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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationFri, 17 Dec 2010 12:02:48 +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/17/t1292587261le9vytj5amj4994.htm/, Retrieved Mon, 06 May 2024 22:21:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=111407, Retrieved Mon, 06 May 2024 22:21:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact192
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Paired and Unpaired Two Samples Tests about the Mean] [Dagelijkse omzet ...] [2010-10-25 11:22:12] [b98453cac15ba1066b407e146608df68]
-   PD  [Paired and Unpaired Two Samples Tests about the Mean] [ws 5 - question 1] [2010-10-29 11:09:06] [ec7b4b7cc1a30b20be5ec01cdf2adbbd]
- RMPD    [Histogram] [paper - histogram] [2010-12-15 15:48:33] [ec7b4b7cc1a30b20be5ec01cdf2adbbd]
- RMPD      [Pearson Correlation] [paper - correlatie] [2010-12-17 11:31:48] [ec7b4b7cc1a30b20be5ec01cdf2adbbd]
- RMPD          [Kendall tau Correlation Matrix] [paper - spearman ...] [2010-12-17 12:02:48] [6ea41cf020a5319fc3c331a4158019e5] [Current]
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Dataseries X:
296.95	17.20
296.84	17.20
287.54	17.20
287.81	17.20
283.99	20.63
275.79	20.63
269.52	20.63
278.35	20.63
283.43	19.32
289.46	19.32
282.30	19.32
293.55	19.32
304.78	12.99
300.99	12.99
315.29	12.99
316.21	12.99
331.79	18.13
329.38	18.13
317.27	18.13
317.98	18.13
340.28	28.37
339.21	28.37
336.71	28.37
340.11	28.37
347.72	24.35
328.68	24.35
303.05	24.35
299.83	24.35
320.04	24.99
317.94	24.99
303.31	24.99
308.85	24.99
319.19	28.84
314.52	28.84
312.39	28.84
315.77	28.84
320.23	37.88
309.45	37.88
296.54	37.88
297.28	37.88
301.39	54.04
306.68	54.04
305.91	54.04
314.76	54.04
323.34	64.93
341.58	64.93
330.12	64.93
318.16	64.93
317.84	71.81
325.39	71.81
327.56	71.81
329.77	71.81
333.29	99.75
346.10	99.75
358.00	99.75
344.82	99.75
313.30	61.25
301.26	61.25
306.38	61.25
319.31	61.25




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111407&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111407&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111407&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'George Udny Yule' @ 72.249.76.132







Correlations for all pairs of data series (method=spearman)
GemPrijsTicket_$GemiddeldeOlieprijs_$
GemPrijsTicket_$10.498
GemiddeldeOlieprijs_$0.4981

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=spearman) \tabularnewline
  & GemPrijsTicket_$ & GemiddeldeOlieprijs_$ \tabularnewline
GemPrijsTicket_$ & 1 & 0.498 \tabularnewline
GemiddeldeOlieprijs_$ & 0.498 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111407&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=spearman)[/C][/ROW]
[ROW][C] [/C][C]GemPrijsTicket_$[/C][C]GemiddeldeOlieprijs_$[/C][/ROW]
[ROW][C]GemPrijsTicket_$[/C][C]1[/C][C]0.498[/C][/ROW]
[ROW][C]GemiddeldeOlieprijs_$[/C][C]0.498[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111407&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111407&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=spearman)
GemPrijsTicket_$GemiddeldeOlieprijs_$
GemPrijsTicket_$10.498
GemiddeldeOlieprijs_$0.4981







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
GemPrijsTicket_$;GemiddeldeOlieprijs_$0.51480.49810.3491
p-value(0)(1e-04)(1e-04)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
GemPrijsTicket_$;GemiddeldeOlieprijs_$ & 0.5148 & 0.4981 & 0.3491 \tabularnewline
p-value & (0) & (1e-04) & (1e-04) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111407&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]GemPrijsTicket_$;GemiddeldeOlieprijs_$[/C][C]0.5148[/C][C]0.4981[/C][C]0.3491[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111407&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111407&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
GemPrijsTicket_$;GemiddeldeOlieprijs_$0.51480.49810.3491
p-value(0)(1e-04)(1e-04)



Parameters (Session):
par1 = spearman ;
Parameters (R input):
par1 = spearman ;
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')