Parameter 1 (k or A) in file:F4MODEZY.DAT @ source line:9 optimized to:4999225.21 Parameter 2 (k or A) in file:F4MODEZY.DAT @ source line:12 optimized to:66735.0769 Parameter 3 (k or A) in file:F4MODEZY.DAT @ source line:16 optimized to:8495129.31 Final SUM[ ( X(DATA)-X(MODEL) )^2 ] = 5.550593731763186E-003 Final RMS's for Data Columns (column # ,RMS): 1 0.50281E-03 2 0.12290E-02 3 0.38147E-02 4 0.35446E-02 Final AVG RMSD= 2.272783306375678E-003 Total optimization iteration count= 281 ** Total amount of simulations performed= 918 Parameter, Variance, Standard Deviation, % Stand. Deviat. 1 0.38073E+12 0.61703E+06 12.3 % 2 0.22641E+06 475.83 0.713 % 3 0.78144E+10 88399. 1.04 % Covariance Matrix: 380726511738.027 84395658.4478283 -12399590966.1360 -0.955964597865071 226412.539349878 -37329936.5835151 -0.293481851329124 0.832548732773235 7814427078.66344 -3.009470109205987E-004 1.743535911345125E-004 -1.687514284307081E-004 ******************************************************************** >>>>>>>>>>>>>>>>>>> START OF PREDICTION ANALYSIS <<<<<<<<<<<<<<<<<<< ******************************************************************** ================================================================ **** Start of prediction analysis for data-column: 1 ( E ) R-squared Adjusted Est. Std. Dev. Coefficient of (percent) R-squared of Model Error Mean Var. (percent) 100.000 100.000 1.801E-12 3.584E-09 0.05025 * * * Analysis of Variance * * * Sum of Mean Prob. of Source DF Squares Square Overall F Larger F Regression 1 2.353E-17 2.353E-17 ********* 0.0000 Residual 32 1.038E-22 3.243E-24 Corrected Total 33 2.353E-17 * * * Inference on Coefficients * * * Standard Prob. of Variance Coef. Estimate Error t-statistic Larger |t| Inflation 1 0.0000 1.366E-12 0.5 0.5931 19.55 2 0.9999 3.712E-04 2693.5 0.0000 1.00 * * * Variance-Covariance Matrix for the Coefficient Estimates * * * 1 2 1 1.86495E-24 -4.93805E-16 2 1.37799E-07 * * * Test for Lack of Fit * * * Sum of Mean Prob. of Source DF Squares Square Overall F Larger F Lack of fit 18 1.038E-22 5.766E-24 Inf 0.0000 Pure error 14 0.000E+00 0.000E+00 Residual 32 1.038E-22 * * * 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 X 1 0.0000 0.0000 0.0000 0.2102 -0.7954 -0.7908 0.0842 -0.4080 0.0000 0.0000 0.0000 0.0000 XY 2 0.0000 0.0000 0.0000 0.1939 2.1013 2.2275 0.5309 1.0924 0.0000 0.0000 0.0000 0.0000 X 3 0.0000 0.0000 0.0000 0.1692 0.0093 0.0092 0.0000 0.0041 0.0000 0.0000 0.0000 0.0000 X 4 0.0000 0.0000 0.0000 0.1441 -0.7382 -0.7328 0.0459 -0.3007 0.0000 0.0000 0.0000 0.0000 X 5 0.0000 0.0000 0.0000 0.1195 1.1693 1.1763 0.0928 0.4333 0.0000 0.0000 0.0000 0.0000 Y 6 0.0000 0.0000 0.0000 0.0956 -3.3681 -4.1262 0.5996 -1.3416 0.0000 0.0000 0.0000 0.0000 7 0.0000 0.0000 0.0000 0.0750 1.3720 1.3919 0.0764 0.3965 0.0000 0.0000 0.0000 0.0000 Y 8 0.0000 0.0000 0.0000 0.0366 -2.9394 -3.3862 0.1641 -0.6600 0.0000 0.0000 0.0000 0.0000 9 0.0000 0.0000 0.0000 0.0367 1.8300 1.9036 0.0637 0.3713 0.0000 0.0000 0.0000 0.0000 10 0.0000 0.0000 0.0000 0.0367 1.2371 1.2478 0.0292 0.2435 0.0000 0.0000 0.0000 0.0000 11 0.0000 0.0000 0.0000 0.0367 0.8140 0.8096 0.0126 0.1581 0.0000 0.0000 0.0000 0.0000 12 0.0000 0.0000 0.0000 0.0367 0.5236 0.5176 0.0052 0.1011 0.0000 0.0000 0.0000 0.0000 13 0.0000 0.0000 0.0000 0.0368 0.3304 0.3257 0.0021 0.0636 0.0000 0.0000 0.0000 0.0000 14 0.0000 0.0000 0.0000 0.0368 0.1925 0.1895 0.0007 0.0370 0.0000 