sta108_handout5 - r 11"'.Jo^* Box-Cox transformations...

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11"'.Jo^* r Box- Cox transformations TYansform Y only: fit Y' : 0o * AtX * Ttansform X only: frt Y Bs 1 plXI + e X' x-1'5 x -L x-0'5 Iog(X) x0.5 X p.z .923 .958 .982 .985 .964 .930 Choose the model which maximizes R2. So the best model seems to be Y: 0o* ltlog(x)+e, Fitted model is: Y 48.393 * 13.0941og (X), R2 .985, RZa; :.983. Here is the MINITAB output. The regression equation is Y :48.4 + 13.1log(X) Predictor Coef SE Coef T P Constant L524 37.74 0.000 Iog(X) 13.0936 0.573i 22.85 0.000 S:1.055 R-Sq:Bg.57o R-Sq(adi):98.3%
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This note was uploaded on 09/28/2011 for the course STA STA 108 taught by Professor Jiang during the Summer '09 term at UC Davis.

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