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R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationWed, 15 Dec 2010 15:35:10 +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/15/t1292427218nd51z2sfyaxxdik.htm/, Retrieved Fri, 03 May 2024 04:28:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110480, Retrieved Fri, 03 May 2024 04:28:00 +0000
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-     [Kendall tau Correlation Matrix] [] [2010-12-14 19:21:25] [ed939ef6f97e5f2afb6796311d9e7a5f]
-   PD    [Kendall tau Correlation Matrix] [correlation matrix] [2010-12-15 15:35:10] [7b4029fa8534fd52dfa7d68267386cff] [Current]
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Dataseries X:
6.3	2	4.5	1,00	6.6	42	3	1	3
2.1	1,8	69	2547,00	4603	624	3	5	4
9.1	0,7	27	10,55	179.5	180	4	4	4
15.8	3,9	19	0,02	0.3	35	1	1	1
5.2	1	30.4	160,00	169	392	4	5	4
10.9	3,6	28	3,30	25.6	63	1	2	1
8.3	1,4	50	52,16	440	230	1	1	1
11	1,5	7	0,43	6.4	112	5	4	4
3.2	0,7	30	465,00	423	281	5	5	5
6.3	2,1	3.5	0,08	1.2	42	1	1	1
6.6	4,1	6	0,79	3.5	42	2	2	2
9.5	1,2	10.4	0,20	5	120	2	2	2
3.3	0,5	20	27,66	115	148	5	5	5
11	3,4	3.9	0,12	1	16	3	1	2
4.7	1,5	41	85,00	325	310	1	3	1
10.4	3,4	9	0,10	4	28	5	1	3
7.4	0,8	7.6	1,04	5.5	68	5	3	4
2.1	0,8	46	521,00	655	336	5	5	5
7.7	1,4	2.6	0,01	0.14	21,5	5	2	4
17.9	2	24	0,01	0.25	50	1	1	1
6.1	1,9	100	62,00	1320	267	1	1	1
11.9	1,3	3.2	0,02	0.4	19	4	1	3
10.8	2	2	0,05	0.33	30	4	1	3
13.8	5,6	5	1,70	6.3	12	2	1	1
14.3	3,1	6.5	3,50	10.8	120	2	1	1
10	0,9	20.2	10,00	115	170	4	4	4
11.9	1,8	13	1,62	11.4	17	2	1	2
6.5	1,9	27	192,00	180	115	4	4	4
7.5	0,9	18	2,50	12.1	31	5	5	5
10.6	2,6	4.7	0,28	1.9	21	3	1	3
7.4	2,4	9.8	4235,00	50.4	52	1	1	1
8.4	1,2	29	6,80	179	164	2	3	2
5.7	0,9	7	0,75	12.3	225	2	2	2
4.9	0,5	6	3,60	21	225	3	2	3
3.2	0,6	20	55,50	175	151	5	5	5
11	2,3	4.5	0,90	2.6	60	2	1	2
4.9	0,5	7.5	2,00	12.3	200	3	1	3
13.2	2,6	2.3	0,10	2.5	46	3	2	2
9.7	0,6	24	4,19	58	210	4	3	4
12.8	6,6	3	3,50	3.9	14	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'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=110480&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=110480&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110480&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Correlations for all pairs of data series (method=kendall)
SWS_(non_dreaming)PS_(dreaming)L_(lifespan)Wb_(body_weight)Wbr_(brain_weight)Tg_(gestation_time)P_(Predation_index)S_(sleep_exposure)D_(overall_danger)
SWS_(non_dreaming)10.427-0.309-0.441-0.487-0.501-0.218-0.45-0.387
PS_(dreaming)0.4271-0.22-0.223-0.298-0.43-0.38-0.469-0.526
L_(lifespan)-0.309-0.2210.5370.6730.541-0.0630.3950.117
Wb_(body_weight)-0.441-0.2230.53710.7950.5040.0550.4390.193
Wbr_(brain_weight)-0.487-0.2980.6730.79510.5940.060.4660.217
Tg_(gestation_time)-0.501-0.430.5410.5040.59410.0280.4590.196
P_(Predation_index)-0.218-0.38-0.0630.0550.060.02810.490.866
S_(sleep_exposure)-0.45-0.4690.3950.4390.4660.4590.4910.647
