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rwasp_pairs.wasp

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Kendall tau Correlation Matrix

Date of computation

Mon, 13 Dec 2010 18:47:35 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/13/t12922676871t03pzsohro5nhj.htm/, Retrieved Mon, 06 May 2024 12:43:28 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109088, Retrieved Mon, 06 May 2024 12:43:28 +0000

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130

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Kendall tau Correlation Matrix] [Correlation scien...] [2010-12-13 18:47:35] [b6992a7b26e556359948e164e4227eba] [Current]
-   PD    [Kendall tau Correlation Matrix] [Correlation scien...] [2010-12-13 20:30:41] [6bc4f9343b7ea3ef5a59412d1f72bb2b] 
- RMPD    [Multiple Regression] [Multiple regressi...] [2010-12-14 10:04:25] [6bc4f9343b7ea3ef5a59412d1f72bb2b] 
- RMPD      [Recursive Partitioning (Regression Trees)] [SWS Tree no categ...] [2010-12-14 10:20:00] [6bc4f9343b7ea3ef5a59412d1f72bb2b] 
- RMPD      [Recursive Partitioning (Regression Trees)] [SWS Tree no categ...] [2010-12-14 10:29:52] [6bc4f9343b7ea3ef5a59412d1f72bb2b] 
- RMPD      [Recursive Partitioning (Regression Trees)] [PS Tree no catego...] [2010-12-14 10:34:44] [6bc4f9343b7ea3ef5a59412d1f72bb2b] 
- RMPD    [Multiple Regression] [Multiple Regressi...] [2010-12-14 10:10:50] [6bc4f9343b7ea3ef5a59412d1f72bb2b] 

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6,3	0,3	4,5	0,000	6,600	1,6	3	1	3
2,1	0,3	69,0	3,406	4603,000	2,8	3	5	4
9,1	-0,2	27,0	1,023	179,500	2,3	4	4	4
15,8	0,6	19,0	-1,638	0,300	1,5	1	1	1
5,2	0,0	30,4	2,204	169,000	2,6	4	5	4
10,9	0,6	28,0	0,519	25,600	1,8	1	2	1
8,3	0,1	50,0	1,717	440,000	2,4	1	1	1
11,0	0,2	7,0	-0,372	6,400	2,0	5	4	4
3,2	-0,2	30,0	2,667	423,000	2,4	5	5	5
6,3	0,3	3,5	-1,125	1,200	1,6	1	1	1
6,6	0,6	6,0	-0,105	3,500	1,6	2	2	2
9,5	0,1	10,4	-0,699	5,000	2,1	2	2	2
3,3	-0,3	20,0	1,442	115,000	2,2	5	5	5
11,0	0,5	3,9	-0,921	1,000	1,2	3	1	2
4,7	0,2	41,0	1,929	325,000	2,5	1	3	1
10,4	0,5	9,0	-0,996	4,000	1,4	5	1	3
7,4	-0,1	7,6	0,017	5,500	1,8	5	3	4
2,1	-0,1	46,0	2,717	655,000	2,5	5	5	5
17,9	0,3	24,0	-2,000	0,250	1,7	1	1	1
6,1	0,3	100,0	1,792	1320,000	2,4	1	1	1
11,9	0,1	3,2	-1,638	0,400	1,3	4	1	3
13,8	0,7	5,0	0,230	6,300	1,1	2	1	1
14,3	0,5	6,5	0,544	10,800	2,1	2	1	1
15,2	0,3	12,0	-0,319	15,500	2,1	2	2	2
10,0	0,0	20,2	1,000	115,000	2,2	4	4	4
11,9	0,3	13,0	0,210	11,400	1,2	2	1	2
6,5	0,3	27,0	2,283	180,000	2,1	4	4	4
7,5	0,0	18,0	0,398	12,100	1,5	5	5	5
10,6	0,4	4,7	-0,553	1,900	1,3	3	1	3
7,4	0,4	9,8	0,627	50,400	1,7	1	1	1
8,4	0,1	29,0	0,833	179,000	2,2	2	3	2
5,7	0,0	7,0	-0,125	12,300	2,4	2	2	2
