6-46. The data shown in Table 6-15 represent the thrust of a jet-turbine engine (y) and six candidate regressors: x₁ = pri- mary speed of rotation, x₂ = secondary speed of rotation, x3 fuel flow rate, x₁ pressure, x, = exhaust temperature, and x = ambient temperature at time of test. = = X6 (a) Fit a multiple linear regression model using x, = fuel flow rate, X4 = pressure, and x = exhaust temperature as the regressors. (b) Test for significance of regression using a = 0.01. Find
6-46. The data shown in Table 6-15 represent the thrust of a jet-turbine engine (y) and six candidate regressors: x₁ = pri- mary speed of rotation, x₂ = secondary speed of rotation, x3 fuel flow rate, x₁ pressure, x, = exhaust temperature, and x = ambient temperature at time of test. = = X6 (a) Fit a multiple linear regression model using x, = fuel flow rate, X4 = pressure, and x = exhaust temperature as the regressors. (b) Test for significance of regression using a = 0.01. Find
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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using r- studio please cod the following parts a-h
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VIEWStep 2: (a) Fitting of multiple linear regression model using x3, x4, and x5 as regressor
VIEWStep 3: (b) Finding the p-value for the test and drawing conclusion
VIEWStep 4: (c) Finding t-test statistics for each regressor using level of significance 0.01
VIEWStep 5: (d) Finding R^2 and adjusted R^2 for the model
VIEWStep 6: (e) Construing the Normal probability plot of the model and interpretation of the graph
VIEWStep 7: (f) Plotting the residuals vs fitted value of the dependent variable
VIEWStep 8: (g) Plotting the residuals versus x3
VIEWStep 9: (h) Prediction for the thrust for engine for which x3=20000, x4=170, and x5=1589
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