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Author's title

Author

*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

Wed, 14 Dec 2011 12:58:35 -0500

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/2011/Dec/14/t1323885534t1ctnwqfyq83qy2.htm/, Retrieved Wed, 01 May 2024 15:10:40 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=155160, Retrieved Wed, 01 May 2024 15:10:40 +0000

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Original text written by user:

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No (this computation is public)

User-defined keywords

Estimated Impact

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]
- RMP   [Kendall tau Correlation Matrix] [WS 10 Kendall's t...] [2011-12-14 16:01:30] [a98cda5652e91ff8cb6c2e418e82d3de]
- RMPD    [Multiple Regression] [WS 10 Multiple Re...] [2011-12-14 17:55:39] [a98cda5652e91ff8cb6c2e418e82d3de]
- RMP         [Kendall tau Correlation Matrix] [WS 10 Kendall] [2011-12-14 17:58:35] [312c935a345ba403c8b6fcfc5a5ec794] [Current]

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Dataseries X:

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Histogram

Boxplots

13	53	41	7	2
16	86	39	5	2
19	66	30	5	2
15	67	31	5	1
14	76	34	8	2
13	78	35	6	2
19	53	39	5	2
15	80	34	6	2
14	74	36	5	2
15	76	37	4	2
16	79	38	6	1
16	54	36	5	2
16	67	38	5	1
16	54	39	6	2
17	87	33	7	2
15	58	32	6	1
15	75	36	7	1
20	88	38	6	2
18	64	39	8	1
16	57	32	7	2
16	66	32	5	1
16	68	31	5	2
19	54	39	7	2
16	56	37	7	2
17	86	39	5	1
17	80	41	4	2
16	76	36	10	1
15	69	33	6	2
16	78	33	5	2
14	67	34	5	1
15	80	31	5	2
12	54	27	5	1
14	71	37	6	2
16	84	34	5	2
14	74	34	5	1
7	71	32	5	1
10	63	29	5	1
14	71	36	5	1
16	76	29	5	2
16	69	35	5	1
16	74	37	5	1
14	75	34	7	2
20	54	38	5	1
14	52	35	6	1
14	69	38	7	2
11	68	37	7	2
14	65	38	5	2
15	75	33	5	2
16	74	36	4	2
14	75	38	5	1
16	72	32	4	2
14	67	32	5	1
12	63	32	5	1
16	62	34	7	2
9	63	32	5	1
14	76	37	5	2
16	74	39	6	2
16	67	29	4	2
15	73	37	6	1
16	70	35	6	2
12	53	30	5	1
16	77	38	7	1
16	77	34	6	2
14	52	31	8	2
16	54	34	7	2
17	80	35	5	1
18	66	36	6	2
18	73	30	6	1
12	63	39	5	2
16	69	35	5	1
10	67	38	5	1
14	54	31	5	2
18	81	34	4	2
18	69	38	6	1
16	84	34	6	1
17	80	39	6	2
16	70	37	6	2
16	69	34	7	2
13	77	28	5	1
16	54	37	7	1
16	79	33	6	1
20	30	37	5	1
16	71	35	5	2
15	73	37	4	1
15	72	32	8	2
16	77	33	8	2
14	75	38	5	1
16	69	33	5	2
16	54	29	6	2
15	70	33	4	2
12	73	31	5	2
17	54	36	5	2
16	77	35	5	2
15	82	32	5	2
13	80	29	6	2
16	80	39	6	2
16	69	37	5	2
16	78	35	6	2
16	81	37	5	1
14	76	32	7	1
16	76	38	5	2
16	73	37	6	1
20	85	36	6	2
15	66	32	6	1
16	79	33	4	2
13	68	40	5	1
17	76	38	5	2
16	71	41	7	1
16	54	36	6	1
12	46	43	9	2
16	82	30	6	2
16	74	31	6	2
17	88	32	5	2
13	38	32	6	1
12	76	37	5	2
18	86	37	8	1
14	54	33	7	2
14	70	34	5	2
13	69	33	7	2
16	90	38	6	2
13	54	33	6	2
16	76	31	9	2
13	89	38	7	2
16	76	37	6	2
15	73	33	5	2
16	79	31	5	2
15	90	39	6	1
17	74	44	6	2
15	81	33	7	2
12	72	35	5	2
16	71	32	5	1
10	66	28	5	1
16	77	40	6	2
12	65	27	4	1
14	74	37	5	1
15	82	32	7	2
13	54	28	5	1
15	63	34	7	1
11	54	30	7	2
12	64	35	6	2
8	69	31	5	1
16	54	32	8	2
15	84	30	5	1
17	86	30	5	2
16	77	31	5	1
10	89	40	6	2
18	76	32	4	2
13	60	36	5	1
16	75	32	5	1
13	73	35	7	1
10	85	38	6	2
15	79	42	7	2
16	71	34	10	1
16	72	35	6	2
14	69	35	8	2
10	78	33	4	2
17	54	36	5	2
13	69	32	6	2
15	81	33	7	2
16	84	34	7	2
12	84	32	6	2
13	69	34	6	2