4,9	-0,3	6,0	0,556	21,000	2,4	3	2	3
3,2	-0,2	20,0	1,744	175,000	2,2	5	5	5
11,0	0,4	4,5	-0,046	2,600	1,8	2	1	2
4,9	-0,3	7,5	0,301	12,300	2,3	3	1	3
13,2	0,4	2,3	-0,983	2,500	1,7	3	2	2
9,7	-0,2	24,0	0,622	58,000	2,3	4	3	4
12,8	0,8	3,0	0,544	3,900	1,1	2	1	1

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109088&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109088&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109088&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Correlations for all pairs of data series (method=pearson)
	SWS	logPS	maxLifeSpan	logBodyWeight	brainWeight	logGestationTime	predation	sleepExposure	danger
SWS	1	0.583	-0.385	-0.712	-0.388	-0.602	-0.369	-0.58	-0.542
logPS	0.583	1	-0.153	-0.364	-0.007	-0.634	-0.55	-0.578	-0.686
maxLifeSpan	-0.385	-0.153	1	0.652	0.659	0.596	-0.111	0.319	0.06
logBodyWeight	-0.712	-0.364	0.652	1	0.539	0.692	0.253	0.662	0.432
brainWeight	-0.388	-0.007	0.659	0.539	1	0.442	-0.003	0.318	0.159
logGestationTime	-0.602	-0.634	0.596	0.692	0.442	1	0.142	0.577	0.348
predation	-0.369	-0.55	-0.111	0.253	-0.003	0.142	1	0.68	0.93
sleepExposure	-0.58	-0.578	0.319	0.662	0.318	0.577	0.68	1	0.819
danger	-0.542	-0.686	0.06	0.432	0.159	0.348	0.93	0.819	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & SWS & logPS & maxLifeSpan & logBodyWeight & brainWeight & logGestationTime & predation & sleepExposure & danger \tabularnewline
SWS & 1 & 0.583 & -0.385 & -0.712 & -0.388 & -0.602 & -0.369 & -0.58 & -0.542 \tabularnewline
logPS & 0.583 & 1 & -0.153 & -0.364 & -0.007 & -0.634 & -0.55 & -0.578 & -0.686 \tabularnewline
maxLifeSpan & -0.385 & -0.153 & 1 & 0.652 & 0.659 & 0.596 & -0.111 & 0.319 & 0.06 \tabularnewline
logBodyWeight & -0.712 & -0.364 & 0.652 & 1 & 0.539 & 0.692 & 0.253 & 0.662 & 0.432 \tabularnewline
brainWeight & -0.388 & -0.007 & 0.659 & 0.539 & 1 & 0.442 & -0.003 & 0.318 & 0.159 \tabularnewline
logGestationTime & -0.602 & -0.634 & 0.596 & 0.692 & 0.442 & 1 & 0.142 & 0.577 & 0.348 \tabularnewline
predation & -0.369 & -0.55 & -0.111 & 0.253 & -0.003 & 0.142 & 1 & 0.68 & 0.93 \tabularnewline
sleepExposure & -0.58 & -0.578 & 0.319 & 0.662 & 0.318 & 0.577 & 0.68 & 1 & 0.819 \tabularnewline
danger & -0.542 & -0.686 & 0.06 & 0.432 & 0.159 & 0.348 & 0.93 & 0.819 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109088&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]SWS[/C][C]logPS[/C][C]maxLifeSpan[/C][C]logBodyWeight[/C][C]brainWeight[/C][C]logGestationTime[/C][C]predation[/C][C]sleepExposure[/C][C]danger[/C][/ROW]
[ROW][C]SWS[/C][C]1[/C][C]0.583[/C][C]-0.385[/C][C]-0.712[/C][C]-0.388[/C][C]-0.602[/C][C]-0.369[/C][C]-0.58[/C][C]-0.542[/C][/ROW]
