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Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationMon, 13 Dec 2010 10:11:04 +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/t12922350199byxtetyumenbaz.htm/, Retrieved Mon, 06 May 2024 18:04:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108758, Retrieved Mon, 06 May 2024 18:04:30 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
- RMP     [ARIMA Forecasting] [Unemployment] [2010-11-29 20:46:45] [b98453cac15ba1066b407e146608df68]
- RMPD        [Kendall tau Correlation Matrix] [Proberen: Alle NA...] [2010-12-13 10:11:04] [67e3c2d70de1dbb070b545ca6c893d5e] [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
8.6	.0	50.0	3.000	25.000	28.0	2	2	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
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
7.7	1.4	2.6	.005	.140	21.5	5	2	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
10.8	2.0	2.0	.048	.330	30.0	4	1	1
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
NA	1.0	23.6	250.000	490.000	440.0	5	5	2
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=108758&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=108758&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108758&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=spearman)
SlowwPsleepLifespanWeightWbrainGdrachtPredationSplaatsDanger
Sloww10.585-0.385-0.632-0.632-0.618-0.397-0.5550.063
Psleep0.5851-0.386-0.397-0.482-0.538-0.491-0.595-0.024
Lifespan-0.385-0.38610.6930.7940.622-0.0660.477-0.068
Weight-0.632-0.3970.69310.9330.7030.1690.57-0.031
Wbrain-0.632-0.4820.7940.93310.7850.1280.5790.018
Gdracht-0.618-0.5380.6220.7030.78510.1480.5660.073
Predation-0.397-0.491-0.0660.1690.1280.14810.6320.051
Splaats-0.555-0.5950.4770.570.5790.5660.63210.032
Danger0.063-0.024-0.068-0.0310.0180.0730.0510.0321

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=spearman) \tabularnewline
  & Sloww & Psleep & Lifespan & Weight & Wbrain & Gdracht & Predation & Splaats & Danger \tabularnewline
Sloww & 1 & 0.585 & -0.385 & -0.632 & -0.632 & -0.618 & -0.397 & -0.555 & 0.063 \tabularnewline
Psleep & 0.585 & 1 & -0.386 & -0.397 & -0.482 & -0.538 & -0.491 & -0.595 & -0.024 \tabularnewline
Lifespan & -0.385 & -0.386 & 1 & 0.693 & 0.794 & 0.622 & -0.066 & 0.477 & -0.068 \tabularnewline
Weight & -0.632 & -0.397 & 0.693 & 1 & 0.933 & 0.703 & 0.169 & 0.57 & -0.031 \tabularnewline
Wbrain & -0.632 & -0.482 & 0.794 & 0.933 & 1 & 0.785 & 0.128 & 0.579 & 0.018 \tabularnewline
Gdracht & -0.618 & -0.538 & 0.622 & 0.703 & 0.785 & 1 & 0.148 & 0.566 & 0.073 \tabularnewline
Predation & -0.397 & -0.491 & -0.066 & 0.169 & 0.128 & 0.148 & 1 & 0.632 & 0.051 \tabularnewline
