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*The author of this computation has been verified*

R Software Module

rwasp_pairs.wasp

Title produced by software

Kendall tau Correlation Matrix

Date of computation

Fri, 02 Dec 2016 09:57:40 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/02/t1480669084ddsybstd2rrvc4a.htm/, Retrieved Tue, 07 May 2024 11:04:09 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=297556, Retrieved Tue, 07 May 2024 11:04:09 +0000

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No (this computation is public)

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Estimated Impact

117

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-       [Kendall tau Correlation Matrix] [fuckthisshit] [2016-12-02 08:57:40] [34b674d558c9d5fa20516c65c4cfbe6a] [Current]

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Dataseries X:

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0	2	4	3	5	4	16
5	3	3	4	5	4	16
4	4	5	4	5	4	NA
3	4	3	3	4	4	NA
4	4	5	4	5	4	18
3	4	4	4	5	5	NA
3	4	4	3	3	4	NA
3	4	5	4	4	4	NA
4	5	4	4	5	5	18
4	5	5	4	5	5	19
4	4	2	4	5	4	15
4	4	5	3	5	4	17
4	4	4	3	4	5	16
3	3	5	4	4	5	18
4	4	5	4	2	5	16
3	4	5	4	4	5	NA
3	4	5	4	4	5	NA
NA	NA	5	NA	5	5	NA
5	5	4	3	4	4	NA
4	4	4	4	5	4	17
3	4	5	3	4	5	NA
4	4	4	4	5	5	18
4	4	5	4	4	5	NA
4	4	5	4	4	4	NA
4	4	5	4	4	5	NA
3	4	4	4	4	4	16
3	4	4	3	5	5	17
4	4	4	4	4	4	16
2	4	5	4	5	5	19
5	4	4	4	4	4	16
4	3	5	4	4	4	17
4	5	5	4	5	5	19
5	4	5	4	4	5	NA
4	3	5	4	NA	5	14
2	3	5	4	5	4	18
4	5	2	4	4	4	NA
3	4	5	4	4	4	17
4	3	5	3	4	5	17
4	3	3	4	4	4	15
4	4	5	4	4	4	NA
5	4	4	4	4	4	16
4	5	5	4	5	5	19
3	3	4	4	4	4	16
5	5	5	3	5	5	18
5	4	5	3	4	4	16
4	4	4	3	4	5	NA
4	4	4	4	4	4	16
3	5	5	3	3	4	15
4	4	4	4	5	4	NA
2	3	4	2	NA	4	10
4	5	5	4	4	4	NA
5	5	2	4	5	4	NA
5	5	5	4	4	4	17
4	3	5	4	5	5	19
4	3	4	3	4	5	16
4	4	5	4	4	4	NA
3	4	4	3	3	4	14
3	4	4	4	4	3	15
4	4	4	3	5	4	NA
4	4	4	4	5	4	17
5	5	3	4	5	5	17
2	4	4	4	5	5	18
4	4	4	4	5	5	18
3	4	4	4	2	4	14
4	4	5	4	5	5	19
4	2	4	4	4	4	16
4	4	4	3	5	3	15
4	4	4	3	5	4	16
5	4	5	3	3	5	16
3	4	4	3	5	5	NA
3	4	4	3	4	5	NA
4	5	5	5	5	4	NA
4	4	3	4	NA	4	NA
4	4	4	4	4	4	NA
4	4	4	5	5	4	18
3	4	3	4	4	4	15
4	4	4	4	5	4	17
3	4	5	3	5	5	18
3	3	5	4	4	5	18
4	3	5	4	4	4	NA
4	4	5	4	4	5	18
3	3	3	4	4	4	NA
4	4	4	4	5	4	17
4	4	3	4	5	5	NA
4	4	4	4	5	5	18
5	4	4	4	4	4	16
5	4	3	5	4	5	17
4	4	5	4	5	5	NA
3	4	5	4	4	5	18
3	NA	4	4	4	4	16
4	2	3	3	4	4	NA
4	4	5	4	4	3	16
4	4	5	4	4	5	NA
4	4	4	4	5	4	17
4	5	4	4	5	3	NA
3	4	4	3	5	5	17
4	4	5	4	4	5	18
5	4	3	4	4	5	16
5	4	5	5	4	5	19
4	5	4	4	5	5	NA
3	4	5	4	4	5	NA
5	3	4	4	5	5	18
4	4	5	4	4	5	18
5	4	4	4	4	5	NA
3	4	4	3	NA	4	NA
5	4	4	5	5	5	NA
4	4	5	3	NA	5	NA
4	4	3	3	4	3	NA
4	4	5	4	4	4	17
4	4	5	4	4	4	NA
3	4	5	4	5	3	NA
4	4	4	4	4	4	NA
4	4	4	3	4	5	16
3	3	4	3	5	5	NA
4	4	4	3	4	4	15
3	4	5	4	4	4	17
4	4	5	4	3	4	NA
5	4	5	1	5	5	16
5	4	5	4	5	5	19
4	4	4	4	4	3	15
4	4	5	3	4	4	16
3	4	4	3	4	5	NA
4	4	4	4	4	4	16
4	4	4	4	5	4	NA
4	5	3	4	4	4	15
3	4	4	4	4	4	16
4	4	4	3	4	4	NA
4	4	4	4	4	5	NA
3	4	3	3	4	4	NA
4	4	4	3	4	3	14
3	2	4	2	4	4	NA
4	4	4	3	5	4	16
5	4	4	3	5	4	NA
2	4	4	3	3	5	15
3	3	4	4	4	4	NA
4	4	4	3	4	4	15
5	5	4	4	5	4	NA
NA	NA	2	NA	NA	NA	2
4	5	5	4	4	4	17
5	5	5	5	5	4	19
4	5	5	4	5	5	NA
4	4	4	3	4	5	16
3	4	5	4	5	4	NA
4	4	5	4	4	4	17
4	4	2	4	4	4	14
4	4	3	4	5	5	17
4	4	4	4	5	5	18
5	4	5	3	5	4	17
4	3	5	4	4	4	NA
4	4	5	4	4	4	NA
3	3	2	3	4	4	13
4	5	5	4	4	3	16
4	4	4	3	4	4	15
4	4	4	4	4	5	17
3	4	5	3	5	5	NA
4	4	5	4	4	5	18
5	4	5	4	5	4	NA
4	4	5	4	3	4	NA
2	3	5	4	4	4	17
4	4	4	4	4	5	17
4	3	4	3	5	5	17
4	4	4	4	4	3	15
4	5	5	5	4	4	NA
5	4	3	4	4	4	NA
5	4	4	3	4	4	NA
3	3	1	4	5	5	15
4	4	4	4	4	5	NA
4	4	4	4	5	4	17
2	3	4	5	5	4	3

