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R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationMon, 13 Dec 2010 10:04:59 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/13/t1292235016j24y5o5r4xl4n94.htm/, Retrieved Mon, 06 May 2024 16:37:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108757, Retrieved Mon, 06 May 2024 16:37:10 +0000
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Estimated Impact127
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [Bonuspunt - Kenda...] [2010-12-13 10:04:59] [514029464b0621595fe21c9fa38c7009] [Current]
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Dataseries X:
6.3	2.0	4.5	1.000	6.600	42.0	3	1	1
2.1	1.8	69.0	2547.000	4603.000	624.0	3	5	4
9.1	.7	27.0	10.550	179.500	180.0	4	4	1
15.8	3.9	19.0	.023	.300	35.0	1	1	4
5.2	1.0	30.4	160.000	169.000	392.0	4	5	1
10.9	3.6	28.0	3.300	25.600	63.0	1	2	1
8.3	1.4	50.0	52.160	440.000	230.0	1	1	4
11.0	1.5	7.0	.425	6.400	112.0	5	4	5
3.2	.7	30.0	465.000	423.000	281.0	5	5	2
6.3	2.1	3.5	.075	1.200	42.0	1	1	2
6.6	4.1	6.0	.785	3.500	42.0	2	2	2
9.5	1.2	10.4	.200	5.000	120.0	2	2	1
3.3	.5	20.0	27.660	115.000	148.0	5	5	2
11.0	3.4	3.9	.120	1.000	16.0	3	1	1
4.7	1.5	41.0	85.000	325.000	310.0	1	3	1
10.4	3.4	9.0	.101	4.000	28.0	5	1	4
7.4	.8	7.6	1.040	5.500	68.0	5	3	5
2.1	.8	46.0	521.000	655.000	336.0	5	5	1
17.9	2.0	24.0	.010	.250	50.0	1	1	1
6.1	1.9	100.0	62.000	1320.000	267.0	1	1	1
11.9	1.3	3.2	.023	.400	19.0	4	1	3
13.8	5.6	5.0	1.700	6.300	12.0	2	1	1
14.3	3.1	6.5	3.500	10.800	120.0	2	1	5
15.2	1.8	12.0	.480	15.500	140.0	2	2	4
10.0	.9	20.2	10.000	115.000	170.0	4	4	2
11.9	1.8	13.0	1.620	11.400	17.0	2	1	4
6.5	1.9	27.0	192.000	180.000	115.0	4	4	5
7.5	.9	18.0	2.500	12.100	31.0	5	5	2
10.6	2.6	4.7	.280	1.900	21.0	3	1	1
7.4	2.4	9.8	4.235	50.400	52.0	1	1	2
8.4	1.2	29.0	6.800	179.000	164.0	2	3	2
5.7	.9	7.0	.750	12.300	225.0	2	2	3
4.9	.5	6.0	3.600	21.000	225.0	3	2	5
3.2	.6	20.0	55.500	175.000	151.0	5	5	2
11.0	2.3	4.5	.900	2.600	60.0	2	1	3
4.9	.5	7.5	2.000	12.300	200.0	3	1	2
13.2	2.6	2.3	.104	2.500	46.0	3	2	4
9.7	.6	24.0	4.190	58.000	210.0	4	3	1
12.8	6.6	3.0	3.500	3.900	14.0	2	1	1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108757&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108757&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108757&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Correlations for all pairs of data series (method=kendall)
SlowwPsleepLifespanWeightWbrainGdrachtPredationSplaatsDanger
Sloww10.417-0.3-0.481-0.492-0.485-0.242-0.430.07
Psleep0.4171-0.237-0.278-0.324-0.461-0.392-0.471-0.03
Lifespan-0.3-0.23710.5250.650.533-0.0060.41-0.137
Weight-0.481-0.2780.52510.7920.5210.160.481-0.097
Wbrain-0.492-0.3240.650.79210.5990.1260.491-0.049
