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R Software Module

Patrick.Wessarwasp_pairs.wasp

Title produced by software

Kendall tau Correlation Matrix

Date of computation

Mon, 20 Dec 2010 12:49:48 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/20/t1292849337odlfqrdppa2milv.htm/, Retrieved Fri, 03 May 2024 17:26:30 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112888, Retrieved Fri, 03 May 2024 17:26:30 +0000

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Estimated Impact

103

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 17:44:33] [b98453cac15ba1066b407e146608df68]
-   PD    [Kendall tau Correlation Matrix] [] [2010-12-20 12:49:48] [76f6fcd790878de142f355e7238b5c71] [Current]

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Dataseries X:

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Boxplots

2	5	2	3	3	4	4
2	4	2	4	3	4	4
4	4	2	4	2	5	4
2	4	2	2	2	2	4
3	2	2	2	3	2	4
4	5	1	3	2	4	5
3	5	1	2	1	4	4
3	4	3	3	3	4	3
3	3	2	3	2	4	4
2	4	1	3	2	2	4
4	4	4	3	3	3	4
4	2	2	4	2	4	4
3	3	3	2	2	3	4
3	3	2	2	2	4	2
4	4	1	1	3	4	3
4	5	1	1	1	4	4
3	4	2	3	3	4	3
3	2	2	2	2	2	2
3	4	2	2	3	4	4
4	4	2	3	4	4	3
2	4	1	4	2	4	3
5	4	2	4	3	3	4
4	4	4	3	5	2	3
2	4	2	2	2	4	3
3	5	2	3	2	2	4
4	4	2	4	3	3	4
4	4	2	3	2	4	4
3	4	2	2	2	3	4
4	4	3	1	2	4	4
4	4	2	3	2	4	4
1	4	1	2	3	4	5
4	4	4	4	4	4	4
5	2	1	4	1	4	4
2	4	2	5	3	4	4
4	4	2	2	3	4	3
3	5	2	4	2	5	4
2	5	2	4	1	4	3
4	4	2	2	1	2	4
5	3	2	4	2	4	4
4	4	2	4	2	4	3
4	5	2	2	2	5	5
4	4	2	3	1	4	4
3	4	2	2	2	2	3
4	5	2	4	1	4	3
2	4	2	3	2	4	3
2	5	1	1	2	4	4
4	4	2	2	4	2	4
2	4	1	5	2	5	4
4	4	2	2	2	4	4
