A research department of an American automobile company wants to develop a model to predict gasoline mileage (measured in MPG) of the company's vehicles by using their horsepower and weights (measured in pounds). To do this, it took a random sample of 50 vehicles to perform a regression analysis as follows:SUMMARY OUTPUT Regression Statistics Multiple R 0.865689 R Square 0.749417 Adjusted R Square 0.738754 Standard Error 4.176602 Observations 50 ANOVA df SS MS F Regression 2451.973702 1225.987 d Residual 819.8680976 c Total 49 3271.8418 Standard Coefficients Error t Stat Intercept 58.15708 2.658248208 21.87797 Horsepower -0.11753 0.032643428 -3.60028 Weight -0.00687 0.001401173 -4.90349 (a) State the multiple regression equation. Interpret the meanings of the coefficients for horsepower and weight. (b) Test the validity of this multiple regression equation at the significance level of 1%. Show your reasoning