Gdracht-0.485-0.4610.5330.5210.59910.0750.462-0.005
Predation-0.242-0.392-0.0060.160.1260.07510.5220.126
Splaats-0.43-0.4710.410.4810.4910.4620.52210.023
Danger0.07-0.03-0.137-0.097-0.049-0.0050.1260.0231

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Sloww & Psleep & Lifespan & Weight & Wbrain & Gdracht & Predation & Splaats & Danger \tabularnewline
Sloww & 1 & 0.417 & -0.3 & -0.481 & -0.492 & -0.485 & -0.242 & -0.43 & 0.07 \tabularnewline
Psleep & 0.417 & 1 & -0.237 & -0.278 & -0.324 & -0.461 & -0.392 & -0.471 & -0.03 \tabularnewline
Lifespan & -0.3 & -0.237 & 1 & 0.525 & 0.65 & 0.533 & -0.006 & 0.41 & -0.137 \tabularnewline
Weight & -0.481 & -0.278 & 0.525 & 1 & 0.792 & 0.521 & 0.16 & 0.481 & -0.097 \tabularnewline
Wbrain & -0.492 & -0.324 & 0.65 & 0.792 & 1 & 0.599 & 0.126 & 0.491 & -0.049 \tabularnewline
Gdracht & -0.485 & -0.461 & 0.533 & 0.521 & 0.599 & 1 & 0.075 & 0.462 & -0.005 \tabularnewline
Predation & -0.242 & -0.392 & -0.006 & 0.16 & 0.126 & 0.075 & 1 & 0.522 & 0.126 \tabularnewline
Splaats & -0.43 & -0.471 & 0.41 & 0.481 & 0.491 & 0.462 & 0.522 & 1 & 0.023 \tabularnewline
Danger & 0.07 & -0.03 & -0.137 & -0.097 & -0.049 & -0.005 & 0.126 & 0.023 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108757&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Sloww[/C][C]Psleep[/C][C]Lifespan[/C][C]Weight[/C][C]Wbrain[/C][C]Gdracht[/C][C]Predation[/C][C]Splaats[/C][C]Danger[/C][/ROW]
[ROW][C]Sloww[/C][C]1[/C][C]0.417[/C][C]-0.3[/C][C]-0.481[/C][C]-0.492[/C][C]-0.485[/C][C]-0.242[/C][C]-0.43[/C][C]0.07[/C][/ROW]
[ROW][C]Psleep[/C][C]0.417[/C][C]1[/C][C]-0.237[/C][C]-0.278[/C][C]-0.324[/C][C]-0.461[/C][C]-0.392[/C][C]-0.471[/C][C]-0.03[/C][/ROW]
[ROW][C]Lifespan[/C][C]-0.3[/C][C]-0.237[/C][C]1[/C][C]0.525[/C][C]0.65[/C][C]0.533[/C][C]-0.006[/C][C]0.41[/C][C]-0.137[/C][/ROW]
[ROW][C]Weight[/C][C]-0.481[/C][C]-0.278[/C][C]0.525[/C][C]1[/C][C]0.792[/C][C]0.521[/C][C]0.16[/C][C]0.481[/C][C]-0.097[/C][/ROW]
[ROW][C]Wbrain[/C][C]-0.492[/C][C]-0.324[/C][C]0.65[/C][C]0.792[/C][C]1[/C][C]0.599[/C][C]0.126[/C][C]0.491[/C][C]-0.049[/C][/ROW]
[ROW][C]Gdracht[/C][C]-0.485[/C][C]-0.461[/C][C]0.533[/C][C]0.521[/C][C]0.599[/C][C]1[/C][C]0.075[/C][C]0.462[/C][C]-0.005[/C][/ROW]
[ROW][C]Predation[/C][C]-0.242[/C][C]-0.392[/C][C]-0.006[/C][C]0.16[/C][C]0.126[/C][C]0.075[/C][C]1[/C][C]0.522[/C][C]0.126[/C][/ROW]
[ROW][C]Splaats[/C][C]-0.43[/C][C]-0.471[/C][C]0.41[/C][C]0.481[/C][C]0.491[/C][C]0.462[/C][C]0.522[/C][C]1[/C][C]0.023[/C][/ROW]
[ROW][C]Danger[/C][C]0.07[/C][C]-0.03[/C][C]-0.137[/C][C]-0.097[/C][C]-0.049[/C][C]-0.005[/C][C]0.126[/C][C]0.023[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108757&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108757&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series (method=kendall)
