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## 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 ‘***’.

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