[ROW][C]logPS[/C][C]0.583[/C][C]1[/C][C]-0.153[/C][C]-0.364[/C][C]-0.007[/C][C]-0.634[/C][C]-0.55[/C][C]-0.578[/C][C]-0.686[/C][/ROW]
[ROW][C]maxLifeSpan[/C][C]-0.385[/C][C]-0.153[/C][C]1[/C][C]0.652[/C][C]0.659[/C][C]0.596[/C][C]-0.111[/C][C]0.319[/C][C]0.06[/C][/ROW]
[ROW][C]logBodyWeight[/C][C]-0.712[/C][C]-0.364[/C][C]0.652[/C][C]1[/C][C]0.539[/C][C]0.692[/C][C]0.253[/C][C]0.662[/C][C]0.432[/C][/ROW]
[ROW][C]brainWeight[/C][C]-0.388[/C][C]-0.007[/C][C]0.659[/C][C]0.539[/C][C]1[/C][C]0.442[/C][C]-0.003[/C][C]0.318[/C][C]0.159[/C][/ROW]
[ROW][C]logGestationTime[/C][C]-0.602[/C][C]-0.634[/C][C]0.596[/C][C]0.692[/C][C]0.442[/C][C]1[/C][C]0.142[/C][C]0.577[/C][C]0.348[/C][/ROW]
[ROW][C]predation[/C][C]-0.369[/C][C]-0.55[/C][C]-0.111[/C][C]0.253[/C][C]-0.003[/C][C]0.142[/C][C]1[/C][C]0.68[/C][C]0.93[/C][/ROW]
[ROW][C]sleepExposure[/C][C]-0.58[/C][C]-0.578[/C][C]0.319[/C][C]0.662[/C][C]0.318[/C][C]0.577[/C][C]0.68[/C][C]1[/C][C]0.819[/C][/ROW]
[ROW][C]danger[/C][C]-0.542[/C][C]-0.686[/C][C]0.06[/C][C]0.432[/C][C]0.159[/C][C]0.348[/C][C]0.93[/C][C]0.819[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109088&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109088&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=pearson)
	SWS	logPS	maxLifeSpan	logBodyWeight	brainWeight	logGestationTime	predation	sleepExposure	danger
SWS	1	0.583	-0.385	-0.712	-0.388	-0.602	-0.369	-0.58	-0.542
logPS	0.583	1	-0.153	-0.364	-0.007	-0.634	-0.55	-0.578	-0.686
maxLifeSpan	-0.385	-0.153	1	0.652	0.659	0.596	-0.111	0.319	0.06
logBodyWeight	-0.712	-0.364	0.652	1	0.539	0.692	0.253	0.662	0.432
brainWeight	-0.388	-0.007	0.659	0.539	1	0.442	-0.003	0.318	0.159
logGestationTime	-0.602	-0.634	0.596	0.692	0.442	1	0.142	0.577	0.348
predation	-0.369	-0.55	-0.111	0.253	-0.003	0.142	1	0.68	0.93
sleepExposure	-0.58	-0.578	0.319	0.662	0.318	0.577	0.68	1	0.819
danger	-0.542	-0.686	0.06	0.432	0.159	0.348	0.93	0.819	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
SWS;logPS	0.5831	0.6062	0.44
p-value	(1e-04)	(0)	(2e-04)
SWS;maxLifeSpan	-0.3845	-0.4282	-0.2999
p-value	(0.0156)	(0.0065)	(0.0077)
SWS;logBodyWeight	-0.7116	-0.6585	-0.4813
p-value	(0)	(0)	(0)
SWS;brainWeight	-0.388	-0.6599	-0.4922
p-value	(0.0147)	(0)	(0)
SWS;logGestationTime	-0.6021	-0.6724	-0.5022
p-value	(1e-04)	(0)	(0)
SWS;predation	-0.3689	-0.3119	-0.2421
p-value	(0.0208)	(0.0533)	(0.0458)
SWS;sleepExposure	-0.5795	-0.5491	-0.4299
p-value	(1e-04)	(3e-04)	(5e-04)
SWS;danger	-0.5422	-0.4905	-0.3888
p-value	(4e-04)	(0.0015)	(0.0014)
logPS;maxLifeSpan	-0.1532	-0.3692	-0.238
p-value	(0.3519)	(0.0207)	(0.0404)
logPS;logBodyWeight	-0.3643	-0.4175	-0.2712
p-value	(0.0226)	(0.0082)	(0.0192)
logPS;brainWeight	-0.007	-0.4971	-0.3193