SlowwPsleepLifespanWeightWbrainGdrachtPredationSplaatsDanger
Sloww10.417-0.3-0.481-0.492-0.485-0.242-0.430.07
Psleep0.4171-0.237-0.278-0.324-0.461-0.392-0.471-0.03
Lifespan-0.3-0.23710.5250.650.533-0.0060.41-0.137
Weight-0.481-0.2780.52510.7920.5210.160.481-0.097
Wbrain-0.492-0.3240.650.79210.5990.1260.491-0.049
Gdracht-0.485-0.4610.5330.5210.59910.0750.462-0.005
Predation-0.242-0.392-0.0060.160.1260.07510.5220.126
Splaats-0.43-0.4710.410.4810.4910.4620.52210.023
Danger0.07-0.03-0.137-0.097-0.049-0.0050.1260.0231







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Sloww;Psleep0.52980.59180.4165
p-value(5e-04)(1e-04)(2e-04)
Sloww;Lifespan-0.3845-0.4282-0.2999
p-value(0.0156)(0.0065)(0.0077)
Sloww;Weight-0.3948-0.6585-0.4813
p-value(0.0129)(0)(0)
Sloww;Wbrain-0.388-0.6599-0.4922
p-value(0.0147)(0)(0)
Sloww;Gdracht-0.6208-0.6623-0.485
p-value(0)(0)(0)
Sloww;Predation-0.3689-0.3119-0.2421
p-value(0.0208)(0.0533)(0.0458)
Sloww;Splaats-0.5795-0.5491-0.4299
p-value(1e-04)(3e-04)(5e-04)
Sloww;Danger0.12680.09870.0696
p-value(0.4418)(0.55)(0.5708)
Psleep;Lifespan-0.2409-0.3893-0.2373
p-value(0.1396)(0.0143)(0.036)
Psleep;Weight-0.088-0.4395-0.2777
p-value(0.5942)(0.0051)(0.0139)
Psleep;Wbrain-0.0886-0.5242-0.3242
p-value(0.5915)(6e-04)(0.0041)
Psleep;Gdracht-0.4681-0.6521-0.4606
p-value(0.0027)(0)(0)
Psleep;Predation-0.4342-0.5339-0.3919
p-value(0.0057)(5e-04)(0.0013)
Psleep;Splaats-0.533-0.6156-0.4706
p-value(5e-04)(0)(1e-04)
Psleep;Danger-0.0953-0.058-0.0296
p-value(0.564)(0.7259)(0.8107)
Lifespan;Weight0.49230.70630.5251
p-value(0.0015)(0)(0)
Lifespan;Wbrain0.65940.80330.6499
p-value(0)(0)(0)
Lifespan;Gdracht0.69130.71150.533
p-value(0)(0)(0)
Lifespan;Predation-0.11070.0122-0.006
p-value(0.5023)(0.9412)(0.9604)
Lifespan;Splaats0.31920.52420.4101
p-value(0.0476)(6e-04)(9e-04)
Lifespan;Danger-0.158-0.1506-0.1374
p-value(0.3369)(0.3602)(0.2624)
Weight;Wbrain0.95570.92840.7916
p-value(0)(0)(0)
Weight;Gdracht0.7190.70950.5207
p-value(0)(0)(0)
Weight;Predation0.11010.21470.1602
p-value(0.5045)(0.1893)(0.1846)
Weight;Splaats0.40240.59540.4811
p-value(0.0111)(1e-04)(1e-04)
Weight;Danger0.1293-0.1197-0.097
p-value(0.4329)(0.4681)(0.4277)
Wbrain;Gdracht0.73690.80820.5993
p-value(0)(0)(0)
Wbrain;Predation-0.00340.16750.1257
p-value(0.9835)(0.3082)(0.2976)
Wbrain;Splaats0.31750.59760.4905
p-value(0.0489)(1e-04)(1e-04)
Wbrain;Danger0.0912-0.0549-0.0493
p-value(0.5808)(0.7401)(0.687)
Gdracht;Predation0.13160.11620.075
p-value(0.4247)(0.4813)(0.5352)
Gdracht;Splaats0.56630.57710.4617
p-value(2e-04)(1e-04)(2e-04)
Gdracht;Danger-0.00710.0013-0.0046
