36 59 (A) Whe gasoline is pumped into the tank of a car, vapors are vented into the atmosphere. An experiment was performed to determine whether the amount of saper, can be predicted using the following variables X, - tank temperature CFL X, line temperature, X, - vapor pressure in tank (psi), and X-vapor pressure of gasoline (psi). The data obtained was in the following table 29 24 26 22 27 21 33 34 33 31 33 37 59 53 51 51 545 60 60 3.32 1.10 3.18 3.19 120 103 478 4.72 4.60 3.42 3.26 J.IN 2.08 3.41 4.59 4.72 4.41 Use MINITAB's multiple regression program to obtain C) SSR(X31XSSR (X, X, X,ASR(X.X.XX only state the answers) 03.0) 16 () An analysis of the data and make your concesions (3.0) State the dah degree polynomial regression model in te variable (0.5) State the second-order (degree 2) polynomial repressie model in 2 variables and explain the terms in the model (1.0) i) Explain briefly how you can do regression with qualitative productor variables (1.5) 36 59 (A) Whe gasoline is pumped into the tank of a car, vapors are vented into the atmosphere. An experiment was performed to determine whether the amount of saper, can be predicted using the following variables X, - tank temperature CFL X, line temperature, X, - vapor pressure in tank (psi), and X-vapor pressure of gasoline (psi). The data obtained was in the following table 29 24 26 22 27 21 33 34 33 31 33 37 59 53 51 51 545 60 60 3.32 1.10 3.18 3.19 120 103 478 4.72 4.60 3.42 3.26 J.IN 2.08 3.41 4.59 4.72 4.41 Use MINITAB's multiple regression program to obtain C) SSR(X31XSSR (X, X, X,ASR(X.X.XX only state the answers) 03.0) 16 () An analysis of the data and make your concesions (3.0) State the dah degree polynomial regression model in te variable (0.5) State the second-order (degree 2) polynomial repressie model in 2 variables and explain the terms in the model (1.0) i) Explain briefly how you can do regression with qualitative productor variables (1.5)