The following table shows predicted product demand using your particular forecasting method along with the actual demand thatoccurred:FORECASTACTUAL1,4801,5301,3801,4801,6801,5801,7301,7801,6301,680Compute the tracking signal using the mean absolute deviation and running sum of forecast errors.Note: Negative values should be indicated by a minus sign. Round your "Mean Absolute Deviation", "Tracking Signal" to 2 decimalplaces and all other answers to the nearest whole number.Period Forecast Actual Deviation RSFEAbsoluteDeviationSum ofAbsoluteMADTSDeviation11,480 1,530-50-50505050.00-1.0021,3801,480-100-15010015075.00-2.0031,6801,580100-5010025083.33-0.6041,7301,6301005010035087.500.5751,7801,68010015010045090.001.67

Approach to solving the question:Rational Detailed explanation:Period 1Deviation: −50RSFE: −50Sum of…

Answered: The following table shows predicted…

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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If month one has 240,000 demands, month two 250,080 demands, month three 325,00 demands, month four 370,000 demands, month five 420,000 demands and month six 509,00 demands. Use a forecast for the first month of 240,000, an initial trend forecast of 50,000, and smoothing parameters of 0.35 for both demand smoothing and trend smoothing. Compute the forecasts and trends using double exponential smoothing
The following table shows the actual demand observed over the last 11 years: Year 1 2 3 4 5 6 7 8 9 10 11 Demand 7 9 6 10 12 7 12 12 9 9 8 Part 2 Using exponential smoothing with α = 0.30 and a forecast for year 1 of 6.0, provide the forecast from periods 2 through 12 (round your responses to one decimal place). Part 3 Provide the forecast from periods 2 through 12 using the naive approach (enter your responses as whole numbers).
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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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.
tab s lock Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be related to the number of television appearances by the popular group Maroon 5 during the month Ges collected the data shown in the following table V esc This exercise contains only parts b, c, and d. b) Using the least-squares regression method, the equation for forecasting is (round your responses to four decimal places): c) The estimate for guitar sales if Maroon 5 performed on TV 9 times = d) The correlation coefficient (r) for this model The coefficient of determination (2) for this model= The percentage of variation in sales that can be explained by TV appearances = Q A N @ 2 W S 31/1 X ** 3 8.0 F3 E D C $ Maroon 5 TV Appearances Demand for Guitars sales (round your response to two decimal places). (round your response to four decimal places). (round your response to four decimal places). 4 889 R F % 5 V d Es FS Y = T G % (round your response to two decimal places). A 6…
Develop a forecast for the next month using a four-month moving average method. Use the Excel Functions SLOPE and INTERCEPT to write the linear regression prediction equation with Months as the independent variable and sales as the dependent variable. Use the prediction equation to estimate the number of sales in month 9.
Y9
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?
Holiday Lodge The Holiday Lodge is a large hotel and casino in the Adirondacks. The relatively new hotel is two years old, and the manager is trying to develop a plan to staff the maintenance department. The hotel’s manager wants to use the two years of data below to forecast one month ahead of maintenance calls. The data is provided in the spreadsheet named HOLIDAY LODGE DATA.XLS Month Calls 1 46 2 39 3 28 4 21 5 14 6 16 7 14 8 13 9 9 10 13 11 18 12 15 13 12 14 6 15 19 16 9 17 12 18 14 19 16 20 12 21 13 22 9 23 14 24 15 Develop a forecast for month 25 using a 4 month moving average, exponential smoothing (a = 0.2) and regression. Which forecast is preferred? Why?

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