The data shown in Table 6-15 represent the thrust of a jet-turbine engine (y) and six candidate regressors: x1 primary speed of rotation, x2 secondary speed of rotation, x3

fuel flow rate, x4 pressure, x5 exhaust temperature, and x6 ambient temperature at time of test.

(a) Fit a multiple linear regression model using x3 fuel flow rate, x4 pressure, and x5 exhaust temperature as the regressors.

(b) Test for significance of regression using 0.01. Find the P-value for this test. What are your conclusions?

(c) Find the t-test statistic for each regressor. Using 0.01, explain carefully the conclusion you can draw from these statistics.

(d) Find R2 and the adjusted statistic for this model. Comment on the meaning of each value and its usefulness in assessing the model.

(e) Construct a normal probability plot of the residuals and interpret this graph.

(f) Plot the residuals versus . Are there any indications of inequality of variance or nonlinearity?

(g) Plot the residuals versus x3. Is there any indication of nonlinearity?

(h) Predict the thrust for an engine for which x3 20000, x4 170, and x5 1589.

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