Splaats & -0.555 & -0.595 & 0.477 & 0.57 & 0.579 & 0.566 & 0.632 & 1 & 0.032 \tabularnewline
Danger & 0.063 & -0.024 & -0.068 & -0.031 & 0.018 & 0.073 & 0.051 & 0.032 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108758&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=spearman)[/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]0.585[/C][C]-0.385[/C][C]-0.632[/C][C]-0.632[/C][C]-0.618[/C][C]-0.397[/C][C]-0.555[/C][C]0.063[/C][/ROW]
[ROW][C]Psleep[/C][C]0.585[/C][C]1[/C][C]-0.386[/C][C]-0.397[/C][C]-0.482[/C][C]-0.538[/C][C]-0.491[/C][C]-0.595[/C][C]-0.024[/C][/ROW]
[ROW][C]Lifespan[/C][C]-0.385[/C][C]-0.386[/C][C]1[/C][C]0.693[/C][C]0.794[/C][C]0.622[/C][C]-0.066[/C][C]0.477[/C][C]-0.068[/C][/ROW]
[ROW][C]Weight[/C][C]-0.632[/C][C]-0.397[/C][C]0.693[/C][C]1[/C][C]0.933[/C][C]0.703[/C][C]0.169[/C][C]0.57[/C][C]-0.031[/C][/ROW]
[ROW][C]Wbrain[/C][C]-0.632[/C][C]-0.482[/C][C]0.794[/C][C]0.933[/C][C]1[/C][C]0.785[/C][C]0.128[/C][C]0.579[/C][C]0.018[/C][/ROW]
[ROW][C]Gdracht[/C][C]-0.618[/C][C]-0.538[/C][C]0.622[/C][C]0.703[/C][C]0.785[/C][C]1[/C][C]0.148[/C][C]0.566[/C][C]0.073[/C][/ROW]
[ROW][C]Predation[/C][C]-0.397[/C][C]-0.491[/C][C]-0.066[/C][C]0.169[/C][C]0.128[/C][C]0.148[/C][C]1[/C][C]0.632[/C][C]0.051[/C][/ROW]
[ROW][C]Splaats[/C][C]-0.555[/C][C]-0.595[/C][C]0.477[/C][C]0.57[/C][C]0.579[/C][C]0.566[/C][C]0.632[/C][C]1[/C][C]0.032[/C][/ROW]
[ROW][C]Danger[/C][C]0.063[/C][C]-0.024[/C][C]-0.068[/C][C]-0.031[/C][C]0.018[/C][C]0.073[/C][C]0.051[/C][C]0.032[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108758&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108758&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=spearman)
SlowwPsleepLifespanWeightWbrainGdrachtPredationSplaatsDanger
Sloww10.585-0.385-0.632-0.632-0.618-0.397-0.5550.063
Psleep0.5851-0.386-0.397-0.482-0.538-0.491-0.595-0.024
Lifespan-0.385-0.38610.6930.7940.622-0.0660.477-0.068
Weight-0.632-0.3970.69310.9330.7030.1690.57-0.031
Wbrain-0.632-0.4820.7940.93310.7850.1280.5790.018
Gdracht-0.618-0.5380.6220.7030.78510.1480.5660.073
Predation-0.397-0.491-0.0660.1690.1280.14810.6320.051
Splaats-0.555-0.5950.4770.570.5790.5660.63210.032
Danger0.063-0.024-0.068-0.0310.0180.0730.0510.0321







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Sloww;Psleep0.51840.58520.4104
p-value(7e-04)(1e-04)(3e-04)
Sloww;Lifespan-0.3652-0.3849-0.2668
p-value(0.0222)(0.0155)(0.0176)
Sloww;Weight-0.4054-0.6318-0.4573
p-value(0.0104)(0)(0)
Sloww;Wbrain-0.3939-0.6322-0.4654
p-value(0.0131)(0)(0)
Sloww;Gdracht-0.606-0.618-0.4524
p-value(0)(0)(1e-04)
Sloww;Predation-0.4415-0.3968-0.3029
p-value(0.0049)(0.0124)(0.0125)
Sloww;Splaats-0.5984-0.5551-0.4321
p-value(1e-04)(2e-04)(5e-04)
