ANOVA summary of the impact of the importance sampling variants on the time
p=0.050-16
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 9.9980 2.4995 39.531 < 2.2e-16 ***
Residuals 245 15.4912 0.0632
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 0.03 - - -
sb 0.11 0.62 - -
wb 6.9e-16 1.7e-12 6.0e-14 -
pb 6.9e-16 4.2e-12 7.6e-13 0.23
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 0.19 - - -
sb 0.19 0.85 - -
wb 7.8e-09 7.8e-09 7.8e-09 -
pb 7.8e-09 7.8e-09 7.8e-09 0.22
P value adjustment method: holm
p=0.050-50
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 139.221 34.805 145.87 < 2.2e-16 ***
Residuals 245 58.458 0.239
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 1.7e-09 - - -
sb 0.251 1.1e-07 - -
wb < 2e-16 < 2e-16 < 2e-16 -
pb < 2e-16 < 2e-16 < 2e-16 0.047
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 9.7e-09 - - -
sb 0.235 7.7e-07 - -
wb 7.8e-09 7.8e-09 7.8e-09 -
pb 7.8e-09 7.8e-09 7.8e-09 0.074
P value adjustment method: holm
p=0.050-83
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 344.41 86.10 322 < 2.2e-16 ***
Residuals 245 65.51 0.27
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb < 2e-16 - - -
sb 9.4e-16 0.0011 - -
wb 3.8e-13 < 2e-16 < 2e-16 -
pb < 2e-16 < 2e-16 < 2e-16 0.0011
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 7.8e-09 5e-04 - -
wb 1.5e-08 7.8e-09 7.8e-09 -
pb 7.8e-09 7.8e-09 7.8e-09 1.1e-05
P value adjustment method: holm
p=0.075-16
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 0.51715 0.12929 39.705 < 2.2e-16 ***
Residuals 245 0.79778 0.00326
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 8.1e-07 - - -
sb 5.7e-06 0.36 - -
wb 1.4e-07 < 2e-16 9.7e-16 -
pb 2.9e-05 < 2e-16 4.8e-13 0.36
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 1.0e-05 - - -
sb 1.2e-05 0.24 - -
wb 1.8e-06 7.8e-09 7.8e-09 -
pb 6.0e-05 7.8e-09 7.8e-09 0.11
P value adjustment method: holm
p=0.075-50
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 34.241 8.560 47.715 < 2.2e-16 ***
Residuals 245 43.954 0.179
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 0.00041 - - -
sb 0.16898 0.02453 - -
wb < 2e-16 4.9e-12 2.0e-09 -
pb < 2e-16 4.4e-12 1.6e-09 0.70492
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 1.9e-05 - - -
sb 0.659 0.021 - -
wb 7.8e-09 7.8e-09 7.8e-09 -
pb 7.8e-09 7.8e-09 7.8e-09 0.685
P value adjustment method: holm
p=0.075-83
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 308.877 77.219 113.21 < 2.2e-16 ***
Residuals 245 167.105 0.682
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb < 2e-16 - - -
sb 4.5e-07 4.3e-07 - -
wb 1.1e-09 < 2e-16 6.4e-12 -
pb 1.9e-12 < 2e-16 6.4e-12 0.010
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 1.1e-07 7.2e-06 - -
wb 3.5e-08 7.8e-09 7.8e-09 -
pb 7.8e-09 7.8e-09 7.8e-09 0.00038
P value adjustment method: holm
p=0.100-16
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 0.23752 0.05938 44.946 < 2.2e-16 ***
Residuals 245 0.32368 0.00132
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 2.7e-15 - - -
sb < 2e-16 0.0051 - -
wb 0.0051 2.2e-12 < 2e-16 -
pb 6.8e-05 1.7e-08 2.2e-15 0.0504
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 7.8e-09 0.00809 - -
wb 0.00804 4.2e-08 7.8e-09 -
pb 0.00016 4.2e-07 7.8e-09 0.04569
P value adjustment method: holm
p=0.100-50
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 7.8763 1.9691 22.554 7.108e-16 ***
Residuals 245 21.3898 0.0873
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 0.105 - - -
sb 0.845 0.105 - -
wb 1.2e-10 2.0e-07 3.4e-08 -
pb 2.1e-09 2.7e-07 6.1e-08 0.012
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 0.00063 - - -
sb 0.83935 4.5e-05 - -
wb 7.8e-09 7.8e-09 7.8e-09 -
pb 7.8e-09 7.8e-09 7.8e-09 0.00443
P value adjustment method: holm
p=0.100-83
