MODEL 2: Assume the variable SPORT is-1 if type of vehicle is sport utility, and

Question

MODEL 2: Assume the variable SPORT is-1 if type of vehicle is sport utility, and regression is estimated using Suggested-price and SPORT a. (2pt) Comment on the goodness of fit for MODEL 2. 0 otherwise. A MODEL2 - Summaryb Adjusted R Std. Error of the Model R Square uare Estimate 588 port 7942 631 4.298 a. Predictors: (Constant) b. Dependent Variable: ResaleYalue MODEL 2 -Coefficientsa nstandardize Coefficients ar Coefficients Beta b. (lpt)Write down the estimated regression equation for MODEL 2. Model B Std. Error Si onstant 42.554 3.562 11.947 po c. (4pt) Report the statistical significance of the coefficients d. (6pt) Interpret the intercept for MODEL 2. e. (3pt) Interpret the coefficient for the variables Sport and SuggestedPrice f. (3pt) Explain why you think "Sport" is important/unimportant explanatory variable in this model (2pt) Curvature from the data is captured by a quadratic model using only Suggested price as explanatory variable. Regression analysis results are shown in table below. Consider previous MODEL 1, MODEL 2 and the quadratic models, which one you think fits the data best? Explain why. g. endent Variable: Resale value Model Summa Parameter Estimates d12 18 Constant 56.72 Equation df1 Si b1 b2 ratic 264 3.24 0629 0.0009 0.0003 he independent vanable is h. (2pt) Write down the quadratic model equation. i. (2pt) What is the average Resale Value in the quadratic model

Explanation / Answer

a. The goodness of fit of a model is indicated by the value of R Square.

The value of R Square is 0.631. Thus, we can say that the model is an average fit to the data.

b. The estimated regression equation is given by:

y = 42.554 + 0.000(SuggestedPrice) + 7.917 (Sport)

c. The statistical significance of the variables is as follows:

SuggestedPrice: 0.069

Thus, SuggestedPrice is not a significant variable.

Sport: 0.001

Thus, Sport is a significant variable.

d. An intercept  is the expected mean value of Y when all X=0.

The intercept of the model is 42.554, i.e y = 42.554 when both SuggestedPrice and Sport are zero.

The p value of the intercept on running the regression model is found to be 0.000.

Since the p value is very low, we can say that the intercept is significant.

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