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Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationFri, 05 Oct 2012 11:34:55 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Oct/05/t1349451320bg8k3uik05etlh4.htm/, Retrieved Thu, 02 May 2024 17:46:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=172358, Retrieved Thu, 02 May 2024 17:46:31 +0000
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Original text written by user:
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User-defined keywords
Estimated Impact123
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Survey Scores] [E-Learn 2008 table 1] [2008-09-07 11:33:54] [b98453cac15ba1066b407e146608df68]
F RM D  [Survey Scores] [ATTLES] [2010-04-05 12:47:13] [b98453cac15ba1066b407e146608df68]
F RMPD    [Notched Boxplots] [Compare ATTLES Sc...] [2010-10-03 17:09:07] [b98453cac15ba1066b407e146608df68]
- RMP         [Kendall tau Correlation Matrix] [WS 2 Task 6] [2012-10-05 15:34:55] [4c93b3a0c48c946a3a36627369b78a37] [Current]
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Dataseries X:
41	34	38	30
39	33	32	28
30	29	35	31
31	34	33	35
34	32	37	35
35	35	29	37
39	41	31	39
34	27	36	31
36	40	35	38
37	40	38	37
38	36	31	37
36	40	34	35
38	43	35	37
39	40	38	42
33	33	37	28
32	37	33	37
36	32	32	36
38	26	38	37
39	36	38	33
32	39	32	40
32	38	33	30
31	34	31	36
39	35	38	33
37	41	39	40
39	42	32	37
41	36	32	37
36	39	35	39
33	33	37	35
33	33	33	36
34	36	33	34
31	37	28	36
27	36	32	32
37	34	31	33
34	32	37	27
34	35	30	37
32	39	33	32
29	30	31	31
36	25	33	31
29	29	31	32
35	39	33	37
37	31	32	25
34	26	33	30
38	28	32	37
35	40	33	37
38	32	28	40
37	35	35	35
38	32	39	35
33	41	34	43
36	34	38	32
38	36	32	42
32	38	38	35
32	34	30	27
32	32	33	30
34	34	38	31
32	32	32	36
37	40	32	36
39	43	34	41
29	35	34	34
37	45	36	36
35	36	34	33
30	39	28	35
38	31	34	28
34	36	35	33
31	36	35	38
34	37	31	37
35	40	37	39
36	35	35	34
30	36	27	32
39	32	40	36
35	36	37	36
38	37	36	35
31	42	38	33
34	37	39	42
38	36	41	36
34	36	27	33
39	33	30	36
37	37	37	32
34	35	31	35
28	37	31	38
37	28	27	33
33	33	36	32
37	45	38	38
35	38	37	39
37	43	33	39
32	37	34	39
33	36	31	30
38	40	39	38
33	39	34	38
29	43	32	42
33	32	33	41
31	37	36	31
36	34	32	39
35	44	41	40
32	35	28	31
29	34	30	34
39	37	36	23
37	40	35	28
35	36	31	36
37	44	34	41
32	35	36	29
38	34	36	31
37	40	35	33
36	34	37	35
32	39	28	35
33	36	39	34
40	40	32	40
38	37	35	34
41	35	39	36
36	45	35	35
43	39	42	39




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=172358&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 Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=172358&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=172358&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 Maurice George Kendall' @ kendall.wessa.net







Correlations for all pairs of data series (method=pearson)
Y2010CUCY2010SUS
Y2010C10.1180.3450.136
UC0.11810.1510.449
Y2010S0.3450.15110.048
US0.1360.4490.0481