Sloww;Danger0.10550.06270.0401
p-value(0.5228)(0.7048)(0.7433)
Psleep;Lifespan-0.2505-0.3862-0.2414
p-value(0.119)(0.0138)(0.0308)
Psleep;Weight-0.0735-0.3967-0.2471
p-value(0.6522)(0.0113)(0.0266)
Psleep;Wbrain-0.0703-0.4825-0.2913
p-value(0.6664)(0.0016)(0.0089)
Psleep;Gdracht-0.4017-0.5382-0.3724
p-value(0.0102)(3e-04)(8e-04)
Psleep;Predation-0.4379-0.4915-0.3616
p-value(0.0047)(0.0013)(0.0027)
Psleep;Splaats-0.4981-0.5948-0.4477
p-value(0.0011)(1e-04)(3e-04)
Psleep;Danger-0.0491-0.0244-0.0059
p-value(0.7633)(0.8814)(0.9613)
Lifespan;Weight0.47650.69280.5042
p-value(0.0019)(0)(0)
Lifespan;Wbrain0.63460.79410.6254
p-value(0)(0)(0)
Lifespan;Gdracht0.59110.6220.4558
p-value(1e-04)(0)(0)
Lifespan;Predation-0.1629-0.0662-0.0688
p-value(0.3151)(0.6848)(0.5653)
Lifespan;Splaats0.28350.47670.3652
p-value(0.0763)(0.0019)(0.0026)
Lifespan;Danger-0.1236-0.0679-0.0749
p-value(0.4473)(0.6774)(0.5362)
Weight;Wbrain0.95630.93260.8046
p-value(0)(0)(0)
Weight;Gdracht0.70580.70290.5148
p-value(0)(0)(0)
Weight;Predation0.09960.16910.1258
p-value(0.5408)(0.297)(0.292)
Weight;Splaats0.40430.57040.4572
p-value(0.0097)(1e-04)(2e-04)
Weight;Danger0.1313-0.0312-0.0322
p-value(0.4193)(0.8485)(0.7897)
Wbrain;Gdracht0.71720.78460.5817
p-value(0)(0)(0)
Wbrain;Predation-0.00960.12790.0929
p-value(0.9529)(0.4316)(0.4364)
Wbrain;Splaats0.31930.57940.478
p-value(0.0446)(1e-04)(1e-04)
Wbrain;Danger0.0990.01790.0015
p-value(0.5432)(0.9127)(0.9903)
Gdracht;Predation0.19180.14840.1002
p-value(0.2358)(0.3607)(0.4019)
Gdracht;Splaats0.59710.56620.4534
p-value(0)(1e-04)(2e-04)
Gdracht;Danger0.02850.07280.0528
p-value(0.8615)(0.6553)(0.6624)
Predation;Splaats0.67220.6320.5382
p-value(0)(0)(0)
Predation;Danger0.02690.05080.044
p-value(0.8691)(0.7555)(0.7369)
Splaats;Danger-0.02850.03220.0286
p-value(0.8616)(0.8435)(0.8292)

\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 & 0.5184 & 0.5852 & 0.4104 \tabularnewline
p-value & (7e-04) & (1e-04) & (3e-04) \tabularnewline
Sloww;Lifespan & -0.3652 & -0.3849 & -0.2668 \tabularnewline
p-value & (0.0222) & (0.0155) & (0.0176) \tabularnewline
Sloww;Weight & -0.4054 & -0.6318 & -0.4573 \tabularnewline
p-value & (0.0104) & (0) & (0) \tabularnewline
Sloww;Wbrain & -0.3939 & -0.6322 & -0.4654 \tabularnewline
p-value & (0.0131) & (0) & (0) \tabularnewline
Sloww;Gdracht & -0.606 & -0.618 & -0.4524 \tabularnewline
p-value & (0) & (0) & (1e-04) \tabularnewline
Sloww;Predation & -0.4415 & -0.3968 & -0.3029 \tabularnewline
p-value & (0.0049) & (0.0124) & (0.0125) \tabularnewline
Sloww;Splaats & -0.5984 & -0.5551 & -0.4321 \tabularnewline
p-value & (1e-04) & (2e-04) & (5e-04) \tabularnewline
Sloww;Danger & 0.1055 & 0.0627 & 0.0401 \tabularnewline