D_(overall_danger)-0.387-0.5260.1170.1930.2170.1960.8660.6471

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & SWS_(non_dreaming) & PS_(dreaming) & L_(lifespan) & Wb_(body_weight) & Wbr_(brain_weight) & Tg_(gestation_time) & P_(Predation_index) & S_(sleep_exposure) & D_(overall_danger) \tabularnewline
SWS_(non_dreaming) & 1 & 0.427 & -0.309 & -0.441 & -0.487 & -0.501 & -0.218 & -0.45 & -0.387 \tabularnewline
PS_(dreaming) & 0.427 & 1 & -0.22 & -0.223 & -0.298 & -0.43 & -0.38 & -0.469 & -0.526 \tabularnewline
L_(lifespan) & -0.309 & -0.22 & 1 & 0.537 & 0.673 & 0.541 & -0.063 & 0.395 & 0.117 \tabularnewline
Wb_(body_weight) & -0.441 & -0.223 & 0.537 & 1 & 0.795 & 0.504 & 0.055 & 0.439 & 0.193 \tabularnewline
Wbr_(brain_weight) & -0.487 & -0.298 & 0.673 & 0.795 & 1 & 0.594 & 0.06 & 0.466 & 0.217 \tabularnewline
Tg_(gestation_time) & -0.501 & -0.43 & 0.541 & 0.504 & 0.594 & 1 & 0.028 & 0.459 & 0.196 \tabularnewline
P_(Predation_index) & -0.218 & -0.38 & -0.063 & 0.055 & 0.06 & 0.028 & 1 & 0.49 & 0.866 \tabularnewline
S_(sleep_exposure) & -0.45 & -0.469 & 0.395 & 0.439 & 0.466 & 0.459 & 0.49 & 1 & 0.647 \tabularnewline
D_(overall_danger) & -0.387 & -0.526 & 0.117 & 0.193 & 0.217 & 0.196 & 0.866 & 0.647 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110480&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]SWS_(non_dreaming)[/C][C]PS_(dreaming)[/C][C]L_(lifespan)[/C][C]Wb_(body_weight)[/C][C]Wbr_(brain_weight)[/C][C]Tg_(gestation_time)[/C][C]P_(Predation_index)[/C][C]S_(sleep_exposure)[/C][C]D_(overall_danger)[/C][/ROW]
[ROW][C]SWS_(non_dreaming)[/C][C]1[/C][C]0.427[/C][C]-0.309[/C][C]-0.441[/C][C]-0.487[/C][C]-0.501[/C][C]-0.218[/C][C]-0.45[/C][C]-0.387[/C][/ROW]
[ROW][C]PS_(dreaming)[/C][C]0.427[/C][C]1[/C][C]-0.22[/C][C]-0.223[/C][C]-0.298[/C][C]-0.43[/C][C]-0.38[/C][C]-0.469[/C][C]-0.526[/C][/ROW]
[ROW][C]L_(lifespan)[/C][C]-0.309[/C][C]-0.22[/C][C]1[/C][C]0.537[/C][C]0.673[/C][C]0.541[/C][C]-0.063[/C][C]0.395[/C][C]0.117[/C][/ROW]
[ROW][C]Wb_(body_weight)[/C][C]-0.441[/C][C]-0.223[/C][C]0.537[/C][C]1[/C][C]0.795[/C][C]0.504[/C][C]0.055[/C][C]0.439[/C][C]0.193[/C][/ROW]
[ROW][C]Wbr_(brain_weight)[/C][C]-0.487[/C][C]-0.298[/C][C]0.673[/C][C]0.795[/C][C]1[/C][C]0.594[/C][C]0.06[/C][C]0.466[/C][C]0.217[/C][/ROW]
[ROW][C]Tg_(gestation_time)[/C][C]-0.501[/C][C]-0.43[/C][C]0.541[/C][C]0.504[/C][C]0.594[/C][C]1[/C][C]0.028[/C][C]0.459[/C][C]0.196[/C][/ROW]
[ROW][C]P_(Predation_index)[/C][C]-0.218[/C][C]-0.38[/C][C]-0.063[/C][C]0.055[/C][C]0.06[/C][C]0.028[/C][C]1[/C][C]0.49[/C][C]0.866[/C][/ROW]
[ROW][C]S_(sleep_exposure)[/C][C]-0.45[/C][C]-0.469[/C][C]0.395[/C][C]0.439[/C][C]0.466[/C][C]0.459[/C][C]0.49[/C][C]1[/C][C]0.647[/C][/ROW]
[ROW][C]D_(overall_danger)[/C][C]-0.387[/C][C]-0.526[/C][C]0.117[/C][C]0.193[/C][C]0.217[/C][C]0.196[/C][C]0.866[/C][C]0.647[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110480&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110480&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)
