Lori Cook has developed the following forecasting model:where y demand for Kool Air conditioners andx= the outside temperature (degrees Fahrenheit)a) When the temperature outside is 70° F, demand forecast =b) When the temperature outside is 80° F, demand forecast =c) When the temperature outside is 90° F, demand forecast =2F2W#32000E$4F4R%5F5Tair conditioners (enter your response as an integer).air conditioners (enter your response as an integer).air conditioners (enter your response as an integer).MacBook Air6F6Y&7y = 36.0 +4.30x,F7U*8DIIFB(9DDF9VThis question)00F10

Regression is a statistical technique used in the fields of finance, investing, and other…

Answered: Lori Cook has developed the following…

Practical Management Science

6th Edition

ISBN:9781337406659

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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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12.7 The Intrepid mutual fund of growth stocks has had the following average monthly price for the past 10 months. Month 1 2 3 4 5 6 7 8 9 10 Fund Price 62.7 63.9 68.0 66.4 67.2 65.8 68.2 69.3 67.2 70.1 Compute the exponentially smoothed forecast with a = 0.40, the adjusted exponentially smoothed forecast with a = 0.40 and ß = 0.30, and the linear trend line forecast. Compare the accuracy of the three forecasts using cumulative error and MAD, and indicate which forecast appears to be most accurate.
A check-processing center uses exponetial smoothing to forecast the number of incoming checks each month. the number of checks recewived in June was 40 million while the forecast was 42 million. A smoothibg constant of 0.15 is used. a) Using exponential smoothing and given a the forecast for the month of July={__} million checks received (round your response to one decimal place
A concert promoter is forecasting this year's attendance for one of his concerts based on the following historical data: Year Attendance Four Years ago 10,000 Three Years ago 12,000 Two Years ago 18,000 Last Year 20,000 What is this year's forecast using exponential smoothing with alpha = 0.2, if last year's smoothed forecast was 15,000?
Respond to each of the items using the following time series data. Period Demand 144 2 172 3 157 4 160 144 181 7 160 8 176 9. 149 10 183 11 182 12 149 13 153 14 164 15 153 16 104 Click here for the Excel Data File b. Compute all possible forecasts using a five-period moving average. (Round your answers to 1 decimal place.) Absolute Period Demand 5-period SMA Errors 1 144 172 3 157 4. 160 5 144 181 7 160 8 176 9 149 10 183 11 182 12 149 13 153 14 164 LO
George has forecasted that annual demand for his sailboats in year 5 will equal 6,000 sailboats Based on the given data and using the multiplicative seasonal model, the demand level for George's sailboats in the spring of year 5 will be nothing sailboats (enter a whole number). Note:- Do not provide handwritten solution. Maintain accuracy and quality in your answer. Take care of plagiarism. Answer completely. You will get up vote for sure.
The number of cases of merlot wine sold by the Connor Owen winery in an eight-year period is as follows: CASES OF MERLOT WINE 276 362 YEAR 2005 2006 2007 2008 2009 2010 2011 2012 404 462 364 506 416 382 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. (Round your intermediate calculations and final answer to the nearest whole number.) Answer is complete but not entirely correct. Forecast for 2012 372
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.
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 previous month. Gershon has collected the data shown in the following table: Maroon 5 TV Appearances Demand for Guitars Y = 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): + 4 2 X 5 7 5 9 7 6 7 6 10 7
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…
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The manager of the Carpet City outlet needs to make an accurate forecast of the demand for Soft Shag carpet (its biggest seller). If the manager does not order enough carpet from the carpet mill, customers will buy their carpet from one of Carpet City's many competitors. The manager has collected the following demand data for the past 8 months: Demand for Soft Shag Month Carpet (1,000 yd.) 1 8 2 12 3 7 4 9 5 15 6 11 7 10 8 12 Compute the exponentially smoothed forecast (a = .20) for the given data. Compute an adjusted exponentially smoothed forecast (with a = .20 and β = .20) for the given data

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