Demand for oil changes at Garcia's Garage has been as follows:Number of Oil ChangesJanuary44February49March66ITApril59May53June585963MonthJulyAugusta. Use simple linear regression analysis to develop a forecasting model for monthly demand. In this application, the dependent variable, Y, is monthly demand and the independent variable, X, is the month. For JanuThe forecasting model is given by the equation Y=+x. (Enter your responses rounded to two decimal places)JShow Transcribed Text>. Use the model to forecast demand for September, October, and November. Here, X=9, 10, and 11, respectively. (Enter your responses rounded to two decimal places.)Forecast for the number ofOil ChangesShow Transcribed TextMonthSeptemberOctoberNovembercan you do all the parts please corrrect

Answered: Demand for oil changes at Garcia's…

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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The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week of Pints Used August 31 360 September 7 370 September 14 412 September 21 383 September 28 371 October 5 371 a) The forecasted demand for the week of October 12 using a 3-week moving average= {__] Pints (round your response to two decimal places).
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.…
The monthly sales for Yazici Batteries, Inc., were as follows: Month Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Sales 21 20 15 12 15 16 15 17 19 21 20 24 Using a method of trend projection, the forecast for the next month (Jan) = ______ sales (round your response to two decimal places).
The number of cases of merlot wine sold by the Connor Owen winery in an eight-year period is as follows: YEAR CASES OF MERLOT WINE 1 270 2 356 3 398 4 456 5 358 6 500 7 410 8 376 Using an exponential smoothing model with an alpha value of 0.20, estimate the smoothed value calculated as of the end of year 8. Use the average demand for years 1 through 3 as your initial forecast for year 4, and then smooth the forecast forward to year 8. Note: Round your intermediate calculations and final answer to the nearest whole number.
Use the data set below to answer the following questions: [Gunakan set data di bawah untuk menjawab soalan-soalan berikut:] Table 1: Monthly sales unit IJadual 1: Unit jualan bulanau) Month Sales Units [Bulan] 1 [Unit Jualan] 1100 2 1200 3 1450 4 1800 2100 2700 i) Calculate the three-period simple moving average forecasts for months 4, 5 and 6. (Hitunskau rawalan pALata bergerak nudak weNEgUrakan empat-tenroh untuk bulau 5 dan 6.) Calculate the four-period weighted moving average forecasts for months 5 and 6 usıng weights of 0.05, 0.15, 0.30, and 0.50 from the earliest period to the latest period, respectively.
can you make an operations management analysis for this forecasting
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 105 82 110 112 108 106 130 120 Forecast Demand 100 108 97 98 108 102 105 107 November December For the given forecast, the tracking signal = MADS (round your response to two decimal places).
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 For the given forecast, the tracking signal = = MADS (round your response to two decimal places). November December Actual Demand 100 80 1/10 115 105 110 125 120 Forecast Demand 100 104 99 101 104 104 105 109
Demand for oil changes at Garcia's Garage has been as follows: Month January February March April May June July August Number of Oil Changes 38 55 56 60 58 01 70 52 a. Use simple linear regression analysis to develop a forecasting model for monthly demand. In this application, the dependent variable, Y, is monthly demand and the independent variable, X, is the month. For January, let X=1; for February, let X 2; and so on. The forecasting model is given by the equation Y=X (Enter your responses rounded to two decimal places)
With the multiplicative seasonal method of forecasting: the seasonal amplitude is a constant, regardless of the magnitude of average demand. there can be only four seasons in the time-series data. the times series cannot exhibit a trend. seasonal factors are multiplied by an estimate of average demand to arrive at a seasonal forecast.
please answer within 30 minutes.
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 3 3 8 5 8 6 Demand for Guitars 2 5 6 4 11 6 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): Y = + c) The estimate for guitar sales if Maroon 5 performed on TV 11times = sales (round your response to two decimal places). d) The correlation coefficient (r)for this model = (round your response to four decimal places). The coefficient of determination (r2) for this model = (round your response to…

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