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Author*The author of this computation has been verified*
R Software ModulePatrick.Wessarwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationFri, 10 Dec 2010 12:53:49 +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/10/t12919855777b2jqqn7b27o8kb.htm/, Retrieved Mon, 29 Apr 2024 08:10:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107622, Retrieved Mon, 29 Apr 2024 08:10:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact226
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [] [2010-12-05 18:04:16] [b98453cac15ba1066b407e146608df68]
F   PD    [Kendall tau Correlation Matrix] [Workshop 10 - Ken...] [2010-12-10 12:53:49] [708f372e2a7a3c78ea31b4de2d1213f8] [Current]
Feedback Forum
2010-12-16 12:39:07 [Stefanie Van Esbroeck] [reply
Je maakt een correcte berekening van de Kendall Tau Correlation Matrix. Je interpreteerde de gegeven output ook correct. Enkel zou ik hier ook een theoretische uitleg aan toevoegen. Zo kan je zeggen dat deze matrix dezelfde output weergeeft maar dat deze output betrouwbaardere resultaten laat zien omdat dit model robuuster is. Je interpretatie is eigenlijk verkeerd. Je kijkt hier ook weer naar de normaalverdeling maar aangezien de Kendall Tau zich van de normaalverdeling niets aantrekt, is het ook niet nuttig om deze dan ook te interpreteren hier. Eigenlijk toont dit model hethzelfde als de Pearson correlatie maar dan robuuster. Om je conclusie te vormen zou ik dan voornamelijk kijken naar de p-waarde en de scatterplot.

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Dataseries X:
0	1	24	14	11	12	24	26
1	1	25	11	7	8	25	23
1	0	17	6	17	8	30	25
0	1	18	12	10	8	19	23
1	0	16	10	12	7	22	29
1	1	20	10	11	4	25	25
1	1	16	11	11	11	23	21
1	1	18	16	12	7	17	22
1	1	17	11	13	7	21	25
0	1	23	13	14	12	19	24
1	1	30	12	16	10	19	18
1	1	18	12	10	8	16	15
0	1	15	11	11	8	23	22
0	1	12	4	15	4	27	28
1	1	21	9	9	9	22	20
0	1	20	8	17	7	22	24
1	1	27	15	11	9	23	21
0	1	34	16	18	11	21	20
1	1	21	9	14	13	19	21
0	1	31	14	10	8	18	23
0	1	19	11	11	8	20	28
1	1	16	8	15	9	23	24
1	1	20	9	15	6	25	24
0	1	21	9	13	9	19	24
0	1	22	9	16	9	24	23
1	1	17	9	13	6	22	23
0	1	24	10	9	6	25	29
1	1	25	16	18	16	26	24
1	1	26	11	18	5	29	18
1	1	25	8	12	7	32	25
1	1	17	9	17	9	25	21
0	1	32	16	9	6	29	26
0	1	33	11	9	6	28	22
0	0	32	12	18	12	28	22
0	1	25	12	12	7	29	23
0	1	29	14	18	10	26	30
1	1	22	9	14	9	25	23
0	1	18	10	15	8	14	17
1	1	17	9	16	5	25	23
0	1	20	10	10	8	26	23
0	1	15	12	11	8	20	25
1	1	20	14	14	10	18	24
0	1	33	14	9	6	32	24
