Maryland, was selected with the objective of developing a model to predict the taxes (in $) based on the assessed value of houses (in $thousands) and the age of the houses (in years) (stored in SilverSpring):

a. State the multiple regression equation.

b. Interpret the meaning of the slopes in this equation.

c. Predict the mean taxes for a house that has an assessed value of

$400,000 and is 50 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 taxes and the two independent variables (assessed value 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 taxes and assessed value. How does the interpretation of the slope here differ from that of Problem 13.77 on page 533?

l. 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 taxes. Based on your answers to (a) through (l), do you agree with this statement? Explain.