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297556&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

1 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=297556&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297556&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	1 seconds
R Server	Big Analytics Cloud Computing Center

Correlations for all pairs of data series (method=pearson)
	SK1	SK2	SK3	SK4	SK5	SK6	TVDC
SK1	1	0.369	0.026	0.034	0.051	0.062	0.228
SK2	0.369	1	0.186	0.057	-0.007	-0.003	0.214
SK3	0.026	0.186	1	-0.074	-0.088	0.083	0.413
SK4	0.034	0.057	-0.074	1	0.041	-0.053	0.108
SK5	0.051	-0.007	-0.088	0.041	1	0.143	0.284
SK6	0.062	-0.003	0.083	-0.053	0.143	1	0.433
TVDC	0.228	0.214	0.413	0.108	0.284	0.433	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & SK1 & SK2 & SK3 & SK4 & SK5 & SK6 & TVDC \tabularnewline
SK1 & 1 & 0.369 & 0.026 & 0.034 & 0.051 & 0.062 & 0.228 \tabularnewline
SK2 & 0.369 & 1 & 0.186 & 0.057 & -0.007 & -0.003 & 0.214 \tabularnewline
SK3 & 0.026 & 0.186 & 1 & -0.074 & -0.088 & 0.083 & 0.413 \tabularnewline
SK4 & 0.034 & 0.057 & -0.074 & 1 & 0.041 & -0.053 & 0.108 \tabularnewline
SK5 & 0.051 & -0.007 & -0.088 & 0.041 & 1 & 0.143 & 0.284 \tabularnewline
SK6 & 0.062 & -0.003 & 0.083 & -0.053 & 0.143 & 1 & 0.433 \tabularnewline
TVDC & 0.228 & 0.214 & 0.413 & 0.108 & 0.284 & 0.433 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297556&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]SK1[/C][C]SK2[/C][C]SK3[/C][C]SK4[/C][C]SK5[/C][C]SK6[/C][C]TVDC[/C][/ROW]
[ROW][C]SK1[/C][C]1[/C][C]0.369[/C][C]0.026[/C][C]0.034[/C][C]0.051[/C][C]0.062[/C][C]0.228[/C][/ROW]
[ROW][C]SK2[/C][C]0.369[/C][C]1[/C][C]0.186[/C][C]0.057[/C][C]-0.007[/C][C]-0.003[/C][C]0.214[/C][/ROW]
[ROW][C]SK3[/C][C]0.026[/C][C]0.186[/C][C]1[/C][C]-0.074[/C][C]-0.088[/C][C]0.083[/C][C]0.413[/C][/ROW]
[ROW][C]SK4[/C][C]0.034[/C][C]0.057[/C][C]-0.074[/C][C]1[/C][C]0.041[/C][C]-0.053[/C][C]0.108[/C][/ROW]
[ROW][C]SK5[/C][C]0.051[/C][C]-0.007[/C][C]-0.088[/C][C]0.041[/C][C]1[/C][C]0.143[/C][C]0.284[/C][/ROW]
[ROW][C]SK6[/C][C]0.062[/C][C]-0.003[/C][C]0.083[/C][C]-0.053[/C][C]0.143[/C][C]1[/C][C]0.433[/C][/ROW]
[ROW][C]TVDC[/C][C]0.228[/C][C]0.214[/C][C]0.413[/C][C]0.108[/C][C]0.284[/C][C]0.433[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=297556&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297556&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)
	SK1	SK2	SK3	SK4	SK5	SK6	TVDC
SK1	1	0.369	0.026	0.034	0.051	0.062	0.228
SK2	0.369	1	0.186	0.057	-0.007	-0.003	0.214
SK3	0.026	0.186	1	-0.074	-0.088	0.083	0.413
SK4	0.034	0.057	-0.074	1	0.041	-0.053	0.108
SK5	0.051	-0.007	-0.088	0.041	1	0.143	0.284
SK6	0.062	-0.003	0.083	-0.053	0.143	1	0.433
TVDC	0.228	0.214	0.413	0.108	0.284	0.433	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
SK1;SK2	0.369	0.2933	0.2696
p-value	(2e-04)	(0.0032)	(0.0031)
SK1;SK3	0.0264	0.0221	0.0197
p-value	(0.7957)	(0.8284)	(0.8285)
SK1;SK4	0.0341	0.0626	0.0585
p-value	(0.7373)	(0.5382)	(0.5274)
SK1;SK5	0.0514	0.0905	0.0853
p-value	(0.6134)	(0.3732)	(0.3567)
SK1;SK6	0.0617	0.0712	0.0642
p-value	(0.5441)	(0.4837)	(0.4867)
SK1;TVDC	0.2284	0.1367	0.1158
p-value	(0.023)	(0.1774)	(0.1716)
SK2;SK3	0.1858	0.1677	0.156
p-value	(0.0655)	(0.097)	(0.0926)
SK2;SK4	0.0565	0.0563	0.0528
p-value	(0.5783)	(0.5799)	(0.5776)
SK2;SK5	-0.0065	0.0204	0.0184
p-value	(0.9489)	(0.8409)	(0.8461)
SK2;SK6	-0.0025	-0.0043	-0.004
p-value	(0.9803)	(0.9665)	(0.9665)
SK2;TVDC	0.2137	0.1498	0.129
p-value	(0.0337)	(0.1388)	(0.1364)
SK3;SK4	-0.0736	-0.0299	-0.0281