SWS_(non_dreaming)PS_(dreaming)L_(lifespan)Wb_(body_weight)Wbr_(brain_weight)Tg_(gestation_time)P_(Predation_index)S_(sleep_exposure)D_(overall_danger)
SWS_(non_dreaming)10.427-0.309-0.441-0.487-0.501-0.218-0.45-0.387
PS_(dreaming)0.4271-0.22-0.223-0.298-0.43-0.38-0.469-0.526
L_(lifespan)-0.309-0.2210.5370.6730.541-0.0630.3950.117
Wb_(body_weight)-0.441-0.2230.53710.7950.5040.0550.4390.193
Wbr_(brain_weight)-0.487-0.2980.6730.79510.5940.060.4660.217
Tg_(gestation_time)-0.501-0.430.5410.5040.59410.0280.4590.196
P_(Predation_index)-0.218-0.38-0.0630.0550.060.02810.490.866
S_(sleep_exposure)-0.45-0.4690.3950.4390.4660.4590.4910.647
D_(overall_danger)-0.387-0.5260.1170.1930.2170.1960.8660.6471







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
SWS_(non_dreaming);PS_(dreaming)0.55410.60740.4269
p-value(2e-04)(0)(1e-04)
SWS_(non_dreaming);L_(lifespan)-0.382-0.4395-0.3094
p-value(0.015)(0.0045)(0.0053)
SWS_(non_dreaming);Wb_(body_weight)-0.2564-0.6096-0.4409
p-value(0.1103)(0)(1e-04)
SWS_(non_dreaming);Wbr_(brain_weight)-0.3899-0.6531-0.4868
p-value(0.0129)(0)(0)
SWS_(non_dreaming);Tg_(gestation_time)-0.6372-0.6746-0.5006
p-value(0)(0)(0)
SWS_(non_dreaming);P_(Predation_index)-0.3409-0.2799-0.2181
p-value(0.0314)(0.0802)(0.0678)
SWS_(non_dreaming);S_(sleep_exposure)-0.5926-0.5713-0.4498
p-value(1e-04)(1e-04)(2e-04)
SWS_(non_dreaming);D_(overall_danger)-0.5363-0.4832-0.3874
p-value(4e-04)(0.0016)(0.0012)
PS_(dreaming);L_(lifespan)-0.2298-0.3754-0.2202
p-value(0.1537)(0.017)(0.0485)
PS_(dreaming);Wb_(body_weight)-4e-04-0.3776-0.2225
p-value(0.9981)(0.0163)(0.046)
PS_(dreaming);Wbr_(brain_weight)-0.0863-0.4969-0.2976
p-value(0.5966)(0.0011)(0.0075)
PS_(dreaming);Tg_(gestation_time)-0.4503-0.6255-0.4297
p-value(0.0036)(0)(1e-04)
PS_(dreaming);P_(Predation_index)-0.4374-0.52-0.3803
p-value(0.0048)(6e-04)(0.0016)
PS_(dreaming);S_(sleep_exposure)-0.5255-0.6186-0.4695
p-value(5e-04)(0)(1e-04)
PS_(dreaming);D_(overall_danger)-0.6086-0.6769-0.5257
p-value(0)(0)(0)
L_(lifespan);Wb_(body_weight)0.20010.71390.5368
p-value(0.2157)(0)(0)
L_(lifespan);Wbr_(brain_weight)0.65820.820.6727
p-value(0)(0)(0)
L_(lifespan);Tg_(gestation_time)0.70380.73410.541
p-value(0)(0)(0)
L_(lifespan);P_(Predation_index)-0.1568-0.0606-0.0626
p-value(0.3338)(0.7103)(0.5996)
L_(lifespan);S_(sleep_exposure)0.33320.51320.3949
p-value(0.0357)(7e-04)(0.0012)
L_(lifespan);D_(overall_danger)0.03040.15770.1174
p-value(0.8522)(0.3312)(0.3263)
Wb_(body_weight);Wbr_(brain_weight)0.47660.92910.7954
p-value(0.0019)(0)(0)
Wb_(body_weight);Tg_(gestation_time)0.29570.69290.5042
p-value(0.0639)(0)(0)
Wb_(body_weight);P_(Predation_index)-0.14430.06940.0554
p-value(0.3742)(0.6706)(0.6417)
Wb_(body_weight);S_(sleep_exposure)0.09190.53590.4394
p-value(0.5729)(4e-04)(3e-04)
