ANOVA summary of the impact of the significance levels on the time p=0.050-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 11.4602 3.8201 62.374 < 2.2e-16 *** Residuals 196 12.0040 0.0612 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 9.1e-06 - - 0.05 0.052 0.052 - 0.1 1.2e-10 5.0e-11 3.7e-11 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.7e-05 - - 0.05 0.078 0.078 - 0.1 4.7e-09 4.7e-09 4.7e-09 P value adjustment method: holm p=0.050-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 1.0779 0.3593 12.307 2.067e-07 *** Residuals 196 5.7219 0.0292 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.00080 - - 0.05 1.5e-05 0.28199 - 0.1 0.00410 0.00080 0.00018 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.0013 - - 0.05 8.7e-05 0.1134 - 0.1 0.0759 0.0013 3.8e-05 P value adjustment method: holm p=0.050-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.5478 0.1826 2.1517 0.09505 . Residuals 196 16.6343 0.0849 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.12 - - 0.05 0.09 0.45 - 0.1 0.45 0.45 0.25 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.0600 - - 0.05 4.9e-05 0.0009 - 0.1 0.0066 0.0600 0.9154 P value adjustment method: holm p=0.075-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.12659 0.04220 9.4776 7.081e-06 *** Residuals 196 0.87261 0.00445 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 9.9e-05 - - 0.05 5.0e-10 7.9e-05 - 0.1 0.15448 0.01018 0.00017 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.00022 - - 0.05 1.5e-07 0.00019 - 0.1 0.33438 0.00289 5.4e-06 P value adjustment method: holm p=0.075-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.16034 0.05345 6.0109 0.0006148 *** Residuals 196 1.74281 0.00889 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.0017 - - 0.05 1.5e-10 1.0e-06 - 0.1 0.9221 0.3256 0.0017 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.00226 - - 0.05 2.2e-07 1.6e-05 - 0.1 0.33492 0.95381 0.00029 P value adjustment method: holm p=0.075-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.16810 0.05603 11.350 6.755e-07 *** Residuals 196 0.96766 0.00494 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.0011 - - 0.05 2.8e-06 0.0348 - 0.1 9.6e-12 9.5e-06 0.0348 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.0020 - - 0.05 4.9e-06 0.0028 - 0.1 4.3e-07 4.9e-06 0.0028 P value adjustment method: holm p=0.100-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.067121 0.022374 15.418 4.808e-09 *** Residuals 196 0.284431 0.001451 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 3.3e-08 - - 0.05 4.3e-13 2.1e-05 - 0.1 3.7e-07 0.478 0.063 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 6.8e-07 - - 0.05 7.6e-09 3.5e-05 - 0.1 1.2e-05 0.159 0.085 P value adjustment method: holm p=0.100-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.09373 0.03124 8.1875 3.67e-05 *** Residuals 196 0.74795 0.00382 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.0013 - - 0.05 2.8e-07 0.0362 - 0.1 0.0009 0.2377 0.5350 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.00037 - - 0.05 3.4e-06 0.03157 - 0.1 0.00014 0.03157 0.92310 P value adjustment method: holm p=0.100-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.16556 0.05519 24.465 1.722e-13 *** Residuals 196 0.44212 0.00226 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.00089 - - 0.05 1.4e-11 3.9e-05 - 0.1 3.1e-12 2.5e-09 0.00089 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.00079 - - 0.05 7.8e-08 3.7e-05 - 0.1 8.6e-08 4.2e-07 0.00079 P value adjustment method: holm p=0.125-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.089166 0.029722 24.839 1.152e-13 *** Residuals 196 0.234530 0.001197 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 7.1e-06 - - 0.05 3.3e-14 2.3e-05 - 0.1 6.8e-15 1.1e-09 0.023 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 2.0e-05 - - 0.05 8.5e-09 1.8e-05 - 0.1 6.7e-09 1.9e-07 0.019 P value adjustment method: holm p=0.125-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.15427 0.05142 30.740 2.484e-16 *** Residuals 196 0.32789 0.00167 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 5.9e-08 - - 0.05 1.5e-15 6.7e-06 - 0.1 1.1e-12 2.2e-05 0.021 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.3e-06 - - 0.05 6.0e-09 2.3e-05 - 0.1 6.5e-08 1.3e-06 5.9e-05 P value adjustment method: holm p=0.125-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.14719 0.04906 27.150 9.952e-15 *** Residuals 196 0.35420 0.00181 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.09 - - 0.05 5.7e-08 2.0e-06 - 0.1 1.1e-13 3.2e-13 8.1e-07 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.049 - - 0.05 1.2e-06 4.2e-06 - 0.1 8.3e-08 8.3e-08 9.1e-06 P value adjustment method: holm p=0.150-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.166667 