p-value & (0.5228) & (0.7048) & (0.7433) \tabularnewline
Psleep;Lifespan & -0.2505 & -0.3862 & -0.2414 \tabularnewline
p-value & (0.119) & (0.0138) & (0.0308) \tabularnewline
Psleep;Weight & -0.0735 & -0.3967 & -0.2471 \tabularnewline
p-value & (0.6522) & (0.0113) & (0.0266) \tabularnewline
Psleep;Wbrain & -0.0703 & -0.4825 & -0.2913 \tabularnewline
p-value & (0.6664) & (0.0016) & (0.0089) \tabularnewline
Psleep;Gdracht & -0.4017 & -0.5382 & -0.3724 \tabularnewline
p-value & (0.0102) & (3e-04) & (8e-04) \tabularnewline
Psleep;Predation & -0.4379 & -0.4915 & -0.3616 \tabularnewline
p-value & (0.0047) & (0.0013) & (0.0027) \tabularnewline
Psleep;Splaats & -0.4981 & -0.5948 & -0.4477 \tabularnewline
p-value & (0.0011) & (1e-04) & (3e-04) \tabularnewline
Psleep;Danger & -0.0491 & -0.0244 & -0.0059 \tabularnewline
p-value & (0.7633) & (0.8814) & (0.9613) \tabularnewline
Lifespan;Weight & 0.4765 & 0.6928 & 0.5042 \tabularnewline
p-value & (0.0019) & (0) & (0) \tabularnewline
Lifespan;Wbrain & 0.6346 & 0.7941 & 0.6254 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Lifespan;Gdracht & 0.5911 & 0.622 & 0.4558 \tabularnewline
p-value & (1e-04) & (0) & (0) \tabularnewline
Lifespan;Predation & -0.1629 & -0.0662 & -0.0688 \tabularnewline
p-value & (0.3151) & (0.6848) & (0.5653) \tabularnewline
Lifespan;Splaats & 0.2835 & 0.4767 & 0.3652 \tabularnewline
p-value & (0.0763) & (0.0019) & (0.0026) \tabularnewline
Lifespan;Danger & -0.1236 & -0.0679 & -0.0749 \tabularnewline
p-value & (0.4473) & (0.6774) & (0.5362) \tabularnewline
Weight;Wbrain & 0.9563 & 0.9326 & 0.8046 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Weight;Gdracht & 0.7058 & 0.7029 & 0.5148 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Weight;Predation & 0.0996 & 0.1691 & 0.1258 \tabularnewline
p-value & (0.5408) & (0.297) & (0.292) \tabularnewline
Weight;Splaats & 0.4043 & 0.5704 & 0.4572 \tabularnewline
p-value & (0.0097) & (1e-04) & (2e-04) \tabularnewline
Weight;Danger & 0.1313 & -0.0312 & -0.0322 \tabularnewline
p-value & (0.4193) & (0.8485) & (0.7897) \tabularnewline
Wbrain;Gdracht & 0.7172 & 0.7846 & 0.5817 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Wbrain;Predation & -0.0096 & 0.1279 & 0.0929 \tabularnewline
p-value & (0.9529) & (0.4316) & (0.4364) \tabularnewline
Wbrain;Splaats & 0.3193 & 0.5794 & 0.478 \tabularnewline
p-value & (0.0446) & (1e-04) & (1e-04) \tabularnewline
Wbrain;Danger & 0.099 & 0.0179 & 0.0015 \tabularnewline
p-value & (0.5432) & (0.9127) & (0.9903) \tabularnewline
Gdracht;Predation & 0.1918 & 0.1484 & 0.1002 \tabularnewline
p-value & (0.2358) & (0.3607) & (0.4019) \tabularnewline
Gdracht;Splaats & 0.5971 & 0.5662 & 0.4534 \tabularnewline