p-value	(0.469)	(0.7689)	(0.7651)
SK3;SK5	-0.0881	-0.0699	-0.0647
p-value	(0.3856)	(0.492)	(0.4911)
SK3;SK6	0.0829	0.1334	0.1228
p-value	(0.4148)	(0.1879)	(0.1906)
SK3;TVDC	0.4127	0.544	0.4732
p-value	(0)	(0)	(0)
SK4;SK5	0.0414	0.0668	0.0647
p-value	(0.6842)	(0.511)	(0.5006)
SK4;SK6	-0.0534	-0.035	-0.0331
p-value	(0.5999)	(0.7309)	(0.7301)
SK4;TVDC	0.1082	0.349	0.3086
p-value	(0.2866)	(4e-04)	(4e-04)
SK5;SK6	0.1426	0.1857	0.1755
p-value	(0.1591)	(0.0657)	(0.0667)
SK5;TVDC	0.2836	0.4833	0.429
p-value	(0.0044)	(0)	(0)
SK6;TVDC	0.4329	0.5666	0.5005
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
SK1;SK2 & 0.369 & 0.2933 & 0.2696 \tabularnewline
p-value & (2e-04) & (0.0032) & (0.0031) \tabularnewline
SK1;SK3 & 0.0264 & 0.0221 & 0.0197 \tabularnewline
p-value & (0.7957) & (0.8284) & (0.8285) \tabularnewline
SK1;SK4 & 0.0341 & 0.0626 & 0.0585 \tabularnewline
p-value & (0.7373) & (0.5382) & (0.5274) \tabularnewline
SK1;SK5 & 0.0514 & 0.0905 & 0.0853 \tabularnewline
p-value & (0.6134) & (0.3732) & (0.3567) \tabularnewline
SK1;SK6 & 0.0617 & 0.0712 & 0.0642 \tabularnewline
p-value & (0.5441) & (0.4837) & (0.4867) \tabularnewline
SK1;TVDC & 0.2284 & 0.1367 & 0.1158 \tabularnewline
p-value & (0.023) & (0.1774) & (0.1716) \tabularnewline
SK2;SK3 & 0.1858 & 0.1677 & 0.156 \tabularnewline
p-value & (0.0655) & (0.097) & (0.0926) \tabularnewline
SK2;SK4 & 0.0565 & 0.0563 & 0.0528 \tabularnewline
p-value & (0.5783) & (0.5799) & (0.5776) \tabularnewline
SK2;SK5 & -0.0065 & 0.0204 & 0.0184 \tabularnewline
p-value & (0.9489) & (0.8409) & (0.8461) \tabularnewline
SK2;SK6 & -0.0025 & -0.0043 & -0.004 \tabularnewline
p-value & (0.9803) & (0.9665) & (0.9665) \tabularnewline
SK2;TVDC & 0.2137 & 0.1498 & 0.129 \tabularnewline
p-value & (0.0337) & (0.1388) & (0.1364) \tabularnewline
SK3;SK4 & -0.0736 & -0.0299 & -0.0281 \tabularnewline
p-value & (0.469) & (0.7689) & (0.7651) \tabularnewline
SK3;SK5 & -0.0881 & -0.0699 & -0.0647 \tabularnewline
p-value & (0.3856) & (0.492) & (0.4911) \tabularnewline
SK3;SK6 & 0.0829 & 0.1334 & 0.1228 \tabularnewline
p-value & (0.4148) & (0.1879) & (0.1906) \tabularnewline
SK3;TVDC & 0.4127 & 0.544 & 0.4732 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
SK4;SK5 & 0.0414 & 0.0668 & 0.0647 \tabularnewline
p-value & (0.6842) & (0.511) & (0.5006) \tabularnewline
SK4;SK6 & -0.0534 & -0.035 & -0.0331 \tabularnewline
p-value & (0.5999) & (0.7309) & (0.7301) \tabularnewline
SK4;TVDC & 0.1082 & 0.349 & 0.3086 \tabularnewline
p-value & (0.2866) & (4e-04) & (4e-04) \tabularnewline
SK5;SK6 & 0.1426 & 0.1857 & 0.1755 \tabularnewline
p-value & (0.1591) & (0.0657) & (0.0667) \tabularnewline
SK5;TVDC & 0.2836 & 0.4833 & 0.429 \tabularnewline
p-value & (0.0044) & (0) & (0) \tabularnewline
SK6;TVDC & 0.4329 & 0.5666 & 0.5005 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297556&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]SK1;SK2[/C][C]0.369[/C][C]0.2933[/C][C]0.2696[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](0.0032)[/C][C](0.0031)[/C][/ROW]
[ROW][C]SK1;SK3[/C][C]0.0264[/C][C]0.0221[/C][C]0.0197[/C][/ROW]
[ROW][C]p-value[/C][C](0.7957)[/C][C](0.8284)[/C][C](0.8285)[/C][/ROW]
[ROW][C]SK1;SK4[/C][C]0.0341[/C][C]0.0626[/C][C]0.0585[/C][/ROW]
[ROW][C]p-value[/C][C](0.7373)[/C][C](0.5382)[/C][C](0.5274)[/C][/ROW]
[ROW][C]SK1;SK5[/C][C]0.0514[/C][C]0.0905[/C][C]0.0853[/C][/ROW]
[ROW][C]p-value[/C][C](0.6134)[/C][C](0.3732)[/C][C](0.3567)[/C][/ROW]
[ROW][C]SK1;SK6[/C][C]0.0617[/C][C]0.0712[/C][C]0.0642[/C][/ROW]
[ROW][C]p-value[/C][C](0.5441)[/C][C](0.4837)[/C][C](0.4867)[/C][/ROW]