p-value	(0.9664)	(0.0013)	(0.0058)
logPS;logGestationTime	-0.6345	-0.647	-0.4798
p-value	(0)	(0)	(1e-04)
logPS;predation	-0.5502	-0.535	-0.4032
p-value	(3e-04)	(4e-04)	(0.0013)
logPS;sleepExposure	-0.5782	-0.5976	-0.4712
p-value	(1e-04)	(1e-04)	(2e-04)
logPS;danger	-0.6864	-0.675	-0.5376
p-value	(0)	(0)	(0)
maxLifeSpan;logBodyWeight	0.6524	0.7063	0.5251
p-value	(0)	(0)	(0)
maxLifeSpan;brainWeight	0.6594	0.8033	0.6499
p-value	(0)	(0)	(0)
maxLifeSpan;logGestationTime	0.5957	0.6945	0.5304
p-value	(1e-04)	(0)	(0)
maxLifeSpan;predation	-0.1107	0.0122	-0.006
p-value	(0.5023)	(0.9412)	(0.9604)
maxLifeSpan;sleepExposure	0.3192	0.5242	0.4101
p-value	(0.0476)	(6e-04)	(9e-04)
maxLifeSpan;danger	0.0605	0.2072	0.1615
p-value	(0.7146)	(0.2057)	(0.1831)
logBodyWeight;brainWeight	0.539	0.9284	0.7916
p-value	(4e-04)	(0)	(0)
logBodyWeight;logGestationTime	0.6925	0.7051	0.522
p-value	(0)	(0)	(0)
logBodyWeight;predation	0.2529	0.2147	0.1602
p-value	(0.1204)	(0.1893)	(0.1846)
logBodyWeight;sleepExposure	0.6624	0.5954	0.4811
p-value	(0)	(1e-04)	(1e-04)
logBodyWeight;danger	0.4321	0.3615	0.274
p-value	(0.006)	(0.0238)	(0.0236)
brainWeight;logGestationTime	0.4424	0.8016	0.6039
p-value	(0.0048)	(0)	(0)
brainWeight;predation	-0.0034	0.1675	0.1257
p-value	(0.9835)	(0.3082)	(0.2976)
brainWeight;sleepExposure	0.3175	0.5976	0.4905
p-value	(0.0489)	(1e-04)	(1e-04)
brainWeight;danger	0.1594	0.3414	0.2695
p-value	(0.3323)	(0.0334)	(0.026)
logGestationTime;predation	0.1422	0.1216	0.0906
p-value	(0.388)	(0.4608)	(0.4629)
logGestationTime;sleepExposure	0.5766	0.5823	0.4808
p-value	(1e-04)	(1e-04)	(1e-04)
logGestationTime;danger	0.3482	0.3159	0.2441
p-value	(0.0299)	(0.0501)	(0.0486)
predation;sleepExposure	0.68	0.6186	0.5218
p-value	(0)	(0)	(1e-04)
predation;danger	0.9303	0.9328	0.876
p-value	(0)	(0)	(0)
sleepExposure;danger	0.8192	0.7533	0.6591
p-value	(0)	(0)	(0)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
SWS;logPS & 0.5831 & 0.6062 & 0.44 \tabularnewline
p-value & (1e-04) & (0) & (2e-04) \tabularnewline
SWS;maxLifeSpan & -0.3845 & -0.4282 & -0.2999 \tabularnewline
p-value & (0.0156) & (0.0065) & (0.0077) \tabularnewline
SWS;logBodyWeight & -0.7116 & -0.6585 & -0.4813 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
SWS;brainWeight & -0.388 & -0.6599 & -0.4922 \tabularnewline
p-value & (0.0147) & (0) & (0) \tabularnewline
SWS;logGestationTime & -0.6021 & -0.6724 & -0.5022 \tabularnewline
p-value & (1e-04) & (0) & (0) \tabularnewline
SWS;predation & -0.3689 & -0.3119 & -0.2421 \tabularnewline
p-value & (0.0208) & (0.0533) & (0.0458) \tabularnewline
SWS;sleepExposure & -0.5795 & -0.5491 & -0.4299 \tabularnewline
