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Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationMon, 15 Dec 2008 14:19:14 -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/2008/Dec/15/t1229376061flu0q2s28blwxkp.htm/, Retrieved Thu, 16 May 2024 02:41:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33827, Retrieved Thu, 16 May 2024 02:41:47 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [] [2008-12-15 21:14:33] [74be16979710d4c4e7c6647856088456]
-    D    [Kendall tau Correlation Matrix] [Kendall tau] [2008-12-15 21:19:14] [5925747fb2a6bb4cfcd8015825ee5e92] [Current]
-    D      [Kendall tau Correlation Matrix] [verband tussen in...] [2008-12-17 19:07:06] [5e74953d94072114d25d7276793b561e]
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Dataseries X:
8955.50	356.40	966.20	1235.80	40.60	180144.00
10423.90	394.30	1153.20	1147.10	63.60	173666.00
11617.20	410.90	1328.30	1376.90	66.80	165688.00
9391.10	385.90	1144.50	1157.70	71.50	161570.00
10872.00	523.70	1477.10	1506.00	99.40	156145.00
10230.40	439.10	1234.90	1271.30	78.20	153730.00
9221.00	399.30	1119.10	1240.20	57.20	182698.00
9428.60	372.90	1356.90	1408.30	86.50	200765.00
10934.50	483.20	1217.00	1334.60	66.10	176512.00
10986.00	468.70	1440.50	1601.20	75.00	166618.00
11724.60	498.30	1556.60	1566.40	55.00	158644.00
11180.90	434.40	1303.60	1297.50	66.80	159585.00
11163.20	371.60	1421.50	1487.60	41.40	163095.00
11240.90	408.70	1172.50	1320.90	53.30	159044.00
12107.10	444.50	1422.10	1514.00	71.40	155511.00
10762.30	383.00	1263.00	1290.90	68.20	153745.00
11340.40	388.90	1428.10	1392.50	84.10	150569.00
11266.80	385.10	1347.00	1288.20	94.00	150605.00
9542.70	347.20	1224.20	1304.40	91.40	179612.00
9227.70	315.60	1201.30	1297.80	79.90	194690.00
10571.90	300.90	997.80	1211.00	40.70	189917.00
10774.40	371.20	1248.80	1454.00	60.30	184128.00
10392.80	340.30	1268.60	1405.70	49.10	175335.00
9920.20	301.90	1016.70	1160.80	42.00	179566.00
9884.90	327.40	1194.30	1492.10	54.30	181140.00
10174.50	398.60	1181.80	1263.00	39.30	177876.00
11395.40	379.90	1150.70	1376.30	47.80	175041.00
10760.20	379.70	1247.20	1368.60	74.50	169292.00
10570.10	418.40	1260.60	1427.60	78.80	166070.00
10536.00	367.90	1249.30	1339.80	81.40	166972.00
9902.60	362.50	1223.20	1248.30	66.00	206348.00
8889.00	296.70	1153.00	1309.80	88.80	215706.00
10837.30	343.00	1191.50	1424.00	54.40	202108.00
11624.10	488.30	1303.10	1590.50	75.80	195411.00
10509.00	402.50	1267.10	1423.10	51.60	193111.00
10984.90	500.70	1125.20	1355.30	53.00	195198.00
10649.10	412.80	1322.40	1515.00	62.70	198770.00
10855.70	385.90	1089.20	1385.60	52.30	194163.00
11677.40	461.90	1147.30	1430.00	30.50	190420.00
10760.20	357.40	1196.40	1494.20	49.90	189733.00
10046.20	316.90	1190.20	1580.90	53.80	186029.00
10772.80	339.20	1146.00	1369.80	65.30	191531.00
9987.70	372.30	1139.80	1407.50	62.70	232571.00
8638.70	264.80	1045.60	1388.30	55.40	243477.00
11063.70	325.90	1050.90	1478.50	66.20	227247.00
11855.70	324.10	1117.30	1630.40	67.20	217859.00
10684.50	324.30	1120.00	1413.50	42.40	208679.00
11337.40	318.20	1052.10	1493.80	56.30	213188.00
10478.00	323.40	1065.80	1641.30	44.90	216234.00
11123.90	295.90	1092.50	1465.00	30.00	213586.00
12909.30	425.00	1422.00	1725.10	54.40	209465.00
11339.90	337.80	1367.50	1628.40	47.80	204045.00
10462.20	322.70	1136.30	1679.80	63.60	200237.00
12733.50	430.20	1293.70	1876.00	72.50	203666.00