p-value & (0) & (1e-04) & (2e-04) \tabularnewline
Gdracht;Danger & 0.0285 & 0.0728 & 0.0528 \tabularnewline
p-value & (0.8615) & (0.6553) & (0.6624) \tabularnewline
Predation;Splaats & 0.6722 & 0.632 & 0.5382 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Predation;Danger & 0.0269 & 0.0508 & 0.044 \tabularnewline
p-value & (0.8691) & (0.7555) & (0.7369) \tabularnewline
Splaats;Danger & -0.0285 & 0.0322 & 0.0286 \tabularnewline
p-value & (0.8616) & (0.8435) & (0.8292) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108758&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]0.5184[/C][C]0.5852[/C][C]0.4104[/C][/ROW]
[ROW][C]p-value[/C][C](7e-04)[/C][C](1e-04)[/C][C](3e-04)[/C][/ROW]
[ROW][C]Sloww;Lifespan[/C][C]-0.3652[/C][C]-0.3849[/C][C]-0.2668[/C][/ROW]
[ROW][C]p-value[/C][C](0.0222)[/C][C](0.0155)[/C][C](0.0176)[/C][/ROW]
[ROW][C]Sloww;Weight[/C][C]-0.4054[/C][C]-0.6318[/C][C]-0.4573[/C][/ROW]
[ROW][C]p-value[/C][C](0.0104)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Sloww;Wbrain[/C][C]-0.3939[/C][C]-0.6322[/C][C]-0.4654[/C][/ROW]
[ROW][C]p-value[/C][C](0.0131)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Sloww;Gdracht[/C][C]-0.606[/C][C]-0.618[/C][C]-0.4524[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Sloww;Predation[/C][C]-0.4415[/C][C]-0.3968[/C][C]-0.3029[/C][/ROW]
[ROW][C]p-value[/C][C](0.0049)[/C][C](0.0124)[/C][C](0.0125)[/C][/ROW]
[ROW][C]Sloww;Splaats[/C][C]-0.5984[/C][C]-0.5551[/C][C]-0.4321[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](2e-04)[/C][C](5e-04)[/C][/ROW]
[ROW][C]Sloww;Danger[/C][C]0.1055[/C][C]0.0627[/C][C]0.0401[/C][/ROW]
[ROW][C]p-value[/C][C](0.5228)[/C][C](0.7048)[/C][C](0.7433)[/C][/ROW]
[ROW][C]Psleep;Lifespan[/C][C]-0.2505[/C][C]-0.3862[/C][C]-0.2414[/C][/ROW]
[ROW][C]p-value[/C][C](0.119)[/C][C](0.0138)[/C][C](0.0308)[/C][/ROW]
[ROW][C]Psleep;Weight[/C][C]-0.0735[/C][C]-0.3967[/C][C]-0.2471[/C][/ROW]
[ROW][C]p-value[/C][C](0.6522)[/C][C](0.0113)[/C][C](0.0266)[/C][/ROW]
[ROW][C]Psleep;Wbrain[/C][C]-0.0703[/C][C]-0.4825[/C][C]-0.2913[/C][/ROW]
[ROW][C]p-value[/C][C](0.6664)[/C][C](0.0016)[/C][C](0.0089)[/C][/ROW]
[ROW][C]Psleep;Gdracht[/C][C]-0.4017[/C][C]-0.5382[/C][C]-0.3724[/C][/ROW]
[ROW][C]p-value[/C][C](0.0102)[/C][C](3e-04)[/C][C](8e-04)[/C][/ROW]
[ROW][C]Psleep;Predation[/C][C]-0.4379[/C][C]-0.4915[/C][C]-0.3616[/C][/ROW]
[ROW][C]p-value[/C][C](0.0047)[/C][C](0.0013)[/C][C](0.0027)[/C][/ROW]
[ROW][C]Psleep;Splaats[/C][C]-0.4981[/C][C]-0.5948[/C][C]-0.4477[/C][/ROW]
[ROW][C]p-value[/C][C](0.0011)[/C][C](1e-04)[/C][C](3e-04)[/C][/ROW]
[ROW][C]Psleep;Danger[/C][C]-0.0491[/C][C]-0.0244[/C][C]-0.0059[/C][/ROW]
[ROW][C]p-value[/C][C](0.7633)[/C][C](0.8814)[/C][C](0.9613)[/C][/ROW]