4	3	1	4	2	4	4
1	4	1	4	1	4	4
4	4	2	2	2	4	4
2	4	2	2	2	4	5
1	2	1	2	1	3	3
4	3	5	4	5	5	3
3	5	2	3	2	4	5
2	4	2	4	2	4	5
4	4	1	2	2	4	4
3	5	1	3	1	4	4
2	3	2	2	3	2	3
2	5	2	2	1	4	4
3	4	1	3	1	4	4
2	5	1	2	2	4	5
1	4	2	3	3	4	4
3	4	1	2	2	3	4
2	5	1	4	2	4	5
3	4	2	2	2	2	4
3	4	1	5	4	4	3
3	5	1	1	1	4	4
2	4	2	3	2	4	4
3	3	1	2	2	4	4
2	4	1	2	2	4	4
4	5	3	3	2	4	4
4	5	3	4	2	3	4
4	5	2	4	1	4	4
2	4	2	2	2	4	3
3	4	1	3	2	4	4
4	5	3	4	2	4	3
3	5	2	2	2	4	5
4	4	2	2	1	4	4
2	5	2	4	4	4	5
3	3	2	2	2	2	5
3	4	1	4	3	3	4
4	4	4	2	2	5	4
2	4	1	3	1	3	4
4	4	1	4	2	3	4
2	4	1	3	2	4	4
2	5	1	1	1	4	5
4	4	4	3	2	4	4
3	4	2	2	1	4	3
4	4	2	2	2	4	4
2	5	1	1	1	3	3
2	3	1	3	2	4	4
3	3	1	2	2	4	4
3	5	3	3	3	4	4
5	5	4	5	4	5	4
2	4	4	3	1	4	4
3	4	3	4	3	4	3
4	4	2	2	1	2	3
3	4	2	2	1	3	3
4	4	3	3	2	3	3
3	4	1	2	1	3	3
3	4	3	2	3	4	2
2	4	2	2	2	4	3
3	5	2	3	2	2	5
2	2	2	5	1	3	2
3	4	2	2	2	3	2
2	2	4	3	2	4	3
4	4	3	3	1	4	3
2	5	1	1	2	2	3
4	3	1	1	2	3	4
4	4	2	3	4	4	4
1	3	1	4	3	4	3
5	4	3	5	2	5	2
2	4	2	3	5	3	3
3	4	2	3	1	3	4
4	2	2	3	2	4	2
1	1	1	2	1	3	4
5	4	3	3	2	3	4
3	3	1	2	1	2	2
3	4	1	3	1	4	3
3	3	2	2	2	3	3
3	3	3	4	2	4	3
2	5	2	2	2	5	4
2	4	1	2	3	4	4
4	3	2	4	2	3	4
4	4	1	4	1	3	3
3	4	2	3	2	3	4
3	4	1	3	2	3	4
3	4	2	3	3	4	4
4	3	3	4	2	4	2
3	4	2	2	2	3	4
4	4	1	1	2	2	5
4	4	1	3	1	3	4
2	4	2	2	2	2	4
4	4	2	3	2	4	4
2	3	1	2	2	4	3
4	4	2	2	3	4	1
3	4	3	3	1	4	4
3	2	4	2	3	4	3
2	2	2	4	4	4	3
2	4	4	4	2	5	3
5	2	5	2	5	3	1
2	4	1	2	1	4	4
4	3	3	3	2	4	5
3	4	2	4	3	4	4
3	3	2	4	2	5	3
3	2	2	4	2	3	4
3	2	1	1	3	2	3
4	4	4	4	2	4	4
4	3	2	4	1	3	4
4	4	2	3	2	4	4
4	4	3	1	1	5	5
4	2	1	2	2	3	2
5	5	4	2	3	3	3
3	4	2	2	2	3	3
3	4	2	3	2	5	4
4	4	4	3	2	4	4
4	3	4	3	4	2	3

