Parameter 1 (k or A) in file:F3MODORG.TXT @ source line:9 optimized to:0.159997793E+10 Final RMS's for Data Columns (column # ,RMS): 1 0.35863 2 0.10435E-01 3 0.13237E-01 Final AVG RMSD= 0.127434233541054 Total optimization iteration count= 74 ** Total amount of simulations performed= 132 Parameter, Variance, Standard Deviation, % Stand. Deviat. 1 0.13913E+13 0.11795E+07 0.737E-01% Covariance Matrix: 1391320987878.51 5.750845838823218E-002 -7.165629677131814E-003 ******************************************************************** >>>>>>>>>>>>>>>>>>> START OF PREDICTION ANALYSIS <<<<<<<<<<<<<<<<<<< ******************************************************************** ================================================================ **** Start of prediction analysis for data-column: 1 ( X ) R-squared Adjusted Est. Std. Dev. Coefficient of (percent) R-squared of Model Error Mean Var. (percent) 96.767 96.659 2.939E-07 8.218E-07 35.77 * * * Analysis of Variance * * * Sum of Mean Prob. of Source DF Squares Square Overall F Larger F Regression 1 7.756E-11 7.756E-11 897.853 0.0000 Residual 30 2.591E-12 8.638E-14 Corrected Total 31 8.015E-11 * * * Inference on Coefficients * * * Standard Prob. of Variance Coef. Estimate Error t-statistic Larger |t| Inflation 1 0.0000 0.00000 1.02 0.3181 1.24 2 0.9963 0.03325 29.96 0.0000 1.00 * * * Variance-Covariance Matrix for the Coefficient Estimates * * * 1 2 1 0.00000000 0.00000000 2 0.00110543 * * * Case Analysis * * * Obs. Observed Predicted Residual Leverage Std. Res. Jack Res. Cook's D DFFITS 95.0% CI 95.0% CI 99.0% PI 99.0% PI 1 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 2 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 3 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 4 0.0000 0.0000 0.0000 0.0387 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 5 0.0000 0.0000 0.0000 0.0387 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 6 0.0000 0.0000 0.0000 0.0387 -0.2040 -0.2007 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 7 0.0000 0.0000 0.0000 0.0387 -0.2039 -0.2007 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 8 0.0000 0.0000 0.0000 0.0387 -0.2056 -0.2022 0.0009 -0.0406 0.0000 0.0000 0.0000 0.0000 9 0.0000 0.0000 0.0000 0.0387 -0.2026 -0.1993 0.0008 -0.0400 0.0000 0.0000 0.0000 0.0000 10 0.0000 0.0000 0.0000 0.0385 -0.1886 -0.1856 0.0007 -0.0372 0.0000 0.0000 0.0000 0.0000 11 0.0000 0.0000 0.0000 0.0380 0.0284 0.0280 0.0000 0.0056 0.0000 0.0000 0.0000 0.0000 Y 12 0.0000 0.0000 0.0000 0.0317 5.4455 49.8400 0.4847 9.0109 0.0000 0.0000 0.0000 0.0000 X 13 0.0000 0.0000 0.0000 0.2522 -0.2426 -0.2388 0.0099 -0.1387 0.0000 0.0000 0.0000 0.0000 X 14 0.0000 0.0000 0.0000 0.2482 -0.1324 -0.1303 0.0029 -0.0748 0.0000 0.0000 0.0000 0.0000 X 15 0.0000 0.0000 0.0000 0.2321 -0.2683 -0.2641 0.0109 -0.1452 0.0000 0.0000 0.0000 0.0000 X 16 0.0000 0.0000 0.0000 0.1598 -0.1070 -0.1052 0.0011 -0.0459 0.0000 0.0000 0.0000 0.0000 17 0.0000 0.0000 0.0000 0.0672 -0.1429 -0.1405 0.0007 -0.0377 0.0000 0.0000 0.0000 0.0000 18 0.0000 0.0000 0.0000 0.0477 0.3431 0.3380 0.0029 0.0756 0.0000 0.0000 0.0000 0.0000 19 0.0000 0.0000 0.0000 0.0323 -0.3484 -0.3432 0.0020 -0.0627 0.0000 0.0000 0.0000 0.0000 20 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 21 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 