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Portable Network Graphic  |  1994-04-29  |  73KB  |  816x1056  |  8-bit (256 colors)
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OCR: The Lack of Fit table is displayed when you have observations that are exact replicates of each other in terms of the X variables The error that you can measure for these exact replicates caller pure error This the portion of the sample error that cannot be explained predicted The difference between the residual error from the model and the pure error called lack of fit error lack of fit is significant then you should consider adding interaction terms if appropriate, or trying to better capture the functional form of regressor click on a table for more help Lack of Fit Source DF Sum of Squares Mean Square Ratio Lack of Fit 947 065 189 413 0. .4339 Pure Error 28 12223.574 436 .556 Prob>F Total Error 33 13170 638 0. .8211 Max 0.3642 calle interactior column