ANOVA summary on the impact of the instance size and the distribution of the nodes on the cost p=0.050-00 Df Sum Sq Mean Sq F value Pr(>F) size 2 10.02 5.01 2.9666 0.05302 . dis 1 4.93 4.93 2.9219 0.08844 . size:dis 2 11.84 5.92 3.5076 0.03123 * Residuals 294 496.26 1.69 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.64 - 1000 0.24 0.24 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.093 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.707 - 1000 0.068 0.068 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.0051 P value adjustment method: holm p=0.050-83 Df Sum Sq Mean Sq F value Pr(>F) size 2 732 366 0.9621 0.3833 dis 1 916 916 2.4062 0.1219 size:dis 2 379 190 0.4984 0.6080 Residuals 294 111912 381 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.7 - 1000 0.7 0.7 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.12 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.33 - 1000 0.33 0.40 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.4 P value adjustment method: holm p=0.100-00 Df Sum Sq Mean Sq F value Pr(>F) size 2 23.81 11.90 4.3587 0.01363 * dis 1 3.07 3.07 1.1240 0.28992 size:dis 2 17.12 8.56 3.1337 0.04501 * Residuals 294 802.89 2.73 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.150 - 1000 0.015 0.188 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.3 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.118 - 1000 0.019 0.607 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.49 P value adjustment method: holm p=0.100-83 Df Sum Sq Mean Sq F value Pr(>F) size 2 912 456 1.8788 0.15460 dis 1 182 182 0.7495 0.38735 size:dis 2 1192 596 2.4550 0.08762 . Residuals 294 71361 243 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.31 - 1000 0.63 0.31 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.39 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.34 - 1000 0.65 0.19 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.4 P value adjustment method: holm p=0.150-00 Df Sum Sq Mean Sq F value Pr(>F) size 2 9.25 4.63 1.2017 0.3022 dis 1 0.02 0.02 0.0062 0.9374 size:dis 2 7.46 3.73 0.9688 0.3807 Residuals 294 1131.72 3.85 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.33 - 1000 0.85 0.85 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.94 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.18 - 1000 0.80 0.80 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.91 P value adjustment method: holm p=0.150-83 Df Sum Sq Mean Sq F value Pr(>F) size 2 1917 959 2.3760 0.0947 . dis 1 588 588 1.4566 0.2284 size:dis 2 329 165 0.4080 0.6653 Residuals 294 118605 403 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.405 - 1000 0.098 0.449 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.23 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.34 - 1000 0.34 0.71 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.25 P value adjustment method: holm p=0.200-00 Df Sum Sq Mean Sq F value Pr(>F) size 2 29.47 14.74 3.1621 0.04378 * dis 1 7.02 7.02 1.5054 0.22083 size:dis 2 6.40 3.20 0.6861 0.50432 Residuals 294 1370.10 4.66 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.187 - 1000 0.056 0.442 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.22 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.2776 - 1000 0.0072 0.2776 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.27 P value adjustment method: holm p=0.200-83 Df Sum Sq Mean Sq F value Pr(>F) size 2 32 16 0.0579 0.94374 dis 1 764 764 2.7644 0.09745 . size:dis 2 28 14 0.0507 0.95055 Residuals 294 81223 276 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 1 - 1000 1 1 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.095 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 1 - 1000 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.15 P value adjustment method: holm ANOVA summary of the impact of the instance size and the distribution of the nodes on the cost p=0.050-00 Df Sum Sq Mean Sq F value Pr(>F) size 2 10.02 5.01 2.9666 0.05302 . dis 1 4.93 4.93 2.9219 0.08844 . size:dis 2 11.84 5.92 3.5076 0.03123 * Residuals 294 496.26 1.69 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.64 - 1000 0.24 0.24 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.093 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.707 - 1000 0.068 0.068 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.0051 P value adjustment method: holm p=0.050-83 Df Sum Sq Mean Sq F value Pr(>F) size 2 732 366 0.9621 0.3833 dis 1 916 916 2.4062 0.1219 size:dis 2 379 190 0.4984 0.6080 Residuals 294 111912 381 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.7 - 1000 0.7 0.7 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.12 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.33 - 1000 0.33 0.40 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.4 P value adjustment method: holm p=0.100-00 Df Sum Sq Mean Sq F value Pr(>F) size 2 23.81 11.90 4.3587 0.01363 * dis 1 3.07 3.07 1.1240 0.28992 size:dis 2 17.12 8.56 3.1337 0.04501 * Residuals 294 802.89 2.73 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.150 - 1000 0.015 0.188 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.3 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.118 - 1000 0.019 0.607 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.49 P value adjustment method: holm p=0.100-83 Df Sum Sq Mean Sq F value Pr(>F) size 2 912 456 1.8788 0.15460 dis 1 182 182 0.7495 0.38735 size:dis 2 1192 596 2.4550 0.08762 . Residuals 294 71361 243 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.31 - 1000 0.63 0.31 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.39 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.34 - 1000 0.65 0.19 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.4 P value adjustment method: holm p=0.150-00 Df Sum Sq Mean Sq F value Pr(>F) size 2 9.25 4.63 1.2017 0.3022 dis 1 0.02 0.02 0.0062 0.9374 size:dis 2 7.46 3.73 0.9688 0.3807 Residuals 294 1131.72 3.85 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.33 - 1000 0.85 0.85 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.94 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.18 - 1000 0.80 0.80 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.91 P value adjustment method: holm p=0.150-83 Df Sum Sq Mean Sq F value Pr(>F) size 2 1917 959 2.3760 0.0947 . dis 1 588 588 1.4566 0.2284 size:dis 2 329 165 0.4080 0.6653 Residuals 294 118605 403 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.405 - 1000 0.098 0.449 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.23 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.34 - 1000 0.34 0.71 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.25 P value adjustment method: holm p=0.200-00 Df Sum Sq Mean Sq F value Pr(>F) size 2 29.47 14.74 3.1621 0.04378 * dis 1 7.02 7.02 1.5054 0.22083 size:dis 2 6.40 3.20 0.6861 0.50432 Residuals 294 1370.10 4.66 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.187 - 1000 0.056 0.442 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.22 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 0.2776 - 1000 0.0072 0.2776 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.27 P value adjustment method: holm p=0.200-83 Df Sum Sq Mean Sq F value Pr(>F) size 2 32 16 0.0579 0.94374 dis 1 764 764 2.7644 0.09745 . size:dis 2 28 14 0.0507 0.95055 Residuals 294 81223 276 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$size 100 300 300 1 - 1000 1 1 P value adjustment method: holm Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$dis c u 0.095 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$size 100 300 300 1 - 1000 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$dis c u 0.15 P value adjustment method: holm