p-value(0.9658)(0.9937)(0.9699)
Predation;Splaats0.680.61860.5218
p-value(0)(0)(1e-04)
Predation;Danger0.13450.15360.126
p-value(0.4143)(0.3506)(0.3404)
Splaats;Danger-0.02730.02310.0232
p-value(0.869)(0.8888)(0.8631)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Sloww;Psleep & 0.5298 & 0.5918 & 0.4165 \tabularnewline
p-value & (5e-04) & (1e-04) & (2e-04) \tabularnewline
Sloww;Lifespan & -0.3845 & -0.4282 & -0.2999 \tabularnewline
p-value & (0.0156) & (0.0065) & (0.0077) \tabularnewline
Sloww;Weight & -0.3948 & -0.6585 & -0.4813 \tabularnewline
p-value & (0.0129) & (0) & (0) \tabularnewline
Sloww;Wbrain & -0.388 & -0.6599 & -0.4922 \tabularnewline
p-value & (0.0147) & (0) & (0) \tabularnewline
Sloww;Gdracht & -0.6208 & -0.6623 & -0.485 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Sloww;Predation & -0.3689 & -0.3119 & -0.2421 \tabularnewline
p-value & (0.0208) & (0.0533) & (0.0458) \tabularnewline
Sloww;Splaats & -0.5795 & -0.5491 & -0.4299 \tabularnewline
p-value & (1e-04) & (3e-04) & (5e-04) \tabularnewline
Sloww;Danger & 0.1268 & 0.0987 & 0.0696 \tabularnewline
p-value & (0.4418) & (0.55) & (0.5708) \tabularnewline
Psleep;Lifespan & -0.2409 & -0.3893 & -0.2373 \tabularnewline
p-value & (0.1396) & (0.0143) & (0.036) \tabularnewline
Psleep;Weight & -0.088 & -0.4395 & -0.2777 \tabularnewline
p-value & (0.5942) & (0.0051) & (0.0139) \tabularnewline
Psleep;Wbrain & -0.0886 & -0.5242 & -0.3242 \tabularnewline
p-value & (0.5915) & (6e-04) & (0.0041) \tabularnewline
Psleep;Gdracht & -0.4681 & -0.6521 & -0.4606 \tabularnewline
p-value & (0.0027) & (0) & (0) \tabularnewline
Psleep;Predation & -0.4342 & -0.5339 & -0.3919 \tabularnewline
p-value & (0.0057) & (5e-04) & (0.0013) \tabularnewline
Psleep;Splaats & -0.533 & -0.6156 & -0.4706 \tabularnewline
p-value & (5e-04) & (0) & (1e-04) \tabularnewline
Psleep;Danger & -0.0953 & -0.058 & -0.0296 \tabularnewline
p-value & (0.564) & (0.7259) & (0.8107) \tabularnewline
Lifespan;Weight & 0.4923 & 0.7063 & 0.5251 \tabularnewline
p-value & (0.0015) & (0) & (0) \tabularnewline
Lifespan;Wbrain & 0.6594 & 0.8033 & 0.6499 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Lifespan;Gdracht & 0.6913 & 0.7115 & 0.533 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Lifespan;Predation & -0.1107 & 0.0122 & -0.006 \tabularnewline
p-value & (0.5023) & (0.9412) & (0.9604) \tabularnewline
Lifespan;Splaats & 0.3192 & 0.5242 & 0.4101 \tabularnewline
p-value & (0.0476) & (6e-04) & (9e-04) \tabularnewline
Lifespan;Danger & -0.158 & -0.1506 & -0.1374 \tabularnewline
p-value & (0.3369) & (0.3602) & (0.2624) \tabularnewline
