The partially completed regression output to predict the selling price of a house based onthe age of the house in years (Age), the living area of the house in square feet (Living Area)and the number of bedrooms (Bedrooms) is given belowRegression StatisticsMultiple RR SquareAdjusted R SquareStandard ErrorObservationsANOVARegressionResidualTotal0.848636,009.01dfSS36,709,265,905.7014 50,972,400,000.00Coefficients Standard Error108,597.3721-580.687086.828231,261.9127MS101,922.33332,092.498127.699411,006.8696t StatInterceptAgeLiving AreaBedrooms[NOTE: Do not include a comma in your response]1)The predicted selling price for a home that is 10 years of age, has 2,000 square feet ofliving area and has three bedrooms is $(to 2 d.p.) 6) Which one of the following statements describes the results of the hypothesis test for theoverall regression model using alpha = 0.05?O Because the test statistic is greater than the critical value, we reject the null hypothesisand conclude that there is a relationship between the dependent variable and theindependent variables.O Because the test statistic is greater than the critical value, we fail to reject the nullhypothesis and conclude that there is a relationship between the dependent variable andthe independent variables.O Because the test statistic is less than the critical value, we fail to reject the null hypothesisand conclude that there is no relationship between the dependent variable and theindependent variables.Because the test statistic is less than the critical value, we reject the null hypothesis andconclude that there is no relationship between the dependent variable and theindependent variables.

It is required to predict the selling price for a 10 years-old home that has a living area of 2,000…

The partially completed regression output to predict the selling price of a house based on the age of the house in years (Age), the living area of the house in square feet (Living Area) and the number of bedrooms (Bedrooms) is given below Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total 0.8486 36,009.01 df SS 36,709,265,905.70 14 50,972,400,000.00 Coefficients Standard Error 108,597.3721 -580.6870 86.8282 31,261.9127 MS 101,922.3333 2,092.4981 27.6994 11,006.8696 t Stat Intercept Age Living Area Bedrooms [NOTE: Do not include a comma in your response] 1)The predicted selling price for a home that is 10 years of age, has 2,000 square feet of living area and has three bedrooms is $ . (to 2 d.p.)