Beachcomer Ltd Is A Local Car Dealership That Sells Used And New Vehicles. The Manager Of The Company Wants To Know How Different Variables Affect The Sales Of His Vehicles. A Random Sample Of Yearly Data Was Taken With The View To Testing The Model. SALES = A+BAGE + YMIL + SENG Where SALES = Amount That A Vehicle Is Sold For (000's), AGE = Age Of Vehicle, MIL= The Total Mileage Of The Vehicle At The Point Of Sale And ENG = The Size Of The Engine. The Sample Of Data Was Processed Using MINITAB And The Following Is An Extract Of The Output Obtained: The Regression Equation Is ***** Coef StDev T-ratio P-value Predictor Constant 1.7586 0.2525 6.9648 0.0000 AGE 0.2124 0.3175 * 0.5042 MIL -0.7527 0.3586 -2.0991 ** ENG 4.8124 0.6196 7.7664 0.0000 R-sq= 56.1 % R-sq (adj) = 59.8 % Analysis Of Variance Source DF SS MS F P Regression 3 413.1291 138.7097 *** 0.00 Error 50 457.7607 2.2888 Total 53 Fill In The Missing Values ‘*’, ‘**’, ‘***’and ‘***’.

Beachcomer Ltd is a local car dealership that sells used and new vehicles. The manager of the company wants to know how different variables affect the sales of his vehicles. A random sample of yearly data was taken with the view to testing the model. SALES = a+BAGE + yMIL + SENG Where SALES = amount that a vehicle is sold for (000’s), AGE = age of vehicle, MIL= the total mileage of the vehicle at the point of sale and ENG = the size of the engine. The sample of data was processed using MINITAB and the following is an extract of the output obtained: The regression equation is ***** Coef StDev t-ratio p-value Predictor Constant 1.7586 0.2525 6.9648 0.0000 AGE 0.2124 0.3175 * 0.5042 MIL -0.7527 0.3586 -2.0991 ENG 4.8124 0.6196 7.7664 0.0000 R-sq= 56.1 % R-sq (adj) = 59.8 % Analysis of Variance Source DF SS MS F P Regression 3 413.1291 138.7097 * 0.00 Error 50 457.7607 2.2888 Total 53 Fill in the missing values ‘’, ‘’, ‘’and ‘***’.

- October 5, 2022 - Edwin Tunner

Beachcomer Ltd is a local car dealership that sells used and new vehicles. The manager of the company wants to know how different variables affect the sales of his vehicles. A random sample of yearly data was taken with the view to testing the model. SALES = a+BAGE + yMIL + SENG

Where SALES = amount that a vehicle is sold for (000’s), AGE = age of vehicle, MIL= the total mileage of the vehicle at the point of sale and ENG = the size of the engine. The sample of data was processed using MINITAB and the following is an extract of the output obtained:

The regression equation is *****

Coef StDev t-ratio p-value

Predictor

Constant 1.7586 0.2525 6.9648 0.0000

AGE 0.2124 0.3175 * 0.5042

MIL -0.7527 0.3586 -2.0991 **

ENG 4.8124 0.6196 7.7664 0.0000

R-sq= 56.1 % R-sq (adj) = 59.8 %

Analysis of Variance

Source DF SS MS F P

Regression 3 413.1291 138.7097 *** 0.00

Error 50 457.7607 2.2888

Total 53

Fill in the missing values ‘*’, ‘**’, ‘***’and ‘***’.

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