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Grondstofprijsindex, Werkloosheidsgraad, Totale industr productieindex & br...

Author*Unverified author*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationMon, 09 Nov 2009 14:19:00 -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/09/t1257801835i7h0d9iwfyl14ue.htm/, Retrieved Thu, 28 Mar 2024 10:41:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=55062, Retrieved Thu, 28 Mar 2024 10:41:10 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsDe indexen zijn met basisjaar 2000 = 100 Werkloosheidsgraad is in % Brutoschuld(overheid) is in Miljoen Euro
Estimated Impact213
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [Grondstofprijsind...] [2009-11-09 21:19:00] [c483349466b1550829c7523719d2d027] [Current]
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Dataseries X:
117,1	95,1	8,9	269285
118,7	97	8,8	269829
126,5	112,7	8,3	270911
127,5	102,9	7,5	266844
134,6	97,4	7,2	271244
131,8	111,4	7,4	269907
135,9	87,4	8,8	271296
142,7	96,8	9,3	270157
141,7	114,1	9,3	271322
153,4	110,3	8,7	267179
145	103,9	8,2	264101
137,7	101,6	8,3	265518
148,3	94,6	8,5	269419
152,2	95,9	8,6	268714
169,4	104,7	8,5	272482
168,6	102,8	8,2	268351
161,1	98,1	8,1	268175
174,1	113,9	7,9	270674
179	80,9	8,6	272764
190,6	95,7	8,7	272599
190	113,2	8,7	270333
181,6	105,9	8,5	270846
174,8	108,8	8,4	270491
180,5	102,3	8,5	269160
196,8	99	8,7	274027
193,8	100,7	8,7	273784
197	115,5	8,6	276663
216,3	100,7	8,5	274525
221,4	109,9	8,3	271344
217,9	114,6	8	271115
229,7	85,4	8,2	270798
227,4	100,5	8,1	273911
204,2	114,8	8,1	273985
196,6	116,5	8	271917
198,8	112,9	7,9	273338
207,5	102	7,9	270601
190,7	106	8	273547
201,6	105,3	8	275363
210,5	118,8	7,9	281229
223,5	106,1	8	277793
223,8	109,3	7,7	279913
231,2	117,2	7,2	282500
244	92,5	7,5	280041
234,7	104,2	7,3	282166
250,2	112,5	7	290304
265,7	122,4	7	283519
287,6	113,3	7	287816
283,3	100	7,2	285226
295,4	110,7	7,3	287595
312,3	112,8	7,1	289741
333,8	109,8	6,8	289148
347,7	117,3	6,4	288301
383,2	109,1	6,1	290155
407,1	115,9	6,5	289648
413,6	96	7,7	288225
362,7	99,8	7,9	289351
321,9	116,8	7,5	294735
239,4	115,7	6,9	305333
191	99,4	6,6	309030
159,7	94,3	6,9	310215
163,4	91	7,7	321935




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55062&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55062&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55062&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( Prijsindexgrondst , Tot.indus.prod )0.2519814250978680.00412007193349506
tau( Prijsindexgrondst , werkloosheidsgraad )-0.4599933470010342.6033505625123e-07
tau( Prijsindexgrondst , Brutoschuld )0.5890710382513661.9690249430937e-11
tau( Tot.indus.prod , werkloosheidsgraad )-0.2523413355185560.00473533639624063
tau( Tot.indus.prod , Brutoschuld )0.1601530532617690.068250501259548
tau( werkloosheidsgraad , Brutoschuld )-0.4967482633473642.67283373204822e-08

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( Prijsindexgrondst , Tot.indus.prod ) & 0.251981425097868 & 0.00412007193349506 \tabularnewline
tau( Prijsindexgrondst , werkloosheidsgraad ) & -0.459993347001034 & 2.6033505625123e-07 \tabularnewline
tau( Prijsindexgrondst , Brutoschuld ) & 0.589071038251366 & 1.9690249430937e-11 \tabularnewline
tau( Tot.indus.prod , werkloosheidsgraad ) & -0.252341335518556 & 0.00473533639624063 \tabularnewline
tau( Tot.indus.prod , Brutoschuld ) & 0.160153053261769 & 0.068250501259548 \tabularnewline
tau( werkloosheidsgraad , Brutoschuld ) & -0.496748263347364 & 2.67283373204822e-08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55062&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( Prijsindexgrondst , Tot.indus.prod )[/C][C]0.251981425097868[/C][C]0.00412007193349506[/C][/ROW]
[ROW][C]tau( Prijsindexgrondst , werkloosheidsgraad )[/C][C]-0.459993347001034[/C][C]2.6033505625123e-07[/C][/ROW]
[ROW][C]tau( Prijsindexgrondst , Brutoschuld )[/C][C]0.589071038251366[/C][C]1.9690249430937e-11[/C][/ROW]
[ROW][C]tau( Tot.indus.prod , werkloosheidsgraad )[/C][C]-0.252341335518556[/C][C]0.00473533639624063[/C][/ROW]
[ROW][C]tau( Tot.indus.prod , Brutoschuld )[/C][C]0.160153053261769[/C][C]0.068250501259548[/C][/ROW]
[ROW][C]tau( werkloosheidsgraad , Brutoschuld )[/C][C]-0.496748263347364[/C][C]2.67283373204822e-08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55062&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55062&T=1

As an alternative you can also use a 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( Prijsindexgrondst , Tot.indus.prod )0.2519814250978680.00412007193349506
tau( Prijsindexgrondst , werkloosheidsgraad )-0.4599933470010342.6033505625123e-07
tau( Prijsindexgrondst , Brutoschuld )0.5890710382513661.9690249430937e-11
tau( Tot.indus.prod , werkloosheidsgraad )-0.2523413355185560.00473533639624063
tau( Tot.indus.prod , Brutoschuld )0.1601530532617690.068250501259548
tau( werkloosheidsgraad , Brutoschuld )-0.4967482633473642.67283373204822e-08



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')