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...


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



Constant1.7586            0.2525             6.9648      0.0000



AGE0.2124            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


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



Constant1.7586            0.2525             6.9648      0.0000



AGE0.2124            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


Give an interpretation of the term "R-sq" and comment on its value


Jun 08, 2022
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