The regression equation is
LISTPRICE = 28.3 + 5.70 LIVINGAREA - 3.29 ROOMS - 5.94 BEDRMS + 1.65 BATHRMS - 0.314 AGE + 5.63 ACRES + 0.0215 TAXES
Predictor Coef SE Coef T P
Constant 28.34 27.82 1.02 0.314
LIVINGAREA 5.698 1.036 5.50 0.000
ROOMS -3.291 5.621 -0.59 0.561
BEDRMS -5.936 7.309 -0.81 0.421
BATHRMS 1.646 7.034 0.23 0.816
AGE -0.3145 0.1517 -2.07 0.044
ACRES 5.626 3.455 1.63 0.111
TAXES 0.021470 0.004479 4.79 0.000
R-Sq = 91.5%
Above is info for Multiple regression. The output variable was LISTPRICE for homes selling in a particular region. The square footage of the home, the number of rooms, number of bedrooms, number of bathrooms, the age of the house, the amount of land include with the house and the amount of property taxes were considered as variables that may have an impact on the LISTPRICE of the house. Using what you know about t-scores, identify which of the variables have a significant influence on the LISTPRICE. At a level of 1% which variables are significant?