Please show workings or provide necessary document(you can useexcel if possible), Your help is appreciated

QUESTION 2 One of the most promising methods for extracting crude oil employs a carbon dioxide (CO2) flooding technique. When flooded into oil pockets, CO2 enhances oil recovery by displacing the crude oil. In a microscopic investigation of the CO2 flooding process, flow tubes were dipped into sample oil pockets containing a known amount The oil pockets were flooded with CO2 and the percentage of oil displaced was recorded. The experiment was conducted at three different flow pressures and three different dipping angles. The displacement test data are recorded in Table 2. Table 2 Pressure (X1) (Pounds per Square Inch) Dipping Angle (X2) (Degrees) Oil Recovery (y) (Percentage) 1000 1000 1000 1500 1500 1500 2000 2000 2000 0 15 30 0 15 30 0 15 30 60.58 72.72 79.99 66.83 80.78 89.78 69.18 80.31 91.99 a.) b.) Write a complete second-order model with interaction relating percentage oil recovery y to pressure x, and dipping angle x. It is believed that the second order terms can be left out of the model. Write a complete first order model with interaction relating percentage oil recovery y to pressure Xi and dipping angle x2. Microsoft Excel was used to obtain the two models in questions a.) and b.) and the following results was obtained: c. SUMMARY OUTPUT FOR QUESTION 2 Regression Statistics Multiple R 0.981851006 R Square 0.964031398 Adjusted R Square 0.942450237 Standard Error 2.508384606 Observations ANOVA off Regression Residual Total SS MS Significance F 3 843.1908333 281.0636111 44.67004274 0.000493383 5 31.45996667 6.291993333 8 874.6508 Intercept X Variable 1 X Variable 2 X Variable 3 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% 54.5 5.034158413 10.82603993 0.000116695 41.55930497 67.44069503 0.007696667 0.003238311 2.376753688 0.06341952 -0.000627662 0.016020995 0.554111111 0.259962823 2.131501365 0.086240036 -0.114143507 1.222365729 0.000113333 0.000167226 0.67772701 0.528031686 -0.000316533 0.0005432 SUMMARY OUTPUT FOR QUESTION 2 Regression Statistics Multiple R 0.997457774 R Square 0.994922012 Adjusted R Square 0.986458697 Standard Error 1.216753422 Observations 9 ANOVA of Regression Residual Total SS MS F Significance F 5 870.2093333 174.0418667 117.5570232 0.001223007 3 4.441466667 1.480488889 8 874.6508 Intercept X Variable 1 X Variable 2 X Variable 3 X Variable 4 X Variable 5 Coefficients Standard Error Stat P-value Lower 95% Upper 95% 26.19333333 7.579656577 3.45574144 0.040766103 2.071460635 50.31520603 0.047716667 0.010443308 4.569114190.019666674 0.014481369 0.080951965 0.760111111 0.170474187 4.4588047190.021002747 0.217585654 1.302636568 0.000113333 8.11169E-05 1.3971606490.256772122 -0.000144817 0.000371484 -1.334E-05 3.4415E-06-3.876218589 0.030400321 -2.42924E-05-2.38761E-06 -0.006866667 0.003823887-1.795729451 0.170407335 -0.019035993 0.00530266 Is there sufficient evidence to support the statement made in b.)? Motivate your answer statistically. Use a = 0.05.