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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 computationThu, 12 Nov 2009 01:45:49 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/12/t1258015665rz4537xho5z4g8h.htm/, Retrieved Fri, 03 May 2024 18:44:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=55887, Retrieved Fri, 03 May 2024 18:44:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact192

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] [3/11/2009] [2009-11-02 21:25:00] [b98453cac15ba1066b407e146608df68]
- R  D    [Kendall tau Correlation Matrix] [Kendall tau Corre...] [2009-11-12 08:45:49] [d5837f25ec8937f9733a894c487f865c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3	104.29	101.2	   521
3.21	104.56	101.1	   501
3.37	104.79	100.7	   518
3.51	105.08	100.1	   547
3.75	105.21	99.9	   629
4.11	105.43	99.7	   572
4.25	105.69	99.5	   582
4.25	105.74	99.2	   574
4.5	106.2	        99	   461
4.7	106.04	99	   576
4.75	106.45	99.3	   460
4.75	106.4	        99.5	   455 
4.75	106.48	99.7	   444
4.75	106.83	100	   488
4.75	107.14	100.4	   513
4.75	107.94	100.6	   468
4.58	108.46	100.7	   488
4.5	108.81	100.7	   536
4.5	108.92	100.6	   486
4.49	108.99	100.5	   460
4.03	109.16	100.6	   376
3.75	109.22	100.5	   503
3.39	109.43	100.4	   369
3.25	109.23	100.3	   353
3.25	109.93	100.4	   359
3.25	110.09	100.4	   400
3.25	110.33	100.4	   374
3.25	110.11	100.4	   430
3.25	110.35	100.4	   433
3.25	110.09	100.5	   418
3.25	110.44	100.6	   438
3.25	110.39	100.6	   389
3.25	110.62	100.5	   368
3.25	110.43	100.5	   386
3.25	110.46	100.7	   261
2.85	110.55	101.1	   294
2.75	110.94	101.5	   263
2.75	111.56	101.9	   293
2.55	111.82	102.1	   303
2.5	111.73	102.1	   326
2.5	111.57	102.1	   314
2.1	111.85	102.4	   332
2	112.06	102.8	   347
2	112.2	        103.1	   290
2	112.47	103.1	   340
2	112.15	102.9	   371
2	112.36	102.4	   340
2	112.32	101.9	   376
2	112.67	101.3	   322
2	113.02	100.7	   364
2	113.05	100.6	   379
2	113.5	        101	   343
2	113.67	101.5	   358
2	113.65	101.9	   433
2	114	        102.1    344
2	114.03	102.3	   357
2	114.08	102.5	   385
2	114.49	102.9	   392
2	114.48	103.6	   308
2	114.25	104.3	   294

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55887&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55887&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55887&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( Rentevoet , Gezondheidsindex )-0.7156633939214081.92336203198913e-14
tau( Rentevoet , totaleproductie )-0.6667447696382522.51274408250596e-12
tau( Rentevoet , bouwaanvragen )0.4737252829830064.17354532933345e-07
tau( Gezondheidsindex , totaleproductie )0.592164711467545.35336219797955e-11
tau( Gezondheidsindex , bouwaanvragen )-0.5349566636611581.66001186020675e-09
tau( totaleproductie , bouwaanvragen )-0.4629587582894423.01510368803882e-07

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( Rentevoet , Gezondheidsindex ) & -0.715663393921408 & 1.92336203198913e-14 \tabularnewline
tau( Rentevoet , totaleproductie ) & -0.666744769638252 & 2.51274408250596e-12 \tabularnewline
tau( Rentevoet , bouwaanvragen ) & 0.473725282983006 & 4.17354532933345e-07 \tabularnewline
tau( Gezondheidsindex , totaleproductie ) & 0.59216471146754 & 5.35336219797955e-11 \tabularnewline
tau( Gezondheidsindex , bouwaanvragen ) & -0.534956663661158 & 1.66001186020675e-09 \tabularnewline
tau( totaleproductie , bouwaanvragen ) & -0.462958758289442 & 3.01510368803882e-07 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55887&T=1

[TABLE]
[ROW][C]Kendall tau rank correlations for all pairs of data series[/C][/ROW]
[ROW][C]pair[/C][C]tau[/C][C]p-value[/C][/ROW]
[ROW][C]tau( Rentevoet , Gezondheidsindex )[/C][C]-0.715663393921408[/C][C]1.92336203198913e-14[/C][/ROW]
[ROW][C]tau( Rentevoet , totaleproductie )[/C][C]-0.666744769638252[/C][C]2.51274408250596e-12[/C][/ROW]
[ROW][C]tau( Rentevoet , bouwaanvragen )[/C][C]0.473725282983006[/C][C]4.17354532933345e-07[/C][/ROW]
[ROW][C]tau( Gezondheidsindex , totaleproductie )[/C][C]0.59216471146754[/C][C]5.35336219797955e-11[/C][/ROW]
[ROW][C]tau( Gezondheidsindex , bouwaanvragen )[/C][C]-0.534956663661158[/C][C]1.66001186020675e-09[/C][/ROW]
[ROW][C]tau( totaleproductie , bouwaanvragen )[/C][C]-0.462958758289442[/C][C]3.01510368803882e-07[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55887&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55887&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:

Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( Rentevoet , Gezondheidsindex )-0.7156633939214081.92336203198913e-14
tau( Rentevoet , totaleproductie )-0.6667447696382522.51274408250596e-12
tau( Rentevoet , bouwaanvragen )0.4737252829830064.17354532933345e-07
tau( Gezondheidsindex , totaleproductie )0.592164711467545.35336219797955e-11
tau( Gezondheidsindex , bouwaanvragen )-0.5349566636611581.66001186020675e-09
tau( totaleproductie , bouwaanvragen )-0.4629587582894423.01510368803882e-07


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
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='kendall')
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$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Kendall tau rank correlations for all pairs of data series',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'tau',1,TRUE)
a<-table.element(a,'p-value',1,TRUE)
a<-table.row.end(a)
n <- length(y[,1])
n
cor.test(y[1,],y[2,],method='kendall')
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste('tau(',dimnames(t(x))[[2]][i])
dum <- paste(dum,',')
dum <- paste(dum,dimnames(t(x))[[2]][j])
dum <- paste(dum,')')
a<-table.element(a,dum,header=TRUE)
r <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,r$estimate)
a<-table.element(a,r$p.value)
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable.tab')