0.0000 0.0000 0.0000 15 0.0000 0.0000 0.0000 0.0368 0.1002 0.0987 0.0002 0.0193 0.0000 0.0000 0.0000 0.0000 16 0.0000 0.0000 0.0000 0.0368 0.0347 0.0341 0.0000 0.0067 0.0000 0.0000 0.0000 0.0000 17 0.0000 0.0000 0.0000 0.0368 -0.0090 -0.0089 0.0000 -0.0017 0.0000 0.0000 0.0000 0.0000 18 0.0000 0.0000 0.0000 0.0368 -0.1068 -0.1051 0.0002 -0.0205 0.0000 0.0000 0.0000 0.0000 19 0.0000 0.0000 0.0000 0.0368 -0.1075 -0.1059 0.0002 -0.0207 0.0000 0.0000 0.0000 0.0000 20 0.0000 0.0000 0.0000 0.0368 -0.1075 -0.1059 0.0002 -0.0207 0.0000 0.0000 0.0000 0.0000 21 0.0000 0.0000 0.0000 0.0368 -0.1080 -0.1064 0.0002 -0.0208 0.0000 0.0000 0.0000 0.0000 22 0.0000 0.0000 0.0000 0.0368 -0.1080 -0.1064 0.0002 -0.0208 0.0000 0.0000 0.0000 0.0000 23 0.0000 0.0000 0.0000 0.0368 -0.1080 -0.1064 0.0002 -0.0208 0.0000 0.0000 0.0000 0.0000 24 0.0000 0.0000 0.0000 0.0368 -0.1080 -0.1064 0.0002 -0.0208 0.0000 0.0000 0.0000 0.0000 25 0.0000 0.0000 0.0000 0.0368 -0.1080 -0.1064 0.0002 -0.0208 0.0000 0.0000 0.0000 0.0000 26 0.0000 0.0000 0.0000 0.0368 -0.1080 -0.1064 0.0002 -0.0208 0.0000 0.0000 0.0000 0.0000 27 0.0000 0.0000 0.0000 0.0368 -0.1080 -0.1064 0.0002 -0.0208 0.0000 0.0000 0.0000 0.0000 28 0.0000 0.0000 0.0000 0.0368 -0.1080 -0.1064 0.0002 -0.0208 0.0000 0.0000 0.0000 0.0000 29 0.0000 0.0000 0.0000 0.0368 -0.1080 -0.1064 0.0002 -0.0208 0.0000 0.0000 0.0000 0.0000 30 0.0000 0.0000 0.0000 0.0368 -0.1080 -0.1064 0.0002 -0.0208 0.0000 0.0000 0.0000 0.0000 31 0.0000 0.0000 0.0000 0.0368 -0.1080 -0.1064 0.0002 -0.0208 0.0000 0.0000 0.0000 0.0000 32 0.0000 0.0000 0.0000 0.0368 -0.1080 -0.1064 0.0002 -0.0208 0.0000 0.0000 0.0000 0.0000 33 0.0000 0.0000 0.0000 0.0368 -0.1080 -0.1064 0.0002 -0.0208 0.0000 0.0000 0.0000 0.0000 34 0.0000 0.0000 0.0000 0.0368 -0.1080 -0.1064 0.0002 -0.0208 0.0000 0.0000 0.0000 0.0000 1 Observed-O and Predicted-P vs. Independent Variable Times 10** -9 : : 4.0 -: M : : : : : : : : : 3.5 -: : : : : : : R : e : s : p 3.0 -: o : n : s : e : : V : a : r : i : 2 a 2.5 -: b : l : e : 2 : : : : 2 : : 2.0 -: : 2 : : : : 2 : : : 2 : 1.5 -:2 :................................................................ : : : : : : : 1.5 2.0 2.5 3.0 3.5 4.0 4.5 Independent Variable Times 10** -9 1 Standardized Residuals vs Independent Variable : : 2.4 -: : : * : : : * : : : : * 1.2 -: * * : : : * : : : * : * : * : * 0.0 -: * 2 R : M e : s : i : d : u : * a :* l : s : -1.2 -: : : : : : : : : : -2.4 -: : : : : * : : : : * : -3.6 -: :................................................................ : : : : : : : 1.5 2.0 2.5 3.0 3.5 4.0 4.5 Independent Variable Times 10** -9 1 Probability plot for half-normal distribution 4.0 +:::::::::::::::::::::::::::::::::::::::::::::::::::::::::. . . . . . . . . 3.2 + . . . . . . . . . 2.4 + . . . . * . . . . * . 1.6 + . . * . . * . . * . O . . b 0.8 + * . s . . e . * . r . * . v . * * . a 0.0 +-------------------**-*----------------------------------. t . ************** ** . i . . o . . n . . s -0.8 + ** . . . . . . . . . -1.6 + . . . . . . . . . -2.4 + . . . . . .* . . . -3.2 + . * . . . . . . . -4.0 ++:+:::+:::::::+::::::::::+::::::::::+::::::+:::::::::::::+ .