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 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=112888&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=112888&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112888&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	3 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Correlations for all pairs of data series (method=pearson)
	standards	organization	punished	secondrate	mistakes	competent	neat
standards	1	0.008	0.365	0.104	0.102	0.006	-0.083
organization	0.008	1	-0.051	-0.035	-0.095	0.199	0.362
punished	0.365	-0.051	1	0.193	0.373	0.129	-0.191
secondrate	0.104	-0.035	0.193	1	0.168	0.287	-0.022
mistakes	0.102	-0.095	0.373	0.168	1	-0.012	-0.152
competent	0.006	0.199	0.129	0.287	-0.012	1	0.104
neat	-0.083	0.362	-0.191	-0.022	-0.152	0.104	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & standards & organization & punished & secondrate & mistakes & competent & neat \tabularnewline
standards & 1 & 0.008 & 0.365 & 0.104 & 0.102 & 0.006 & -0.083 \tabularnewline
organization & 0.008 & 1 & -0.051 & -0.035 & -0.095 & 0.199 & 0.362 \tabularnewline
punished & 0.365 & -0.051 & 1 & 0.193 & 0.373 & 0.129 & -0.191 \tabularnewline
secondrate & 0.104 & -0.035 & 0.193 & 1 & 0.168 & 0.287 & -0.022 \tabularnewline
mistakes & 0.102 & -0.095 & 0.373 & 0.168 & 1 & -0.012 & -0.152 \tabularnewline
competent & 0.006 & 0.199 & 0.129 & 0.287 & -0.012 & 1 & 0.104 \tabularnewline
neat & -0.083 & 0.362 & -0.191 & -0.022 & -0.152 & 0.104 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112888&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]standards[/C][C]organization[/C][C]punished[/C][C]secondrate[/C][C]mistakes[/C][C]competent[/C][C]neat[/C][/ROW]
[ROW][C]standards[/C][C]1[/C][C]0.008[/C][C]0.365[/C][C]0.104[/C][C]0.102[/C][C]0.006[/C][C]-0.083[/C][/ROW]
[ROW][C]organization[/C][C]0.008[/C][C]1[/C][C]-0.051[/C][C]-0.035[/C][C]-0.095[/C][C]0.199[/C][C]0.362[/C][/ROW]
[ROW][C]punished[/C][C]0.365[/C][C]-0.051[/C][C]1[/C][C]0.193[/C][C]0.373[/C][C]0.129[/C][C]-0.191[/C][/ROW]
[ROW][C]secondrate[/C][C]0.104[/C][C]-0.035[/C][C]0.193[/C][C]1[/C][C]0.168[/C][C]0.287[/C][C]-0.022[/C][/ROW]
[ROW][C]mistakes[/C][C]0.102[/C][C]-0.095[/C][C]0.373[/C][C]0.168[/C][C]1[/C][C]-0.012[/C][C]-0.152[/C][/ROW]
[ROW][C]competent[/C][C]0.006[/C][C]0.199[/C][C]0.129[/C][C]0.287[/C][C]-0.012[/C][C]1[/C][C]0.104[/C][/ROW]
[ROW][C]neat[/C][C]-0.083[/C][C]0.362[/C][C]-0.191[/C][C]-0.022[/C][C]-0.152[/C][C]0.104[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112888&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112888&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)
	standards	organization	punished	secondrate	mistakes	competent	neat
standards	1	0.008	0.365	0.104	0.102	0.006	-0.083
organization	0.008	1	-0.051	-0.035	-0.095	0.199	0.362
punished	0.365	-0.051	1	0.193	0.373	0.129	-0.191
secondrate	0.104	-0.035	0.193	1	0.168	0.287	-0.022
mistakes	0.102	-0.095	0.373	0.168	1	-0.012	-0.152
competent	0.006	0.199	0.129	0.287	-0.012	1	0.104