p-value & (1e-04) & (3e-04) & (5e-04) \tabularnewline
SWS;danger & -0.5422 & -0.4905 & -0.3888 \tabularnewline
p-value & (4e-04) & (0.0015) & (0.0014) \tabularnewline
logPS;maxLifeSpan & -0.1532 & -0.3692 & -0.238 \tabularnewline
p-value & (0.3519) & (0.0207) & (0.0404) \tabularnewline
logPS;logBodyWeight & -0.3643 & -0.4175 & -0.2712 \tabularnewline
p-value & (0.0226) & (0.0082) & (0.0192) \tabularnewline
logPS;brainWeight & -0.007 & -0.4971 & -0.3193 \tabularnewline
p-value & (0.9664) & (0.0013) & (0.0058) \tabularnewline
logPS;logGestationTime & -0.6345 & -0.647 & -0.4798 \tabularnewline
p-value & (0) & (0) & (1e-04) \tabularnewline
logPS;predation & -0.5502 & -0.535 & -0.4032 \tabularnewline
p-value & (3e-04) & (4e-04) & (0.0013) \tabularnewline
logPS;sleepExposure & -0.5782 & -0.5976 & -0.4712 \tabularnewline
p-value & (1e-04) & (1e-04) & (2e-04) \tabularnewline
logPS;danger & -0.6864 & -0.675 & -0.5376 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
maxLifeSpan;logBodyWeight & 0.6524 & 0.7063 & 0.5251 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
maxLifeSpan;brainWeight & 0.6594 & 0.8033 & 0.6499 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
maxLifeSpan;logGestationTime & 0.5957 & 0.6945 & 0.5304 \tabularnewline
p-value & (1e-04) & (0) & (0) \tabularnewline
maxLifeSpan;predation & -0.1107 & 0.0122 & -0.006 \tabularnewline
p-value & (0.5023) & (0.9412) & (0.9604) \tabularnewline
maxLifeSpan;sleepExposure & 0.3192 & 0.5242 & 0.4101 \tabularnewline
p-value & (0.0476) & (6e-04) & (9e-04) \tabularnewline
maxLifeSpan;danger & 0.0605 & 0.2072 & 0.1615 \tabularnewline
p-value & (0.7146) & (0.2057) & (0.1831) \tabularnewline
logBodyWeight;brainWeight & 0.539 & 0.9284 & 0.7916 \tabularnewline
p-value & (4e-04) & (0) & (0) \tabularnewline
logBodyWeight;logGestationTime & 0.6925 & 0.7051 & 0.522 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
logBodyWeight;predation & 0.2529 & 0.2147 & 0.1602 \tabularnewline
p-value & (0.1204) & (0.1893) & (0.1846) \tabularnewline
logBodyWeight;sleepExposure & 0.6624 & 0.5954 & 0.4811 \tabularnewline
p-value & (0) & (1e-04) & (1e-04) \tabularnewline
logBodyWeight;danger & 0.4321 & 0.3615 & 0.274 \tabularnewline
p-value & (0.006) & (0.0238) & (0.0236) \tabularnewline
brainWeight;logGestationTime & 0.4424 & 0.8016 & 0.6039 \tabularnewline
p-value & (0.0048) & (0) & (0) \tabularnewline
brainWeight;predation & -0.0034 & 0.1675 & 0.1257 \tabularnewline
p-value & (0.9835) & (0.3082) & (0.2976) \tabularnewline
brainWeight;sleepExposure & 0.3175 & 0.5976 & 0.4905 \tabularnewline
p-value & (0.0489) & (1e-04) & (1e-04) \tabularnewline
brainWeight;danger & 0.1594 & 0.3414 & 0.2695 \tabularnewline
