Question: You want to develop a model to predict the taxes of houses, based on asking price. A sample of 61 single-family houses listed for sale

You want to develop a model to predict the taxes of houses, based on asking price. A sample of 61 single-family houses listed for sale in Silver Spring, Maryland, a suburb of Washington, DC, is selected. The taxes (in $) and the asking price of the houses (in $thousands) are recorded and stored in SilverSpring.

a. Construct a scatter plot and, assuming a linear relationship, use the least-squares method to compute the regression coefficients b0 and b1.

b. Interpret the meaning of the Y intercept, b0, and the slope, b1, in this problem.

c. Use the prediction line developed in (a) to predict the mean taxes for a house whose asking price is $400,000.

d. Determine the coefficient of determination, r2, and interpret its meaning in this problem.

e. Perform a residual analysis on your results and evaluate the regression assumptions.

f. At the 0.05 level of significance, is there evidence of a linear relationship between taxes and asking price?

g. What conclusions can you reach concerning the relationship between taxes and asking price?

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a b b 0 1424 and b 1 9017 The Y intercept b 0 would be the mean yearly taxes when the asking price i... View full answer

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