Data were collected on cars of different models made by different manufacturers.

Question

Data were collected on cars of different models made by different manufacturers. SPSS output for the least-squares regression model is given below:

What percent of the variation in four-year resale value can be explained by using Type, Price, and Engine in the linear regression model?

Engine The size of the engine Price The price of the vehicle in thousands of dollars Type 0 if the vehicle is a car 1 if the vehicle is a truck Model Summary Adjusted Std. Error of 1 962 926 924 3191 ANOVA Sum of Model Squares Mean Square Regression 1 4568.642 4856.214 477.010 000 Residual 1170.761 115 10.181 Total 157 39.404 118 Coefficients Un standardized 95% Confidence Interval for B Coefficients Model B Std. Error Lower Bound Upper Bound 300 385 (Constant) 2.679 .897 Type 643 2.064 930 Price 028 .817 .874 386 2.658 1.129 Engine 1.893

Explanation / Answer

Here You have to given the excel output .

R^2=coefficeint of determination is explained percent of variation

Here R^2= 0.926 mean 92.6% variation resale value can be explain by using type , price and engine.

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