1	1	23	14	17	7	25	21
0	1	26	16	5	4	23	24
0	1	18	9	12	8	21	24
1	1	20	10	12	8	20	28
1	1	11	6	6	4	15	16
0	1	28	8	24	20	30	20
1	1	26	13	12	8	24	29
1	1	22	10	12	8	26	27
0	1	17	8	14	6	24	22
0	1	12	7	7	4	22	28
0	1	17	9	12	9	24	25
1	0	19	12	14	7	24	28
0	1	18	13	8	9	24	24
0	1	10	10	11	5	19	23
0	1	29	11	9	5	31	30
0	1	31	8	11	8	22	24
0	1	9	13	10	6	19	25
1	0	20	11	11	8	25	25
1	1	28	8	12	7	20	22
1	1	19	9	9	7	21	23
1	1	29	15	18	11	23	23
1	1	26	9	15	6	25	25
1	1	23	10	12	8	20	21
0	1	13	14	13	6	21	25
1	1	21	12	14	9	22	24
0	1	19	12	10	8	23	29
1	1	28	11	13	6	25	22
1	1	23	14	13	10	25	27
1	0	18	6	11	8	17	26
0	1	21	12	13	8	19	22
1	1	20	8	16	10	25	24
1	1	21	10	11	5	26	24
1	1	28	12	16	14	27	22
0	1	26	14	14	8	17	24
1	1	10	5	8	6	19	24
0	0	16	11	9	5	17	23
0	1	22	10	15	6	22	20
0	1	19	9	11	10	21	27
1	1	31	10	21	12	32	26
0	1	31	16	14	9	21	25
1	1	29	13	18	12	21	21
0	1	19	9	12	7	18	21
1	1	22	10	13	8	18	19
0	1	15	7	12	6	19	21
1	1	20	9	19	10	20	16
0	1	23	14	11	10	20	29
1	1	24	9	13	10	19	15
1	1	25	14	15	11	22	21
1	1	13	8	12	7	14	19
1	1	28	8	16	12	18	24
1	0	25	7	18	11	35	17
1	1	9	6	8	11	29	23
0	1	17	11	9	6	20	19
0	1	25	14	15	9	22	24
1	1	15	8	6	6	20	25
0	1	19	20	8	7	19	25
1	0	15	8	10	4	22	24
1	1	20	11	11	8	24	26
1	1	18	10	14	9	21	26
1	1	33	14	11	8	26	25
1	1	16	9	12	8	16	21
0	1	17	9	11	5	23	26
1	1	16	8	9	4	18	23
0	1	21	10	12	8	16	23
0	1	26	13	20	10	26	22
1	1	18	12	13	9	21	13
1	1	22	13	12	13	22	15
1	1	30	14	9	9	23	14
1	1	24	14	24	20	21	10
1	1	29	16	11	6	27	24
1	1	31	9	17	9	25	19
1	0	20	9	11	7	21	20
1	1	20	7	11	9	26	22
1	1	28	16	16	8	24	24
1	1	17	9	13	6	19	21
0	1	28	14	11	8	24	24
1	1	31	16	19	16	17	20




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107622&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107622&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107622&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Correlations for all pairs of data series (method=pearson)
GeslachtBrowserCMDAPEPCPSO
Geslacht1-0.133-0.017-0.1620.1530.1320.033-0.271
Browser-0.13310.0990.179-0.0240.064-0.115-0.082
CM-0.0170.09910.4920.3380.3570.37-0.056
DA-0.1620.1790.49210.0610.235-0.0210.019
PE0.153-0.0240.3380.06110.6130.205-0.249
PC0.1320.0640.3570.2350.61310.074-0.298
PS0.033-0.1150.37-0.0210.2050.07410.235
O-0.271-0.082-0.0560.019-0.249-0.2980.2351

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Geslacht & Browser & CM & DA & PE & PC & PS & O \tabularnewline
Geslacht & 1 & -0.133 & -0.017 & -0.162 & 0.153 & 0.132 & 0.033 & -0.271 \tabularnewline
