Develop a model to predict the assessed value of houses (in $thousands), using the size of the houses (in thousands of square feet) and the age of the houses (in years) from the following table (stored in House2):

a. State the multiple regression equation.
b. Interpret the meaning of the slopes in this equation.
c. Predict the assessed value for a house that has a size of 1,750 square feet and is 10 years old.
d. Perform a residual analysis on the results and determine whether the regression assumptions are valid.
e. Determine whether there is a significant relationship between assessed value and the two independent variables (size and age) at the 0.05 level of significance.
f. Determine the p-value in (e) and interpret its meaning.
g. Interpret the meaning of the coefficient of multiple determination in this problem.
h. Determine the adjusted r2.
i. At the 0.05 level of significance, determine whether each independent variable makes a significant contribution to the regression model. Indicate the most appropriate regression model for this set of data.
j. Determine the p-values in (i) and interpret their meaning,
k. Construct a 95% confidence interval estimate of the population slope between assessed value and size. How does the interpretation of the slope here differ from that of Problem 13.77 on page 515?
1. Compute and interpret the coefficients of partial determination.
m. The real estate assessor's office has been publicly quoted as saying that the age of a house has no bearing on its assessed value. Based on your answers to (a) through (1), do you agree with this statement? Explain.

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