p-value & (0.3323) & (0.0334) & (0.026) \tabularnewline
logGestationTime;predation & 0.1422 & 0.1216 & 0.0906 \tabularnewline
p-value & (0.388) & (0.4608) & (0.4629) \tabularnewline
logGestationTime;sleepExposure & 0.5766 & 0.5823 & 0.4808 \tabularnewline
p-value & (1e-04) & (1e-04) & (1e-04) \tabularnewline
logGestationTime;danger & 0.3482 & 0.3159 & 0.2441 \tabularnewline
p-value & (0.0299) & (0.0501) & (0.0486) \tabularnewline
predation;sleepExposure & 0.68 & 0.6186 & 0.5218 \tabularnewline
p-value & (0) & (0) & (1e-04) \tabularnewline
predation;danger & 0.9303 & 0.9328 & 0.876 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
sleepExposure;danger & 0.8192 & 0.7533 & 0.6591 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109088&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]SWS;logPS[/C][C]0.5831[/C][C]0.6062[/C][C]0.44[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](2e-04)[/C][/ROW]
[ROW][C]SWS;maxLifeSpan[/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]SWS;logBodyWeight[/C][C]-0.7116[/C][C]-0.6585[/C][C]-0.4813[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]SWS;brainWeight[/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]SWS;logGestationTime[/C][C]-0.6021[/C][C]-0.6724[/C][C]-0.5022[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]SWS;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]SWS;sleepExposure[/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]SWS;danger[/C][C]-0.5422[/C][C]-0.4905[/C][C]-0.3888[/C][/ROW]
[ROW][C]p-value[/C][C](4e-04)[/C][C](0.0015)[/C][C](0.0014)[/C][/ROW]
[ROW][C]logPS;maxLifeSpan[/C][C]-0.1532[/C][C]-0.3692[/C][C]-0.238[/C][/ROW]
[ROW][C]p-value[/C][C](0.3519)[/C][C](0.0207)[/C][C](0.0404)[/C][/ROW]
[ROW][C]logPS;logBodyWeight[/C][C]-0.3643[/C][C]-0.4175[/C][C]-0.2712[/C][/ROW]
[ROW][C]p-value[/C][C](0.0226)[/C][C](0.0082)[/C][C](0.0192)[/C][/ROW]
[ROW][C]logPS;brainWeight[/C][C]-0.007[/C][C]-0.4971[/C][C]-0.3193[/C][/ROW]
[ROW][C]p-value[/C][C](0.9664)[/C][C](0.0013)[/C][C](0.0058)[/C][/ROW]
[ROW][C]logPS;logGestationTime[/C][C]-0.6345[/C][C]-0.647[/C][C]-0.4798[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](1e-04)[/C][/ROW]
[ROW][C]logPS;predation[/C][C]-0.5502[/C][C]-0.535[/C][C]-0.4032[/C][/ROW]
[ROW][C]p-value[/C][C](3e-04)[/C][C](4e-04)[/C][C](0.0013)[/C][/ROW]