Browser & -0.133 & 1 & 0.099 & 0.179 & -0.024 & 0.064 & -0.115 & -0.082 \tabularnewline
CM & -0.017 & 0.099 & 1 & 0.492 & 0.338 & 0.357 & 0.37 & -0.056 \tabularnewline
DA & -0.162 & 0.179 & 0.492 & 1 & 0.061 & 0.235 & -0.021 & 0.019 \tabularnewline
PE & 0.153 & -0.024 & 0.338 & 0.061 & 1 & 0.613 & 0.205 & -0.249 \tabularnewline
PC & 0.132 & 0.064 & 0.357 & 0.235 & 0.613 & 1 & 0.074 & -0.298 \tabularnewline
PS & 0.033 & -0.115 & 0.37 & -0.021 & 0.205 & 0.074 & 1 & 0.235 \tabularnewline
O & -0.271 & -0.082 & -0.056 & 0.019 & -0.249 & -0.298 & 0.235 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107622&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Geslacht[/C][C]Browser[/C][C]CM[/C][C]DA[/C][C]PE[/C][C]PC[/C][C]PS[/C][C]O[/C][/ROW]
[ROW][C]Geslacht[/C][C]1[/C][C]-0.133[/C][C]-0.017[/C][C]-0.162[/C][C]0.153[/C][C]0.132[/C][C]0.033[/C][C]-0.271[/C][/ROW]
[ROW][C]Browser[/C][C]-0.133[/C][C]1[/C][C]0.099[/C][C]0.179[/C][C]-0.024[/C][C]0.064[/C][C]-0.115[/C][C]-0.082[/C][/ROW]
[ROW][C]CM[/C][C]-0.017[/C][C]0.099[/C][C]1[/C][C]0.492[/C][C]0.338[/C][C]0.357[/C][C]0.37[/C][C]-0.056[/C][/ROW]
[ROW][C]DA[/C][C]-0.162[/C][C]0.179[/C][C]0.492[/C][C]1[/C][C]0.061[/C][C]0.235[/C][C]-0.021[/C][C]0.019[/C][/ROW]
[ROW][C]PE[/C][C]0.153[/C][C]-0.024[/C][C]0.338[/C][C]0.061[/C][C]1[/C][C]0.613[/C][C]0.205[/C][C]-0.249[/C][/ROW]
[ROW][C]PC[/C][C]0.132[/C][C]0.064[/C][C]0.357[/C][C]0.235[/C][C]0.613[/C][C]1[/C][C]0.074[/C][C]-0.298[/C][/ROW]
[ROW][C]PS[/C][C]0.033[/C][C]-0.115[/C][C]0.37[/C][C]-0.021[/C][C]0.205[/C][C]0.074[/C][C]1[/C][C]0.235[/C][/ROW]
[ROW][C]O[/C][C]-0.271[/C][C]-0.082[/C][C]-0.056[/C][C]0.019[/C][C]-0.249[/C][C]-0.298[/C][C]0.235[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107622&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107622&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)
GeslachtBrowserCMDAPEPCPSO
Geslacht1-0.133-0.017-0.1620.1530.1320.033-0.271
Browser-0.13310.0990.179-0.0240.064-0.115-0.082
CM-0.0170.09910.4920.3380.3570.37-0.056
DA-0.1620.1790.49210.0610.235-0.0210.019
PE0.153-0.0240.3380.06110.6130.205-0.249
PC0.1320.0640.3570.2350.61310.074-0.298
PS0.033-0.1150.37-0.0210.2050.07410.235
O-0.271-0.082-0.0560.019-0.249-0.2980.2351







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Geslacht;Browser-0.1325-0.1325-0.1325
p-value(0.1491)(0.1491)(0.1483)
Geslacht;CM-0.0166-0.0049-0.0041
p-value(0.8569)(0.9577)(0.9575)
Geslacht;DA-0.1623-0.1671-0.1438
p-value(0.0765)(0.0681)(0.0683)
Geslacht;PE0.15310.18970.1618
p-value(0.095)(0.038)(0.0385)
