Question

The commercial division of a real estate firm is conducting a regression analysis of the relationship...

The commercial division of a real estate firm is conducting a regression analysis of the relationship between x, annual gross rents (in thousands of dollars), and y, selling price (in thousands of dollars) for apartment buildings. Data were collected on several properties recently sold and the following computer output was obtained.

The regression equation is
Y = 20.0 + 7.27 X
Predictor Coef SE Coef T
Constant 20.000 3.2213 6.21
X   7.270 1.3626 5.29
Analysis of Variance
SOURCE DF SS
Regression 1 41,587.2
Residual Error 7
Total 8 51,984.6

A) How many apartment buildings were in the sample?

B) Write the estimated regression equation (to 2 decimals if necessary).
ŷ =   +   

C) What is the value of sb1   (to 4 decimals)?

D)

Use the F statistic to test the significance of the relationship at a .05 level of significance.

Compute the F test statistic (to 2 decimals).

E) Predict the selling price of an apartment building with gross annual rents of $60,000 (to 1 decimal).
$  thousands.

Homework Answers

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
The commercial division of a real estate firm is conducting a regression analysis of the relationship...
The commercial division of a real estate firm is conducting a regression analysis of the relationship between x, annual gross rents (in thousands of dollars), and y, selling price (in thousands of dollars) for apartment buildings. Data were collected on several properties recently sold and the following computer output was obtained. The regression equation is Y = 20.0 + 7.26 X Predictor Coef SE Coef T Constant 20.000 3.2213 6.21 X   7.260 1.3625 5.29 Analysis of Variance SOURCE DF SS...
The commercial division of a real estate firm is conducting a regression analysis of the relationship...
The commercial division of a real estate firm is conducting a regression analysis of the relationship between x, annual gross rents (in thousands of dollars), and y, selling price (in thousands of dollars) for apartment buildings. Data were collected on several properties recently sold and the following computer output was obtained. The regression equation is Y =20.0 + 7.29 X Predictor Coef SE Coef T Constant 20.000 3.2213 6.21 X 7.290 1.3628 5.29 Analysis of Variance SOURCE DF SS Regression...
A real estate agent in Athens used regression analysis to investigate the relationship between apartment sales...
A real estate agent in Athens used regression analysis to investigate the relationship between apartment sales prices and the various characteristics of apartments and buildings. The variables collected from a random sample of 25 compartments are as follows: Sale price: The sale price of the apartment (in €) Apartments: Number of apartments in the building Age: Age of the building (in years) Size: Apartment size (area in square meters) Parking spaces: Number of car parking spaces in the building Excellent...
Study the following Minitab output from a regression analysis to predict y from x. a. What...
Study the following Minitab output from a regression analysis to predict y from x. a. What is the equation of the regression model? b. What is the meaning of the coefficient of x? c. What is the result of the test of the slope of the regression model? Let α = .10.Why is the t ratio negative? d. Comment on r2 and the standard error of the estimate. e. Comment on the relationship of the F value to the t...
12.4 Study the following Minitab output from a regression analysis to predict y from x. a....
12.4 Study the following Minitab output from a regression analysis to predict y from x. a. What is the equation of the regression model? b. What is the meaning of the coefficient of x? c. What is the result of the test of the slope of the regression model? Let α = .10.Why is the t ratio negative? d. Comment on r2 and the standard error of the estimate. e. Comment on the relationship of the F value to the...
The following table is the output of simple linear regression analysis. Note that in the lower...
The following table is the output of simple linear regression analysis. Note that in the lower right hand corner of the output we give (in parentheses) the number of observations, n, used to perform the regression analysis and the t statistic for testing H0: β1 = 0 versus Ha: β1 ≠ 0.   ANOVA df SS MS F Significance F   Regression 1     61,091.6455 61,091.6455 .69        .4259   Residual 10     886,599.2711 88,659.9271      Total 11     947,690.9167 (n = 12;...
The general manager of a chain of pharmaceutical stores reported the results of a regression analysis,...
The general manager of a chain of pharmaceutical stores reported the results of a regression analysis, designed to predict the annual sales for all the stores in the chain (Y) – measured in millions of dollars. One independent variable used to predict annual sales of stores is the size of the store (X) – measured in thousands of square feet. Data for 14 pharmaceutical stores were used to fit a linear model. The results of the simple linear regression are...
In a regression analysis involving 30 observations, the following estimated regression equation was obtained. ŷ =...
In a regression analysis involving 30 observations, the following estimated regression equation was obtained. ŷ = 17.6 + 3.8x1 − 2.3x2 + 7.6x3 + 2.7x4 For this estimated regression equation, SST = 1,835 and SSR = 1,800. (a)At α = 0.05, test the significance of the relationship among the variables.State the null and alternative hypotheses. -H0: One or more of the parameters is not equal to zero. Ha: β0 = β1 = β2 = β3 = β4 = 0 -H0:...
Regression Analysis with a Minitab output Assume that your company owns multiple retail outlets in cities...
Regression Analysis with a Minitab output Assume that your company owns multiple retail outlets in cities across the United States. You conduct a study to determine if daily sales levels (in hundreds of dollars) can be predicted by the number of competitors that are located within a one-mile radius of each location and city population (in thousands of people). Therefore, the dependent variable is SALES and the two independent variables are NUMBER OF COMPETITORS and CITY POPULATION. Your research team...
Data on advertising expenditures and revenue (in thousands of dollars) for the Four Seasons Restaurant follow....
Data on advertising expenditures and revenue (in thousands of dollars) for the Four Seasons Restaurant follow.    Advertising expenditures: 1,2,4,6,10,14,20 Revenue: 19,33,44,,41,53,,54,55 A) Let x equal advertising expenditures and y equal revenue. Complete the estimated regression equation below (to 2 decimals). =   +  x B) Compute the following (to 1 decimal). SSE SST SSR MSR MSE C) Test whether revenue and advertising expenditures are related at a .05 level of significance. Compute the F test statistic.