# Question

This data table gives annual costs of 223 commercial leases. All of these leases provide office space in a Midwestern city in the United States. For the response, use the cost of the lease (in dollars per square foot). As explanatory variables, use the reciprocal of the number of square feet and the age of the property in which the office space is located (denoted as Age, in years).

(a) Examine scatterplots of the response versus the two explanatory variables as well as the scatterplot between the explanatory variables. Do you notice any unusual features in the data? Do the relevant plots appear straight enough for multiple regression?

(b) Fit the indicated multiple regression and show a summary of the estimated features of the model.

(c) Does the estimated model appear to meet the conditions for the use of the MRM?

(d) Does this estimated model explain statistically significant variation in the costs per square foot of the leases?

(e) Interpret the slope for the age of the building, including in your answer the confidence interval for this estimate.

(f) Can you identify a lurking variable? Could this lurking variable affect the coefficients of the explanatory variables?

(a) Examine scatterplots of the response versus the two explanatory variables as well as the scatterplot between the explanatory variables. Do you notice any unusual features in the data? Do the relevant plots appear straight enough for multiple regression?

(b) Fit the indicated multiple regression and show a summary of the estimated features of the model.

(c) Does the estimated model appear to meet the conditions for the use of the MRM?

(d) Does this estimated model explain statistically significant variation in the costs per square foot of the leases?

(e) Interpret the slope for the age of the building, including in your answer the confidence interval for this estimate.

(f) Can you identify a lurking variable? Could this lurking variable affect the coefficients of the explanatory variables?

## Answer to relevant Questions

This data table contains accounting and financial data that describe 324 companies operating in the information sector. The variables include the expenses on research and development (R&D), total assets of the company, and ...This data table tracks monthly performance of stock in Apple Computer since 1990. The data include 264 monthly returns on Apple Computer, as well as returns on the entire stock market, Treasury Bills (short-term, 30-day ...The best remedy for a regression model that has collinear predictors is to remove one of those that are correlated. A builder is interested in which types of homes earn a higher price. For a given number of square feet, the builder gathered prices of homes that use the space differently. In addition to price, the homes vary in the number ...An analyst at the United Nations is developing a model that describes GDP (gross domestic product per capita, a measure of the overall production in an economy per citizen) among developed countries. For this analysis, she ...Post your question

0