Wb_(body_weight);D_(overall_danger)-0.03550.25520.1931
p-value(0.828)(0.112)(0.1061)
Wbr_(brain_weight);Tg_(gestation_time)0.7360.80560.5937
p-value(0)(0)(0)
Wbr_(brain_weight);P_(Predation_index)-0.02480.08140.0596
p-value(0.8791)(0.6174)(0.6164)
Wbr_(brain_weight);S_(sleep_exposure)0.3210.5790.4658
p-value(0.0434)(1e-04)(1e-04)
Wbr_(brain_weight);D_(overall_danger)0.14520.28460.2171
p-value(0.3712)(0.0751)(0.0689)
Tg_(gestation_time);P_(Predation_index)0.08020.04920.0284
p-value(0.6227)(0.7628)(0.8114)
Tg_(gestation_time);S_(sleep_exposure)0.57460.5780.4592
p-value(1e-04)(1e-04)(2e-04)
Tg_(gestation_time);D_(overall_danger)0.30140.27040.1961
p-value(0.0588)(0.0915)(0.101)
P_(Predation_index);S_(sleep_exposure)0.62560.58740.4896
p-value(0)(1e-04)(2e-04)
P_(Predation_index);D_(overall_danger)0.92670.92760.8659
p-value(0)(0)(0)
S_(sleep_exposure);D_(overall_danger)0.790.7440.6474
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_(non_dreaming);PS_(dreaming) & 0.5541 & 0.6074 & 0.4269 \tabularnewline
p-value & (2e-04) & (0) & (1e-04) \tabularnewline
SWS_(non_dreaming);L_(lifespan) & -0.382 & -0.4395 & -0.3094 \tabularnewline
p-value & (0.015) & (0.0045) & (0.0053) \tabularnewline
SWS_(non_dreaming);Wb_(body_weight) & -0.2564 & -0.6096 & -0.4409 \tabularnewline
p-value & (0.1103) & (0) & (1e-04) \tabularnewline
SWS_(non_dreaming);Wbr_(brain_weight) & -0.3899 & -0.6531 & -0.4868 \tabularnewline
p-value & (0.0129) & (0) & (0) \tabularnewline
SWS_(non_dreaming);Tg_(gestation_time) & -0.6372 & -0.6746 & -0.5006 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
SWS_(non_dreaming);P_(Predation_index) & -0.3409 & -0.2799 & -0.2181 \tabularnewline
p-value & (0.0314) & (0.0802) & (0.0678) \tabularnewline
SWS_(non_dreaming);S_(sleep_exposure) & -0.5926 & -0.5713 & -0.4498 \tabularnewline
p-value & (1e-04) & (1e-04) & (2e-04) \tabularnewline
SWS_(non_dreaming);D_(overall_danger) & -0.5363 & -0.4832 & -0.3874 \tabularnewline
p-value & (4e-04) & (0.0016) & (0.0012) \tabularnewline
PS_(dreaming);L_(lifespan) & -0.2298 & -0.3754 & -0.2202 \tabularnewline
p-value & (0.1537) & (0.017) & (0.0485) \tabularnewline
PS_(dreaming);Wb_(body_weight) & -4e-04 & -0.3776 & -0.2225 \tabularnewline
p-value & (0.9981) & (0.0163) & (0.046) \tabularnewline
PS_(dreaming);Wbr_(brain_weight) & -0.0863 & -0.4969 & -0.2976 \tabularnewline
p-value & (0.5966) & (0.0011) & (0.0075) \tabularnewline
PS_(dreaming);Tg_(gestation_time) & -0.4503 & -0.6255 & -0.4297 \tabularnewline
p-value & (0.0036) & (0) & (1e-04) \tabularnewline
PS_(dreaming);P_(Predation_index) & -0.4374 & -0.52 & -0.3803 \tabularnewline
p-value & (0.0048) & (6e-04) & (0.0016) \tabularnewline
PS_(dreaming);S_(sleep_exposure) & -0.5255 & -0.6186 & -0.4695 \tabularnewline
p-value & (5e-04) & (0) & (1e-04) \tabularnewline
PS_(dreaming);D_(overall_danger) & -0.6086 & -0.6769 & -0.5257 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