Weight;Wbrain & 0.9557 & 0.9284 & 0.7916 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Weight;Gdracht & 0.719 & 0.7095 & 0.5207 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Weight;Predation & 0.1101 & 0.2147 & 0.1602 \tabularnewline
p-value & (0.5045) & (0.1893) & (0.1846) \tabularnewline
Weight;Splaats & 0.4024 & 0.5954 & 0.4811 \tabularnewline
p-value & (0.0111) & (1e-04) & (1e-04) \tabularnewline
Weight;Danger & 0.1293 & -0.1197 & -0.097 \tabularnewline
p-value & (0.4329) & (0.4681) & (0.4277) \tabularnewline
Wbrain;Gdracht & 0.7369 & 0.8082 & 0.5993 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Wbrain;Predation & -0.0034 & 0.1675 & 0.1257 \tabularnewline
p-value & (0.9835) & (0.3082) & (0.2976) \tabularnewline
Wbrain;Splaats & 0.3175 & 0.5976 & 0.4905 \tabularnewline
p-value & (0.0489) & (1e-04) & (1e-04) \tabularnewline
Wbrain;Danger & 0.0912 & -0.0549 & -0.0493 \tabularnewline
p-value & (0.5808) & (0.7401) & (0.687) \tabularnewline
Gdracht;Predation & 0.1316 & 0.1162 & 0.075 \tabularnewline
p-value & (0.4247) & (0.4813) & (0.5352) \tabularnewline
Gdracht;Splaats & 0.5663 & 0.5771 & 0.4617 \tabularnewline
p-value & (2e-04) & (1e-04) & (2e-04) \tabularnewline
Gdracht;Danger & -0.0071 & 0.0013 & -0.0046 \tabularnewline
p-value & (0.9658) & (0.9937) & (0.9699) \tabularnewline
Predation;Splaats & 0.68 & 0.6186 & 0.5218 \tabularnewline
p-value & (0) & (0) & (1e-04) \tabularnewline
Predation;Danger & 0.1345 & 0.1536 & 0.126 \tabularnewline
p-value & (0.4143) & (0.3506) & (0.3404) \tabularnewline
Splaats;Danger & -0.0273 & 0.0231 & 0.0232 \tabularnewline
p-value & (0.869) & (0.8888) & (0.8631) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108757&T=2

[TABLE]
[ROW][C]Correlations for all pairs of data series with p-values[/C][/ROW]
[ROW][C]pair[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]Sloww;Psleep[/C][C]0.5298[/C][C]0.5918[/C][C]0.4165[/C][/ROW]
[ROW][C]p-value[/C][C](5e-04)[/C][C](1e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]Sloww;Lifespan[/C][C]-0.3845[/C][C]-0.4282[/C][C]-0.2999[/C][/ROW]
[ROW][C]p-value[/C][C](0.0156)[/C][C](0.0065)[/C][C](0.0077)[/C][/ROW]
[ROW][C]Sloww;Weight[/C][C]-0.3948[/C][C]-0.6585[/C][C]-0.4813[/C][/ROW]
[ROW][C]p-value[/C][C](0.0129)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Sloww;Wbrain[/C][C]-0.388[/C][C]-0.6599[/C][C]-0.4922[/C][/ROW]
[ROW][C]p-value[/C][C](0.0147)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Sloww;Gdracht[/C][C]-0.6208[/C][C]-0.6623[/C][C]-0.485[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Sloww;Predation[/C][C]-0.3689[/C][C]-0.3119[/C][C]-0.2421[/C][/ROW]
[ROW][C]p-value[/C][C](0.0208)[/C][C](0.0533)[/C][C](0.0458)[/C][/ROW]
[ROW][C]Sloww;Splaats[/C][C]-0.5795[/C][C]-0.5491[/C][C]-0.4299[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](3e-04)[/C][C](5e-04)[/C][/ROW]
