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Description of Statistical Computation

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 computationTue, 21 Dec 2010 12:40:41 +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/t129293512796lem463qm5e19y.htm/, Retrieved Sun, 19 May 2024 18:19:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113416, Retrieved Sun, 19 May 2024 18:19:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsPaper DMA
Estimated Impact108

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [Paper DMA Pearson...] [2010-12-21 12:40:41] [f92ba2b01007f169e2985fcc57236bd0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3030,29	25,64
2803,47	27,97
2767,63	27,62
2882,6	23,31
2863,36	29,07
2897,06	29,58
3012,61	28,63
3142,95	29,92
3032,93	32,68
3045,78	31,54
3110,52	32,43
3013,24	26,54
2987,1	25,85
2995,55	27,6
2833,18	25,71
2848,96	25,38
2794,83	28,57
2845,26	27,64
2915,03	25,36
2892,63	25,9
2604,42	26,29
2641,65	21,74
2659,81	19,2
2638,53	19,32
2720,25	19,82
2745,88	20,36
2735,7	24,31
2811,7	25,97
2799,43	25,61
2555,28	24,67
2304,98	25,59
2214,95	26,09
2065,81	28,37
1940,49	27,34
2042	24,46
1995,37	27,46
1946,81	30,23
1765,9	32,33
1635,25	29,87
1833,42	24,87
1910,43	25,48
1959,67	27,28
1969,6	28,24
2061,41	29,58
2093,48	26,95
2120,88	29,08
2174,56	28,76
2196,72	29,59
2350,44	30,7
2440,25	30,52
2408,64	32,67
2472,81	33,19
2407,6	37,13
2454,62	35,54
2448,05	37,75
2497,84	41,84
2645,64	42,94
2756,76	49,14
2849,27	44,61
2921,44	40,22
2981,85	44,23
3080,58	45,85
3106,22	53,38
3119,31	53,26
3061,26	51,8
3097,31	55,3
3161,69	57,81
3257,16	63,96
3277,01	63,77
3295,32	59,15
3363,99	56,12
3494,17	57,42
3667,03	63,52
3813,06	61,71
3917,96	63,01
3895,51	68,18
3801,06	72,03
3570,12	69,75
3701,61	74,41
3862,27	74,33
3970,1	64,24
4138,52	60,03
4199,75	59,44
4290,89	62,5
4443,91	55,04
4502,64	58,34
4356,98	61,92
4591,27	67,65
4696,96	67,68
4621,4	70,3
4562,84	75,26
4202,52	71,44
4296,49	76,36
4435,23	81,71
4105,18	92,6
4116,68	90,6
3844,49	92,23
3720,98	94,09
3674,4	102,79
3857,62	109,65
3801,06	124,05
3504,37	132,69
3032,6	135,81
3047,03	116,07
2962,34	101,42
2197,82	75,73
2014,45	55,48
1862,83	43,8
1905,41	45,29

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113416&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113416&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113416&T=0

As an alternative you can also use a QR Code:  
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'RServer@AstonUniversity' @ vre.aston.ac.uk






Correlations for all pairs of data series (method=pearson)
Bel20Olie
Bel2010.616
Olie0.6161

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Bel20 & Olie \tabularnewline
Bel20 & 1 & 0.616 \tabularnewline
Olie & 0.616 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113416&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Bel20[/C][C]Olie[/C][/ROW]
[ROW][C]Bel20[/C][C]1[/C][C]0.616[/C][/ROW]
[ROW][C]Olie[/C][C]0.616[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113416&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113416&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series (method=pearson)
Bel20Olie
Bel2010.616
Olie0.6161






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Bel20;Olie0.61580.67370.4595
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
Bel20;Olie & 0.6158 & 0.6737 & 0.4595 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113416&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]Bel20;Olie[/C][C]0.6158[/C][C]0.6737[/C][C]0.4595[/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=113416&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113416&T=2

As an alternative you can also use a QR Code:  
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
Bel20;Olie0.61580.67370.4595
p-value(0)(0)(0)


Figures (Output of Computation)

Input Parameters & R Code

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')