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	'Gwilym Jenkins' @ jenkins.wessa.net

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155160&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155160&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155160&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	'Gwilym Jenkins' @ jenkins.wessa.net

Correlations for all pairs of data series (method=kendall)
	Learning	Belonging	Connected	Age	Gender
Learning	1	0.147	0.159	0.007	0.095
Belonging	0.147	1	0.072	-0.019	0.141
Connected	0.159	0.072	1	0.112	0.03
Age	0.007	-0.019	0.112	1	0.115
Gender	0.095	0.141	0.03	0.115	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Learning & Belonging & Connected & Age & Gender \tabularnewline
Learning & 1 & 0.147 & 0.159 & 0.007 & 0.095 \tabularnewline
Belonging & 0.147 & 1 & 0.072 & -0.019 & 0.141 \tabularnewline
Connected & 0.159 & 0.072 & 1 & 0.112 & 0.03 \tabularnewline
Age & 0.007 & -0.019 & 0.112 & 1 & 0.115 \tabularnewline
Gender & 0.095 & 0.141 & 0.03 & 0.115 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155160&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Learning[/C][C]Belonging[/C][C]Connected[/C][C]Age[/C][C]Gender[/C][/ROW]
[ROW][C]Learning[/C][C]1[/C][C]0.147[/C][C]0.159[/C][C]0.007[/C][C]0.095[/C][/ROW]
[ROW][C]Belonging[/C][C]0.147[/C][C]1[/C][C]0.072[/C][C]-0.019[/C][C]0.141[/C][/ROW]
[ROW][C]Connected[/C][C]0.159[/C][C]0.072[/C][C]1[/C][C]0.112[/C][C]0.03[/C][/ROW]
[ROW][C]Age[/C][C]0.007[/C][C]-0.019[/C][C]0.112[/C][C]1[/C][C]0.115[/C][/ROW]
[ROW][C]Gender[/C][C]0.095[/C][C]0.141[/C][C]0.03[/C][C]0.115[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155160&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155160&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)
	Learning	Belonging	Connected	Age	Gender
Learning	1	0.147	0.159	0.007	0.095
Belonging	0.147	1	0.072	-0.019	0.141
Connected	0.159	0.072	1	0.112	0.03
Age	0.007	-0.019	0.112	1	0.115
Gender	0.095	0.141	0.03	0.115	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
Learning;Belonging	0.089	0.1872	0.1468
p-value	(0.2601)	(0.017)	(0.0113)
Learning;Connected	0.2137	0.2076	0.1586
p-value	(0.0063)	(0.008)	(0.0072)
Learning;Age	0.0506	0.0098	0.0075
p-value	(0.5228)	(0.9018)	(0.9065)
Learning;Gender	0.1189	0.1077	0.0948
p-value	(0.1319)	(0.1724)	(0.1717)
Belonging;Connected	0.0805	0.0983	0.0718
p-value	(0.3083)	(0.2131)	(0.1997)
Belonging;Age	-0.0678	-0.0234	-0.0188
p-value	(0.3913)	(0.7675)	(0.7554)
Belonging;Gender	0.1434	0.1689	0.1409
p-value	(0.0687)	(0.0317)	(0.0321)
Connected;Age	0.1478	0.1481	0.1122
p-value	(0.0606)	(0.0599)	(0.0675)
Connected;Gender	0.0645	0.0357	0.0304
p-value	(0.4149)	(0.652)	(0.6505)
Age;Gender	0.0793	0.1255	0.1149
p-value	(0.3161)	(0.1116)	(0.1113)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Learning;Belonging & 0.089 & 0.1872 & 0.1468 \tabularnewline
p-value & (0.2601) & (0.017) & (0.0113) \tabularnewline
Learning;Connected & 0.2137 & 0.2076 & 0.1586 \tabularnewline
p-value & (0.0063) & (0.008) & (0.0072) \tabularnewline
Learning;Age & 0.0506 & 0.0098 & 0.0075 \tabularnewline
p-value & (0.5228) & (0.9018) & (0.9065) \tabularnewline
Learning;Gender & 0.1189 & 0.1077 & 0.0948 \tabularnewline