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: 0.999572 Probability: 0.00000 ( a perfect fit will have a correlation coefficient = 1.0 ) ( small probability [=0.0] indicates significant correlation ) Fisher's z-coefficient: 4.22505 ================================================== ***** 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 = 0.763 ( Perfect Normality : W=1.0 ) P-value Test of Normality = 9.5367432E-07 ------------------------------------------- *** Residual Statistics: Mean(Average) = 2.9842470E-13 Average Deviation = 1.0046757E-12 Standard Deviation = 1.7764005E-12 Variance = 3.1555990E-24 Skewness = -1.072193 Kurtosis = 5.277860 **** End of prediction analysis for data-column: 1 ================================================================ ================================================================ **** Start of prediction analysis for data-column: 2 ( S ) R-squared Adjusted Est. Std. Dev. Coefficient of (percent) R-squared of Model Error Mean Var. (percent) 100.000 100.000 5.044E-06 0.004338 0.1163 * * * Analysis of Variance * * * Sum of Mean Prob. of Source DF Squares Square Overall F Larger F Regression 1 0.009008 0.009008 ********* 0.0000 Residual 46 0.000000 0.000000 Corrected Total 47 0.009008 * * * Inference on Coefficients * * * Standard Prob. of Variance Coef. Estimate Error t-statistic Larger |t| Inflation 1 0. 7.638E-07 -1.6 0.1226 1.1 2 1. 5.316E-05 18814.8 0.0000 1.0 * * * Variance-Covariance Matrix for the Coefficient Estimates * * * 1 2 1 5.83329E-13 -1.22605E-11 2 2.82560E-09 * * * 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 X 1 0.0590 0.0590 0.0000 0.3525 0.0844 0.0835 0.0019 0.0616 0.0590 0.0590 0.0590 0.0590 XY 2 0.0534 0.0534 0.0000 0.2879 3.7945 4.5280 2.9102 2.8789 0.0534 0.0534 0.0534 0.0534 XY 3 0.0456 0.0456 0.0000 0.2100 -4.1062 -5.1028 2.2411 -2.6309 0.0456 0.0456 0.0456 0.0456 X 4 0.0384 0.0384 0.0000 0.1496 0.2362 0.2338 0.0049 0.0981 0.0384 0.0384 0.0384 0.0384 Y 5 0.0035 0.0036 0.0000 0.0209 -3.0974 -3.4436 0.1024 -0.5031 0.0036 0.0036 0.0035 0.0036 6 0.0025 0.0025 0.0000 0.0212 0.5093 0.5052 0.0028 0.0744 0.0025 0.0025 0.0025 0.0025 Y 7 0.0018 0.0018 0.0000 0.0216 -3.0379 -3.3606 0.1017 -0.4989 0.0018 0.0018 0.0018 0.0018 8 0.0012 0.0012 0.0000 0.0219 -0.8705 -0.8681 0.0085 -0.1299 0.0012 0.0012 0.0012 0.0012 9 0.0009 0.0009 0.0000 0.0222 -0.9998 -0.9998 0.0113 -0.1506 0.0009 0.0009 0.0009 0.0009 10 0.0006 0.0006 0.0000 0.0224 0.0410 0.0405 0.0000 0.0061 0.0006 0.0006 0.0006 0.0006 11 0.0004 0.0004 0.0000 0.0225 -0.3796 -0.3761 0.0017 -0.0571 0.0004 0.0004 0.0004 0.0004 12 0.0003 0.0003 0.0000 0.0227 0.0605 0.0599 0.0000 0.0091 0.0003 0.0003 0.0003 0.0003 13 0.0002 0.0002 0.0000 0.0227 -0.0865 -0.0855 0.0001 -0.0130 0.0002 0.0002 0.0002 0.0002 14 0.0001 0.0001 0.0000 0.0228 0.2201 0.2178 0.0006 0.0333 0.0001 0.0001 0.0001 0.0001 15 0.0001 0.0001 0.0000 0.0228 0.0559 0.0553 0.0000 0.0085 0.0001 0.0001 0.0001 0.0001 16 0.0001 0.0001 0.0000 0.0229 0.1909 0.1889 0.0004 0.0289 0.0001 0.0001 0.0001 0.0001 17 0.0000 0.0000 0.0000 0.0229 0.1571 0.1554 0.0003 0.0238 0.0000 0.0000 0.0000 0.0001 18 0.0000 0.0000 0.0000 0.0229 0.2244 0.2221 0.0006 0.0340 0.0000 0.0000 0.0000 0.0000 19 0.0000 0.0000 0.0000 0.0229 0.2026 0.2005 0.0005 0.0307 0.0000 0.0000 0.0000 0.0000 20 0.0000 0.0000 0.0000 0.0229 0.2178 0.2155 0.0006 0.0330 0.0000 0.0000 0.0000 0.0000 21 0.0000 0.0000 0.0000 0.0229 0.2467 0.2441 0.0007 0.0374 0.0000 0.0000 0.0000 0.0000 22 0.0000 0.0000 0.0000 0.0229 0.2336 0.2312 0.0006 0.0354 0.0000 0.0000 0.0000 0.0000 23 0.0000 0.0000 0.0000 0.0229 0.2414 0.2389 0.0007 0.0366 0.0000 0.0000 0.0000 0.0000 24 0.0000 0.0000 0.0000 0.0229 0.2377 