You want to develop a model to predict the taxes of houses, based on assessed value. A sample of 30 single-family houses listed for sale in Silver Spring, Maryland, a suburb of Washington, DC, is selected. The taxes (in $) and the assessed value of the houses (in $thousands) are recorded and stored in SilverSpring .

(Hint: First determine which are the independent and dependent variables.)

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 assessed value is $400,000.

d. Determine the coefficient of determination, r 2

, 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 assessed value?

g. What conclusions can you reach concerning the relationship between taxes and assessed value?