Geslacht;PC0.13150.14280.1237
p-value(0.1521)(0.1197)(0.1192)
Geslacht;PS0.03310.04990.0423
p-value(0.7194)(0.588)(0.5859)
Geslacht;O-0.2713-0.2297-0.1963
p-value(0.0027)(0.0116)(0.0122)
Browser;CM0.09930.13080.1097
p-value(0.2803)(0.1545)(0.1536)
Browser;DA0.17930.16660.1433
p-value(0.05)(0.069)(0.0691)
Browser;PE-0.0243-0.0101-0.0086
p-value(0.7921)(0.9131)(0.9126)
Browser;PC0.0640.0660.0572
p-value(0.4875)(0.4739)(0.4715)
Browser;PS-0.1151-0.0729-0.0617
p-value(0.2107)(0.4286)(0.4263)
Browser;O-0.0816-0.0898-0.0768
p-value(0.3757)(0.3293)(0.3272)
CM;DA0.49210.48170.3704
p-value(0)(0)(0)
CM;PE0.33770.30420.2339
p-value(2e-04)(7e-04)(4e-04)
CM;PC0.35660.37330.2876
p-value(1e-04)(0)(0)
CM;PS0.36950.35810.2661
p-value(0)(1e-04)(0)
CM;O-0.0564-0.0766-0.055
p-value(0.5408)(0.4054)(0.4034)
DA;PE0.06110.04160.0248
p-value(0.5075)(0.6518)(0.7128)
DA;PC0.23530.23270.1786
p-value(0.0097)(0.0105)(0.009)
DA;PS-0.02070.02210.0181
p-value(0.8222)(0.8109)(0.7866)
DA;O0.01890.06030.0405
p-value(0.8377)(0.513)(0.5479)
PE;PC0.61280.48090.3732
p-value(0)(0)(0)
PE;PS0.20510.14240.1104
p-value(0.0247)(0.1208)(0.0958)
PE;O-0.2492-0.2258-0.1703
p-value(0.0061)(0.0131)(0.0109)
PC;PS0.07360.02630.0206
p-value(0.4241)(0.7752)(0.7594)
PC;O-0.2975-0.2038-0.15
p-value(0.001)(0.0255)(0.0272)
PS;O0.23530.24890.178
p-value(0.0097)(0.0061)(0.0074)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Geslacht;Browser & -0.1325 & -0.1325 & -0.1325 \tabularnewline
p-value & (0.1491) & (0.1491) & (0.1483) \tabularnewline
Geslacht;CM & -0.0166 & -0.0049 & -0.0041 \tabularnewline
p-value & (0.8569) & (0.9577) & (0.9575) \tabularnewline
Geslacht;DA & -0.1623 & -0.1671 & -0.1438 \tabularnewline
p-value & (0.0765) & (0.0681) & (0.0683) \tabularnewline
Geslacht;PE & 0.1531 & 0.1897 & 0.1618 \tabularnewline
p-value & (0.095) & (0.038) & (0.0385) \tabularnewline
Geslacht;PC & 0.1315 & 0.1428 & 0.1237 \tabularnewline
p-value & (0.1521) & (0.1197) & (0.1192) \tabularnewline
Geslacht;PS & 0.0331 & 0.0499 & 0.0423 \tabularnewline
p-value & (0.7194) & (0.588) & (0.5859) \tabularnewline
Geslacht;O & -0.2713 & -0.2297 & -0.1963 \tabularnewline
p-value & (0.0027) & (0.0116) & (0.0122) \tabularnewline
Browser;CM & 0.0993 & 0.1308 & 0.1097 \tabularnewline
p-value & (0.2803) & (0.1545) & (0.1536) \tabularnewline
Browser;DA & 0.1793 & 0.1666 & 0.1433 \tabularnewline
p-value & (0.05) & (0.069) & (0.0691) \tabularnewline
Browser;PE & -0.0243 & -0.0101 & -0.0086 \tabularnewline
p-value & (0.7921) & (0.9131) & (0.9126) \tabularnewline
