Demand for oil changes at Garcia's Garage has been as follows: Month January February March April May June July August G Show Transcribed Text Number of Oil Changes 44 49 66 59 53 58 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 Janu The forecasting model is given by the equation Y=x (Enter your responses rounded to two decimal places) 59 63 >. 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 of Oil Changes Month September October November

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.

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)

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…

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

Which of the following are common metrics for measuring the relative quality of different forecasting methods? OAbsolutely Mean Mean Squared Accuracy O Mean Absolute Percent Error Mean Squared Response OMean Squared Error Mean Absolute Error (a.k.a. Mean Absolute Deviation)

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

In a retail store, the actual sales of a particular product (in thousands of units) over the past few months are as follows: Month Sales 1 16 2 22 3 18 4 20 5 23   Using exponential smoothing method with α (smoothing constant) of 0.75 and the given forecast for month 1 equal to 10, what is the forecast for month 6?