[ROW][C]Sloww;Danger[/C][C]0.1268[/C][C]0.0987[/C][C]0.0696[/C][/ROW]
[ROW][C]p-value[/C][C](0.4418)[/C][C](0.55)[/C][C](0.5708)[/C][/ROW]
[ROW][C]Psleep;Lifespan[/C][C]-0.2409[/C][C]-0.3893[/C][C]-0.2373[/C][/ROW]
[ROW][C]p-value[/C][C](0.1396)[/C][C](0.0143)[/C][C](0.036)[/C][/ROW]
[ROW][C]Psleep;Weight[/C][C]-0.088[/C][C]-0.4395[/C][C]-0.2777[/C][/ROW]
[ROW][C]p-value[/C][C](0.5942)[/C][C](0.0051)[/C][C](0.0139)[/C][/ROW]
[ROW][C]Psleep;Wbrain[/C][C]-0.0886[/C][C]-0.5242[/C][C]-0.3242[/C][/ROW]
[ROW][C]p-value[/C][C](0.5915)[/C][C](6e-04)[/C][C](0.0041)[/C][/ROW]
[ROW][C]Psleep;Gdracht[/C][C]-0.4681[/C][C]-0.6521[/C][C]-0.4606[/C][/ROW]
[ROW][C]p-value[/C][C](0.0027)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Psleep;Predation[/C][C]-0.4342[/C][C]-0.5339[/C][C]-0.3919[/C][/ROW]
[ROW][C]p-value[/C][C](0.0057)[/C][C](5e-04)[/C][C](0.0013)[/C][/ROW]
[ROW][C]Psleep;Splaats[/C][C]-0.533[/C][C]-0.6156[/C][C]-0.4706[/C][/ROW]
[ROW][C]p-value[/C][C](5e-04)[/C][C](0)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Psleep;Danger[/C][C]-0.0953[/C][C]-0.058[/C][C]-0.0296[/C][/ROW]
[ROW][C]p-value[/C][C](0.564)[/C][C](0.7259)[/C][C](0.8107)[/C][/ROW]
[ROW][C]Lifespan;Weight[/C][C]0.4923[/C][C]0.7063[/C][C]0.5251[/C][/ROW]
[ROW][C]p-value[/C][C](0.0015)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Lifespan;Wbrain[/C][C]0.6594[/C][C]0.8033[/C][C]0.6499[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Lifespan;Gdracht[/C][C]0.6913[/C][C]0.7115[/C][C]0.533[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Lifespan;Predation[/C][C]-0.1107[/C][C]0.0122[/C][C]-0.006[/C][/ROW]
[ROW][C]p-value[/C][C](0.5023)[/C][C](0.9412)[/C][C](0.9604)[/C][/ROW]
[ROW][C]Lifespan;Splaats[/C][C]0.3192[/C][C]0.5242[/C][C]0.4101[/C][/ROW]
[ROW][C]p-value[/C][C](0.0476)[/C][C](6e-04)[/C][C](9e-04)[/C][/ROW]
[ROW][C]Lifespan;Danger[/C][C]-0.158[/C][C]-0.1506[/C][C]-0.1374[/C][/ROW]
[ROW][C]p-value[/C][C](0.3369)[/C][C](0.3602)[/C][C](0.2624)[/C][/ROW]
[ROW][C]Weight;Wbrain[/C][C]0.9557[/C][C]0.9284[/C][C]0.7916[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Weight;Gdracht[/C][C]0.719[/C][C]0.7095[/C][C]0.5207[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Weight;Predation[/C][C]0.1101[/C][C]0.2147[/C][C]0.1602[/C][/ROW]
[ROW][C]p-value[/C][C](0.5045)[/C][C](0.1893)[/C][C](0.1846)[/C][/ROW]
[ROW][C]Weight;Splaats[/C][C]0.4024[/C][C]0.5954[/C][C]0.4811[/C][/ROW]
[ROW][C]p-value[/C][C](0.0111)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Weight;Danger[/C][C]0.1293[/C][C]-0.1197[/C][C]-0.097[/C][/ROW]
[ROW][C]p-value[/C][C](0.4329)[/C][C](0.4681)[/C][C](0.4277)[/C][/ROW]
