A commercial real estate company evaluates vacancy rates, square footage, rental

Question

A commercial real estate company evaluates vacancy rates, square footage, rental rates, and operating expenses for commercial properties in a large metropolitan area in order to provide clients with quantitative information upon which to make rental decisions. The data from 81 properties consists of rental rates (v) in percent, age (xi) in years, operating expenses and taxes (x), vacancy rates (x) in proportions, and total square footage (%) in feet squared. Minitab output is on the next page. a. Write the multiple linear regression model b. What is the interpretation of ?? in this model? c. Give the estimated regression equation from Minitab. d. Look at the ANOVA table from Minitab. You don't have to calculate anything; just look at it. Test for the global utility of the model at the 5% significance level. Give the hypotheses, test statistic, and P-value from Minitab, and state the conclusion e. f. Create 95% confidence intervals for ??, ?3, and ?4. Use Aß3?, and the standard errors from the Minitab output. The estimates ß are Coef and the standard errors sp are SE Coef. Predict the rental rate of a 5 year old property with 4.1 tax rate, 0.16 vacancy rate, and area of 100,000 square feet. g. determination

Explanation / Answer

Please see the answer as shown below: -

a.

rental=12.2-0.1420*Age+0.2820*Tax+0.62*Vacancy-0.000008*Area

b.

Age: -0.1420. This means that for every increase of 1 in Age, rental would go down by 0.142

c.

rental=12.2-0.1420*Age+0.2820*Tax+0.62*Vacancy-0.000008*Area

e.

We can see that the p-value of regression is 0.00. Hence, reject the null hypothesis that the independent variables do not affect the dependent variable.

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