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 122.066 30.516 55.065 < 2.2e-16 ***
Residuals 245 135.777 0.554
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.0e-08 - - -
sb 0.05665 2.9e-07 - -
wb 0.00046 2.7e-13 5.1e-10 -
pb 0.00046 2.7e-13 5.2e-10 0.33671
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 5.2e-08 - - -
sb 1.4e-07 1.4e-07 - -
wb 7.8e-09 7.8e-09 7.8e-09 -
pb 7.8e-09 7.8e-09 7.8e-09 0.41
P value adjustment method: holm
p=0.125-16
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 0.182072 0.045518 44.605 < 2.2e-16 ***
Residuals 245 0.250016 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$run.time and currentDataAnova$is.type
ub gb sb wb
gb < 2e-16 - - -
sb < 2e-16 0.809 - -
wb 1.0e-10 4.8e-13 1.4e-13 -
pb 1.0e-14 3.4e-11 6.2e-08 0.027
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 7.8e-09 0.962 - -
wb 4.6e-08 3.0e-08 1.2e-08 -
pb 7.8e-09 4.6e-08 1.7e-06 0.011
P value adjustment method: holm
p=0.125-50
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 2.14841 0.53710 106.68 < 2.2e-16 ***
Residuals 245 1.23350 0.00503
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 3.0e-07 - - -
sb 0.0045 5.7e-05 - -
wb < 2e-16 < 2e-16 < 2e-16 -
pb < 2e-16 < 2e-16 < 2e-16 0.0035
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 1.1e-08 - - -
sb 0.0045 1.1e-05 - -
wb 7.8e-09 7.8e-09 7.8e-09 -
pb 7.8e-09 7.8e-09 7.8e-09 0.0043
P value adjustment method: holm
p=0.125-83
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 42.140 10.535 76.56 < 2.2e-16 ***
Residuals 245 33.713 0.138
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.0e-11 - - -
sb 1.1e-06 1.2e-08 - -
wb < 2e-16 3.6e-14 1.5e-14 -
pb < 2e-16 4.1e-14 1.6e-14 0.51
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 9.3e-08 2.8e-08 - -
wb 7.8e-09 7.8e-09 7.8e-09 -
pb 7.8e-09 7.8e-09 7.8e-09 0.69
P value adjustment method: holm
p=0.150-16
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 0.111661 0.027915 33.901 < 2.2e-16 ***
Residuals 245 0.201744 0.000823
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb < 2e-16 - - -
sb < 2e-16 0.38 - -
wb 1.1e-09 5.3e-09 1.6e-08 -
pb 1.9e-10 1.7e-06 8.4e-07 0.38
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 7.8e-09 0.52 - -
wb 1.7e-07 3.0e-07 5.2e-07 -
pb 2.0e-07 7.8e-06 7.4e-06 0.52
P value adjustment method: holm
p=0.150-50
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 1.00932 0.25233 113.03 < 2.2e-16 ***
Residuals 245 0.54694 0.00223
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 1.9e-14 - - -
sb 3.8e-07 2.5e-07 - -
wb < 2e-16 < 2e-16 < 2e-16 -
pb 8.1e-15 < 2e-16 < 2e-16 0.016
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 3.7e-06 2.7e-06 - -
wb 7.8e-09 7.8e-09 7.8e-09 -
pb 7.8e-09 7.8e-09 7.8e-09 0.0044
P value adjustment method: holm
p=0.150-83
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 25.5937 6.3984 73.7 < 2.2e-16 ***
Residuals 245 21.2702 0.0868
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 8.0e-10 - - -
sb 9.9e-10 1.8e-07 - -
wb < 2e-16 9.4e-13 < 2e-16 -
pb < 2e-16 1.4e-12 < 2e-16 0.25
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 7.8e-09 7.8e-09 - -
wb 7.8e-09 7.8e-09 7.8e-09 -
pb 7.8e-09 7.8e-09 7.8e-09 0.15
P value adjustment method: holm
p=0.175-16
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 0.092557 0.023139 23.858 < 2.2e-16 ***
Residuals 245 0.237621 0.000970
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb < 2e-16 - - -
sb < 2e-16 0.158 - -
wb 5.3e-09 3.8e-10 3.3e-07 -
pb 3.2e-12 2.2e-08 1.9e-05 0.091
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 7.8e-09 0.148 - -
wb 9.1e-08 2.2e-07 5.6e-06 -
pb 5.3e-08 1.3e-06 6.2e-05 0.053
P value adjustment method: holm
p=0.175-50
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 0.68526 0.17132 131.80 < 2.2e-16 ***