[ROW][C]Wbrain;Gdracht[/C][C]0.7369[/C][C]0.8082[/C][C]0.5993[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Wbrain;Predation[/C][C]-0.0034[/C][C]0.1675[/C][C]0.1257[/C][/ROW]
[ROW][C]p-value[/C][C](0.9835)[/C][C](0.3082)[/C][C](0.2976)[/C][/ROW]
[ROW][C]Wbrain;Splaats[/C][C]0.3175[/C][C]0.5976[/C][C]0.4905[/C][/ROW]
[ROW][C]p-value[/C][C](0.0489)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Wbrain;Danger[/C][C]0.0912[/C][C]-0.0549[/C][C]-0.0493[/C][/ROW]
[ROW][C]p-value[/C][C](0.5808)[/C][C](0.7401)[/C][C](0.687)[/C][/ROW]
[ROW][C]Gdracht;Predation[/C][C]0.1316[/C][C]0.1162[/C][C]0.075[/C][/ROW]
[ROW][C]p-value[/C][C](0.4247)[/C][C](0.4813)[/C][C](0.5352)[/C][/ROW]
[ROW][C]Gdracht;Splaats[/C][C]0.5663[/C][C]0.5771[/C][C]0.4617[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](1e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]Gdracht;Danger[/C][C]-0.0071[/C][C]0.0013[/C][C]-0.0046[/C][/ROW]
[ROW][C]p-value[/C][C](0.9658)[/C][C](0.9937)[/C][C](0.9699)[/C][/ROW]
[ROW][C]Predation;Splaats[/C][C]0.68[/C][C]0.6186[/C][C]0.5218[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Predation;Danger[/C][C]0.1345[/C][C]0.1536[/C][C]0.126[/C][/ROW]
[ROW][C]p-value[/C][C](0.4143)[/C][C](0.3506)[/C][C](0.3404)[/C][/ROW]
[ROW][C]Splaats;Danger[/C][C]-0.0273[/C][C]0.0231[/C][C]0.0232[/C][/ROW]
[ROW][C]p-value[/C][C](0.869)[/C][C](0.8888)[/C][C](0.8631)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108757&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108757&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Sloww;Psleep0.52980.59180.4165
p-value(5e-04)(1e-04)(2e-04)
Sloww;Lifespan-0.3845-0.4282-0.2999
p-value(0.0156)(0.0065)(0.0077)
Sloww;Weight-0.3948-0.6585-0.4813
p-value(0.0129)(0)(0)
Sloww;Wbrain-0.388-0.6599-0.4922
p-value(0.0147)(0)(0)
Sloww;Gdracht-0.6208-0.6623-0.485
p-value(0)(0)(0)
Sloww;Predation-0.3689-0.3119-0.2421
p-value(0.0208)(0.0533)(0.0458)
Sloww;Splaats-0.5795-0.5491-0.4299
p-value(1e-04)(3e-04)(5e-04)
Sloww;Danger0.12680.09870.0696
p-value(0.4418)(0.55)(0.5708)
Psleep;Lifespan-0.2409-0.3893-0.2373
p-value(0.1396)(0.0143)(0.036)
Psleep;Weight-0.088-0.4395-0.2777
p-value(0.5942)(0.0051)(0.0139)
Psleep;Wbrain-0.0886-0.5242-0.3242
p-value(0.5915)(6e-04)(0.0041)
Psleep;Gdracht-0.4681-0.6521-0.4606
p-value(0.0027)(0)(0)
Psleep;Predation-0.4342-0.5339-0.3919
p-value(0.0057)(5e-04)(0.0013)
Psleep;Splaats-0.533-0.6156-0.4706
p-value(5e-04)(0)(1e-04)
Psleep;Danger-0.0953-0.058-0.0296
p-value(0.564)(0.7259)(0.8107)
Lifespan;Weight0.49230.70630.5251
p-value(0.0015)(0)(0)
Lifespan;Wbrain0.65940.80330.6499
p-value(0)(0)(0)
Lifespan;Gdracht0.69130.71150.533
p-value(0)(0)(0)
Lifespan;Predation-0.11070.0122-0.006
