is present.Month At1 700 2 685 3 648 4 717 5 713 6 728 7 754 8 762 If the initial forecast for month 1 was 650 units and the trend over that period was 0 units, calculate FIT for the 9-month period. Use smoothing constants, Alpha = 0.1 andAlpha = 0.2.
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
The following gives the number of accidents that occurred on Florida State Highway 101 during the last 4 months: Jan Feb Mar AprMonth 1 2 3 4Number of Accidents 25 40 60 105 Using the least-squares regression method, the trend equation for forecasting is (round your responses to two decimal places): y = ? + ?x
Please do not give solution in image format thanku A small manufacturing firm has recorded a time series of the cost per unit for the firm’s leading product over the past eight years. Year 1 2 3 4 5 6 7 8 Cost/Unit ($) 20 24.5 28.2 27.5 26.6 30 31 36 a) If you are not given a base value or trend, what would be the forecast for the year 10 made at the end of year 8 (α=0.2, β=0.4). b) Forecast for the year 9 using 1) 5-month weighted average using 0.1,0.1,0.1,0.2,0.3, with the heaviest weight applied to the recent month 2) Exponential smoothing using α =0.2 and forecast of 21 for year 5 3) If α value was not provided in the question above, what value of α would you choose?
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.
Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table: 3 8 9 6 7 6 3 7 10 11 Year Year Forecast (000) 1 5 1 5 2 5 4 4 4 5 11 Registrations (000) Use exponential smoothing with a smoothing constant of 0.4 to forecast the registrations at the seminar for years 2 through 12. To begin the procedure, assume that the forecast for year 1 was 5,000 people signing up (round your responses to one decimal place): 2 3 5 6 7 8 10 16 9 11 12 10 D 11 12 a) What is the MAD? Mean absolute deviation based on the forecast developed using the exponential smoothing method (with a smoothing constant (x) = 0.4 and a starting forecast of F₁ = 5) is thousand registrations (round your response to one decimal place). b) What is the MSE? The mean squared error based on the forecast developed using the exponential smoothing method (with a smoothing constant (x) = 0.4 and a starting forecast of F₁ = 5) is (round your response to two decimal…
The following gives the number of accidents that occurred on Florida State Highway 101 during the last 4 months: Month Jan Feb Mar Apr Number of Accidents 30 48 70 90 Part 2 Using the least-squares regression LOADING... method, the trend equation for forecasting is (round your responses to two decimal places): y = enter your response here + enter your response here x Y=?+?x
A company wants to generate a forecast for unit demand for year 2017 using exponential smoothing. The actual demand in year 2016 was 120. The forecast demand in year 2016 was 110. Using this data and a smoothing constant alpha of 0.1, which of the following is the resulting year 2017 forecast value?
After using your forecasting model for six months, you decide to test it using a tracking signal. Here are the forecast and actual demands for the six-month period: PERIOD FORECAST ACTUAL May 450 500 June 500 550 July 550 400 August 600 500 September 650 675 October 700 600 Find the tracking signal of each month
The monthly sales for Yazici Batteries, Inc., were as follows: Jan Feb Mar Apr May Jun Jul Aug Sept Oct 21 23 17 14 11 16 16 18 Nov Dec 20 20 20 24 Month Sales 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) Using exponential smoothing with a = 0.30 and a September forecast of 21.00, the forecast for the next period (Jan) = sales (round your response to two decimal places). Using a method of trend projection, the forecast for the next month (Jan) = sales (round your response to two decimal places). c) The method…
The monthly sales for Yazici Batteries, Inc., were as follows: Month Sales Jan 19 Feb Mar 17 21 Apr May Jun Jul Aug Sept Oct 12 15 18 15 19 20 20 This exercise contains only parts b and c. b) The forecast for the next month (Jan) using the naive method = 22 sales (round your response to a whole number). Nov Dec 20 22 The forecast for the next period (Jan) using a 3-month moving average approach = 20.67 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).

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