0.2353 0.0007 0.0360 0.0000 0.0000 0.0000 0.0000 25 0.0000 0.0000 0.0000 0.0229 0.2418 0.2393 0.0007 0.0367 0.0000 0.0000 0.0000 0.0000 26 0.0000 0.0000 0.0000 0.0229 0.2398 0.2373 0.0007 0.0363 0.0000 0.0000 0.0000 0.0000 27 0.0000 0.0000 0.0000 0.0229 0.2416 0.2392 0.0007 0.0366 0.0000 0.0000 0.0000 0.0000 28 0.0000 0.0000 0.0000 0.0229 0.2458 0.2433 0.0007 0.0373 0.0000 0.0000 0.0000 0.0000 29 0.0000 0.0000 0.0000 0.0229 0.2447 0.2422 0.0007 0.0371 0.0000 0.0000 0.0000 0.0000 30 0.0000 0.0000 0.0000 0.0229 0.2439 0.2413 0.0007 0.0370 0.0000 0.0000 0.0000 0.0000 31 0.0000 0.0000 0.0000 0.0229 0.2433 0.2408 0.0007 0.0369 0.0000 0.0000 0.0000 0.0000 32 0.0000 0.0000 0.0000 0.0229 0.2426 0.2401 0.0007 0.0368 0.0000 0.0000 0.0000 0.0000 33 0.0000 0.0000 0.0000 0.0229 0.2394 0.2369 0.0007 0.0363 0.0000 0.0000 0.0000 0.0000 34 0.0000 0.0000 0.0000 0.0229 0.2400 0.2375 0.0007 0.0364 0.0000 0.0000 0.0000 0.0000 35 0.0000 0.0000 0.0000 0.0229 0.2404 0.2379 0.0007 0.0364 0.0000 0.0000 0.0000 0.0000 36 0.0000 0.0000 0.0000 0.0229 0.2404 0.2380 0.0007 0.0364 0.0000 0.0000 0.0000 0.0000 37 0.0000 0.0000 0.0000 0.0229 0.2408 0.2383 0.0007 0.0365 0.0000 0.0000 0.0000 0.0000 38 0.0000 0.0000 0.0000 0.0229 0.2407 0.2382 0.0007 0.0365 0.0000 0.0000 0.0000 0.0000 39 0.0000 0.0000 0.0000 0.0229 0.2409 0.2384 0.0007 0.0365 0.0000 0.0000 0.0000 0.0000 40 0.0000 0.0000 0.0000 0.0229 0.2409 0.2384 0.0007 0.0365 0.0000 0.0000 0.0000 0.0000 41 0.0000 0.0000 0.0000 0.0229 0.2408 0.2384 0.0007 0.0365 0.0000 0.0000 0.0000 0.0000 42 0.0000 0.0000 0.0000 0.0229 0.2408 0.2383 0.0007 0.0365 0.0000 0.0000 0.0000 0.0000 43 0.0000 0.0000 0.0000 0.0229 0.2409 0.2384 0.0007 0.0365 0.0000 0.0000 0.0000 0.0000 44 0.0000 0.0000 0.0000 0.0229 0.2409 0.2384 0.0007 0.0365 0.0000 0.0000 0.0000 0.0000 45 0.0000 0.0000 0.0000 0.0229 0.2410 0.2385 0.0007 0.0365 0.0000 0.0000 0.0000 0.0000 46 0.0000 0.0000 0.0000 0.0229 0.2409 0.2384 0.0007 0.0365 0.0000 0.0000 0.0000 0.0000 47 0.0000 0.0000 0.0000 0.0229 0.2409 0.2384 0.0007 0.0365 0.0000 0.0000 0.0000 0.0000 48 0.0000 0.0000 0.0000 0.0229 0.2410 0.2385 0.0007 0.0365 0.0000 0.0000 0.0000 0.0000 1 Observed-O and Predicted-P vs. Independent Variable : : 0.060 -: : 2 : : : : : 2 : : : 0.048 -: : : 2 : : : : R : e : 2 s : p 0.036 -: o : n : s : e : : V : a : r : i : a 0.024 -: b : l : e : : : : : : : 0.012 -: : : : : : : : 2 : 2 : 42 0.000 -:M2 :................................................................ : : : : : : : 0.00 0.01 0.02 0.03 0.04 0.05 0.06 Independent Variable 1 Standardized Residuals vs Independent Variable : : 4. -: : * : : : : : : : : 2. -: : : : : : : : * : :M * 0. -:3* * R : e :* s : i : * d : * u : a : l : s : -2. -: : : : : : * * : : : : -4. -: : * : : : : : : : : -6. -: :................................................................ : : : : : : : 0.00 0.01 0.02 0.03 0.04 0.05 0.06 Independent Variable 1 Probability plot for half-normal distribution 5 +:::::::::::::::::::::::::::::::::::::::::::::::::::::::::. . . . . . . . . 4 + . . * . . . . . . . 3 + . . . . . . . . . 2 + . . . . . . . O . . b 1 + . s . . e . * . r . . v . ********************* ** ** * * * * . a 0 +---***---------------------------------------------------. t . . i . * . o . . n . * . s -1 + * . . . . . . . . . -2 + . . . . . . . . . -3 +* . . . . . . . . . -4 + . * . . . . . . . -5 ++:+:::+:::::::+::::::::::+::::::::::+::::::+:::::::::::::+ .