p-value(0.5023)(0.9412)(0.9604)
Lifespan;Splaats0.31920.52420.4101
p-value(0.0476)(6e-04)(9e-04)
Lifespan;Danger-0.158-0.1506-0.1374
p-value(0.3369)(0.3602)(0.2624)
Weight;Wbrain0.95570.92840.7916
p-value(0)(0)(0)
Weight;Gdracht0.7190.70950.5207
p-value(0)(0)(0)
Weight;Predation0.11010.21470.1602
p-value(0.5045)(0.1893)(0.1846)
Weight;Splaats0.40240.59540.4811
p-value(0.0111)(1e-04)(1e-04)
Weight;Danger0.1293-0.1197-0.097
p-value(0.4329)(0.4681)(0.4277)
Wbrain;Gdracht0.73690.80820.5993
p-value(0)(0)(0)
Wbrain;Predation-0.00340.16750.1257
p-value(0.9835)(0.3082)(0.2976)
Wbrain;Splaats0.31750.59760.4905
p-value(0.0489)(1e-04)(1e-04)
Wbrain;Danger0.0912-0.0549-0.0493
p-value(0.5808)(0.7401)(0.687)
Gdracht;Predation0.13160.11620.075
p-value(0.4247)(0.4813)(0.5352)
Gdracht;Splaats0.56630.57710.4617
p-value(2e-04)(1e-04)(2e-04)
Gdracht;Danger-0.00710.0013-0.0046
p-value(0.9658)(0.9937)(0.9699)
Predation;Splaats0.680.61860.5218
p-value(0)(0)(1e-04)
Predation;Danger0.13450.15360.126
p-value(0.4143)(0.3506)(0.3404)
Splaats;Danger-0.02730.02310.0232
p-value(0.869)(0.8888)(0.8631)



Parameters (Session):
par1 = kendall ;
Parameters (R input):
par1 = kendall ;
R code (references can be found in the software module):
panel.tau <- function(x, y, digits=2, prefix='', cex.cor)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
rr <- cor.test(x, y, method=par1)
r <- round(rr$p.value,2)
txt <- format(c(r, 0.123456789), digits=digits)[1]
txt <- paste(prefix, txt, sep='')
if(missing(cex.cor)) cex <- 0.5/strwidth(txt)
text(0.5, 0.5, txt, cex = cex)
}
panel.hist <- function(x, ...)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(usr[1:2], 0, 1.5) )
h <- hist(x, plot = FALSE)
breaks <- h$breaks; nB <- length(breaks)
y <- h$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
n
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$estimate,3))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'Pearson r',1,TRUE)
a<-table.element(a,'Spearman rho',1,TRUE)
a<-table.element(a,'Kendall tau',1,TRUE)
a<-table.row.end(a)
cor.test(y[1,],y[2,],method=par1)
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='')
a<-table.element(a,dum,header=TRUE)
rp <- cor.test(y[i,],y[j,],method='pearson')
a<-table.element(a,round(rp$estimate,4))
rs <- cor.test(y[i,],y[j,],method='spearman')
a<-table.element(a,round(rs$estimate,4))
rk <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,round(rk$estimate,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=T)
a<-table.element(a,paste('(',round(rp$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rs$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rk$p.value,4),')',sep=''))
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')