Residuals 245 0.31844 0.00130
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb < 2e-16 - - -
sb 5.5e-11 1.2e-10 - -
wb 3.7e-12 < 2e-16 < 2e-16 -
pb 1.7e-08 < 2e-16 < 2e-16 7e-04
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 2.6e-08 1.6e-07 - -
wb 1.5e-08 7.8e-09 7.8e-09 -
pb 1.6e-07 7.8e-09 7.8e-09 0.00049
P value adjustment method: holm
p=0.175-83
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 16.887 4.222 23.807 < 2.2e-16 ***
Residuals 245 43.447 0.177
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 0.00027 - - -
sb 5.7e-11 0.00932 - -
wb < 2e-16 1.2e-05 < 2e-16 -
pb < 2e-16 1.2e-05 < 2e-16 0.79789
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 7.8e-09 3.1e-08 - -
wb 7.8e-09 7.8e-09 7.8e-09 -
pb 7.8e-09 7.8e-09 7.8e-09 1
P value adjustment method: holm
p=0.200-16
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 0.062683 0.015671 24.318 < 2.2e-16 ***
Residuals 245 0.157879 0.000644
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb < 2e-16 - - -
sb < 2e-16 0.00331 - -
wb 3.9e-10 2.4e-08 0.00034 -
pb 6.3e-16 0.00023 0.06741 0.06741
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 1.1e-08 0.00686 - -
wb 3.3e-07 7.0e-07 0.00105 -
pb 7.8e-09 0.00035 0.06118 0.06118
P value adjustment method: holm
p=0.200-50
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 1.372 0.343 2.3338 0.05632 .
Residuals 245 36.021 0.147
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb < 2e-16 - - -
sb 0.61 0.61 - -
wb 2.5e-07 < 2e-16 0.61 -
pb 9.4e-05 < 2e-16 0.61 0.61
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 1.9e-08 2.5e-05 - -
wb 1.7e-06 7.8e-09 7.8e-09 -
pb 4.3e-05 7.8e-09 8.1e-09 0.18
P value adjustment method: holm
p=0.200-83
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 8.6185 2.1546 216.88 < 2.2e-16 ***
Residuals 245 2.4340 0.0099
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb < 2e-16 - - -
sb < 2e-16 6.1e-13 - -
wb < 2e-16 < 2e-16 < 2e-16 -
pb < 2e-16 < 2e-16 < 2e-16 0.12
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 7.8e-09 7.8e-09 - -
wb 7.8e-09 7.8e-09 7.8e-09 -
pb 7.8e-09 7.8e-09 7.8e-09 0.10
P value adjustment method: holm
p=0.300-16
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 0.028974 0.007244 11.577 1.261e-08 ***
Residuals 245 0.153291 0.000626
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 3.6e-16 - - -
sb 2.5e-08 9.0e-06 - -
wb 9.0e-06 2.6e-08 0.036 -
pb 2.5e-10 9.0e-06 0.938 0.016
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 8.3e-09 - - -
sb 9.0e-07 4.0e-05 - -
wb 4.9e-05 7.5e-07 0.039 -
pb 2.1e-07 4.9e-05 0.969 0.018
P value adjustment method: holm
p=0.300-50
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 0.181079 0.045270 74.791 < 2.2e-16 ***
Residuals 245 0.148295 0.000605
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb < 2e-16 - - -
sb < 2e-16 2.7e-12 - -
wb 0.365 < 2e-16 1.0e-14 -
pb 0.011 < 2e-16 1.8e-11 0.094
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 7.8e-09 2.8e-08 - -
wb 0.364 7.8e-09 9.1e-09 -
pb 0.013 7.8e-09 9.1e-08 0.178
P value adjustment method: holm
p=0.300-83
Df Sum Sq Mean Sq F value Pr(>F)
is.type 4 2.68516 0.67129 212.23 < 2.2e-16 ***
Residuals 245 0.77493 0.00316
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Pairwise comparisons using t tests with non-pooled SD
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb < 2e-16 - - -
sb < 2e-16 1.2e-10 - -
wb 1.4e-11 < 2e-16 < 2e-16 -
pb 4.0e-10 < 2e-16 < 2e-16 0.12
P value adjustment method: holm
Pairwise comparisons using Wilcoxon rank sum test
data: currentDataAnova$run.time and currentDataAnova$is.type
ub gb sb wb
gb 7.8e-09 - - -
sb 7.8e-09 1.0e-08 - -
wb 1.0e-08 7.8e-09 7.8e-09 -
pb 4.8e-08 7.8e-09 7.8e-09 0.11
P value adjustment method: holm