0.055556 58.178 < 2.2e-16 *** Residuals 196 0.187165 0.000955 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 8.3e-09 - - 0.05 < 2e-16 8.3e-09 - 0.1 < 2e-16 6.7e-15 1.3e-06 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 2.8e-07 - - 0.05 4.7e-09 2.8e-07 - 0.1 4.7e-09 4.7e-09 5.7e-06 P value adjustment method: holm p=0.150-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.216489 0.072163 58.94 < 2.2e-16 *** Residuals 196 0.239972 0.001224 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 4.9e-05 - - 0.05 < 2e-16 3.1e-10 - 0.1 < 2e-16 2.2e-15 5.1e-05 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 6.9e-05 - - 0.05 4.7e-09 4.9e-08 - 0.1 4.7e-09 1.2e-08 6.9e-05 P value adjustment method: holm p=0.150-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.184805 0.061602 40.974 < 2.2e-16 *** Residuals 196 0.294676 0.001503 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 7.0e-06 - - 0.05 1.3e-13 2.9e-07 - 0.1 < 2e-16 < 2e-16 1.8e-09 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.5e-05 - - 0.05 6.0e-09 6.0e-06 - 0.1 6.0e-09 6.0e-09 2.5e-07 P value adjustment method: holm p=0.175-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.216590 0.072197 70.769 < 2.2e-16 *** Residuals 196 0.199955 0.001020 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 5.6e-11 - - 0.05 < 2e-16 2.7e-12 - 0.1 < 2e-16 < 2e-16 1.1e-10 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 3.1e-08 - - 0.05 4.7e-09 3.1e-08 - 0.1 4.7e-09 4.7e-09 3.1e-08 P value adjustment method: holm p=0.175-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.161480 0.053827 53.137 < 2.2e-16 *** Residuals 196 0.198544 0.001013 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 2.5e-06 - - 0.05 2.3e-16 4.4e-10 - 0.1 < 2e-16 < 2e-16 2.4e-07 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 4.3e-06 - - 0.05 4.7e-09 2.0e-07 - 0.1 4.7e-09 9.7e-09 4.3e-06 P value adjustment method: holm p=0.175-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.173574 0.057858 61.227 < 2.2e-16 *** Residuals 196 0.185215 0.000945 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 3.6e-07 - - 0.05 3.2e-15 1.0e-10 - 0.1 < 2e-16 < 2e-16 3.3e-06 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 2.8e-06 - - 0.05 6.8e-09 6.5e-08 - 0.1 4.7e-09 6.0e-09 3.1e-06 P value adjustment method: holm p=0.200-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.184322 0.061441 75.08 < 2.2e-16 *** Residuals 196 0.160393 0.000818 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 2.4e-07 - - 0.05 < 2e-16 2.3e-12 - 0.1 < 2e-16 < 2e-16 2.7e-10 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 2.8e-06 - - 0.05 4.7e-09 1.1e-08 - 0.1 4.7e-09 4.7e-09 3.3e-08 P value adjustment method: holm p=0.200-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.175193 0.058398 55.067 < 2.2e-16 *** Residuals 196 0.207853 0.001060 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 4.4e-09 - - 0.05 < 2e-16 3.6e-10 - 0.1 < 2e-16 < 2e-16 2.7e-06 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 4.3e-07 - - 0.05 4.7e-09 2.4e-07 - 0.1 4.7e-09 4.7e-09 1.0e-05 P value adjustment method: holm p=0.200-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.152174 0.050725 51.337 < 2.2e-16 *** Residuals 196 0.193660 0.000988 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 7.6e-09 - - 0.05 < 2e-16 8.1e-05 - 0.1 < 2e-16 < 2e-16 2.1e-10 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 3.0e-07 - - 0.05 8.7e-09 6.2e-05 - 0.1 4.7e-09 4.7e-09 5.2e-08 P value adjustment method: holm p=0.300-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.172996 0.057665 76.79 < 2.2e-16 *** Residuals 196 0.147186 0.000751 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.1e-12 - - 0.05 < 2e-16 3.6e-15 - 0.1 < 2e-16 < 2e-16 < 2e-16 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 4.7e-09 - - 0.05 4.7e-09 4.7e-09 - 0.1 4.7e-09 4.7e-09 4.7e-09 P value adjustment method: holm p=0.300-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.128275 0.042758 67.19 < 2.2e-16 *** Residuals 196 0.124731 0.000636 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.3e-08 - - 0.05 < 2e-16 3.7e-12 - 0.1 < 2e-16 < 2e-16 4.6e-10 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 3.1e-07 - - 0.05 4.7e-09 1.7e-08 - 0.1 4.7e-09 4.7e-09 1.2e-07 P value adjustment method: holm p=0.300-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.116045 0.038682 49.964 < 2.2e-16 *** Residuals 196 0.151740 0.000774 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 2.1e-06 - - 0.05 < 2e-16 6.3e-11 - 0.1 < 2e-16 < 2e-16 2.1e-09 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$alpha 0.01 0.02 0.05 0.02 2.8e-06 - - 0.05 4.7e-09 3.7e-08 - 0.1 4.7e-09 4.7e-09 7.1e-08 P value adjustment method: holm