L_(lifespan);Wb_(body_weight) & 0.2001 & 0.7139 & 0.5368 \tabularnewline
p-value & (0.2157) & (0) & (0) \tabularnewline
L_(lifespan);Wbr_(brain_weight) & 0.6582 & 0.82 & 0.6727 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
L_(lifespan);Tg_(gestation_time) & 0.7038 & 0.7341 & 0.541 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
L_(lifespan);P_(Predation_index) & -0.1568 & -0.0606 & -0.0626 \tabularnewline
p-value & (0.3338) & (0.7103) & (0.5996) \tabularnewline
L_(lifespan);S_(sleep_exposure) & 0.3332 & 0.5132 & 0.3949 \tabularnewline
p-value & (0.0357) & (7e-04) & (0.0012) \tabularnewline
L_(lifespan);D_(overall_danger) & 0.0304 & 0.1577 & 0.1174 \tabularnewline
p-value & (0.8522) & (0.3312) & (0.3263) \tabularnewline
Wb_(body_weight);Wbr_(brain_weight) & 0.4766 & 0.9291 & 0.7954 \tabularnewline
p-value & (0.0019) & (0) & (0) \tabularnewline
Wb_(body_weight);Tg_(gestation_time) & 0.2957 & 0.6929 & 0.5042 \tabularnewline
p-value & (0.0639) & (0) & (0) \tabularnewline
Wb_(body_weight);P_(Predation_index) & -0.1443 & 0.0694 & 0.0554 \tabularnewline
p-value & (0.3742) & (0.6706) & (0.6417) \tabularnewline
Wb_(body_weight);S_(sleep_exposure) & 0.0919 & 0.5359 & 0.4394 \tabularnewline
p-value & (0.5729) & (4e-04) & (3e-04) \tabularnewline
Wb_(body_weight);D_(overall_danger) & -0.0355 & 0.2552 & 0.1931 \tabularnewline
p-value & (0.828) & (0.112) & (0.1061) \tabularnewline
Wbr_(brain_weight);Tg_(gestation_time) & 0.736 & 0.8056 & 0.5937 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Wbr_(brain_weight);P_(Predation_index) & -0.0248 & 0.0814 & 0.0596 \tabularnewline
p-value & (0.8791) & (0.6174) & (0.6164) \tabularnewline
Wbr_(brain_weight);S_(sleep_exposure) & 0.321 & 0.579 & 0.4658 \tabularnewline
p-value & (0.0434) & (1e-04) & (1e-04) \tabularnewline
Wbr_(brain_weight);D_(overall_danger) & 0.1452 & 0.2846 & 0.2171 \tabularnewline
p-value & (0.3712) & (0.0751) & (0.0689) \tabularnewline
Tg_(gestation_time);P_(Predation_index) & 0.0802 & 0.0492 & 0.0284 \tabularnewline
p-value & (0.6227) & (0.7628) & (0.8114) \tabularnewline
Tg_(gestation_time);S_(sleep_exposure) & 0.5746 & 0.578 & 0.4592 \tabularnewline
p-value & (1e-04) & (1e-04) & (2e-04) \tabularnewline
Tg_(gestation_time);D_(overall_danger) & 0.3014 & 0.2704 & 0.1961 \tabularnewline
p-value & (0.0588) & (0.0915) & (0.101) \tabularnewline
P_(Predation_index);S_(sleep_exposure) & 0.6256 & 0.5874 & 0.4896 \tabularnewline
p-value & (0) & (1e-04) & (2e-04) \tabularnewline
P_(Predation_index);D_(overall_danger) & 0.9267 & 0.9276 & 0.8659 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
S_(sleep_exposure);D_(overall_danger) & 0.79 & 0.744 & 0.6474 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110480&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_(non_dreaming);PS_(dreaming)[/C][C]0.5541[/C][C]0.6074[/C][C]0.4269[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](0)[/C][C](1e-04)[/C][/ROW]