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: 1.00000 Probability: 0.00000 ( a perfect fit will have a correlation coefficient = 1.0 ) ( small probability [=0.0] indicates significant correlation ) Fisher's z-coefficient: 7.85962 ================================================== ***** 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 = 0.612 ( Perfect Normality : W=1.0 ) P-value Test of Normality = 0.0000000E+00 ------------------------------------------- *** Residual Statistics: Mean(Average) = -6.5119849E-07 Average Deviation = 2.4359003E-06 Standard Deviation = 5.2913529E-06 Variance = 2.7998416E-11 Skewness = 0.2438821 Kurtosis = 7.688009 **** End of prediction analysis for data-column: 2 ================================================================ ================================================================ **** Start of prediction analysis for data-column: 3 ( ES ) R-squared Adjusted Est. Std. Dev. Coefficient of (percent) R-squared of Model Error Mean Var. (percent) 100.000 100.000 1.663E-12 4.426E-10 0.3756 * * * Analysis of Variance * * * Sum of Mean Prob. of Source DF Squares Square Overall F Larger F Regression 1 2.489E-17 2.489E-17 ********* 0.0000 Residual 42 1.161E-22 2.764E-24 Corrected Total 43 2.489E-17 * * * Inference on Coefficients * * * Standard Prob. of Variance Coef. Estimate Error t-statistic Larger |t| Inflation 1 0.0000 2.909E-13 -0.7 0.5052 1.347 2 0.9997 3.332E-04 3000.4 0.0000 1.000 * * * Variance-Covariance Matrix for the Coefficient Estimates * * * 1 2 1 8.46079E-26 -4.91731E-17 2 1.11018E-07 * * * 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 X 1 0.0000 0.0000 0.0000 0.1892 1.1759 1.1814 0.1614 0.5707 0.0000 0.0000 0.0000 0.0000 XY 2 0.0000 0.0000 0.0000 0.1740 -1.9394 -2.0082 0.3962 -0.9217 0.0000 0.0000 0.0000 0.0000 X 3 0.0000 0.0000 0.0000 0.1510 0.2738 0.2708 0.0067 0.1142 0.0000 0.0000 0.0000 0.0000 X 4 0.0000 0.0000 0.0000 0.1276 1.0485 1.0498 0.0804 0.4015 0.0000 0.0000 0.0000 0.0000 X 5 0.0000 0.0000 0.0000 0.1048 -1.0287 -1.0294 0.0619 -0.3522 0.0000 0.0000 0.0000 0.0000 Y 6 0.0000 0.0000 0.0000 0.0827 3.8195 4.6712 0.6573 1.4022 0.0000 0.0000 0.0000 0.0000 7 0.0000 0.0000 0.0000 0.0637 -1.3103 -1.3219 0.0584 -0.3447 0.0000 0.0000 0.0000 0.0000 8 0.0000 0.0000 0.0000 0.0475 0.8960 0.8939 0.0200 0.1997 0.0000 0.0000 0.0000 0.0000 Y 9 0.0000 0.0000 0.0000 0.0360 -4.1181 -5.2693 0.3164 -1.0179 0.0000 0.0000 0.0000 0.0000 10 0.0000 0.0000 0.0000 0.0282 0.8297 0.8265 0.0100 0.1408 0.0000 0.0000 0.0000 0.0000 11 0.0000 0.0000 0.0000 0.0242 -1.1524 -1.1570 0.0165 -0.1823 0.0000 0.0000 0.0000 0.0000 12 0.0000 0.0000 0.0000 0.0228 0.2519 0.2491 0.0007 0.0380 0.0000 0.0000 0.0000 0.0000 13 0.0000 0.0000 0.0000 0.0230 -0.9901 -0.9899 0.0115 -0.1519 0.0000 0.0000 0.0000 0.0000 14 0.0000 0.0000 0.0000 0.0241 -0.0186 -0.0184 0.0000 -0.0029 0.0000 0.0000 0.0000 0.0000 15 0.0000 0.0000 0.0000 0.0254 -0.5512 -0.5466 0.0040 -0.0882 0.0000 0.0000 0.0000 0.0000 16 0.0000 0.0000 0.0000 0.0266 0.1056 0.1043 0.0002 0.0172 0.0000 0.0000 0.0000 0.0000 17 0.0000 0.0000 0.0000 0.0276 -0.2359 -0.2333 0.0008 -0.0393 0.0000 0.0000 0.0000 0.0000 18 0.0000 0.0000 0.0000 0.0285 0.1112 0.1099 0.0002 0.0188 0.0000 0.0000 0.0000 0.0000 19 0.0000 0.0000 0.0000 0.0291 -0.0482 -0.0476 0.0000 -0.0082 0.0000 0.0000 0.0000 0.0000 20 0.0000 0.0000 0.0000 0.0295 0.0796 0.0787 0.0001 0.0137 0.0000 0.0000 0.0000 