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Name ______________________________________ Due Saturday Dec, 1 at noon. In the Fall of 2011, data was collected for 30 randomly selected apartments...

In the Fall of 2011, data was collected for 30 randomly selected apartments in the San Diego area in an attempt to determine the major determinants of rent prices. The group collecting the data believe that rent price is determined by apartment size in square feet, existence of a tennis court(s) in the complex and the existence of gated security for the complex. Complete the following steps:

1. Use Excel to construct an (xy) scatterplot for y=Rent versus x=Square Feet. Put the scatterplot in a new worksheet. Be sure to provide a meaningful title and informative axis labels.

2. Regress the dependent variable rent on the independent variables square feet, tennis court, gated security. Put your regression output in the designated area of the worksheet "Data." Use the regression output to answer questions a - e below:

a. Type the estimated regression function.
y-hat = estimated monthly rent = ____________________________________________.

b. What percentage of the total variability in monthly rent is explained by the variability in the square feet, tennis court(s) and gated security variables? ________________

c. What is the observed significance level of the estimated regression model? ____________________

d. For the given sample of apartments, what is the average value of an additional square foot of apartment space? _______________

e. What value from the printout measures the observed level of significance for the variable "gated security", in the regression model?_________________

Name ______________________________________ Due Saturday Dec, 1 at noon. In the Fall of 2011, data was collected for 30 randomly selected apartments in the San Diego area in an attempt to determine the major determinants of rent prices. The group collecting the data believe that rent price is determined by apartment size in square feet, existence of a tennis court(s) in the complex and the existence of gated security for the complex. Complete the following steps: 1. Use Excel to construct an (xy) scatterplot for y=Rent versus x=Square Feet. Put the scatterplot in a new worksheet. Be sure to provide a meaningful title and informative axis labels. (5 points) 2. Regress the dependent variable rent on the independent variables square feet, tennis court, gated security. Put your regression output in the designated area of the worksheet "Data." Use the regression output to answer questions a - e below: a. Type the estimated regression function. (3 points) y-hat = estimated monthly rent = 407.372*.799(rent). b. What percentage of the total variability in monthly rent is explained by the variability in the square feet, tennis court(s) and gated security variables? (3 points)________________ c. What is the observed significance level of the estimated regression model? (3 points)____________________ d. For the given sample of apartments, what is the average value of an additional square foot of apartment space? (3 points)_______________ e. What value from the printout measures the observed level of significance for the variable "gated security", in the regression model?(3 points) _________________
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Apartment Rent Square Feet Tennis Court Gated Security 1 $724.00 844 0 1 2 $900.00 1097 0 1 3 $1,247.00 1100 1 1 4 $1,172.00 1111 1 1 5 $810.00 908 1 0 6 $1,150.00 1540 1 0 7 $700.00 785 1 1 Place the regression output in the shaded area below 8 $730.00 1100 1 1 SUMMARY OUTPUT 9 $746.00 1005 0 0 10 $890.00 1220 0 0 Regression Statistics 11 $725.00 879 1 1 Multiple R 0.6959933955 12 $569.00 640 1 1 R Square 0.4844068065 13 $680.00 1280 0 1 Adjusted R Square 0.4659927639 14 $1,020.00 1544 1 0 Standard Error 198.76561671 15 $750.00 1185 1 0 Observations 30 16 $649.00 706 1 0 17 $1,135.00 1000 1 0 ANOVA 18 $720.00 1240 1 1 df SS MS F Significance F 19 $560.00 828 1 1 Regression 1 1039306.42916 1039306.4292 26.306380213 1.949283E-005 20 $600.00 1050 0 0 Residual 28 1106217.57084 39507.770387 21 $859 880 1 1 Total 29 2145524 22 $790 860 1 1 23 $1,225 1650 1 1 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 24 $1,035 1390 1 1 Intercept 407.37205807 142.848122669 2.8517844719 0.0080776733 114.760947278 699.98316886 114.76094728 699.98316886 25 $749 1145 1 0 Rent 0.7986039917 0.1557044161 5.1289745771 1.94928E-005 0.479657958 1.1175500254 0.479657958 1.1175500254 26 $832 1215 1 1 27 $1,003 1214 1 1 28 $1,565 1700 1 1 29 $1,095 1384 1 1 30 $990 980 1 1
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Take home 3. solutions.xlsx

Name ______________________________________
Due Saturday Dec, 1 at noon. In the Fall of 2011, data was collected for 30 randomly selected apartments in the San Diego area in an attempt to
determine...

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