[ROW][C]SWS_(non_dreaming);L_(lifespan)[/C][C]-0.382[/C][C]-0.4395[/C][C]-0.3094[/C][/ROW]
[ROW][C]p-value[/C][C](0.015)[/C][C](0.0045)[/C][C](0.0053)[/C][/ROW]
[ROW][C]SWS_(non_dreaming);Wb_(body_weight)[/C][C]-0.2564[/C][C]-0.6096[/C][C]-0.4409[/C][/ROW]
[ROW][C]p-value[/C][C](0.1103)[/C][C](0)[/C][C](1e-04)[/C][/ROW]
[ROW][C]SWS_(non_dreaming);Wbr_(brain_weight)[/C][C]-0.3899[/C][C]-0.6531[/C][C]-0.4868[/C][/ROW]
[ROW][C]p-value[/C][C](0.0129)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]SWS_(non_dreaming);Tg_(gestation_time)[/C][C]-0.6372[/C][C]-0.6746[/C][C]-0.5006[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]SWS_(non_dreaming);P_(Predation_index)[/C][C]-0.3409[/C][C]-0.2799[/C][C]-0.2181[/C][/ROW]
[ROW][C]p-value[/C][C](0.0314)[/C][C](0.0802)[/C][C](0.0678)[/C][/ROW]
[ROW][C]SWS_(non_dreaming);S_(sleep_exposure)[/C][C]-0.5926[/C][C]-0.5713[/C][C]-0.4498[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](1e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]SWS_(non_dreaming);D_(overall_danger)[/C][C]-0.5363[/C][C]-0.4832[/C][C]-0.3874[/C][/ROW]
[ROW][C]p-value[/C][C](4e-04)[/C][C](0.0016)[/C][C](0.0012)[/C][/ROW]
[ROW][C]PS_(dreaming);L_(lifespan)[/C][C]-0.2298[/C][C]-0.3754[/C][C]-0.2202[/C][/ROW]
[ROW][C]p-value[/C][C](0.1537)[/C][C](0.017)[/C][C](0.0485)[/C][/ROW]
[ROW][C]PS_(dreaming);Wb_(body_weight)[/C][C]-4e-04[/C][C]-0.3776[/C][C]-0.2225[/C][/ROW]
[ROW][C]p-value[/C][C](0.9981)[/C][C](0.0163)[/C][C](0.046)[/C][/ROW]
[ROW][C]PS_(dreaming);Wbr_(brain_weight)[/C][C]-0.0863[/C][C]-0.4969[/C][C]-0.2976[/C][/ROW]
[ROW][C]p-value[/C][C](0.5966)[/C][C](0.0011)[/C][C](0.0075)[/C][/ROW]
[ROW][C]PS_(dreaming);Tg_(gestation_time)[/C][C]-0.4503[/C][C]-0.6255[/C][C]-0.4297[/C][/ROW]
[ROW][C]p-value[/C][C](0.0036)[/C][C](0)[/C][C](1e-04)[/C][/ROW]
[ROW][C]PS_(dreaming);P_(Predation_index)[/C][C]-0.4374[/C][C]-0.52[/C][C]-0.3803[/C][/ROW]
[ROW][C]p-value[/C][C](0.0048)[/C][C](6e-04)[/C][C](0.0016)[/C][/ROW]
[ROW][C]PS_(dreaming);S_(sleep_exposure)[/C][C]-0.5255[/C][C]-0.6186[/C][C]-0.4695[/C][/ROW]
[ROW][C]p-value[/C][C](5e-04)[/C][C](0)[/C][C](1e-04)[/C][/ROW]
[ROW][C]PS_(dreaming);D_(overall_danger)[/C][C]-0.6086[/C][C]-0.6769[/C][C]-0.5257[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]L_(lifespan);Wb_(body_weight)[/C][C]0.2001[/C][C]0.7139[/C][C]0.5368[/C][/ROW]
[ROW][C]p-value[/C][C](0.2157)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]L_(lifespan);Wbr_(brain_weight)[/C][C]0.6582[/C][C]0.82[/C][C]0.6727[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]L_(lifespan);Tg_(gestation_time)[/C][C]0.7038[/C][C]0.7341[/C][C]0.541[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]L_(lifespan);P_(Predation_index)[/C][C]-0.1568[/C][C]-0.0606[/C][C]-0.0626[/C][/ROW]
[ROW][C]p-value[/C][C](0.3338)[/C][C](0.7103)[/C][C](0.5996)[/C][/ROW]
