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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 computationThu, 22 Dec 2011 11:54:08 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/22/t1324572866i2xum996sn3v80z.htm/, Retrieved Fri, 03 May 2024 03:59:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=159719, Retrieved Fri, 03 May 2024 03:59:35 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90
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]
- RMPD  [Kendall tau Correlation Matrix] [Workshop 10_Pearson ] [2011-12-12 21:39:29] [f722e8e78b9e5c5ebaa2263f273aa636]
-    D      [Kendall tau Correlation Matrix] [Paper: Pearson Co...] [2011-12-22 16:54:08] [3e64eea457df40fcb7af8f28e1ee6256] [Current]
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Dataseries X:
2	210907	79	94
4	179321	108	103
-4	173326	86	148
4	133131	44	90
4	258873	104	124
-1	230964	102	115
1	344297	80	108
3	174415	73	114
-1	223632	105	120
4	294424	107	124
3	325107	84	126
1	106408	33	37
-2	265769	96	120
-3	269651	106	93
-4	149112	56	95
2	152871	59	90
2	362301	76	110
-4	183167	91	138
3	277965	115	133
2	218946	76	96
2	244052	101	164
5	233328	92	102
-2	206161	75	99
-2	207176	56	114
-3	196553	41	99
2	143246	67	104
2	182192	77	138
2	194979	66	151
4	143756	105	120
4	275541	116	115
2	152299	62	98
2	193339	100	71
-4	130585	67	107
3	112611	46	73
3	148446	135	129
2	182079	124	118
-1	243060	58	104
-3	162765	68	107
1	225060	93	139
-3	133328	56	56
3	100750	83	93
3	132487	71	98
-3	317394	116	82
-4	184510	64	140
2	128423	32	120
-1	97839	25	66
3	172494	46	139
2	229242	63	119
5	351619	95	141
2	324598	113	133
-2	195838	111	98
3	199476	87	105
-2	92499	25	55
6	181633	47	73
-3	271856	109	86
3	95227	37	48
-2	118612	54	43
1	65475	16	46
2	121848	37	52
2	76302	29	68
-3	98104	55	47
-2	30989	5	41
1	31774	0	47
-4	150580	27	71
1	59382	29	24




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159719&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159719&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159719&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 time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Correlations for all pairs of data series (method=pearson)
TotTimeCompLFB
Tot10.130.1550.154
Time0.1310.6950.618
Comp0.1550.69510.633
LFB0.1540.6180.6331

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Tot & Time & Comp & LFB \tabularnewline
Tot & 1 & 0.13 & 0.155 & 0.154 \tabularnewline
Time & 0.13 & 1 & 0.695 & 0.618 \tabularnewline
Comp & 0.155 & 0.695 & 1 & 0.633 \tabularnewline
LFB & 0.154 & 0.618 & 0.633 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159719&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Tot[/C][C]Time[/C][C]Comp[/C][C]LFB[/C][/ROW]
[ROW][C]Tot[/C][C]1[/C][C]0.13[/C][C]0.155[/C][C]0.154[/C][/ROW]
[ROW][C]Time[/C][C]0.13[/C][C]1[/C][C]0.695[/C][C]0.618[/C][/ROW]
[ROW][C]Comp[/C][C]0.155[/C][C]0.695[/C][C]1[/C][C]0.633[/C][/ROW]
[ROW][C]LFB[/C][C]0.154[/C][C]0.618[/C][C]0.633[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159719&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159719&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)
TotTimeCompLFB
Tot10.130.1550.154
Time0.1310.6950.618
Comp0.1550.69510.633
LFB0.1540.6180.6331







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Tot;Time0.13010.12420.0899
p-value(0.3018)(0.3242)(0.3155)
Tot;Comp0.15530.2110.1566
p-value(0.2168)(0.0916)(0.0812)
Tot;LFB0.15350.1980.138
p-value(0.2221)(0.1139)(0.1255)
Time;Comp0.6950.71660.5462
p-value(0)(0)(0)
Time;LFB0.61810.60830.4404
p-value(0)(0)(0)
Comp;LFB0.6330.57860.4115
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
Tot;Time & 0.1301 & 0.1242 & 0.0899 \tabularnewline
p-value & (0.3018) & (0.3242) & (0.3155) \tabularnewline
Tot;Comp & 0.1553 & 0.211 & 0.1566 \tabularnewline
p-value & (0.2168) & (0.0916) & (0.0812) \tabularnewline
Tot;LFB & 0.1535 & 0.198 & 0.138 \tabularnewline
p-value & (0.2221) & (0.1139) & (0.1255) \tabularnewline
Time;Comp & 0.695 & 0.7166 & 0.5462 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time;LFB & 0.6181 & 0.6083 & 0.4404 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Comp;LFB & 0.633 & 0.5786 & 0.4115 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159719&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]Tot;Time[/C][C]0.1301[/C][C]0.1242[/C][C]0.0899[/C][/ROW]
[ROW][C]p-value[/C][C](0.3018)[/C][C](0.3242)[/C][C](0.3155)[/C][/ROW]
[ROW][C]Tot;Comp[/C][C]0.1553[/C][C]0.211[/C][C]0.1566[/C][/ROW]
[ROW][C]p-value[/C][C](0.2168)[/C][C](0.0916)[/C][C](0.0812)[/C][/ROW]
[ROW][C]Tot;LFB[/C][C]0.1535[/C][C]0.198[/C][C]0.138[/C][/ROW]
[ROW][C]p-value[/C][C](0.2221)[/C][C](0.1139)[/C][C](0.1255)[/C][/ROW]
[ROW][C]Time;Comp[/C][C]0.695[/C][C]0.7166[/C][C]0.5462[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time;LFB[/C][C]0.6181[/C][C]0.6083[/C][C]0.4404[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Comp;LFB[/C][C]0.633[/C][C]0.5786[/C][C]0.4115[/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=159719&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159719&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
Tot;Time0.13010.12420.0899
p-value(0.3018)(0.3242)(0.3155)
Tot;Comp0.15530.2110.1566
p-value(0.2168)(0.0916)(0.0812)
Tot;LFB0.15350.1980.138
p-value(0.2221)(0.1139)(0.1255)
Time;Comp0.6950.71660.5462
p-value(0)(0)(0)
Time;LFB0.61810.60830.4404
p-value(0)(0)(0)
Comp;LFB0.6330.57860.4115
p-value(0)(0)(0)



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')