Browser;PC & 0.064 & 0.066 & 0.0572 \tabularnewline
p-value & (0.4875) & (0.4739) & (0.4715) \tabularnewline
Browser;PS & -0.1151 & -0.0729 & -0.0617 \tabularnewline
p-value & (0.2107) & (0.4286) & (0.4263) \tabularnewline
Browser;O & -0.0816 & -0.0898 & -0.0768 \tabularnewline
p-value & (0.3757) & (0.3293) & (0.3272) \tabularnewline
CM;DA & 0.4921 & 0.4817 & 0.3704 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CM;PE & 0.3377 & 0.3042 & 0.2339 \tabularnewline
p-value & (2e-04) & (7e-04) & (4e-04) \tabularnewline
CM;PC & 0.3566 & 0.3733 & 0.2876 \tabularnewline
p-value & (1e-04) & (0) & (0) \tabularnewline
CM;PS & 0.3695 & 0.3581 & 0.2661 \tabularnewline
p-value & (0) & (1e-04) & (0) \tabularnewline
CM;O & -0.0564 & -0.0766 & -0.055 \tabularnewline
p-value & (0.5408) & (0.4054) & (0.4034) \tabularnewline
DA;PE & 0.0611 & 0.0416 & 0.0248 \tabularnewline
p-value & (0.5075) & (0.6518) & (0.7128) \tabularnewline
DA;PC & 0.2353 & 0.2327 & 0.1786 \tabularnewline
p-value & (0.0097) & (0.0105) & (0.009) \tabularnewline
DA;PS & -0.0207 & 0.0221 & 0.0181 \tabularnewline
p-value & (0.8222) & (0.8109) & (0.7866) \tabularnewline
DA;O & 0.0189 & 0.0603 & 0.0405 \tabularnewline
p-value & (0.8377) & (0.513) & (0.5479) \tabularnewline
PE;PC & 0.6128 & 0.4809 & 0.3732 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PE;PS & 0.2051 & 0.1424 & 0.1104 \tabularnewline
p-value & (0.0247) & (0.1208) & (0.0958) \tabularnewline
PE;O & -0.2492 & -0.2258 & -0.1703 \tabularnewline
p-value & (0.0061) & (0.0131) & (0.0109) \tabularnewline
PC;PS & 0.0736 & 0.0263 & 0.0206 \tabularnewline
p-value & (0.4241) & (0.7752) & (0.7594) \tabularnewline
PC;O & -0.2975 & -0.2038 & -0.15 \tabularnewline
p-value & (0.001) & (0.0255) & (0.0272) \tabularnewline
PS;O & 0.2353 & 0.2489 & 0.178 \tabularnewline
p-value & (0.0097) & (0.0061) & (0.0074) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107622&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]Geslacht;Browser[/C][C]-0.1325[/C][C]-0.1325[/C][C]-0.1325[/C][/ROW]
[ROW][C]p-value[/C][C](0.1491)[/C][C](0.1491)[/C][C](0.1483)[/C][/ROW]
[ROW][C]Geslacht;CM[/C][C]-0.0166[/C][C]-0.0049[/C][C]-0.0041[/C][/ROW]
[ROW][C]p-value[/C][C](0.8569)[/C][C](0.9577)[/C][C](0.9575)[/C][/ROW]
[ROW][C]Geslacht;DA[/C][C]-0.1623[/C][C]-0.1671[/C][C]-0.1438[/C][/ROW]
[ROW][C]p-value[/C][C](0.0765)[/C][C](0.0681)[/C][C](0.0683)[/C][/ROW]
[ROW][C]Geslacht;PE[/C][C]0.1531[/C][C]0.1897[/C][C]0.1618[/C][/ROW]
[ROW][C]p-value[/C][C](0.095)[/C][C](0.038)[/C][C](0.0385)[/C][/ROW]
