ANOVA summary of the impact of the significance levels on the time p=0.050 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 3.7701 1.2567 67.163 < 2.2e-16 *** Residuals 196 3.6674 0.0187 --- 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 0.0041 - - 0.05 9.2e-05 0.1176 - 0.1 2.9e-10 9.5e-11 4.8e-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 0.00829 - - 0.05 0.00024 0.11561 - 0.1 4.7e-09 4.7e-09 4.7e-09 P value adjustment method: holm p=0.075 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.09989 0.03330 16.836 9.029e-10 *** Residuals 196 0.38762 0.00198 --- 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 2.0e-05 - - 0.05 6.4e-14 0.00018 - 0.1 0.26418 0.00018 1.3e-08 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 4.1e-05 - - 0.05 1.0e-08 0.00023 - 0.1 0.56899 0.00023 3.4e-07 P value adjustment method: holm p=0.100 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.117322 0.039107 31.050 < 2.2e-16 *** Residuals 196 0.246864 0.001260 --- 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 6.9e-07 - - 0.05 < 2e-16 1.1e-09 - 0.1 2.1e-12 7.4e-07 0.36 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 5.4e-06 - - 0.05 4.7e-09 1.4e-07 - 0.1 4.4e-08 2.3e-06 0.37 P value adjustment method: holm p=0.125 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.212736 0.070912 53.468 < 2.2e-16 *** Residuals 196 0.259943 0.001326 --- 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 1.7e-06 - - 0.05 < 2e-16 3.0e-12 - 0.1 < 2e-16 8.0e-13 0.029 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 5.7e-06 - - 0.05 6.7e-09 1.6e-08 - 0.1 4.7e-09 8.7e-09 0.029 P value adjustment method: holm p=0.150 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.240824 0.080275 64.925 < 2.2e-16 *** Residuals 196 0.242340 0.001236 --- 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 2.6e-07 - - 0.05 < 2e-16 1.3e-11 - 0.1 < 2e-16 < 2e-16 2.6e-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 4.5e-06 - - 0.05 4.7e-09 3.5e-08 - 0.1 4.7e-09 4.7e-09 4.5e-06 P value adjustment method: holm p=0.175 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.252978 0.084326 81.774 < 2.2e-16 *** Residuals 196 0.202116 0.001031 --- 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 7.9e-12 - - 0.05 < 2e-16 1.8e-10 - 0.1 < 2e-16 < 2e-16 2.7e-08 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 2.9e-08 - - 0.05 4.7e-09 9.3e-08 - 0.1 4.7e-09 4.7e-09 4.9e-07 P value adjustment method: holm p=0.200 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.279358 0.093119 104.59 < 2.2e-16 *** Residuals 196 0.174504 0.000890 --- 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-08 - - 0.05 < 2e-16 4.9e-16 - 0.1 < 2e-16 < 2e-16 5.3e-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 9.9e-07 - - 0.05 4.7e-09 4.7e-09 - 0.1 4.7e-09 4.7e-09 5.4e-08 P value adjustment method: holm p=0.300 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.222467 0.074156 105.41 < 2.2e-16 *** Residuals 196 0.137881 0.000703 --- 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 2.6e-15 - - 0.05 < 2e-16 < 2e-16 - 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=0.400 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 0.167563 0.055854 93.53 < 2.2e-16 *** Residuals 196 0.117047 0.000597 --- 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-14 - - 0.05 < 2e-16 < 2e-16 - 0.1 < 2e-16 < 2e-16 1.1e-15 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