neat	-0.083	0.362	-0.191	-0.022	-0.152	0.104	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
standards;organization	0.0078	-0.0337	-0.0291
p-value	(0.9218)	(0.6728)	(0.6728)
standards;punished	0.3655	0.3515	0.3112
p-value	(0)	(0)	(0)
standards;secondrate	0.1038	0.1141	0.1011
p-value	(0.1927)	(0.1522)	(0.1338)
standards;mistakes	0.1024	0.0619	0.053
p-value	(0.1989)	(0.4384)	(0.439)
standards;competent	0.0065	-0.0035	-0.0024
p-value	(0.9356)	(0.9652)	(0.9721)
standards;neat	-0.083	-0.0242	-0.0211
p-value	(0.2981)	(0.7622)	(0.761)
organization;punished	-0.0506	-0.0281	-0.0252
p-value	(0.5268)	(0.7247)	(0.7176)
organization;secondrate	-0.0347	-0.0358	-0.0307
p-value	(0.6641)	(0.6542)	(0.6547)
organization;mistakes	-0.0954	-0.1074	-0.0936
p-value	(0.2315)	(0.1778)	(0.1791)
organization;competent	0.1986	0.1996	0.1766
p-value	(0.0121)	(0.0117)	(0.0119)
organization;neat	0.3619	0.3362	0.3033
p-value	(0)	(0)	(0)
punished;secondrate	0.193	0.2074	0.1816
p-value	(0.0148)	(0.0087)	(0.0078)
punished;mistakes	0.3727	0.2951	0.2623
p-value	(0)	(2e-04)	(2e-04)
punished;competent	0.1291	0.1278	0.1123
p-value	(0.1048)	(0.1083)	(0.1087)
punished;neat	-0.1912	-0.1604	-0.1406
p-value	(0.0157)	(0.0434)	(0.045)
secondrate;mistakes	0.1684	0.1433	0.1234
p-value	(0.0339)	(0.0715)	(0.0707)
secondrate;competent	0.2873	0.2621	0.2306
p-value	(2e-04)	(8e-04)	(8e-04)
secondrate;neat	-0.0216	-0.0111	-0.0112
p-value	(0.7869)	(0.8899)	(0.8713)
mistakes;competent	-0.0122	0.0272	0.0241
p-value	(0.8788)	(0.7337)	(0.7303)
mistakes;neat	-0.152	-0.0986	-0.0863
p-value	(0.0558)	(0.2165)	(0.2182)
competent;neat	0.1036	0.1158	0.1037
p-value	(0.1938)	(0.1461)	(0.142)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
standards;organization & 0.0078 & -0.0337 & -0.0291 \tabularnewline
p-value & (0.9218) & (0.6728) & (0.6728) \tabularnewline
standards;punished & 0.3655 & 0.3515 & 0.3112 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
standards;secondrate & 0.1038 & 0.1141 & 0.1011 \tabularnewline
p-value & (0.1927) & (0.1522) & (0.1338) \tabularnewline
standards;mistakes & 0.1024 & 0.0619 & 0.053 \tabularnewline
p-value & (0.1989) & (0.4384) & (0.439) \tabularnewline
standards;competent & 0.0065 & -0.0035 & -0.0024 \tabularnewline
p-value & (0.9356) & (0.9652) & (0.9721) \tabularnewline
standards;neat & -0.083 & -0.0242 & -0.0211 \tabularnewline
p-value & (0.2981) & (0.7622) & (0.761) \tabularnewline
organization;punished & -0.0506 & -0.0281 & -0.0252 \tabularnewline
p-value & (0.5268) & (0.7247) & (0.7176) \tabularnewline
organization;secondrate & -0.0347 & -0.0358 & -0.0307 \tabularnewline
p-value & (0.6641) & (0.6542) & (0.6547) \tabularnewline
organization;mistakes & -0.0954 & -0.1074 & -0.0936 \tabularnewline
p-value & (0.2315) & (0.1778) & (0.1791) \tabularnewline
organization;competent & 0.1986 & 0.1996 & 0.1766 \tabularnewline
p-value & (0.0121) & (0.0117) & (0.0119) \tabularnewline
organization;neat & 0.3619 & 0.3362 & 0.3033 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
