A realtor used the regression model, Y = beta0 + beta1X1 +beta2X2 + epsilon, to
ID: 3176283 • Letter: A
Question
A realtor used the regression model, Y = beta0 + beta1X1 +beta2X2 + epsilon, to predict selling prices of homes (in thousands of $). The variable X1 represents the home size (square feet), and X2 represents the number of bedrooms. The following information is available: ANOVA Source DF SS MS F Regression 2 6101.6 Error 219.6 Total 10 Coefficient Standard Error t statistic Intercept 26.28 22.88 1.15 Size 0.12352 0.02435 5.07 Bedrooms 20.183 6.697 3.01 Suppose that the independent variable X2 = Bedrooms is dropped from the regression model. Which of the following is most likely?
Explanation / Answer
Y = beta0 + beta1X1 +beta2X2 + epsilon
X1 represents the home size (square feet), and X2 represents the number of bedrooms
The t statitic is 3.01, from what I can read. If this variable is removed from regression model ( option haven't put down) will lead to loss of R2 , as this variable is significant.
The overall p value of the model' signifiance will increase, ( model is less fit)
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