Please use minitab to answer...Help me with only a, b, e, f, g for 8.4 and b for 8.5... Answer step by step and I need it asap

E A 1 2 3 4 5 6 7 od B C D Y X x^2 106 -16.9833 288.4335 106 -18.9833 360.3668 97 -12.9833 168.5669 113 -13.9833 195.5335 96 -14.9833 224.5002 119 -18.9833 360.3668 92 -12.9833 168.5669 112 -18.9833 360.3668 92 -11.9833 143.6002 102 -11.9833 143.6002 107 -17.9833 323.4002 107 -12.9833 168.5669 102 -16.9833 288.4335 115 -15.9833 255.4668 101 -17.9833 323.4002 87 -4.98333 24.83358 91 -2.98333 8.900258 97 -3.98333 15.86692 82 -0.98333 0.966938 78 -2.98333 8.900258 95 -5.98333 35.80024 98 -6.98333 48.7669 Sheet1 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 . 1 READY B1 - . XV fxY A E F F 24 25 26 27 28 29 30 B D 94 -7.98333 63.73356 96 -6.98333 48.7669 100 -5.98333 35.80024 84 0.01667 0.000278 70 -0.98333 0.966938 104 -8.98333 80.70022 76 -0.98333 0.966938 93 -2.98333 8.900258 73 8.01667 64.267 73 3.01667 9.100298 76 0.01667 0.000278 80 3.01667 9.100298 84 3.01667 9.100298 71 4.01667 16.13364 64 6.01667 36.20032 88 5.01667 25.16698 79 0.01667 0.000278 88 5.01667 25.16698 73 5.01667 25.16698 74 9.01667 81.30034 76 1.01667 1.033618 87 10.01667 100.3337 70 8.01667 64.267 Sheet1 + 31 32 33 34 35 36 37 38 39 40 41 42 3 3 43 44 45 46 4 5 READY Tyne here to marchi B1 - EX fx Y A E F F 41 42 43 4 4 44 4 4 4 D 88 5.01667 25.16698 73 5.01667 25.16698 74 9.01667 81.30034 76 1.01667 1.033618 87 10.01667 100.3337 70 8.01667 64.267 69 18.01667 324.6004 54 18.01667 324.6004 62 18.01667 324.6004 78 12.01667 144.4004 65 10.01667 100.3337 64 13.01667 169.4337 74 16.01667 256.5337 87 18.01667 324.6004 63 18.01667 324.6004 82 11.01667 121.367 80 15.01667 225.5004 52 17.01667 289.5671 56 16.01667 256.5337 70 12.01667 144.4004 74 16.01667 256.5337 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 1 5 Sheet1 READY e *8.4. Refer to Muscle mass Problem 1.27. Second-order regression model (8.2) with independent normal error terms is expected to be appropriate. a Fit regression model (8.2). Plot the fitted regression function and the data. Does the quadratic regression function appear to be a good fit here? Find R. b. Test whether or not there is a regression relation; use a =.05. State the alternatives, decision rule, and conclusion. c. Estimate the mean muscle mass for women aged 48 years; use a 95 percent confidence interval. Interpret your interval. d. Predict the muscle mass for a woman whose age is 48 years; use a 95 percent prediction interval. Interpret your interval. e. Test whether the quadratic term can be dropped from the regression model; use a = .05. State the alternatives, decision rule, and conclusion f. Express the fitted regression function obtained in part (a) in terms of the original variable X. g. Calculate the coefficient of simple correlation between X and X? and between x and x2. Is the use of a centered variable helpful here? *8.5. Refer to Muscle mass Problems 1.27 and 8.4. a. Obtain the residuals from the fit in 8.4a and plot them against and against x on separate graphs. Also prepare a normal probability plot. Interpret your plots. b. Test formally for lack of fit of the quadratic regression function; use a=.05. State the alternatives, decision rule, and conclusion. What assumptions did you make implicitly in this test