[ROW][C]logPS;sleepExposure[/C][C]-0.5782[/C][C]-0.5976[/C][C]-0.4712[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](1e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]logPS;danger[/C][C]-0.6864[/C][C]-0.675[/C][C]-0.5376[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]maxLifeSpan;logBodyWeight[/C][C]0.6524[/C][C]0.7063[/C][C]0.5251[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]maxLifeSpan;brainWeight[/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]maxLifeSpan;logGestationTime[/C][C]0.5957[/C][C]0.6945[/C][C]0.5304[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]maxLifeSpan;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]maxLifeSpan;sleepExposure[/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]maxLifeSpan;danger[/C][C]0.0605[/C][C]0.2072[/C][C]0.1615[/C][/ROW]
[ROW][C]p-value[/C][C](0.7146)[/C][C](0.2057)[/C][C](0.1831)[/C][/ROW]
[ROW][C]logBodyWeight;brainWeight[/C][C]0.539[/C][C]0.9284[/C][C]0.7916[/C][/ROW]
[ROW][C]p-value[/C][C](4e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]logBodyWeight;logGestationTime[/C][C]0.6925[/C][C]0.7051[/C][C]0.522[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]logBodyWeight;predation[/C][C]0.2529[/C][C]0.2147[/C][C]0.1602[/C][/ROW]
[ROW][C]p-value[/C][C](0.1204)[/C][C](0.1893)[/C][C](0.1846)[/C][/ROW]
[ROW][C]logBodyWeight;sleepExposure[/C][C]0.6624[/C][C]0.5954[/C][C]0.4811[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]logBodyWeight;danger[/C][C]0.4321[/C][C]0.3615[/C][C]0.274[/C][/ROW]
[ROW][C]p-value[/C][C](0.006)[/C][C](0.0238)[/C][C](0.0236)[/C][/ROW]
[ROW][C]brainWeight;logGestationTime[/C][C]0.4424[/C][C]0.8016[/C][C]0.6039[/C][/ROW]
[ROW][C]p-value[/C][C](0.0048)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]brainWeight;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]brainWeight;sleepExposure[/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]brainWeight;danger[/C][C]0.1594[/C][C]0.3414[/C][C]0.2695[/C][/ROW]
[ROW][C]p-value[/C][C](0.3323)[/C][C](0.0334)[/C][C](0.026)[/C][/ROW]
[ROW][C]logGestationTime;predation[/C][C]0.1422[/C][C]0.1216[/C][C]0.0906[/C][/ROW]
[ROW][C]p-value[/C][C](0.388)[/C][C](0.4608)[/C][C](0.4629)[/C][/ROW]
[ROW][C]logGestationTime;sleepExposure[/C][C]0.5766[/C][C]0.5823[/C][C]0.4808[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]logGestationTime;danger[/C][C]0.3482[/C][C]0.3159[/C][C]0.2441[/C][/ROW]
[ROW][C]p-value[/C][C](0.0299)[/C][C](0.0501)[/C][C](0.0486)[/C][/ROW]
[ROW][C]predation;sleepExposure[/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]0.9303[/C][C]0.9328[/C][C]0.876[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]sleepExposure;danger[/C][C]0.8192[/C][C]0.7533[/C][C]0.6591[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109088&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109088&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
pair	Pearson r	Spearman rho	Kendall tau
SWS;logPS	0.5831	0.6062	0.44
p-value	(1e-04)	(0)	(2e-04)
SWS;maxLifeSpan	-0.3845	-0.4282	-0.2999