[ROW][C]Lifespan;Weight[/C][C]0.4765[/C][C]0.6928[/C][C]0.5042[/C][/ROW]
[ROW][C]p-value[/C][C](0.0019)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Lifespan;Wbrain[/C][C]0.6346[/C][C]0.7941[/C][C]0.6254[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Lifespan;Gdracht[/C][C]0.5911[/C][C]0.622[/C][C]0.4558[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Lifespan;Predation[/C][C]-0.1629[/C][C]-0.0662[/C][C]-0.0688[/C][/ROW]
[ROW][C]p-value[/C][C](0.3151)[/C][C](0.6848)[/C][C](0.5653)[/C][/ROW]
[ROW][C]Lifespan;Splaats[/C][C]0.2835[/C][C]0.4767[/C][C]0.3652[/C][/ROW]
[ROW][C]p-value[/C][C](0.0763)[/C][C](0.0019)[/C][C](0.0026)[/C][/ROW]
[ROW][C]Lifespan;Danger[/C][C]-0.1236[/C][C]-0.0679[/C][C]-0.0749[/C][/ROW]
[ROW][C]p-value[/C][C](0.4473)[/C][C](0.6774)[/C][C](0.5362)[/C][/ROW]
[ROW][C]Weight;Wbrain[/C][C]0.9563[/C][C]0.9326[/C][C]0.8046[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Weight;Gdracht[/C][C]0.7058[/C][C]0.7029[/C][C]0.5148[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Weight;Predation[/C][C]0.0996[/C][C]0.1691[/C][C]0.1258[/C][/ROW]
[ROW][C]p-value[/C][C](0.5408)[/C][C](0.297)[/C][C](0.292)[/C][/ROW]
[ROW][C]Weight;Splaats[/C][C]0.4043[/C][C]0.5704[/C][C]0.4572[/C][/ROW]
[ROW][C]p-value[/C][C](0.0097)[/C][C](1e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]Weight;Danger[/C][C]0.1313[/C][C]-0.0312[/C][C]-0.0322[/C][/ROW]
[ROW][C]p-value[/C][C](0.4193)[/C][C](0.8485)[/C][C](0.7897)[/C][/ROW]
[ROW][C]Wbrain;Gdracht[/C][C]0.7172[/C][C]0.7846[/C][C]0.5817[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Wbrain;Predation[/C][C]-0.0096[/C][C]0.1279[/C][C]0.0929[/C][/ROW]
[ROW][C]p-value[/C][C](0.9529)[/C][C](0.4316)[/C][C](0.4364)[/C][/ROW]
[ROW][C]Wbrain;Splaats[/C][C]0.3193[/C][C]0.5794[/C][C]0.478[/C][/ROW]
[ROW][C]p-value[/C][C](0.0446)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Wbrain;Danger[/C][C]0.099[/C][C]0.0179[/C][C]0.0015[/C][/ROW]
[ROW][C]p-value[/C][C](0.5432)[/C][C](0.9127)[/C][C](0.9903)[/C][/ROW]
[ROW][C]Gdracht;Predation[/C][C]0.1918[/C][C]0.1484[/C][C]0.1002[/C][/ROW]
[ROW][C]p-value[/C][C](0.2358)[/C][C](0.3607)[/C][C](0.4019)[/C][/ROW]
[ROW][C]Gdracht;Splaats[/C][C]0.5971[/C][C]0.5662[/C][C]0.4534[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]Gdracht;Danger[/C][C]0.0285[/C][C]0.0728[/C][C]0.0528[/C][/ROW]
[ROW][C]p-value[/C][C](0.8615)[/C][C](0.6553)[/C][C](0.6624)[/C][/ROW]
[ROW][C]Predation;Splaats[/C][C]0.6722[/C][C]0.632[/C][C]0.5382[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Predation;Danger[/C][C]0.0269[/C][C]0.0508[/C][C]0.044[/C][/ROW]
[ROW][C]p-value[/C][C](0.8691)[/C][C](0.7555)[/C][C](0.7369)[/C][/ROW]