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Y2010C & UC & Y2010S & US \tabularnewline
Y2010C & 1 & 0.118 & 0.345 & 0.136 \tabularnewline
UC & 0.118 & 1 & 0.151 & 0.449 \tabularnewline
Y2010S & 0.345 & 0.151 & 1 & 0.048 \tabularnewline
US & 0.136 & 0.449 & 0.048 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=172358&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Y2010C[/C][C]UC[/C][C]Y2010S[/C][C]US[/C][/ROW]
[ROW][C]Y2010C[/C][C]1[/C][C]0.118[/C][C]0.345[/C][C]0.136[/C][/ROW]
[ROW][C]UC[/C][C]0.118[/C][C]1[/C][C]0.151[/C][C]0.449[/C][/ROW]
[ROW][C]Y2010S[/C][C]0.345[/C][C]0.151[/C][C]1[/C][C]0.048[/C][/ROW]
[ROW][C]US[/C][C]0.136[/C][C]0.449[/C][C]0.048[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=172358&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=172358&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)
Y2010CUCY2010SUS
Y2010C10.1180.3450.136
UC0.11810.1510.449
Y2010S0.3450.15110.048
US0.1360.4490.0481







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Y2010C;UC0.11780.11120.0821
p-value(0.2202)(0.2474)(0.2365)
Y2010C;Y2010S0.34480.30440.228
p-value(2e-04)(0.0012)(0.0011)
Y2010C;US0.13590.1930.1408
p-value(0.157)(0.0434)(0.0421)
UC;Y2010S0.15090.14680.1029
p-value(0.1155)(0.1259)(0.1373)
UC;US0.44940.48640.3603
p-value(0)(0)(0)
Y2010S;US0.04810.01930.0205
p-value(0.618)(0.8415)(0.7664)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Y2010C;UC & 0.1178 & 0.1112 & 0.0821 \tabularnewline
p-value & (0.2202) & (0.2474) & (0.2365) \tabularnewline
Y2010C;Y2010S & 0.3448 & 0.3044 & 0.228 \tabularnewline
p-value & (2e-04) & (0.0012) & (0.0011) \tabularnewline
Y2010C;US & 0.1359 & 0.193 & 0.1408 \tabularnewline
p-value & (0.157) & (0.0434) & (0.0421) \tabularnewline
UC;Y2010S & 0.1509 & 0.1468 & 0.1029 \tabularnewline
p-value & (0.1155) & (0.1259) & (0.1373) \tabularnewline
UC;US & 0.4494 & 0.4864 & 0.3603 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Y2010S;US & 0.0481 & 0.0193 & 0.0205 \tabularnewline
p-value & (0.618) & (0.8415) & (0.7664) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=172358&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]Y2010C;UC[/C][C]0.1178[/C][C]0.1112[/C][C]0.0821[/C][/ROW]
[ROW][C]p-value[/C][C](0.2202)[/C][C](0.2474)[/C][C](0.2365)[/C][/ROW]
[ROW][C]Y2010C;Y2010S[/C][C]0.3448[/C][C]0.3044[/C][C]0.228[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](0.0012)[/C][C](0.0011)[/C][/ROW]
[ROW][C]Y2010C;US[/C][C]0.1359[/C][C]0.193[/C][C]0.1408[/C][/ROW]
[ROW][C]p-value[/C][C](0.157)[/C][C](0.0434)[/C][C](0.0421)[/C][/ROW]
[ROW][C]UC;Y2010S[/C][C]0.1509[/C][C]0.1468[/C][C]0.1029[/C][/ROW]
[ROW][C]p-value[/C][C](0.1155)[/C][C](0.1259)[/C][C](0.1373)[/C][/ROW]
[ROW][C]UC;US[/C][C]0.4494[/C][C]0.4864[/C][C]0.3603[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Y2010S;US[/C][C]0.0481[/C][C]0.0193[/C][C]0.0205[/C][/ROW]
[ROW][C]p-value[/C][C](0.618)[/C][C](0.8415)[/C][C](0.7664)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=172358&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=172358&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
Y2010C;UC0.11780.11120.0821
p-value(0.2202)(0.2474)(0.2365)
Y2010C;Y2010S0.34480.30440.228
p-value(2e-04)(0.0012)(0.0011)
Y2010C;US0.13590.1930.1408
p-value(0.157)(0.0434)(0.0421)
UC;Y2010S0.15090.14680.1029
p-value(0.1155)(0.1259)(0.1373)
UC;US0.44940.48640.3603
p-value(0)(0)(0)
Y2010S;US0.04810.01930.0205
p-value(0.618)(0.8415)(0.7664)



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')