0.0000 21 0.0000 0.0000 0.0000 0.0306 0.1202 0.1188 0.0002 0.0211 0.0000 0.0000 0.0000 0.0000 22 0.0000 0.0000 0.0000 0.0306 0.1200 0.1186 0.0002 0.0211 0.0000 0.0000 0.0000 0.0000 23 0.0000 0.0000 0.0000 0.0306 0.1189 0.1175 0.0002 0.0209 0.0000 0.0000 0.0000 0.0000 24 0.0000 0.0000 0.0000 0.0306 0.1191 0.1177 0.0002 0.0209 0.0000 0.0000 0.0000 0.0000 25 0.0000 0.0000 0.0000 0.0306 0.1192 0.1178 0.0002 0.0209 0.0000 0.0000 0.0000 0.0000 26 0.0000 0.0000 0.0000 0.0306 0.1193 0.1179 0.0002 0.0209 0.0000 0.0000 0.0000 0.0000 27 0.0000 0.0000 0.0000 0.0306 0.1194 0.1179 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 28 0.0000 0.0000 0.0000 0.0306 0.1194 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 29 0.0000 0.0000 0.0000 0.0306 0.1194 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 30 0.0000 0.0000 0.0000 0.0306 0.1194 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 31 0.0000 0.0000 0.0000 0.0306 0.1195 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 32 0.0000 0.0000 0.0000 0.0306 0.1195 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 33 0.0000 0.0000 0.0000 0.0306 0.1194 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 34 0.0000 0.0000 0.0000 0.0306 0.1194 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 35 0.0000 0.0000 0.0000 0.0306 0.1195 0.1181 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 36 0.0000 0.0000 0.0000 0.0306 0.1194 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 37 0.0000 0.0000 0.0000 0.0306 0.1194 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 38 0.0000 0.0000 0.0000 0.0306 0.1195 0.1181 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 39 0.0000 0.0000 0.0000 0.0306 0.1194 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 40 0.0000 0.0000 0.0000 0.0306 0.1194 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 41 0.0000 0.0000 0.0000 0.0306 0.1194 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 42 0.0000 0.0000 0.0000 0.0306 0.1194 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 43 0.0000 0.0000 0.0000 0.0306 0.1194 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 44 0.0000 0.0000 0.0000 0.0306 0.1194 0.1180 0.0002 0.0210 0.0000 0.0000 0.0000 0.0000 1 Observed-O and Predicted-P vs. Independent Variable Times 10** -9 : : 2.5 -: 2 : : 2 : : : 2 : : : : 2 2.0 -: : : : 2 : : : R : 2 e : s : p 1.5 -: o : 2 n : s : e : : 2 V : a : r : i : a 1.0 -: 2 b : l : e : : 2 : : : 2 : : 0.5 -: 2 : : : 2 : : 2 : 2 : 2 : 2 : 42 0.0 -:M :................................................................ : : : : : : : 0.0 0.4 0.8 1.2 1.6 2.0 2.4 Independent Variable Times 10** -9 1 Standardized Residuals vs Independent Variable : : 4. -: : * : : : : : : : : 2. -: : : : : * : * : * * : : :M ** * * 0. -: 2 * R : * e : s : * i : d : * * u : * a : * l : s : -2. -: * : : : : : : : : : -4. -: : * : : : : : : : : -6. -: :................................................................ : : : : : : : 0.0 0.4 0.8 1.2 1.6 2.0 2.4 Independent Variable Times 10** -9 1 Probability plot for half-normal distribution 5 +:::::::::::::::::::::::::::::::::::::::::::::::::::::::::. . . . . . . . . 4 + . . * . . . . . . . 3 + . . . . . . . . . 2 + . . . . . . . O . * . b 1 + * . s . * * . e . . r . . v . ******************** ** ** * . a 0 +----***--------------------------------------------------. t . * . i . . o . * . n . . s -1 + * . . * . .