Sale prices of apartments. A Minneapolis, Minnesota, real estate appraiser used regression analysis to explore the relationship between the sale prices of apartment buildings and various characteristics of the buildings. Data on a random sample of 23 apartment buildings were collected and a multiple linear regression model is estimated. The estimation results are given below. The dependent variable is sale prices; the independent variables include number of apartment units, age of the apartment, lot size and building area. SUMMARY OUTPUT Regression Statistics Multiple R 0.99 R Square 0.98 Adjusted R Square 0.97 Standard Error 34778.5 Observations 25 ANOVA Significance df SS MS F F Regression 4 1.05E+12 2.62E+11 216.9576 3.63E-16 Residual Total 20 2.42E+10 1.21E+09 24 1.07E+12 Standard Upper Lower Uppe Coefficients Error t Stat P-value Lower 95% 95% 95.0% 95.0% Intercept Apartments 113483.98 27231.42 4.17 0.00 56680.24 170287.72 56680.24 170287 4998.03 1468.71 3.40 0.00 1934.35 8061.71 1934.35 8061 Age -1053.38 287.78 -3.66 0.00 -1653.68 -453.08 -1653.68 -453 LotSize 0.13 2.96 0.04 0.97 -6.05 6.30 -6.05 6 BldArea 14.97 1.49 10.05 0.00 11.86 18.07 11.86 18 a. Interpret the adjusted R-squared.