[ROW][C]SK1;TVDC[/C][C]0.2284[/C][C]0.1367[/C][C]0.1158[/C][/ROW]
[ROW][C]p-value[/C][C](0.023)[/C][C](0.1774)[/C][C](0.1716)[/C][/ROW]
[ROW][C]SK2;SK3[/C][C]0.1858[/C][C]0.1677[/C][C]0.156[/C][/ROW]
[ROW][C]p-value[/C][C](0.0655)[/C][C](0.097)[/C][C](0.0926)[/C][/ROW]
[ROW][C]SK2;SK4[/C][C]0.0565[/C][C]0.0563[/C][C]0.0528[/C][/ROW]
[ROW][C]p-value[/C][C](0.5783)[/C][C](0.5799)[/C][C](0.5776)[/C][/ROW]
[ROW][C]SK2;SK5[/C][C]-0.0065[/C][C]0.0204[/C][C]0.0184[/C][/ROW]
[ROW][C]p-value[/C][C](0.9489)[/C][C](0.8409)[/C][C](0.8461)[/C][/ROW]
[ROW][C]SK2;SK6[/C][C]-0.0025[/C][C]-0.0043[/C][C]-0.004[/C][/ROW]
[ROW][C]p-value[/C][C](0.9803)[/C][C](0.9665)[/C][C](0.9665)[/C][/ROW]
[ROW][C]SK2;TVDC[/C][C]0.2137[/C][C]0.1498[/C][C]0.129[/C][/ROW]
[ROW][C]p-value[/C][C](0.0337)[/C][C](0.1388)[/C][C](0.1364)[/C][/ROW]
[ROW][C]SK3;SK4[/C][C]-0.0736[/C][C]-0.0299[/C][C]-0.0281[/C][/ROW]
[ROW][C]p-value[/C][C](0.469)[/C][C](0.7689)[/C][C](0.7651)[/C][/ROW]
[ROW][C]SK3;SK5[/C][C]-0.0881[/C][C]-0.0699[/C][C]-0.0647[/C][/ROW]
[ROW][C]p-value[/C][C](0.3856)[/C][C](0.492)[/C][C](0.4911)[/C][/ROW]
[ROW][C]SK3;SK6[/C][C]0.0829[/C][C]0.1334[/C][C]0.1228[/C][/ROW]
[ROW][C]p-value[/C][C](0.4148)[/C][C](0.1879)[/C][C](0.1906)[/C][/ROW]
[ROW][C]SK3;TVDC[/C][C]0.4127[/C][C]0.544[/C][C]0.4732[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]SK4;SK5[/C][C]0.0414[/C][C]0.0668[/C][C]0.0647[/C][/ROW]
[ROW][C]p-value[/C][C](0.6842)[/C][C](0.511)[/C][C](0.5006)[/C][/ROW]
[ROW][C]SK4;SK6[/C][C]-0.0534[/C][C]-0.035[/C][C]-0.0331[/C][/ROW]
[ROW][C]p-value[/C][C](0.5999)[/C][C](0.7309)[/C][C](0.7301)[/C][/ROW]
[ROW][C]SK4;TVDC[/C][C]0.1082[/C][C]0.349[/C][C]0.3086[/C][/ROW]
[ROW][C]p-value[/C][C](0.2866)[/C][C](4e-04)[/C][C](4e-04)[/C][/ROW]
[ROW][C]SK5;SK6[/C][C]0.1426[/C][C]0.1857[/C][C]0.1755[/C][/ROW]
[ROW][C]p-value[/C][C](0.1591)[/C][C](0.0657)[/C][C](0.0667)[/C][/ROW]
[ROW][C]SK5;TVDC[/C][C]0.2836[/C][C]0.4833[/C][C]0.429[/C][/ROW]
[ROW][C]p-value[/C][C](0.0044)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]SK6;TVDC[/C][C]0.4329[/C][C]0.5666[/C][C]0.5005[/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=297556&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297556&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
SK1;SK2	0.369	0.2933	0.2696
p-value	(2e-04)	(0.0032)	(0.0031)
SK1;SK3	0.0264	0.0221	0.0197
p-value	(0.7957)	(0.8284)	(0.8285)
SK1;SK4	0.0341	0.0626	0.0585
p-value	(0.7373)	(0.5382)	(0.5274)
SK1;SK5	0.0514	0.0905	0.0853
p-value	(0.6134)	(0.3732)	(0.3567)
SK1;SK6	0.0617	0.0712	0.0642
p-value	(0.5441)	(0.4837)	(0.4867)
SK1;TVDC	0.2284	0.1367	0.1158
p-value	(0.023)	(0.1774)	(0.1716)
SK2;SK3	0.1858	0.1677	0.156
p-value	(0.0655)	(0.097)	(0.0926)
SK2;SK4	0.0565	0.0563	0.0528
p-value	(0.5783)	(0.5799)	(0.5776)
SK2;SK5	-0.0065	0.0204	0.0184
p-value	(0.9489)	(0.8409)	(0.8461)
SK2;SK6	-0.0025	-0.0043	-0.004
p-value	(0.9803)	(0.9665)	(0.9665)
SK2;TVDC	0.2137	0.1498	0.129
p-value	(0.0337)	(0.1388)	(0.1364)
SK3;SK4	-0.0736	-0.0299	-0.0281
p-value	(0.469)	(0.7689)	(0.7651)
SK3;SK5	-0.0881	-0.0699	-0.0647
p-value	(0.3856)	(0.492)	(0.4911)
SK3;SK6	0.0829	0.1334	0.1228
p-value	(0.4148)	(0.1879)	(0.1906)
SK3;TVDC	0.4127	0.544	0.4732
p-value	(0)	(0)	(0)
SK4;SK5	0.0414	0.0668	0.0647
p-value	(0.6842)	(0.511)	(0.5006)
SK4;SK6	-0.0534	-0.035	-0.0331
p-value	(0.5999)	(0.7309)	(0.7301)
SK4;TVDC	0.1082	0.349	0.3086
p-value	(0.2866)	(4e-04)	(4e-04)
SK5;SK6	0.1426	0.1857	0.1755
p-value	(0.1591)	(0.0657)	(0.0667)
SK5;TVDC	0.2836	0.4833	0.429
p-value	(0.0044)	(0)	(0)
SK6;TVDC	0.4329	0.5666	0.5005
p-value	(0)	(0)	(0)

Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I error	Pearson r	Spearman rho	Kendall tau
0.01	0.19	0.24	0.24
0.02	0.19	0.24	0.24
0.03	0.24	0.24	0.24
0.04	0.29	0.24	0.24
0.05	0.29	0.24	0.24
0.06	0.29	0.24	0.24
0.07	0.33	0.29	0.29
0.08	0.33	0.29	0.29
0.09	0.33	0.29	0.29
0.1	0.33	0.33	0.33

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Correlation Tests \tabularnewline
Number of significant by total number of Correlations \tabularnewline
Type I error & Pearson r & Spearman rho & Kendall tau \tabularnewline
0.01 & 0.19 & 0.24 & 0.24 \tabularnewline
0.02 & 0.19 & 0.24 & 0.24 \tabularnewline
0.03 & 0.24 & 0.24 & 0.24 \tabularnewline
0.04 & 0.29 & 0.24 & 0.24 \tabularnewline
0.05 & 0.29 & 0.24 & 0.24 \tabularnewline
0.06 & 0.29 & 0.24 & 0.24 \tabularnewline
0.07 & 0.33 & 0.29 & 0.29 \tabularnewline
0.08 & 0.33 & 0.29 & 0.29 \tabularnewline
0.09 & 0.33 & 0.29 & 0.29 \tabularnewline
0.1 & 0.33 & 0.33 & 0.33 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297556&T=3