[ROW][C]Geslacht;PC[/C][C]0.1315[/C][C]0.1428[/C][C]0.1237[/C][/ROW]
[ROW][C]p-value[/C][C](0.1521)[/C][C](0.1197)[/C][C](0.1192)[/C][/ROW]
[ROW][C]Geslacht;PS[/C][C]0.0331[/C][C]0.0499[/C][C]0.0423[/C][/ROW]
[ROW][C]p-value[/C][C](0.7194)[/C][C](0.588)[/C][C](0.5859)[/C][/ROW]
[ROW][C]Geslacht;O[/C][C]-0.2713[/C][C]-0.2297[/C][C]-0.1963[/C][/ROW]
[ROW][C]p-value[/C][C](0.0027)[/C][C](0.0116)[/C][C](0.0122)[/C][/ROW]
[ROW][C]Browser;CM[/C][C]0.0993[/C][C]0.1308[/C][C]0.1097[/C][/ROW]
[ROW][C]p-value[/C][C](0.2803)[/C][C](0.1545)[/C][C](0.1536)[/C][/ROW]
[ROW][C]Browser;DA[/C][C]0.1793[/C][C]0.1666[/C][C]0.1433[/C][/ROW]
[ROW][C]p-value[/C][C](0.05)[/C][C](0.069)[/C][C](0.0691)[/C][/ROW]
[ROW][C]Browser;PE[/C][C]-0.0243[/C][C]-0.0101[/C][C]-0.0086[/C][/ROW]
[ROW][C]p-value[/C][C](0.7921)[/C][C](0.9131)[/C][C](0.9126)[/C][/ROW]
[ROW][C]Browser;PC[/C][C]0.064[/C][C]0.066[/C][C]0.0572[/C][/ROW]
[ROW][C]p-value[/C][C](0.4875)[/C][C](0.4739)[/C][C](0.4715)[/C][/ROW]
[ROW][C]Browser;PS[/C][C]-0.1151[/C][C]-0.0729[/C][C]-0.0617[/C][/ROW]
[ROW][C]p-value[/C][C](0.2107)[/C][C](0.4286)[/C][C](0.4263)[/C][/ROW]
[ROW][C]Browser;O[/C][C]-0.0816[/C][C]-0.0898[/C][C]-0.0768[/C][/ROW]
[ROW][C]p-value[/C][C](0.3757)[/C][C](0.3293)[/C][C](0.3272)[/C][/ROW]
[ROW][C]CM;DA[/C][C]0.4921[/C][C]0.4817[/C][C]0.3704[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CM;PE[/C][C]0.3377[/C][C]0.3042[/C][C]0.2339[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](7e-04)[/C][C](4e-04)[/C][/ROW]
[ROW][C]CM;PC[/C][C]0.3566[/C][C]0.3733[/C][C]0.2876[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CM;PS[/C][C]0.3695[/C][C]0.3581[/C][C]0.2661[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](0)[/C][/ROW]
[ROW][C]CM;O[/C][C]-0.0564[/C][C]-0.0766[/C][C]-0.055[/C][/ROW]
[ROW][C]p-value[/C][C](0.5408)[/C][C](0.4054)[/C][C](0.4034)[/C][/ROW]
[ROW][C]DA;PE[/C][C]0.0611[/C][C]0.0416[/C][C]0.0248[/C][/ROW]
[ROW][C]p-value[/C][C](0.5075)[/C][C](0.6518)[/C][C](0.7128)[/C][/ROW]
[ROW][C]DA;PC[/C][C]0.2353[/C][C]0.2327[/C][C]0.1786[/C][/ROW]
[ROW][C]p-value[/C][C](0.0097)[/C][C](0.0105)[/C][C](0.009)[/C][/ROW]
[ROW][C]DA;PS[/C][C]-0.0207[/C][C]0.0221[/C][C]0.0181[/C][/ROW]
[ROW][C]p-value[/C][C](0.8222)[/C][C](0.8109)[/C][C](0.7866)[/C][/ROW]
[ROW][C]DA;O[/C][C]0.0189[/C][C]0.0603[/C][C]0.0405[/C][/ROW]
[ROW][C]p-value[/C][C](0.8377)[/C][C](0.513)[/C][C](0.5479)[/C][/ROW]
[ROW][C]PE;PC[/C][C]0.6128[/C][C]0.4809[/C][C]0.3732[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PE;PS[/C][C]0.2051[/C][C]0.1424[/C][C]0.1104[/C][/ROW]
