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Author's title

Author*The author of this computation has been verified*
R Software ModulePatrick.Wessarwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationTue, 21 Dec 2010 10:45:37 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/21/t1292928331ge6u6xxbqckwcx6.htm/, Retrieved Fri, 10 May 2024 21:41:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113250, Retrieved Fri, 10 May 2024 21:41:39 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact182
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]
- R PD  [Kendall tau Correlation Matrix] [WS10 Pearson] [2010-12-11 15:52:20] [afe9379cca749d06b3d6872e02cc47ed]
-   PD    [Kendall tau Correlation Matrix] [WS10 Pearson] [2010-12-13 13:35:44] [afe9379cca749d06b3d6872e02cc47ed]
-    D        [Kendall tau Correlation Matrix] [Paper - Pearson c...] [2010-12-21 10:45:37] [89d441ae0711e9b79b5d358f420c1317] [Current]
-   P           [Kendall tau Correlation Matrix] [Paper - Kendall's...] [2010-12-21 10:59:27] [18fa53e8b37a5effc0c5f8a5122cdd2d]
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Dataseries X:
105.31	1576.23	29.29	710.45
105.63	1546.37	28.99	720
106.02	1545.05	28.91	720
105.85	1552.34	29.29	720
106.57	1594.3	30.96	754.78
106.48	1605.78	30.57	802.73
106.60	1673.21	30.59	845.24
106.75	1612.94	31.39	893.91
106.69	1566.34	31.28	931.43
106.69	1530.17	31.1	940
106.93	1582.54	31.7	947.73
107.21	1702.16	32.57	960
107.88	1701.93	32.49	996.96
108.84	1811.15	32.46	1000
108.96	1924.2	32.3	1000
109.52	2034.25	32.97	1000
108.45	2011.13	32.9	1013.04
108.67	2013.04	32.93	1095.24
108.96	2151.67	33.72	1159.09
108.76	1902.09	33.33	1200
107.85	1944.01	33.44	1200
108.78	1916.67	33.89	1282.61
107.51	1967.31	34.34	1513.64
108.83	2119.88	33.56	1669.05
111.54	2216.38	32.67	1700
111.74	2522.83	32.57	1700
112.04	2647.64	33.23	1700
111.74	2631.23	32.85	1665.91
111.81	2693.41	32.61	1650
111.86	3021.76	32.57	1650
114.23	2953.67	32.98	1619.57
114.80	2796.8	31.33	1599.05
115.17	2672.05	29.8	1572.73
115.11	2251.23	28.06	1470
114.43	2046.08	25.47	1268
114.66	2420.04	24.65	1217.39
115.11	2608.89	23.94	1154.09
117.74	2660.47	23.89	984
118.18	2493.98	23.54	900
118.56	2541.7	24.28	900
117.63	2554.6	25.51	916.67
117.71	2699.61	27.03	957.73
117.46	2805.48	27.09	966.09
117.37	2956.66	27.3	980
117.34	3149.51	27.11	990.91
117.09	3372.5	26.39	1000.91
116.65	3379.33	27.54	1042.38
116.71	3517.54	26.85	1142.61
116.82	3527.34	26.82	1214.29
117.33	3281.06	25.9	1218
117.95	3089.65	24.96	1202.61
123.53	3222.76	25.4	1200
124.91	3165.76	24.38	1228.57
125.99	3232.43	24.73	1195.91
126.29	3229.54	25.43	1180
125.68	3071.74	26.04	1210.91
125.52	2850.17	25.59	1272.27




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113250&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113250&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113250&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'Gwilym Jenkins' @ 72.249.127.135







Correlations for all pairs of data series (method=pearson)
PC&SPCacaoPSuikerPNoten
PC&S10.847-0.750.211
PCacao0.8471-0.5490.389
PSuiker-0.75-0.54910.287
PNoten0.2110.3890.2871

