about the mod about the model? the qui (d) Fit SEx8 1 1 0 0 1 1 2 23 3.6 13 20 2
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about the mod about the model? the qui (d) Fit SEx8 1 1 0 0 1 1 2 23 3.6 13 20 2.1 27 28 3.4 3.6 4.0 3.9 3.8 E to tistical softwa the quadratic 8.2 Finding and plotting residuals. Consider the data on and y shown in the table. STIRES (a) Fit the model EO)- Bo Bix to the data. PRESSURE inch (b) Calculate the residuals for the model. any r. pounds per sq. (c) Plot the residuals versus r. Do you detect trends? If so, what does the pattern sugges 30 about the model? 31 SEx8 2 32 20 18 32 47 50 33 33 34 MINITAB output for Exercise 8.4 The regression equation is vo 98.6 0.256 PRESSURE 36 Predictor Coef SE Coef 0.000 98.6149 0.4037 244.26 PREssURE -0.255594 0.008646 -29.56 0.000 8.4 Elasticity of n s 0.6484 R-sq 99.04 R-sq(adj) 98.94 abrasive mate Analysis of Variance ness. Anothe is elasticity. T Source 367.34 873.87 0.000 367.34 Regression were investiga Residual Error 9 371.12 Total (September 1 compress a m Residuals Versus PRESSURE and gold in a (esponse is VOLUME) pressed volu zero-pressur different pre in the table straight-line a MINITAB (a) Calculat (b) Plot the a trend? (c) Propose part b (d) Fit and PRESSUREExplanation / Answer
Residuals are the difference between the outputs of the fitted line and the actual outputs.
Thus,
E(y) = 4.907 + 2.0396x
The residual values are given in the table above.
The plot of residual vs X is given below.
No particular pattern can be observed in the residual plots,
Hope this helps.
SUMMARY OUTPUT Regression Statistics Multiple R 0.979737663 R Square 0.959885889 Adjusted R Square 0.954871625 Standard Error 4.154165444 Observations 10 ANOVA df SS MS F Significance F Regression 1 3303.543276 3303.543276 191.4310683 7.19676E-07 Residual 8 138.0567243 17.25709053 Total 9 3441.6 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -3.17918858 2.746984781 -1.15733753 0.280519235 -9.513746844 3.155369684 -9.51375 3.15537 x 2.490984222 0.180038243 13.83586167 7.19676E-07 2.07581529 2.906153155 2.075815 2.906153 RESIDUAL OUTPUT Observation Predicted y Residuals 1 1.802779865 3.197220135 2 6.78474831 3.21525169 3 14.25770098 -2.257700977 4 21.73065364 0.269346356 5 26.71262209 -1.712622089 6 34.18557476 -7.185574756 7 41.65852742 -2.658527423 8 46.64049587 3.359504132 9 49.13148009 -2.13148009 10 59.09541698 5.90458302Related Questions
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