Enabled Exam 3 Saved Help Save & Exit A real estate agency collects data concerning y-sales price of a house (in thousands of dollars), x1= home size (in hundreds of square feet), x2=rating (an overall "niceness rating" for the house from 1 [worst] to 10 [best]) The agency developed and estimated a multiple regression model that predicts the house sales price as shown in the table below: SUMMARY OUTPUT Regression Statistics Multiple R 0.995049355 R Square 0.99012322 Adjusted R Square 0.987301282 Standard Error 3.241635644 Observations 10 ANOVA IP SS MS F Significance F Regression 7373.951588 3686976 350.8665 9.57533E-08 Residual 73.55741155 10.5082 Total 7447.509 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 29.34681183 4.891442017 5.999624 0.000542 17.78038941 40.91323425 x1 5.61280584 0.228520722 24.56147 4.73E-08 5.072440198 6.153171481 3.834422338 0.43320097 8.851371 4.75E-05 2810064817 4.858779858 Calculate the predicted house sales price for a house that has 1,700 square feet and a rating of 5. (Provide exact dollar amounts. Do not round the coefficients. Round your answer to the nearest whole number) Sales price ($) =