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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 12:19:54 -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/t13245746818ehg6fcq1slskw1.htm/, Retrieved Fri, 03 May 2024 06:43:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=159757, Retrieved Fri, 03 May 2024 06:43:04 +0000
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-       [Kendall tau Correlation Matrix] [pearson correlati...] [2011-12-22 17:19:54] [9aaeed430538c8fa0389aee05c40e1f1] [Current]
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Dataseries X:
210907	56	396	0
120982	56	297	0
176508	54	559	0
179321	89	967	NA
123185	40	270	NA
52746	25	143	NA
385534	92	1562	NA
33170	18	109	NA
101645	63	371	NA
149061	44	656	0
165446	33	511	NA
237213	84	655	0
173326	88	465	NA
133131	55	525	1
258873	60	885	NA
180083	66	497	NA
324799	154	1436	0
230964	53	612	0
236785	119	865	1
135473	41	385	NA
202925	61	567	NA
215147	58	639	NA
344297	75	963	0
153935	33	398	NA
132943	40	410	NA
174724	92	966	0
174415	100	801	0
225548	112	892	NA
223632	73	513	0
124817	40	469	0
221698	45	683	NA
210767	60	643	NA
170266	62	535	NA
260561	75	625	NA
84853	31	264	NA
294424	77	992	0
101011	34	238	NA
215641	46	818	NA
325107	99	937	NA
7176	17	70	NA
167542	66	507	NA
106408	30	260	0
96560	76	503	0
265769	146	927	0
269651	67	1269	NA
149112	56	537	1
175824	107	910	0
152871	58	532	0
111665	34	345	0
116408	61	918	NA
362301	119	1635	0
78800	42	330	NA
183167	66	557	0
277965	89	1178	NA
150629	44	740	NA
168809	66	452	NA
24188	24	218	NA
329267	259	764	0
65029	17	255	NA
101097	64	454	NA
218946	41	866	1
244052	68	574	0
341570	168	1276	1
103597	43	379	0
233328	132	825	NA
256462	105	798	NA
206161	71	663	NA
311473	112	1069	NA
235800	94	921	NA
177939	82	858	NA
207176	70	711	NA
196553	57	503	0
174184	53	382	NA
143246	103	464	0
187559	121	717	NA
187681	62	690	NA
119016	52	462	NA
182192	52	657	NA
73566	32	385	NA
194979	62	577	NA
167488	45	619	0
143756	46	479	0
			NA
			NA
			0
			NA
			0
			NA
			0
			NA
			0
			NA
			0
			0
			1
			0
			NA
			NA
			NA
			1
			1
			0
			1
			0
			NA
			NA
			NA
			0
			NA
			1
			NA
			NA
			NA
			NA
			0
			NA
			NA
			0
			0
			0
			1
			0
			NA
			1
			NA
			NA
			NA
			0
			0
			NA
			NA
			1
			NA
			0
			0
			NA
			NA
			NA
			0
			NA
			NA
			1
			NA
			1
			NA
			NA
			1
			1
			NA
			NA
			0
			0
			0
			0
			NA
			0
			NA
			NA
			NA
			0
			NA
			NA
			0
			0
			0
			NA
			NA
			NA
			1
			1
			0
			0
			0
			0
			NA
			NA
			NA
			0
			0
			0
			NA
			NA
			NA
			1
			NA
			NA
			NA
			NA
			NA
			NA
			NA
			1
			NA
			0
			NA
			1
			NA
			0
			NA
			NA
			NA
			NA
			NA
			0
			NA
			NA
			NA
			0
			0
			NA
			NA
			0
			NA
			NA
			0
			0
			NA
			0
			NA
			NA
			0
			0
			0
			NA
			NA
			NA
			NA
			0
			NA
			NA
			0
			0
			NA
			NA
			1
			0
			1
			NA
			0
			NA
			NA
			NA
			NA
			NA
			NA
			NA
			0
			0
			NA
			NA
			0
			0
			NA
			0
			0
			NA
			NA
			NA
			NA
			NA
			NA
			NA
			NA
			0
			NA
			NA
			0
			0
			0
			NA
			NA
			NA
			NA
			NA
			NA
			NA
			NA
			NA
			NA
			0
			NA
			NA
			NA
			NA
			0
			NA
			NA
			NA
			NA




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'AstonUniversity' @ aston.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=159757&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=159757&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159757&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'AstonUniversity' @ aston.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Correlations for all pairs of data series (method=pearson)
timeinrfcloginscompendiumviewsgender
timeinrfc1-0.452-0.319-0.426
logins-0.4521-0.1690.597
compendiumviews-0.319-0.1691-0.293
gender-0.4260.597-0.2931