* . . . . . -2 +* . . . . . . . . . -3 + . . . . . . . . . -4 + . * . . . . . . . -5 ++:+:::+:::::::+::::::::::+::::::::::+::::::+:::::::::::::+ .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: 0.999596 Probability: 0.00000 ( a perfect fit will have a correlation coefficient = 1.0 ) ( small probability [=0.0] indicates significant correlation ) Fisher's z-coefficient: 4.25293 ================================================== ***** 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 = 0.682 ( Perfect Normality : W=1.0 ) P-value Test of Normality = 0.0000000E+00 ------------------------------------------- *** Residual Statistics: Mean(Average) = -3.2007695E-13 Average Deviation = 8.8754329E-13 Standard Deviation = 1.6570972E-12 Variance = 2.7459710E-24 Skewness = -1.024678 Kurtosis = 9.670897 **** End of prediction analysis for data-column: 3 ================================================================ ================================================================ **** Start of prediction analysis for data-column: 4 ( EIS ) R-squared Adjusted Est. Std. Dev. Coefficient of (percent) R-squared of Model Error Mean Var. (percent) 100.000 100.000 9.729E-17 2.730E-14 0.3564 * * * Analysis of Variance * * * Sum of Mean Prob. of Source DF Squares Square Overall F Larger F Regression 1 7.177E-26 7.177E-26 ********* 0.0000 Residual 30 2.840E-31 9.465E-33 Corrected Total 31 7.177E-26 * * * Inference on Coefficients * * * Standard Prob. of Variance Coef. Estimate Error t-statistic Larger |t| Inflation 1 0. 1.985E-17 -0.1 0.8886 1.332 2 1. 3.633E-04 2753.6 0.0000 1.000 * * * Variance-Covariance Matrix for the Coefficient Estimates * * * 1 2 1 3.94100E-34 -3.60163E-21 2 1.31956E-07 * * * 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 X 1 0.0000 0.0000 0.0000 0.2022 -0.7873 -0.7822 0.0785 -0.3938 0.0000 0.0000 0.0000 0.0000 XY 2 0.0000 0.0000 0.0000 0.1859 3.9961 5.7450 1.8231 2.7452 0.0000 0.0000 0.0000 0.0000 X 3 0.0000 0.0000 0.0000 0.1615 0.2076 0.2043 0.0042 0.0897 0.0000 0.0000 0.0000 0.0000 XY 4 0.0000 0.0000 0.0000 0.1369 -4.0228 -5.8280 1.2831 -2.3208 0.0000 0.0000 0.0000 0.0000 5 0.0000 0.0000 0.0000 0.1131 0.7976 0.7927 0.0405 0.2830 0.0000 0.0000 0.0000 0.0000 6 0.0000 0.0000 0.0000 0.0902 0.3177 0.3129 0.0050 0.0986 0.0000 0.0000 0.0000 0.0000 7 0.0000 0.0000 0.0000 0.0709 -1.3612 -1.3816 0.0707 -0.3816 0.0000 0.0000 0.0000 0.0000 8 0.0000 0.0000 0.0000 0.0546 0.3299 0.3249 0.0031 0.0781 0.0000 0.0000 0.0000 0.0000 9 0.0000 0.0000 0.0000 0.0407 -0.0197 -0.0194 0.0000 -0.0040 0.0000 0.0000 0.0000 0.0000 10 0.0000 0.0000 0.0000 0.0408 -0.0189 -0.0186 0.0000 -0.0038 0.0000 0.0000 0.0000 0.0000 11 0.0000 0.0000 0.0000 0.0409 -0.0156 -0.0153 0.0000 -0.0032 0.0000 0.0000 0.0000 0.0000 12 0.0000 0.0000 0.0000 0.0409 0.0265 0.0261 0.0000 0.0054 0.0000 0.0000 0.0000 0.0000 13 0.0000 0.0000 0.0000 0.0410 0.0201 0.0197 0.0000 0.0041 0.0000 0.0000 0.0000 0.0000 14 0.0000 0.0000 0.0000 0.0410 0.0304 0.0299 0.0000 0.0062 0.0000 0.0000 0.0000 0.0000 15 0.0000 0.0000 0.0000 0.0410 0.0315 0.0309 0.0000 0.0064 0.0000 0.0000 0.0000 0.0000 16 0.0000 0.0000 0.0000 0.0411 0.0286 0.0282 0.0000 0.0058 0.0000 0.0000 0.0000 0.0000 17 0.0000 0.0000 0.0000 0.0411 0.0325 0.0320 0.0000 0.0066 0.0000 0.0000 0.0000 0.0000 18 0.0000 0.0000 0.0000 0.0411 0.0316 0.0310 0.0000 0.0064 0.0000 0.0000 0.0000 0.0000 19 0.0000 0.0000 0.0000 0.0411 0.0353 0.0347 0.0000 0.0072 0.0000 0.0000 