[TABLE]
[ROW][C]Meta Analysis of Correlation Tests[/C][/ROW]
[ROW][C]Number of significant by total number of Correlations[/C][/ROW]
[ROW][C]Type I error[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]0.01[/C][C]0.19[/C][C]0.24[/C][C]0.24[/C][/ROW]
[ROW][C]0.02[/C][C]0.19[/C][C]0.24[/C][C]0.24[/C][/ROW]
[ROW][C]0.03[/C][C]0.24[/C][C]0.24[/C][C]0.24[/C][/ROW]
[ROW][C]0.04[/C][C]0.29[/C][C]0.24[/C][C]0.24[/C][/ROW]
[ROW][C]0.05[/C][C]0.29[/C][C]0.24[/C][C]0.24[/C][/ROW]
[ROW][C]0.06[/C][C]0.29[/C][C]0.24[/C][C]0.24[/C][/ROW]
[ROW][C]0.07[/C][C]0.33[/C][C]0.29[/C][C]0.29[/C][/ROW]
[ROW][C]0.08[/C][C]0.33[/C][C]0.29[/C][C]0.29[/C][/ROW]
[ROW][C]0.09[/C][C]0.33[/C][C]0.29[/C][C]0.29[/C][/ROW]
[ROW][C]0.1[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=297556&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297556&T=3

