You want to develop a model to predict the selling price of homes based on assessed value. A sample of 30 recently sold single-family houses in a small city is selected to study the relationship between selling price (in $thousands) and assessed value (in $thousands). The houses in the city were reassessed at full value one year prior to the study. The results are in House1.
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 selling price for a house whose assessed value is $170,000.
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 selling price and assessed value?
g. Construct a 95% confidence interval estimate of the population slope.