0.0000 0.0000 20 0.0000 0.0000 0.0000 0.0411 0.0273 0.0269 0.0000 0.0056 0.0000 0.0000 0.0000 0.0000 21 0.0000 0.0000 0.0000 0.0411 0.0276 0.0271 0.0000 0.0056 0.0000 0.0000 0.0000 0.0000 22 0.0000 0.0000 0.0000 0.0411 0.0295 0.0290 0.0000 0.0060 0.0000 0.0000 0.0000 0.0000 23 0.0000 0.0000 0.0000 0.0411 0.0335 0.0330 0.0000 0.0068 0.0000 0.0000 0.0000 0.0000 24 0.0000 0.0000 0.0000 0.0411 0.0330 0.0324 0.0000 0.0067 0.0000 0.0000 0.0000 0.0000 25 0.0000 0.0000 0.0000 0.0411 0.0293 0.0288 0.0000 0.0060 0.0000 0.0000 0.0000 0.0000 26 0.0000 0.0000 0.0000 0.0411 0.0340 0.0334 0.0000 0.0069 0.0000 0.0000 0.0000 0.0000 27 0.0000 0.0000 0.0000 0.0411 0.0363 0.0356 0.0000 0.0074 0.0000 0.0000 0.0000 0.0000 28 0.0000 0.0000 0.0000 0.0411 0.0282 0.0278 0.0000 0.0057 0.0000 0.0000 0.0000 0.0000 29 0.0000 0.0000 0.0000 0.0411 0.0300 0.0294 0.0000 0.0061 0.0000 0.0000 0.0000 0.0000 30 0.0000 0.0000 0.0000 0.0411 0.0337 0.0331 0.0000 0.0068 0.0000 0.0000 0.0000 0.0000 31 0.0000 0.0000 0.0000 0.0411 0.0337 0.0331 0.0000 0.0069 0.0000 0.0000 0.0000 0.0000 32 0.0000 0.0000 0.0000 0.0411 0.0337 0.0331 0.0000 0.0069 0.0000 0.0000 0.0000 0.0000 1 Observed-O and Predicted-P vs. Independent Variable Times 10**-13 : : 1.5 -: : : : : 2 : : 2 : : : 2 1.2 -: : : 2 : : : 2 : R : e : s : 2 p 0.9 -: o : n : s : 2 e : : V : a : 2 r : i : a 0.6 -: b : l : e : : : : : : : 0.3 -: : : : : : : : : : 0.0 -:M2 :................................................................ : : : : : : : 0.00 0.25 0.50 0.75 1.00 1.25 1.50 Independent Variable Times 10**-13 1 Standardized Residuals vs Independent Variable : : 6. -: : : : : : : : : : 4. -: * : : : : : : : : : 2. -: R : e : s : i : d : u : * a : l : * * s : * 0. -:M* : : : : * : : : * : : -2. -: : : : : : : : : : -4. -: * :................................................................ : : : : : : : 0.00 0.25 0.50 0.75 1.00 1.25 1.50 Independent Variable Times 10**-13 1 Probability plot for half-normal distribution 5 +:::::::::::::::::::::::::::::::::::::::::::::::::::::::::. . . . . . . . . 4 + * . . . . . . . . . 3 + . . . . . . . . . 2 + . . . . . . . O . . b 1 + . s . * . e . . r . * * . v . * . a 0 +--*************-****-**-**-*-*---------------------------. t . . i . . o . . n . * . s -1 + . . . .* . . . . . -2 + . . . . . . . . . -3 + . . . . . . . . . -4 + . . . . . . . . . -5 ++:+:::+:::::::+::::::::::+::::::::::+::::::+:::::::::::::+ .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: 0.717516E-05 Probability: 1.00000 ( a perfect fit will have a correlation coefficient = 1.0 ) ( small probability [=0.0] indicates significant correlation ) Fisher's z-coefficient: 0.717516E-05 ================================================== ***** 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 = 0.567 ( Perfect Normality : W=1.0 ) P-value Test of Normality = 0.0000000E+00 ------------------------------------------- *** Residual Statistics: Mean(Average) = 4.7855393E-18 Average Deviation = 3.8134664E-17 Standard Deviation = 9.6641648E-17 Variance = 9.3396082E-33 Skewness = 0.0000000E+00 Kurtosis = -3.000000 **** End of prediction analysis for data-column: 4 ================================================================ ******************************************************************** >>>>>>>>>>>>>>>>>>>> END OF PREDICTION ANALYSIS <<<<<<<<<<<<<<<<<<<< ********************************************************************