p-value & (0.1319) & (0.1724) & (0.1717) \tabularnewline
Belonging;Connected & 0.0805 & 0.0983 & 0.0718 \tabularnewline
p-value & (0.3083) & (0.2131) & (0.1997) \tabularnewline
Belonging;Age & -0.0678 & -0.0234 & -0.0188 \tabularnewline
p-value & (0.3913) & (0.7675) & (0.7554) \tabularnewline
Belonging;Gender & 0.1434 & 0.1689 & 0.1409 \tabularnewline
p-value & (0.0687) & (0.0317) & (0.0321) \tabularnewline
Connected;Age & 0.1478 & 0.1481 & 0.1122 \tabularnewline
p-value & (0.0606) & (0.0599) & (0.0675) \tabularnewline
Connected;Gender & 0.0645 & 0.0357 & 0.0304 \tabularnewline
p-value & (0.4149) & (0.652) & (0.6505) \tabularnewline
Age;Gender & 0.0793 & 0.1255 & 0.1149 \tabularnewline
p-value & (0.3161) & (0.1116) & (0.1113) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155160&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]Learning;Belonging[/C][C]0.089[/C][C]0.1872[/C][C]0.1468[/C][/ROW]
[ROW][C]p-value[/C][C](0.2601)[/C][C](0.017)[/C][C](0.0113)[/C][/ROW]
[ROW][C]Learning;Connected[/C][C]0.2137[/C][C]0.2076[/C][C]0.1586[/C][/ROW]
[ROW][C]p-value[/C][C](0.0063)[/C][C](0.008)[/C][C](0.0072)[/C][/ROW]
[ROW][C]Learning;Age[/C][C]0.0506[/C][C]0.0098[/C][C]0.0075[/C][/ROW]
[ROW][C]p-value[/C][C](0.5228)[/C][C](0.9018)[/C][C](0.9065)[/C][/ROW]
[ROW][C]Learning;Gender[/C][C]0.1189[/C][C]0.1077[/C][C]0.0948[/C][/ROW]
[ROW][C]p-value[/C][C](0.1319)[/C][C](0.1724)[/C][C](0.1717)[/C][/ROW]
[ROW][C]Belonging;Connected[/C][C]0.0805[/C][C]0.0983[/C][C]0.0718[/C][/ROW]
[ROW][C]p-value[/C][C](0.3083)[/C][C](0.2131)[/C][C](0.1997)[/C][/ROW]
[ROW][C]Belonging;Age[/C][C]-0.0678[/C][C]-0.0234[/C][C]-0.0188[/C][/ROW]
[ROW][C]p-value[/C][C](0.3913)[/C][C](0.7675)[/C][C](0.7554)[/C][/ROW]
[ROW][C]Belonging;Gender[/C][C]0.1434[/C][C]0.1689[/C][C]0.1409[/C][/ROW]
[ROW][C]p-value[/C][C](0.0687)[/C][C](0.0317)[/C][C](0.0321)[/C][/ROW]
[ROW][C]Connected;Age[/C][C]0.1478[/C][C]0.1481[/C][C]0.1122[/C][/ROW]
[ROW][C]p-value[/C][C](0.0606)[/C][C](0.0599)[/C][C](0.0675)[/C][/ROW]
[ROW][C]Connected;Gender[/C][C]0.0645[/C][C]0.0357[/C][C]0.0304[/C][/ROW]
[ROW][C]p-value[/C][C](0.4149)[/C][C](0.652)[/C][C](0.6505)[/C][/ROW]
[ROW][C]Age;Gender[/C][C]0.0793[/C][C]0.1255[/C][C]0.1149[/C][/ROW]
[ROW][C]p-value[/C][C](0.3161)[/C][C](0.1116)[/C][C](0.1113)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155160&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155160&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
Learning;Belonging	0.089	0.1872	0.1468
p-value	(0.2601)	(0.017)	(0.0113)
Learning;Connected	0.2137	0.2076	0.1586
p-value	(0.0063)	(0.008)	(0.0072)
Learning;Age	0.0506	0.0098	0.0075
p-value	(0.5228)	(0.9018)	(0.9065)
Learning;Gender	0.1189	0.1077	0.0948
p-value	(0.1319)	(0.1724)	(0.1717)
Belonging;Connected	0.0805	0.0983	0.0718
p-value	(0.3083)	(0.2131)	(0.1997)
Belonging;Age	-0.0678	-0.0234	-0.0188
p-value	(0.3913)	(0.7675)	(0.7554)
Belonging;Gender	0.1434	0.1689	0.1409
p-value	(0.0687)	(0.0317)	(0.0321)
Connected;Age	0.1478	0.1481	0.1122
p-value	(0.0606)	(0.0599)	(0.0675)
Connected;Gender	0.0645	0.0357	0.0304
p-value	(0.4149)	(0.652)	(0.6505)
Age;Gender	0.0793	0.1255	0.1149
p-value	(0.3161)	(0.1116)	(0.1113)

Figure 1

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code