[ROW][C]p-value[/C][C](0.0247)[/C][C](0.1208)[/C][C](0.0958)[/C][/ROW]
[ROW][C]PE;O[/C][C]-0.2492[/C][C]-0.2258[/C][C]-0.1703[/C][/ROW]
[ROW][C]p-value[/C][C](0.0061)[/C][C](0.0131)[/C][C](0.0109)[/C][/ROW]
[ROW][C]PC;PS[/C][C]0.0736[/C][C]0.0263[/C][C]0.0206[/C][/ROW]
[ROW][C]p-value[/C][C](0.4241)[/C][C](0.7752)[/C][C](0.7594)[/C][/ROW]
[ROW][C]PC;O[/C][C]-0.2975[/C][C]-0.2038[/C][C]-0.15[/C][/ROW]
[ROW][C]p-value[/C][C](0.001)[/C][C](0.0255)[/C][C](0.0272)[/C][/ROW]
[ROW][C]PS;O[/C][C]0.2353[/C][C]0.2489[/C][C]0.178[/C][/ROW]
[ROW][C]p-value[/C][C](0.0097)[/C][C](0.0061)[/C][C](0.0074)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107622&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107622&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
Geslacht;Browser-0.1325-0.1325-0.1325
p-value(0.1491)(0.1491)(0.1483)
Geslacht;CM-0.0166-0.0049-0.0041
p-value(0.8569)(0.9577)(0.9575)
Geslacht;DA-0.1623-0.1671-0.1438
p-value(0.0765)(0.0681)(0.0683)
Geslacht;PE0.15310.18970.1618
p-value(0.095)(0.038)(0.0385)
Geslacht;PC0.13150.14280.1237
p-value(0.1521)(0.1197)(0.1192)
Geslacht;PS0.03310.04990.0423
p-value(0.7194)(0.588)(0.5859)
Geslacht;O-0.2713-0.2297-0.1963
p-value(0.0027)(0.0116)(0.0122)
Browser;CM0.09930.13080.1097
p-value(0.2803)(0.1545)(0.1536)
Browser;DA0.17930.16660.1433
p-value(0.05)(0.069)(0.0691)
Browser;PE-0.0243-0.0101-0.0086
p-value(0.7921)(0.9131)(0.9126)
Browser;PC0.0640.0660.0572
p-value(0.4875)(0.4739)(0.4715)
Browser;PS-0.1151-0.0729-0.0617
p-value(0.2107)(0.4286)(0.4263)
Browser;O-0.0816-0.0898-0.0768
p-value(0.3757)(0.3293)(0.3272)
CM;DA0.49210.48170.3704
p-value(0)(0)(0)
CM;PE0.33770.30420.2339
p-value(2e-04)(7e-04)(4e-04)
CM;PC0.35660.37330.2876
p-value(1e-04)(0)(0)
CM;PS0.36950.35810.2661
p-value(0)(1e-04)(0)
CM;O-0.0564-0.0766-0.055
p-value(0.5408)(0.4054)(0.4034)
DA;PE0.06110.04160.0248
p-value(0.5075)(0.6518)(0.7128)
DA;PC0.23530.23270.1786
p-value(0.0097)(0.0105)(0.009)
DA;PS-0.02070.02210.0181
p-value(0.8222)(0.8109)(0.7866)
DA;O0.01890.06030.0405
p-value(0.8377)(0.513)(0.5479)
PE;PC0.61280.48090.3732
p-value(0)(0)(0)
PE;PS0.20510.14240.1104
p-value(0.0247)(0.1208)(0.0958)
PE;O-0.2492-0.2258-0.1703
p-value(0.0061)(0.0131)(0.0109)
PC;PS0.07360.02630.0206
p-value(0.4241)(0.7752)(0.7594)
PC;O-0.2975-0.2038-0.15
p-value(0.001)(0.0255)(0.0272)
PS;O0.23530.24890.178
p-value(0.0097)(0.0061)(0.0074)



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')