ANOVA summary of the impact of the significance levels on the cost p=0.050-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 15.85 5.28 0.6467 0.5859 Residuals 196 1601.62 8.17 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.00 - - 0.05 0.84 0.25 - 0.1 0.90 0.04 1.00 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.58 - - 0.05 0.42 0.35 - 0.1 0.42 0.10 0.58 P value adjustment method: holm p=0.050-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 25.54 8.51 1.2433 0.2952 Residuals 196 1342.27 6.85 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.00 - - 0.05 0.24 0.53 - 0.1 0.43 0.69 1.00 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm p=0.050-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 13.62 4.54 0.3356 0.7996 Residuals 196 2650.47 13.52 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.23 - - 0.05 1.00 0.78 - 0.1 0.30 1.00 0.78 P value adjustment method: holm p=0.075-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 12.05 4.02 0.6252 0.5995 Residuals 196 1259.29 6.42 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.00 - - 0.05 0.47 0.63 - 0.1 1.00 1.00 1.00 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.000 - - 0.05 0.083 0.194 - 0.1 1.000 1.000 1.000 P value adjustment method: holm p=0.075-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 23.64 7.88 0.7975 0.4966 Residuals 196 1936.78 9.88 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.99 - - 0.05 0.74 0.74 - 0.1 0.63 0.58 0.18 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.000 - - 0.05 1.000 1.000 - 0.1 0.484 0.484 0.055 P value adjustment method: holm p=0.075-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 5.17 1.72 0.1123 0.9528 Residuals 196 3005.01 15.33 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm p=0.100-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 7.08 2.36 0.2782 0.841 Residuals 196 1661.92 8.48 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.000 - - 0.05 1.000 0.509 - 0.1 0.262 0.074 0.839 P value adjustment method: holm p=0.100-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 6.71 2.24 0.3986 0.7542 Residuals 196 1099.41 5.61 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.00 - - 0.05 1.00 0.73 - 0.1 1.00 1.00 1.00 P value adjustment method: holm p=0.100-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 6.30 2.10 0.2289 0.8762 Residuals 196 1796.49 9.17 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm p=0.125-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 12.72 4.24 0.5083 0.677 Residuals 196 1635.51 8.34 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.00 - - 0.05 1.00 1.00 - 0.1 0.76 0.76 1.00 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.99 - - 0.05 0.87 0.85 - 0.1 0.28 0.28 0.36 P value adjustment method: holm p=0.125-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 37.52 12.51 1.2983 0.2763 Residuals 196 1888.11 9.63 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.96 - - 0.05 0.96 0.18 - 0.1 0.17 0.10 0.96 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.4677 - - 0.05 0.4677 0.0122 - 0.1 0.1414 0.0018 0.5822 P value adjustment method: holm p=0.125-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 10.54 3.51 0.4072 0.748 Residuals 196 1690.44 8.62 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.00 - - 0.05 1.00 1.00 - 0.1 1.00 0.43 1.00 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.00 - - 0.05 1.00 1.00 - 0.1 1.00 0.78 1.00 P value adjustment method: holm p=0.150-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 21.67 7.22 1.0392 0.3763 Residuals 196 1362.59 6.95 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.928 - - 0.05 0.928 0.367 - 0.1 0.289 0.928 0.063 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.839 - - 0.05 0.839 0.519 - 0.1 0.429 0.839 0.052 P value adjustment method: holm p=0.150-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 4.86 1.62 0.1682 0.9177 Residuals 196 1887.45 9.63 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm p=0.150-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 7.10 2.37 0.2308 0.8748 Residuals 196 2008.27 10.25 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm p=0.175-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 1.20 0.40 0.0849 0.9682 Residuals 196 922.32 4.71 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.99 - - 0.05 1.00 1.00 - 0.1 1.00 1.00 1.00 P value adjustment method: holm p=0.175-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 5.31 1.77 0.2122 0.8879 Residuals 196 1633.67 8.34 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm p=0.175-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 4.34 1.45 0.166 0.9192 Residuals 196 1706.81 8.71 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm p=0.200-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 15.67 5.22 1.3556 0.2577 Residuals 196 755.18 3.85 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.932 - - 0.05 0.467 0.481 - 0.1 0.094 0.025 0.798 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1.000 - - 0.05 0.454 0.454 - 0.1 0.114 0.037 1.000 P value adjustment method: holm p=0.200-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 1.39 0.46 0.0791 0.9713 Residuals 196 1144.70 5.84 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm p=0.200-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 20.03 6.68 0.6104 0.609 Residuals 196 2143.74 10.94 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.76 - - 0.05 0.76 0.98 - 0.1 0.76 0.39 0.49 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm p=0.300-16 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 23.22 7.74 2.0502 0.1082 Residuals 196 739.95 3.78 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.575 - - 0.05 0.526 0.492 - 0.1 0.117 0.057 0.492 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 0.931 - - 0.05 0.752 0.915 - 0.1 0.067 0.116 0.411 P value adjustment method: holm p=0.300-50 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 9.28 3.09 0.3348 0.8002 Residuals 196 1811.69 9.24 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm p=0.300-83 Df Sum Sq Mean Sq F value Pr(>F) alpha 3 3.48 1.16 0.2073 0.8913 Residuals 196 1095.61 5.59 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$cost and currentDataAnova$alpha 0.01 0.02 0.05 0.02 1 - - 0.05 1 1 - 0.1 1 1 1 P value adjustment method: holm