p-value	(0.0156)	(0.0065)	(0.0077)
SWS;logBodyWeight	-0.7116	-0.6585	-0.4813
p-value	(0)	(0)	(0)
SWS;brainWeight	-0.388	-0.6599	-0.4922
p-value	(0.0147)	(0)	(0)
SWS;logGestationTime	-0.6021	-0.6724	-0.5022
p-value	(1e-04)	(0)	(0)
SWS;predation	-0.3689	-0.3119	-0.2421
p-value	(0.0208)	(0.0533)	(0.0458)
SWS;sleepExposure	-0.5795	-0.5491	-0.4299
p-value	(1e-04)	(3e-04)	(5e-04)
SWS;danger	-0.5422	-0.4905	-0.3888
p-value	(4e-04)	(0.0015)	(0.0014)
logPS;maxLifeSpan	-0.1532	-0.3692	-0.238
p-value	(0.3519)	(0.0207)	(0.0404)
logPS;logBodyWeight	-0.3643	-0.4175	-0.2712
p-value	(0.0226)	(0.0082)	(0.0192)
logPS;brainWeight	-0.007	-0.4971	-0.3193
p-value	(0.9664)	(0.0013)	(0.0058)
logPS;logGestationTime	-0.6345	-0.647	-0.4798
p-value	(0)	(0)	(1e-04)
logPS;predation	-0.5502	-0.535	-0.4032
p-value	(3e-04)	(4e-04)	(0.0013)
logPS;sleepExposure	-0.5782	-0.5976	-0.4712
p-value	(1e-04)	(1e-04)	(2e-04)
logPS;danger	-0.6864	-0.675	-0.5376
p-value	(0)	(0)	(0)
maxLifeSpan;logBodyWeight	0.6524	0.7063	0.5251
p-value	(0)	(0)	(0)
maxLifeSpan;brainWeight	0.6594	0.8033	0.6499
p-value	(0)	(0)	(0)
maxLifeSpan;logGestationTime	0.5957	0.6945	0.5304
p-value	(1e-04)	(0)	(0)
maxLifeSpan;predation	-0.1107	0.0122	-0.006
p-value	(0.5023)	(0.9412)	(0.9604)
maxLifeSpan;sleepExposure	0.3192	0.5242	0.4101
p-value	(0.0476)	(6e-04)	(9e-04)
maxLifeSpan;danger	0.0605	0.2072	0.1615
p-value	(0.7146)	(0.2057)	(0.1831)
logBodyWeight;brainWeight	0.539	0.9284	0.7916
p-value	(4e-04)	(0)	(0)
logBodyWeight;logGestationTime	0.6925	0.7051	0.522
p-value	(0)	(0)	(0)
logBodyWeight;predation	0.2529	0.2147	0.1602
p-value	(0.1204)	(0.1893)	(0.1846)
logBodyWeight;sleepExposure	0.6624	0.5954	0.4811
p-value	(0)	(1e-04)	(1e-04)
logBodyWeight;danger	0.4321	0.3615	0.274
p-value	(0.006)	(0.0238)	(0.0236)
brainWeight;logGestationTime	0.4424	0.8016	0.6039
p-value	(0.0048)	(0)	(0)
brainWeight;predation	-0.0034	0.1675	0.1257
p-value	(0.9835)	(0.3082)	(0.2976)
brainWeight;sleepExposure	0.3175	0.5976	0.4905
p-value	(0.0489)	(1e-04)	(1e-04)
brainWeight;danger	0.1594	0.3414	0.2695
p-value	(0.3323)	(0.0334)	(0.026)
logGestationTime;predation	0.1422	0.1216	0.0906
p-value	(0.388)	(0.4608)	(0.4629)
logGestationTime;sleepExposure	0.5766	0.5823	0.4808
p-value	(1e-04)	(1e-04)	(1e-04)
logGestationTime;danger	0.3482	0.3159	0.2441
p-value	(0.0299)	(0.0501)	(0.0486)
predation;sleepExposure	0.68	0.6186	0.5218
p-value	(0)	(0)	(1e-04)
predation;danger	0.9303	0.9328	0.876
p-value	(0)	(0)	(0)
sleepExposure;danger	0.8192	0.7533	0.6591
p-value	(0)	(0)	(0)

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = pearson ;

Parameters (R input):

par1 = pearson ;

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code