You want to develop a model to predict the assessed value of homes based on their size. A sample of 30 single family houses listed for sale in Silver Spring, Maryland, a suburb of Washington, DC, is selected to study the relationship between assessed value (in $ thousands) and size (in thousands of square feet), and the data is collected 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 assessed value for a house whose size is 2,000 square feet. 

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 assessed value and size? 

g. Construct a 95% confidence interval estimate of the population slope. 

h. What conclusions can you reach about the relationship between the size of the house and its assessed value?