[ROW][C]Splaats;Danger[/C][C]-0.0285[/C][C]0.0322[/C][C]0.0286[/C][/ROW]
[ROW][C]p-value[/C][C](0.8616)[/C][C](0.8435)[/C][C](0.8292)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108758&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108758&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;Psleep0.51840.58520.4104
p-value(7e-04)(1e-04)(3e-04)
Sloww;Lifespan-0.3652-0.3849-0.2668
p-value(0.0222)(0.0155)(0.0176)
Sloww;Weight-0.4054-0.6318-0.4573
p-value(0.0104)(0)(0)
Sloww;Wbrain-0.3939-0.6322-0.4654
p-value(0.0131)(0)(0)
Sloww;Gdracht-0.606-0.618-0.4524
p-value(0)(0)(1e-04)
Sloww;Predation-0.4415-0.3968-0.3029
p-value(0.0049)(0.0124)(0.0125)
Sloww;Splaats-0.5984-0.5551-0.4321
p-value(1e-04)(2e-04)(5e-04)
Sloww;Danger0.10550.06270.0401
p-value(0.5228)(0.7048)(0.7433)
Psleep;Lifespan-0.2505-0.3862-0.2414
p-value(0.119)(0.0138)(0.0308)
Psleep;Weight-0.0735-0.3967-0.2471
p-value(0.6522)(0.0113)(0.0266)
Psleep;Wbrain-0.0703-0.4825-0.2913
p-value(0.6664)(0.0016)(0.0089)
Psleep;Gdracht-0.4017-0.5382-0.3724
p-value(0.0102)(3e-04)(8e-04)
Psleep;Predation-0.4379-0.4915-0.3616
p-value(0.0047)(0.0013)(0.0027)
Psleep;Splaats-0.4981-0.5948-0.4477
p-value(0.0011)(1e-04)(3e-04)
Psleep;Danger-0.0491-0.0244-0.0059
p-value(0.7633)(0.8814)(0.9613)
Lifespan;Weight0.47650.69280.5042
p-value(0.0019)(0)(0)
Lifespan;Wbrain0.63460.79410.6254
p-value(0)(0)(0)
Lifespan;Gdracht0.59110.6220.4558
p-value(1e-04)(0)(0)
Lifespan;Predation-0.1629-0.0662-0.0688
p-value(0.3151)(0.6848)(0.5653)
Lifespan;Splaats0.28350.47670.3652
p-value(0.0763)(0.0019)(0.0026)
Lifespan;Danger-0.1236-0.0679-0.0749
p-value(0.4473)(0.6774)(0.5362)
Weight;Wbrain0.95630.93260.8046
p-value(0)(0)(0)
Weight;Gdracht0.70580.70290.5148
p-value(0)(0)(0)
Weight;Predation0.09960.16910.1258
p-value(0.5408)(0.297)(0.292)
Weight;Splaats0.40430.57040.4572
p-value(0.0097)(1e-04)(2e-04)
Weight;Danger0.1313-0.0312-0.0322
p-value(0.4193)(0.8485)(0.7897)
Wbrain;Gdracht0.71720.78460.5817
p-value(0)(0)(0)
Wbrain;Predation-0.00960.12790.0929
p-value(0.9529)(0.4316)(0.4364)
Wbrain;Splaats0.31930.57940.478
p-value(0.0446)(1e-04)(1e-04)
Wbrain;Danger0.0990.01790.0015
p-value(0.5432)(0.9127)(0.9903)
Gdracht;Predation0.19180.14840.1002
p-value(0.2358)(0.3607)(0.4019)
Gdracht;Splaats0.59710.56620.4534
p-value(0)(1e-04)(2e-04)
Gdracht;Danger0.02850.07280.0528
p-value(0.8615)(0.6553)(0.6624)
Predation;Splaats0.67220.6320.5382
p-value(0)(0)(0)
Predation;Danger0.02690.05080.044
p-value(0.8691)(0.7555)(0.7369)
Splaats;Danger-0.02850.03220.0286
p-value(0.8616)(0.8435)(0.8292)



Parameters (Session):
par1 = spearman ;
Parameters (R input):
par1 = spearman ;
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')