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & timeinrfc & logins & compendiumviews & gender \tabularnewline
timeinrfc & 1 & -0.452 & -0.319 & -0.426 \tabularnewline
logins & -0.452 & 1 & -0.169 & 0.597 \tabularnewline
compendiumviews & -0.319 & -0.169 & 1 & -0.293 \tabularnewline
gender & -0.426 & 0.597 & -0.293 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159757&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]timeinrfc[/C][C]logins[/C][C]compendiumviews[/C][C]gender[/C][/ROW]
[ROW][C]timeinrfc[/C][C]1[/C][C]-0.452[/C][C]-0.319[/C][C]-0.426[/C][/ROW]
[ROW][C]logins[/C][C]-0.452[/C][C]1[/C][C]-0.169[/C][C]0.597[/C][/ROW]
[ROW][C]compendiumviews[/C][C]-0.319[/C][C]-0.169[/C][C]1[/C][C]-0.293[/C][/ROW]
[ROW][C]gender[/C][C]-0.426[/C][C]0.597[/C][C]-0.293[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159757&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159757&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)
timeinrfcloginscompendiumviewsgender
timeinrfc1-0.452-0.319-0.426
logins-0.4521-0.1690.597
compendiumviews-0.319-0.1691-0.293
gender-0.4260.597-0.2931







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
timeinrfc;logins-0.4516-0.07390.0395
p-value(0)(0.3033)(0.4176)
timeinrfc;compendiumviews-0.31870.64670.5033
p-value(1e-04)(0)(0)
timeinrfc;gender-0.4263-0.3243-0.2823
p-value(0)(0)(0)
logins;compendiumviews-0.1689-0.2091-0.0682
p-value(0.0461)(0.0131)(0.2514)
logins;gender0.59680.70260.4655
p-value(0)(0)(0)
compendiumviews;gender-0.2934-0.2939-0.1401
p-value(0.0028)(0.0027)(0.06)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
timeinrfc;logins & -0.4516 & -0.0739 & 0.0395 \tabularnewline
p-value & (0) & (0.3033) & (0.4176) \tabularnewline
timeinrfc;compendiumviews & -0.3187 & 0.6467 & 0.5033 \tabularnewline
p-value & (1e-04) & (0) & (0) \tabularnewline
timeinrfc;gender & -0.4263 & -0.3243 & -0.2823 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
logins;compendiumviews & -0.1689 & -0.2091 & -0.0682 \tabularnewline
p-value & (0.0461) & (0.0131) & (0.2514) \tabularnewline
logins;gender & 0.5968 & 0.7026 & 0.4655 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
compendiumviews;gender & -0.2934 & -0.2939 & -0.1401 \tabularnewline
p-value & (0.0028) & (0.0027) & (0.06) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159757&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]timeinrfc;logins[/C][C]-0.4516[/C][C]-0.0739[/C][C]0.0395[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.3033)[/C][C](0.4176)[/C][/ROW]
[ROW][C]timeinrfc;compendiumviews[/C][C]-0.3187[/C][C]0.6467[/C][C]0.5033[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]timeinrfc;gender[/C][C]-0.4263[/C][C]-0.3243[/C][C]-0.2823[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]logins;compendiumviews[/C][C]-0.1689[/C][C]-0.2091[/C][C]-0.0682[/C][/ROW]
[ROW][C]p-value[/C][C](0.0461)[/C][C](0.0131)[/C][C](0.2514)[/C][/ROW]
[ROW][C]logins;gender[/C][C]0.5968[/C][C]0.7026[/C][C]0.4655[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]compendiumviews;gender[/C][C]-0.2934[/C][C]-0.2939[/C][C]-0.1401[/C][/ROW]
[ROW][C]p-value[/C][C](0.0028)[/C][C](0.0027)[/C][C](0.06)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159757&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159757&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
timeinrfc;logins-0.4516-0.07390.0395
p-value(0)(0.3033)(0.4176)
timeinrfc;compendiumviews-0.31870.64670.5033
p-value(1e-04)(0)(0)
timeinrfc;gender-0.4263-0.3243-0.2823
p-value(0)(0)(0)
logins;compendiumviews-0.1689-0.2091-0.0682
p-value(0.0461)(0.0131)(0.2514)
logins;gender0.59680.70260.4655
p-value(0)(0)(0)
compendiumviews;gender-0.2934-0.2939-0.1401
p-value(0.0028)(0.0027)(0.06)



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')