22 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 23 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 24 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 25 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 26 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 27 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 28 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 29 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 30 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 31 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 32 0.0000 0.0000 0.0000 0.0388 -0.2039 -0.2006 0.0008 -0.0403 0.0000 0.0000 0.0000 0.0000 1 Observed-O and Predicted-P vs. Independent Variable : : 0.000005 -: P : 2O : P : O : : : : : : 0.000004 -: P : O : : : : : R : e : s : p 0.000003 -: o : n : s : e : : P V : O a : r : O i : a 0.000002 -: 2 b : l : e : : : : : : : P 0.000001 -: O : : : : P : : : : :M2 0.000000 -:M :................................................................ : : : : : : : 0.0 0.8 1.6 2.4 3.2 4.0 4.8 Independent Variable Times 10** -6 1 Standardized Residuals vs Independent Variable : : 5.4 -: * : : : : : : : : : 4.2 -: : : : : : : : : : 3.0 -: R : e : s : i : d : u : a : l : s : 1.8 -: : : : : : : : : : 0.6 -: : : * : : : * : * * * :M * * : * : -0.6 -: :................................................................ : : : : : : : 0.0 0.8 1.6 2.4 3.2 4.0 4.8 Independent Variable Times 10** -6 1 Probability plot for half-normal distribution 7.2 +:::::::::::::::::::::::::::::::::::::::::::::::::::::::::. . . . . . . . . 6.4 + . . . . . . . . . 5.6 + . . * . . . . . . . 4.8 + . . . . . . . O . . b 4.0 + . s . . e . . r . . v . . a 3.2 + . t . . i . . o . . n . . s 2.4 + . . . . . . . . . 1.6 + . . . . . . . . . 0.8 + . . . . . . * . . . 0.0 +--------------------------------------*------------------. . ************* **** ** ** * * * * . *** . . . . . -0.8 ++:+:::+:::::::+::::::::::+::::::::::+::::::+:::::::::::::+ .01.10 .25 .50 .75 .90 .95 Cumulative Probability ============================================== ***** CORRELATION COEFFICIENT ANALYSIS ***** ============================================== ( this is also called Pearson's r, or the product- moment correlation coefficient ) This test will indicate how well the predicted values correlate with your experimental values. Correlation Coefficient: 0.983701 Probability: 0.647012E-23 ( a perfect fit will have a correlation coefficient = 1.0 ) ( small probability [=0.0] indicates significant correlation ) Fisher's z-coefficient: 2.40082 ================================================== ***** RESIDUALS MOMENT ANALYSIS ***** ( Residuals = Experim. Data - Predicted Values ) ================================================== ---------------------------------------------- Residual Gaussian Normality Test #1 **** Shapiro-Wilk W-test for Gaussian Normality **** ( how your residuals are distributed ) W = 0.236 ( Perfect Normality : W=1.0 ) P-value Test of Normality = 0.0000000E+00 ------------------------------------------- *** Residual Statistics: Mean(Average) = 5.5872238E-08 Average Deviation = 1.0504316E-07 Standard Deviation = 2.8919220E-07 Variance = 8.3632137E-14 Skewness = 5.047043 Kurtosis = 24.53947 **** End of prediction analysis for data-column: 1 ================================================================ ================================================================ **** Start of prediction analysis for data-column: 2 ( Y ) R-squared Adjusted Est. Std. Dev. Coefficient of (percent) R-squared of Model Error Mean Var. (percent) 99.997 99.997 6.961E-07 6.886E-05 1.011 * * * Analysis of Variance * * * Sum of Mean Prob. of Source DF Squares Square Overall F Larger F Regression 1 4.493E-07 4.493E-07 ********* 0.0000 Residual 30 1.454E-11 4.846E-13 Corrected Total 31 4.493E-07 * * * Inference on Coefficients * * * Standard Prob. of Variance Coef. Estimate Error t-statistic Larger |t| Inflation 1 0.0000 0.000000 1.7 0.0924 1.335 2 0.9992 0.001038 962.9 0.0000 1.000 * * * Variance-Covariance Matrix for the Coefficient Estimates * * * 1 2 1 2.02204E-14 -7.39413E-11 2 1.07680E-06 * * * Case Analysis * * * Obs. Observed Predicted Residual Leverage Std. Res. Jack Res. Cook's D DFFITS 95.0% CI 95.0% CI 99.0% PI 99.0% PI 1 0.0000 0.0000 0.0000 0.0416 -0.3626 -0.3573 0.0029 -0.0745 0.0000 0.0000 0.0000 0.0000 2 0.0000 0.0000 0.0000 0.0416 -0.3618 -0.3565 0.0028 -0.0743 0.0000 0.0000 0.0000 0.0000 3 0.0000 0.0000 0.0000 0.0416 -0.3626 -0.3573 0.0029 -0.0745 0.0000 0.0000 0.0000 0.0000 4 0.0000 0.0000 0.0000 0.0416 -0.3612 -0.3559 0.0028 -0.0742 0.0000 0.0000 0.0000 0.0000 5 0.0000 0.0000 0.0000 0.0416 -0.3616 -0.3563 0.0028 -0.0743 0.0000 0.0000 0.0000 0.0000 6 0.0000 0.0000 0.0000 0.0417 -0.3604 -0.3551 0.0028 -0.0740 0.0000 0.0000 0.0000 0.0000 7 0.0000 0.0000 0.0000 0.0417 -0.3618 -0.3565 0.0028 -0.0743 0.0000 0.0000 0.0000 0.0000 8 0.0000 0.0000 0.0000 0.0417 -0.3567 -0.3515 0.0028 -0.0733 0.0000 0.0000 0.0000 0.0000 9 0.0000 0.0000 0.0000 0.0417 -0.3642 -0.3589 0.0029 -0.0748 0.0000 0.0000 0.0000 0.0000 10 0.0000 0.0000 0.0000 0.0417 -0.3803 -0.3748 0.0031 -0.0782 0.0000 0.0000 0.0000 0.0000 11 0.0000 0.0000 0.0000 0.0417 -0.4375 -0.4315 0.0042 -0.0900 0.0000 0.0000 0.0000 0.0000 12 0.0000 0.0000 0.0000 0.0417 -0.3742 -0.3688 0.0030 -0.0770 0.0000 0.0000 0.0000 0.0000 13 0.0000 0.0000 0.0000 0.0417 -0.3640 -0.3587 0.0029 -0.0748 0.0000 0.0000 0.0000 0.0000 14 0.0000 0.0000 0.0000 0.0417 -0.3630 -0.3577 0.0029 -0.0746 0.0000 0.0000 0.0000 0.0000 15 0.0000 0.0000 0.0000 0.0417 -0.3608 -0.3555 0.0028 -0.0742 0.0000 0.0000 0.0000 0.0000 16 0.0000 0.0000 0.0000 0.0417 -0.3641 -0.3588 0.0029 -0.0749 0.0000 0.0000 0.0000 0.0000 17 0.0000 0.0000 0.0000 0.0417 -0.3642 -0.3589 0.0029 -0.0749 0.0000 0.0000 0.0000 0.0000 18 0.0000 0.0000 0.0000 0.0417 -0.3791 -0.3736 0.0031 -0.0779 0.0000 0.0000 0.0000 0.0000 19 0.0000 0.0000 0.0000 0.0416 -0.3467 -0.3415 0.0026 -0.0712 0.0000 0.0000 0.0000 0.0000 Y 20 0.0000 0.0000 0.0000 0.0407 2.9634 3.4644 0.1864 0.7139 0.0000 0.0000 0.0000 0.0000 21 0.0000 0.0000 0.0000 0.0380 1.3869 1.4095 0.0380 0.2803 0.0000 0.0000 0.0000 0.0000 Y 22 0.0000 0.0000 0.0000 0.0369 2.6351 2.9553 0.1329 0.5782 0.0000 0.0000 0.0000 0.0000 23 0.0000 0.0000 0.0000 0.0341 1.4521 1.4807 0.0372 0.2782 0.0000 0.0000 0.0000 0.0000 24 0.0001 0.0001 0.0000 0.0313 0.9413 0.9394 0.0143 0.1689 0.0001 0.0001 0.0001 0.0001 Y 25 0.0001 0.0001 0.0000 0.0338 -2.3058 -2.4993 0.0929 -0.4673 0.0001 0.0001 0.0001 0.0001 26 0.0002 0.0002 0.0000 0.0472 0.5904 0.5839 0.0086 0.1300 0.0002 0.0002 0.0002 0.0002 27 0.0003 0.0003 