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & PC&S & PCacao & PSuiker & PNoten \tabularnewline
PC&S & 1 & 0.847 & -0.75 & 0.211 \tabularnewline
PCacao & 0.847 & 1 & -0.549 & 0.389 \tabularnewline
PSuiker & -0.75 & -0.549 & 1 & 0.287 \tabularnewline
PNoten & 0.211 & 0.389 & 0.287 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113250&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]PC&S[/C][C]PCacao[/C][C]PSuiker[/C][C]PNoten[/C][/ROW]
[ROW][C]PC&S[/C][C]1[/C][C]0.847[/C][C]-0.75[/C][C]0.211[/C][/ROW]
[ROW][C]PCacao[/C][C]0.847[/C][C]1[/C][C]-0.549[/C][C]0.389[/C][/ROW]
[ROW][C]PSuiker[/C][C]-0.75[/C][C]-0.549[/C][C]1[/C][C]0.287[/C][/ROW]
[ROW][C]PNoten[/C][C]0.211[/C][C]0.389[/C][C]0.287[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113250&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113250&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)
PC&SPCacaoPSuikerPNoten
PC&S10.847-0.750.211
PCacao0.8471-0.5490.389
PSuiker-0.75-0.54910.287
PNoten0.2110.3890.2871







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
PC&S;PCacao0.84680.87270.6913
p-value(0)(0)(0)
PC&S;PSuiker-0.7498-0.6495-0.4058
p-value(0)(0)(0)
PC&S;PNoten0.21090.33790.2142
p-value(0.1153)(0.0101)(0.0192)
PCacao;PSuiker-0.5485-0.4479-0.2334
p-value(0)(5e-04)(0.0104)
PCacao;PNoten0.38910.48820.3386
p-value(0.0028)(1e-04)(2e-04)
PSuiker;PNoten0.28720.26320.1815
p-value(0.0303)(0.048)(0.0473)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
PC&S;PCacao & 0.8468 & 0.8727 & 0.6913 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PC&S;PSuiker & -0.7498 & -0.6495 & -0.4058 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PC&S;PNoten & 0.2109 & 0.3379 & 0.2142 \tabularnewline
p-value & (0.1153) & (0.0101) & (0.0192) \tabularnewline
PCacao;PSuiker & -0.5485 & -0.4479 & -0.2334 \tabularnewline
p-value & (0) & (5e-04) & (0.0104) \tabularnewline
PCacao;PNoten & 0.3891 & 0.4882 & 0.3386 \tabularnewline
p-value & (0.0028) & (1e-04) & (2e-04) \tabularnewline
PSuiker;PNoten & 0.2872 & 0.2632 & 0.1815 \tabularnewline
p-value & (0.0303) & (0.048) & (0.0473) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113250&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]PC&S;PCacao[/C][C]0.8468[/C][C]0.8727[/C][C]0.6913[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PC&S;PSuiker[/C][C]-0.7498[/C][C]-0.6495[/C][C]-0.4058[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PC&S;PNoten[/C][C]0.2109[/C][C]0.3379[/C][C]0.2142[/C][/ROW]
[ROW][C]p-value[/C][C](0.1153)[/C][C](0.0101)[/C][C](0.0192)[/C][/ROW]
[ROW][C]PCacao;PSuiker[/C][C]-0.5485[/C][C]-0.4479[/C][C]-0.2334[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](5e-04)[/C][C](0.0104)[/C][/ROW]
[ROW][C]PCacao;PNoten[/C][C]0.3891[/C][C]0.4882[/C][C]0.3386[/C][/ROW]
[ROW][C]p-value[/C][C](0.0028)[/C][C](1e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]PSuiker;PNoten[/C][C]0.2872[/C][C]0.2632[/C][C]0.1815[/C][/ROW]
[ROW][C]p-value[/C][C](0.0303)[/C][C](0.048)[/C][C](0.0473)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113250&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113250&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
PC&S;PCacao0.84680.87270.6913
p-value(0)(0)(0)
PC&S;PSuiker-0.7498-0.6495-0.4058
p-value(0)(0)(0)
PC&S;PNoten0.21090.33790.2142
p-value(0.1153)(0.0101)(0.0192)
PCacao;PSuiker-0.5485-0.4479-0.2334
p-value(0)(5e-04)(0.0104)
PCacao;PNoten0.38910.48820.3386
p-value(0.0028)(1e-04)(2e-04)
PSuiker;PNoten0.28720.26320.1815
p-value(0.0303)(0.048)(0.0473)



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')