As an alternative you can also use a QR Code:

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

Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I error	Pearson r	Spearman rho	Kendall tau
0.01	0.19	0.24	0.24
0.02	0.19	0.24	0.24
0.03	0.24	0.24	0.24
0.04	0.29	0.24	0.24
0.05	0.29	0.24	0.24
0.06	0.29	0.24	0.24
0.07	0.33	0.29	0.29
0.08	0.33	0.29	0.29
0.09	0.33	0.29	0.29
0.1	0.33	0.33	0.33

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$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
x <- na.omit(x)
y <- t(na.omit(t(y)))
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
print(n)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$estimate,3))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
ncorrs <- (n*n -n)/2
mycorrs <- array(0, dim=c(10,3))
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)
for (iii in 1:10) {
iiid100 <- iii / 100
if (rp$p.value < iiid100) mycorrs[iii, 1] = mycorrs[iii, 1] + 1
if (rs$p.value < iiid100) mycorrs[iii, 2] = mycorrs[iii, 2] + 1
if (rk$p.value < iiid100) mycorrs[iii, 3] = mycorrs[iii, 3] + 1
}
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Correlation Tests',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of significant by total number of Correlations',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Type I error',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)
for (iii in 1:10) {
iiid100 <- iii / 100
a<-table.row.start(a)
a<-table.element(a,round(iiid100,2),header=T)
a<-table.element(a,round(mycorrs[iii,1]/ncorrs,2))
a<-table.element(a,round(mycorrs[iii,2]/ncorrs,2))
a<-table.element(a,round(mycorrs[iii,3]/ncorrs,2))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code