Demand for oil changes at Garcia's Garage has been as follows: Month January February March April May June 58 July August 54 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) Number of Oil Changes 34 50 60 45 53 18893882

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D4
Demand for oil changes at Garcia's Garage has been as follows:
Month
January
February
March
April
May
June
58
July
August
54
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)
Number of Oil Changes
34
50
38892883
60
45
53
56
Transcribed Image Text:Demand for oil changes at Garcia's Garage has been as follows: Month January February March April May June 58 July August 54 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) Number of Oil Changes 34 50 38892883 60 45 53 56
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