punished;secondrate & 0.193 & 0.2074 & 0.1816 \tabularnewline
p-value & (0.0148) & (0.0087) & (0.0078) \tabularnewline
punished;mistakes & 0.3727 & 0.2951 & 0.2623 \tabularnewline
p-value & (0) & (2e-04) & (2e-04) \tabularnewline
punished;competent & 0.1291 & 0.1278 & 0.1123 \tabularnewline
p-value & (0.1048) & (0.1083) & (0.1087) \tabularnewline
punished;neat & -0.1912 & -0.1604 & -0.1406 \tabularnewline
p-value & (0.0157) & (0.0434) & (0.045) \tabularnewline
secondrate;mistakes & 0.1684 & 0.1433 & 0.1234 \tabularnewline
p-value & (0.0339) & (0.0715) & (0.0707) \tabularnewline
secondrate;competent & 0.2873 & 0.2621 & 0.2306 \tabularnewline
p-value & (2e-04) & (8e-04) & (8e-04) \tabularnewline
secondrate;neat & -0.0216 & -0.0111 & -0.0112 \tabularnewline
p-value & (0.7869) & (0.8899) & (0.8713) \tabularnewline
mistakes;competent & -0.0122 & 0.0272 & 0.0241 \tabularnewline
p-value & (0.8788) & (0.7337) & (0.7303) \tabularnewline
mistakes;neat & -0.152 & -0.0986 & -0.0863 \tabularnewline
p-value & (0.0558) & (0.2165) & (0.2182) \tabularnewline
competent;neat & 0.1036 & 0.1158 & 0.1037 \tabularnewline
p-value & (0.1938) & (0.1461) & (0.142) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112888&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]standards;organization[/C][C]0.0078[/C][C]-0.0337[/C][C]-0.0291[/C][/ROW]
[ROW][C]p-value[/C][C](0.9218)[/C][C](0.6728)[/C][C](0.6728)[/C][/ROW]
[ROW][C]standards;punished[/C][C]0.3655[/C][C]0.3515[/C][C]0.3112[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]standards;secondrate[/C][C]0.1038[/C][C]0.1141[/C][C]0.1011[/C][/ROW]
[ROW][C]p-value[/C][C](0.1927)[/C][C](0.1522)[/C][C](0.1338)[/C][/ROW]
[ROW][C]standards;mistakes[/C][C]0.1024[/C][C]0.0619[/C][C]0.053[/C][/ROW]
[ROW][C]p-value[/C][C](0.1989)[/C][C](0.4384)[/C][C](0.439)[/C][/ROW]
[ROW][C]standards;competent[/C][C]0.0065[/C][C]-0.0035[/C][C]-0.0024[/C][/ROW]
[ROW][C]p-value[/C][C](0.9356)[/C][C](0.9652)[/C][C](0.9721)[/C][/ROW]
[ROW][C]standards;neat[/C][C]-0.083[/C][C]-0.0242[/C][C]-0.0211[/C][/ROW]
[ROW][C]p-value[/C][C](0.2981)[/C][C](0.7622)[/C][C](0.761)[/C][/ROW]
[ROW][C]organization;punished[/C][C]-0.0506[/C][C]-0.0281[/C][C]-0.0252[/C][/ROW]
[ROW][C]p-value[/C][C](0.5268)[/C][C](0.7247)[/C][C](0.7176)[/C][/ROW]
[ROW][C]organization;secondrate[/C][C]-0.0347[/C][C]-0.0358[/C][C]-0.0307[/C][/ROW]
[ROW][C]p-value[/C][C](0.6641)[/C][C](0.6542)[/C][C](0.6547)[/C][/ROW]
[ROW][C]organization;mistakes[/C][C]-0.0954[/C][C]-0.1074[/C][C]-0.0936[/C][/ROW]
[ROW][C]p-value[/C][C](0.2315)[/C][C](0.1778)[/C][C](0.1791)[/C][/ROW]
[ROW][C]organization;competent[/C][C]0.1986[/C][C]0.1996[/C][C]0.1766[/C][/ROW]
[ROW][C]p-value[/C][C](0.0121)[/C][C](0.0117)[/C][C](0.0119)[/C][/ROW]
[ROW][C]organization;neat[/C][C]0.3619[/C][C]0.3362[/C][C]0.3033[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]punished;secondrate[/C][C]0.193[/C][C]0.2074[/C][C]0.1816[/C][/ROW]
[ROW][C]p-value[/C][C](0.0148)[/C][C](0.0087)[/C][C](0.0078)[/C][/ROW]