[ROW][C]L_(lifespan);S_(sleep_exposure)[/C][C]0.3332[/C][C]0.5132[/C][C]0.3949[/C][/ROW]
[ROW][C]p-value[/C][C](0.0357)[/C][C](7e-04)[/C][C](0.0012)[/C][/ROW]
[ROW][C]L_(lifespan);D_(overall_danger)[/C][C]0.0304[/C][C]0.1577[/C][C]0.1174[/C][/ROW]
[ROW][C]p-value[/C][C](0.8522)[/C][C](0.3312)[/C][C](0.3263)[/C][/ROW]
[ROW][C]Wb_(body_weight);Wbr_(brain_weight)[/C][C]0.4766[/C][C]0.9291[/C][C]0.7954[/C][/ROW]
[ROW][C]p-value[/C][C](0.0019)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Wb_(body_weight);Tg_(gestation_time)[/C][C]0.2957[/C][C]0.6929[/C][C]0.5042[/C][/ROW]
[ROW][C]p-value[/C][C](0.0639)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Wb_(body_weight);P_(Predation_index)[/C][C]-0.1443[/C][C]0.0694[/C][C]0.0554[/C][/ROW]
[ROW][C]p-value[/C][C](0.3742)[/C][C](0.6706)[/C][C](0.6417)[/C][/ROW]
[ROW][C]Wb_(body_weight);S_(sleep_exposure)[/C][C]0.0919[/C][C]0.5359[/C][C]0.4394[/C][/ROW]
[ROW][C]p-value[/C][C](0.5729)[/C][C](4e-04)[/C][C](3e-04)[/C][/ROW]
[ROW][C]Wb_(body_weight);D_(overall_danger)[/C][C]-0.0355[/C][C]0.2552[/C][C]0.1931[/C][/ROW]
[ROW][C]p-value[/C][C](0.828)[/C][C](0.112)[/C][C](0.1061)[/C][/ROW]
[ROW][C]Wbr_(brain_weight);Tg_(gestation_time)[/C][C]0.736[/C][C]0.8056[/C][C]0.5937[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Wbr_(brain_weight);P_(Predation_index)[/C][C]-0.0248[/C][C]0.0814[/C][C]0.0596[/C][/ROW]
[ROW][C]p-value[/C][C](0.8791)[/C][C](0.6174)[/C][C](0.6164)[/C][/ROW]
[ROW][C]Wbr_(brain_weight);S_(sleep_exposure)[/C][C]0.321[/C][C]0.579[/C][C]0.4658[/C][/ROW]
[ROW][C]p-value[/C][C](0.0434)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Wbr_(brain_weight);D_(overall_danger)[/C][C]0.1452[/C][C]0.2846[/C][C]0.2171[/C][/ROW]
[ROW][C]p-value[/C][C](0.3712)[/C][C](0.0751)[/C][C](0.0689)[/C][/ROW]
[ROW][C]Tg_(gestation_time);P_(Predation_index)[/C][C]0.0802[/C][C]0.0492[/C][C]0.0284[/C][/ROW]
[ROW][C]p-value[/C][C](0.6227)[/C][C](0.7628)[/C][C](0.8114)[/C][/ROW]
[ROW][C]Tg_(gestation_time);S_(sleep_exposure)[/C][C]0.5746[/C][C]0.578[/C][C]0.4592[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](1e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]Tg_(gestation_time);D_(overall_danger)[/C][C]0.3014[/C][C]0.2704[/C][C]0.1961[/C][/ROW]
[ROW][C]p-value[/C][C](0.0588)[/C][C](0.0915)[/C][C](0.101)[/C][/ROW]
[ROW][C]P_(Predation_index);S_(sleep_exposure)[/C][C]0.6256[/C][C]0.5874[/C][C]0.4896[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]P_(Predation_index);D_(overall_danger)[/C][C]0.9267[/C][C]0.9276[/C][C]0.8659[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]S_(sleep_exposure);D_(overall_danger)[/C][C]0.79[/C][C]0.744[/C][C]0.6474[/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=110480&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110480&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
SWS_(non_dreaming);PS_(dreaming)0.55410.60740.4269
p-value(2e-04)(0)(1e-04)
