In the Spring of 2013, 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. (3 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 = **84.4046 + 0.5979×1 + 128.0504×2 + 49.7684×3 **

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) **49.87%**

c. What is the observed significance level of the estimated regression model? (3 points) **The observed significance level is 0.0000974851100791014. As the p-value is much less than o.o5 (0.0000975 < 0.05), there is a significant relationship between the variables in the linear regression model of the data.**

d. For the given sample of apartments, what is the average value of an additional square foot of apartment space? (3 points) **$59.79**

e. What value from the printout measures the observed level of significance for the variable “gated security”, in the regression model?(3 points)