[ROW][C]punished;mistakes[/C][C]0.3727[/C][C]0.2951[/C][C]0.2623[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](2e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]punished;competent[/C][C]0.1291[/C][C]0.1278[/C][C]0.1123[/C][/ROW]
[ROW][C]p-value[/C][C](0.1048)[/C][C](0.1083)[/C][C](0.1087)[/C][/ROW]
[ROW][C]punished;neat[/C][C]-0.1912[/C][C]-0.1604[/C][C]-0.1406[/C][/ROW]
[ROW][C]p-value[/C][C](0.0157)[/C][C](0.0434)[/C][C](0.045)[/C][/ROW]
[ROW][C]secondrate;mistakes[/C][C]0.1684[/C][C]0.1433[/C][C]0.1234[/C][/ROW]
[ROW][C]p-value[/C][C](0.0339)[/C][C](0.0715)[/C][C](0.0707)[/C][/ROW]
[ROW][C]secondrate;competent[/C][C]0.2873[/C][C]0.2621[/C][C]0.2306[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](8e-04)[/C][C](8e-04)[/C][/ROW]
[ROW][C]secondrate;neat[/C][C]-0.0216[/C][C]-0.0111[/C][C]-0.0112[/C][/ROW]
[ROW][C]p-value[/C][C](0.7869)[/C][C](0.8899)[/C][C](0.8713)[/C][/ROW]
[ROW][C]mistakes;competent[/C][C]-0.0122[/C][C]0.0272[/C][C]0.0241[/C][/ROW]
[ROW][C]p-value[/C][C](0.8788)[/C][C](0.7337)[/C][C](0.7303)[/C][/ROW]
[ROW][C]mistakes;neat[/C][C]-0.152[/C][C]-0.0986[/C][C]-0.0863[/C][/ROW]
[ROW][C]p-value[/C][C](0.0558)[/C][C](0.2165)[/C][C](0.2182)[/C][/ROW]
[ROW][C]competent;neat[/C][C]0.1036[/C][C]0.1158[/C][C]0.1037[/C][/ROW]
[ROW][C]p-value[/C][C](0.1938)[/C][C](0.1461)[/C][C](0.142)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112888&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112888&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
standards;organization	0.0078	-0.0337	-0.0291
p-value	(0.9218)	(0.6728)	(0.6728)
standards;punished	0.3655	0.3515	0.3112
p-value	(0)	(0)	(0)
standards;secondrate	0.1038	0.1141	0.1011
p-value	(0.1927)	(0.1522)	(0.1338)
standards;mistakes	0.1024	0.0619	0.053
p-value	(0.1989)	(0.4384)	(0.439)
standards;competent	0.0065	-0.0035	-0.0024
p-value	(0.9356)	(0.9652)	(0.9721)
standards;neat	-0.083	-0.0242	-0.0211
p-value	(0.2981)	(0.7622)	(0.761)
organization;punished	-0.0506	-0.0281	-0.0252
p-value	(0.5268)	(0.7247)	(0.7176)
organization;secondrate	-0.0347	-0.0358	-0.0307
p-value	(0.6641)	(0.6542)	(0.6547)
organization;mistakes	-0.0954	-0.1074	-0.0936
p-value	(0.2315)	(0.1778)	(0.1791)
organization;competent	0.1986	0.1996	0.1766
p-value	(0.0121)	(0.0117)	(0.0119)
organization;neat	0.3619	0.3362	0.3033
p-value	(0)	(0)	(0)
punished;secondrate	0.193	0.2074	0.1816
p-value	(0.0148)	(0.0087)	(0.0078)
punished;mistakes	0.3727	0.2951	0.2623
p-value	(0)	(2e-04)	(2e-04)
punished;competent	0.1291	0.1278	0.1123
p-value	(0.1048)	(0.1083)	(0.1087)
punished;neat	-0.1912	-0.1604	-0.1406
p-value	(0.0157)	(0.0434)	(0.045)
secondrate;mistakes	0.1684	0.1433	0.1234
p-value	(0.0339)	(0.0715)	(0.0707)
secondrate;competent	0.2873	0.2621	0.2306
p-value	(2e-04)	(8e-04)	(8e-04)
secondrate;neat	-0.0216	-0.0111	-0.0112
p-value	(0.7869)	(0.8899)	(0.8713)
mistakes;competent	-0.0122	0.0272	0.0241
p-value	(0.8788)	(0.7337)	(0.7303)
mistakes;neat	-0.152	-0.0986	-0.0863
p-value	(0.0558)	(0.2165)	(0.2182)
competent;neat	0.1036	0.1158	0.1037
p-value	(0.1938)	(0.1461)	(0.142)

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