SWS_(non_dreaming);L_(lifespan)-0.382-0.4395-0.3094
p-value(0.015)(0.0045)(0.0053)
SWS_(non_dreaming);Wb_(body_weight)-0.2564-0.6096-0.4409
p-value(0.1103)(0)(1e-04)
SWS_(non_dreaming);Wbr_(brain_weight)-0.3899-0.6531-0.4868
p-value(0.0129)(0)(0)
SWS_(non_dreaming);Tg_(gestation_time)-0.6372-0.6746-0.5006
p-value(0)(0)(0)
SWS_(non_dreaming);P_(Predation_index)-0.3409-0.2799-0.2181
p-value(0.0314)(0.0802)(0.0678)
SWS_(non_dreaming);S_(sleep_exposure)-0.5926-0.5713-0.4498
p-value(1e-04)(1e-04)(2e-04)
SWS_(non_dreaming);D_(overall_danger)-0.5363-0.4832-0.3874
p-value(4e-04)(0.0016)(0.0012)
PS_(dreaming);L_(lifespan)-0.2298-0.3754-0.2202
p-value(0.1537)(0.017)(0.0485)
PS_(dreaming);Wb_(body_weight)-4e-04-0.3776-0.2225
p-value(0.9981)(0.0163)(0.046)
PS_(dreaming);Wbr_(brain_weight)-0.0863-0.4969-0.2976
p-value(0.5966)(0.0011)(0.0075)
PS_(dreaming);Tg_(gestation_time)-0.4503-0.6255-0.4297
p-value(0.0036)(0)(1e-04)
PS_(dreaming);P_(Predation_index)-0.4374-0.52-0.3803
p-value(0.0048)(6e-04)(0.0016)
PS_(dreaming);S_(sleep_exposure)-0.5255-0.6186-0.4695
p-value(5e-04)(0)(1e-04)
PS_(dreaming);D_(overall_danger)-0.6086-0.6769-0.5257
p-value(0)(0)(0)
L_(lifespan);Wb_(body_weight)0.20010.71390.5368
p-value(0.2157)(0)(0)
L_(lifespan);Wbr_(brain_weight)0.65820.820.6727
p-value(0)(0)(0)
L_(lifespan);Tg_(gestation_time)0.70380.73410.541
p-value(0)(0)(0)
L_(lifespan);P_(Predation_index)-0.1568-0.0606-0.0626
p-value(0.3338)(0.7103)(0.5996)
L_(lifespan);S_(sleep_exposure)0.33320.51320.3949
p-value(0.0357)(7e-04)(0.0012)
L_(lifespan);D_(overall_danger)0.03040.15770.1174
p-value(0.8522)(0.3312)(0.3263)
Wb_(body_weight);Wbr_(brain_weight)0.47660.92910.7954
p-value(0.0019)(0)(0)
Wb_(body_weight);Tg_(gestation_time)0.29570.69290.5042
p-value(0.0639)(0)(0)
Wb_(body_weight);P_(Predation_index)-0.14430.06940.0554
p-value(0.3742)(0.6706)(0.6417)
Wb_(body_weight);S_(sleep_exposure)0.09190.53590.4394
p-value(0.5729)(4e-04)(3e-04)
Wb_(body_weight);D_(overall_danger)-0.03550.25520.1931
p-value(0.828)(0.112)(0.1061)
Wbr_(brain_weight);Tg_(gestation_time)0.7360.80560.5937
p-value(0)(0)(0)
Wbr_(brain_weight);P_(Predation_index)-0.02480.08140.0596
p-value(0.8791)(0.6174)(0.6164)
Wbr_(brain_weight);S_(sleep_exposure)0.3210.5790.4658
p-value(0.0434)(1e-04)(1e-04)
Wbr_(brain_weight);D_(overall_danger)0.14520.28460.2171
p-value(0.3712)(0.0751)(0.0689)
Tg_(gestation_time);P_(Predation_index)0.08020.04920.0284
p-value(0.6227)(0.7628)(0.8114)
Tg_(gestation_time);S_(sleep_exposure)0.57460.5780.4592
p-value(1e-04)(1e-04)(2e-04)
Tg_(gestation_time);D_(overall_danger)0.30140.27040.1961
p-value(0.0588)(0.0915)(0.101)
P_(Predation_index);S_(sleep_exposure)0.62560.58740.4896
p-value(0)(1e-04)(2e-04)
P_(Predation_index);D_(overall_danger)0.92670.92760.8659
p-value(0)(0)(0)
S_(sleep_exposure);D_(overall_danger)0.790.7440.6474
p-value(0)(0)(0)



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')