0.0000 0.1070 -0.5617 -0.5552 0.0189 -0.1922 0.0003 0.0003 0.0003 0.0003 X 28 0.0004 0.0004 0.0000 0.2363 0.9803 0.9796 0.1487 0.5449 0.0004 0.0004 0.0004 0.0004 X 29 0.0004 0.0004 0.0000 0.2361 -0.3892 -0.3837 0.0234 -0.2133 0.0004 0.0004 0.0004 0.0004 X 30 0.0003 0.0003 0.0000 0.1735 0.6028 0.5963 0.0381 0.2732 0.0003 0.0003 0.0003 0.0003 31 0.0003 0.0003 0.0000 0.1154 -0.4783 -0.4720 0.0149 -0.1705 0.0003 0.0003 0.0003 0.0003 32 0.0002 0.0002 0.0000 0.0778 -0.7874 -0.7823 0.0262 -0.2273 0.0002 0.0002 0.0002 0.0002 1 Observed-O and Predicted-P vs. Independent Variable : : 0.00040 -: : : : 3 : O : : : : : 0.00032 -: 2 : : : : : : R : 2 e : 2 s : p 0.00024 -: o : n : s : 2 e : : V : a : r : i : a 0.00016 -: b : 2 l : e : : : : : 2 : : 0.00008 -: : 2 : : : : : 2 : O : 2P : O 0.00000 -:MP :................................................................ : : : : : : : 0.00000 0.00006 0.00012 0.00018 0.00024 0.00030 0.00036 Independent Variable 1 Standardized Residuals vs Independent Variable : : 3.6 -: : : : : : * : : : * : 2.4 -: : : : : : : : : * * : 1.2 -: R : e : * * s : i : d : * * u : a : l : s : 0.0 -: : : :M * :* * : * : : * : : -1.2 -: : : : : : : : : : * -2.4 -: :................................................................ : : : : : : : 0.00000 0.00006 0.00012 0.00018 0.00024 0.00030 0.00036 Independent Variable 1 Probability plot for half-normal distribution 5.6 +:::::::::::::::::::::::::::::::::::::::::::::::::::::::::. . . . . . . . . 4.8 + . . . . . . . . . 4.0 + . . . . . . . . . 3.2 + . . * . . . . . O . * . b 2.4 + . s . . e . . r . . v . . a 1.6 + . t . * * . i . . o . . n . * * . s 0.8 + . . * * . . . . . . . 0.0 +---------------------------------------------------------. . . . *********** **** ** * . . ** . . * . -0.8 +* . . . . . . . . . -1.6 + . . . . . . . * . -2.4 ++:+:::+:::::::+::::::::::+::::::::::+::::::+:::::::::::::+ .01.10 .25 .50 .75 .90 .95 Cumulative Probability ============================================== ***** CORRELATION COEFFICIENT ANALYSIS ***** ============================================== ( this is also called Pearson's r, or the product- moment correlation coefficient ) This test will indicate how well the predicted values correlate with your experimental values. Correlation Coefficient: 0.999984 Probability: 0.00000 ( a perfect fit will have a correlation coefficient = 1.0 ) ( small probability [=0.0] indicates significant correlation ) Fisher's z-coefficient: 5.86143 ================================================== ***** RESIDUALS MOMENT ANALYSIS ***** ( Residuals = Experim. Data - Predicted Values ) ================================================== ---------------------------------------------- Residual Gaussian Normality Test #1 **** Shapiro-Wilk W-test for Gaussian Normality **** ( how your residuals are distributed ) W = 0.776 ( Perfect Normality : W=1.0 ) P-value Test of Normality = 4.1723251E-06 ------------------------------------------- *** Residual Statistics: Mean(Average) = 1.9071068E-07 Average Deviation = 4.6395664E-07 Standard Deviation = 6.9192043E-07 Variance = 4.7875392E-13 Skewness = 1.193391 Kurtosis = 2.357190 **** End of prediction analysis for data-column: 2 ================================================================ ================================================================ **** Start of prediction analysis for data-column: 3 ( Z ) R-squared Adjusted Est. Std. Dev. Coefficient of (percent) R-squared of Model Error Mean Var. (percent) 99.989 99.989 2.300E-06 1.745E-04 1.318 * * * Analysis of Variance * * * Sum of Mean Prob. of Source DF Squares Square Overall F Larger F Regression 1 1.460E-06 1.460E-06 ********* 0.0000 Residual 30 1.586E-10 5.288E-12 Corrected Total 31 1.461E-06 * * * Inference on Coefficients * * * Standard Prob. of Variance Coef. Estimate Error t-statistic Larger |t| Inflation 1 0.0000 0.000001 0.1 0.9372 1.667 2 0.9982 0.001899 525.5 0.0000 1.000 * * * Variance-Covariance Matrix for the Coefficient Estimates * * * 1 2 1 2.75443E-13 -6.30548E-10 2 3.60800E-06 * * * Case Analysis * * * Obs. Observed Predicted Residual Leverage Std. Res. Jack Res. Cook's D DFFITS 95.0% CI 95.0% CI 99.0% PI 99.0% PI 1 0.0000 0.0000 0.0000 0.0521 -0.0186 -0.0183 0.0000 -0.0043 0.0000 0.0000 0.0000 0.0000 2 0.0000 0.0000 0.0000 0.0521 -0.0185 -0.0182 0.0000 -0.0043 0.0000 0.0000 0.0000 0.0000 3 0.0000 0.0000 0.0000 0.0521 -0.0185 -0.0182 0.0000 -0.0043 0.0000 0.0000 0.0000 0.0000 4 0.0000 0.0000 0.0000 0.0521 -0.0187 -0.0183 0.0000 -0.0043 0.0000 0.0000 0.0000 0.0000 5 0.0000 0.0000 0.0000 0.0521 -0.0187 -0.0184 0.0000 -0.0043 0.0000 0.0000 0.0000 0.0000 6 0.0000 0.0000 0.0000 0.0521 -0.0189 -0.0186 0.0000 -0.0043 0.0000 0.0000 0.0000 0.0000 7 0.0000 0.0000 0.0000 0.0521 -0.0186 -0.0183 0.0000 -0.0043 0.0000 0.0000 0.0000 0.0000 8 0.0000 0.0000 0.0000 0.0521 -0.0205 -0.0201 0.0000 -0.0047 0.0000 0.0000 0.0000 0.0000 9 0.0000 0.0000 0.0000 0.0521 -0.0177 -0.0174 0.0000 -0.0041 0.0000 0.0000 0.0000 0.0000 10 0.0000 0.0000 0.0000 0.0520 -0.0113 -0.0111 0.0000 -0.0026 0.0000 0.0000 0.0000 0.0000 11 0.0000 0.0000 0.0000 0.0520 0.0347 0.0341 0.0000 0.0080 0.0000 0.0000 0.0000 0.0000 12 0.0000 0.0000 0.0000 0.0519 1.0150 1.0156 0.0282 0.2375 0.0000 0.0000 0.0000 0.0000 Y 13 0.0000 0.0000 0.0000 0.0456 -3.1297 -3.7495 0.2340 -0.8196 0.0000 0.0000 0.0000 0.0000 14 0.0000 0.0000 0.0000 0.0420 -0.6716 -0.6654 0.0099 -0.1394 0.0000 0.0000 0.0000 0.0001 Y 15 0.0001 0.0001 0.0000 0.0346 3.9448 5.5905 0.2792 1.0591 0.0001 0.0001 0.0001 0.0001 16 0.0003 0.0003 0.0000 0.0476 -1.7835 -1.8546 0.0795 -0.4146 0.0003 0.0003 0.0003 0.0003 17 0.0005 0.0005 0.0000 0.1058 0.2099 0.2066 0.0026 0.0711 0.0005 0.0005 0.0005 0.0005 18 0.0005 0.0005 0.0000 0.1092 0.0699 0.0687 0.0003 0.0240 0.0005 0.0005 0.0005 0.0005 19 0.0005 0.0005 0.0000 0.1096 0.5258 0.5193 0.0170 0.1822 0.0005 0.0005 0.0005 0.0005 20 0.0005 0.0005 0.0000 0.1078 -0.4272 -0.4213 0.0110 -0.1465 0.0005 0.0005 0.0005 0.0005 21 0.0005 0.0005 0.0000 0.1033 0.0682 0.0670 0.0003 0.0227 0.0005 0.0005 0.0005 0.0005 22 0.0005 0.0005 0.0000 0.1011 -0.4075 -0.4018 0.0093 -0.1347 0.0005 0.0005 0.0005 0.0005 23 0.0005 0.0005 0.0000 0.0949 -0.1342 -0.1320 0.0009 -0.0427 0.0005 0.0005 0.0005 0.0005 24 0.0004 0.0004 0.0000 0.0788 -0.0210 -0.0207 0.0000 -0.0060 0.0004 0.0004 0.0004 0.0004 25 0.0004 0.0004 0.0000 0.0687 0.7049 0.6989 0.0183 0.1899 0.0004 0.0004 0.0004 0.0004 26 0.0004 0.0004 0.0000 0.0536 -0.0378 -0.0371 0.0000 -0.0088 0.0004 0.0004 0.0003 0.0004 27 0.0002 0.0002 0.0000 0.0347 0.3156 0.3108 0.0018 0.0589 0.0002 0.0002 0.0002 0.0003 28 0.0001 0.0001 0.0000 0.0382 -0.0530 -0.0521 0.0001 -0.0104 0.0001 0.0001 0.0001 0.0001 29 0.0000 0.0000 0.0000 0.0453 -0.0011 -0.0010 0.0000 -0.0002 0.0000 0.0000 0.0000 0.0000 30 0.0000 0.0000 0.0000 0.0507 -0.0181 -0.0178 0.0000 -0.0041 0.0000 0.0000 0.0000 0.0000 31 0.0000 0.0000 0.0000 0.0518 -0.0189 -0.0186 0.0000 -0.0043 0.0000 0.0000 0.0000 0.0000 32 0.0000 0.0000 0.0000 0.0520 -0.0202 -0.0199 0.0000 -0.0047 0.0000 0.0000 0.0000 0.0000 1 Observed-O and Predicted-P vs. Independent Variable : : 6 0.0005 -: 22 : 2 : 2 : : : : 2 : : : 2 0.0004 -: : : : : P : O : R : P e : O s : p 0.0003 -: o : n : s : e : : 2 V : a : r : i : a 0.0002 -: b : l : e : : : : : : : O 0.0001 -: P : : : 2 : : 2 : : 3 : O : 2 0.0000 -:M :................................................................ : : : : : : : 0.0000 0.0001 0.0002 0.0003 0.0004 0.0005 0.0006 Independent Variable 1 Standardized Residuals vs Independent Variable : : 4.0 -: * : : : : : : : : : 2.5 -: : : : : : : : : : 1.0 -:* R : e : * s : * i : d : * * u :* ** a :M* * * * * l : * s : * -0.5 -: * : * : : : : : : : : * -2.0 -: : : : : : : : : * : -3.5 -: :................................................................ : : : : : : : 0.0000 0.0001 0.0002 0.0003 0.0004 0.0005 0.0006 Independent Variable 1 Probability plot for half-normal distribution 4.8 +:::::::::::::::::::::::::::::::::::::::::::::::::::::::::. . . . . . . . . 4.0 + * . . . . . . . . . 3.2 + . . . . . . . . . 2.4 + . . . . . . . O . . b 1.6 + . s . . e . . r . . v . * . a 0.8 + . t . * . i . * . o . * . n . * . s 0.0 +-----**********-****-**-**-*-----------------------------. . * . . . . ** . . * . -0.8 + . . . . . . . . . -1.6 + . .* . . . . . . . -2.4 + . . . . . . . . . -3.2 ++:+:::+:::::::+::::::::::+::::::::::+::::::+:::::::::::::+ .01.10 .25 .50 .75 .90 .95 Cumulative Probability ============================================== ***** CORRELATION COEFFICIENT ANALYSIS ***** ============================================== ( this is also called Pearson's r, or the product- moment correlation coefficient ) This test will indicate how well the predicted values correlate with your experimental values. Correlation Coefficient: 0.999946 Probability: 0.00000 ( a perfect fit will have a correlation coefficient = 1.0 ) ( small probability [=0.0] indicates significant correlation ) Fisher's z-coefficient: 5.25705 ================================================== ***** RESIDUALS MOMENT ANALYSIS ***** ( Residuals = Experim. Data - Predicted Values ) ================================================== ---------------------------------------------- Residual Gaussian Normality Test #1 **** Shapiro-Wilk W-test for Gaussian Normality **** ( how your residuals are distributed ) W = 0.693 ( Perfect Normality : W=1.0 ) P-value Test of Normality = 5.9604645E-08 ------------------------------------------- *** Residual Statistics: Mean(Average) = -2.6481530E-07 Average Deviation = 1.1270046E-06 Standard Deviation = 2.2940621E-06 Variance = 5.2627212E-12 Skewness = 0.9275326 Kurtosis = 7.345834 **** End of prediction analysis for data-column: 3 ================================================================ ******************************************************************** >>>>>>>>>>>>>>>>>>>> END OF PREDICTION ANALYSIS <<<<<<<<<<<<<<<<<<<< ********************************************************************