10519.20	403.80	1154.80	1669.40	82.20	241476.00
10414.90	333.70	1206.70	1712.40	67.90	260307.00
12476.80	358.10	1199.00	1768.80	67.80	243324.00
12384.60	426.70	1265.00	1820.50	65.60	244460.00
12266.70	376.00	1247.10	1776.20	78.10	233575.00
12919.90	312.00	1116.50	1693.70	41.60	237217.00
11497.30	349.30	1153.90	1799.10	64.30	235243.00
12142.00	340.30	1077.40	1917.50	55.90	230354.00
13919.40	455.70	1132.50	1887.20	78.30	227184.00
12656.80	352.30	1058.80	1787.80	69.80	221678.00
12034.10	481.40	1195.10	1803.80	59.30	217142.00
13199.70	731.90	1263.40	2196.40	103.60	219452.00
10881.30	382.20	1023.10	1759.50	109.70	256446.00
11301.20	392.80	1141.00	2002.60	76.30	265845.00
13643.90	351.60	1116.30	2056.80	81.80	248624.00
12517.00	276.50	1135.60	1851.10	99.60	241114.00
13981.10	371.30	1210.50	1984.30	100.60	229245.00
14275.70	439.00	1230.00	1725.30	79.90	231805.00
13435.00	394.40	1136.50	2096.60	49.30	219277.00
13565.70	445.50	1068.70	1792.20	62.70	219313.00
16216.30	560.00	1372.50	2029.90	101.30	212610.00
12970.00	331.80	1049.90	1785.30	101.20	214771.00
14079.90	404.20	1302.20	2026.50	83.30	211142.00
14235.00	489.80	1305.90	1930.80	127.80	211457.00
12213.40	323.90	1173.50	1845.50	103.70	240048.00
12581.00	269.40	1277.40	1943.10	91.50	240636.00
14130.40	319.20	1238.60	2066.80	95.10	230580.00
14210.80	337.60	1508.60	2354.40	109.00	208795.00
14378.50	399.50	1423.40	2190.70	132.60	197922.00
13142.80	316.70	1375.10	1929.60	79.50	194596.00




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=33827&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=33827&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33827&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( Europa , Afrika )0.1759219418312170.0178784722634078
tau( Europa , Amerika )0.1546406557296960.0373224213063887
tau( Europa , Azië )0.5895854313998621.99840144432528e-15
tau( Europa , Oceanïe )0.2576476959010450.000529366338130277
tau( Europa , Werkloosheid )0.2223497369026240.00275422732937836
tau( Afrika , Amerika )0.3098995823420153.01677366598696e-05
tau( Afrika , Azië )0.02926829388785690.693550935272995
tau( Afrika , Oceanïe )0.1068658828350960.150666063850880
tau( Afrika , Werkloosheid )-0.2002869522914130.0070077634806467
tau( Amerika , Azië )0.1032702237521510.164312961371562
tau( Amerika , Oceanïe )0.2642161421725310.000379029756218285
tau( Amerika , Werkloosheid )-0.2581755593803790.000507476907299231
tau( Azië , Oceanïe )0.2825963955410550.000143809006700080
tau( Azië , Werkloosheid )0.4457831325301211.93421345606737e-09
tau( Oceanïe , Werkloosheid )0.1275130077441350.0862862715998693

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( Europa , Afrika ) & 0.175921941831217 & 0.0178784722634078 \tabularnewline
tau( Europa , Amerika ) & 0.154640655729696 & 0.0373224213063887 \tabularnewline
tau( Europa , Azië ) & 0.589585431399862 & 1.99840144432528e-15 \tabularnewline
tau( Europa , Oceanïe ) & 0.257647695901045 & 0.000529366338130277 \tabularnewline
tau( Europa , Werkloosheid ) & 0.222349736902624 & 0.00275422732937836 \tabularnewline
tau( Afrika , Amerika ) & 0.309899582342015 & 3.01677366598696e-05 \tabularnewline
tau( Afrika , Azië ) & 0.0292682938878569 & 0.693550935272995 \tabularnewline
tau( Afrika , Oceanïe ) & 0.106865882835096 & 0.150666063850880 \tabularnewline
tau( Afrika , Werkloosheid ) & -0.200286952291413 & 0.0070077634806467 \tabularnewline
tau( Amerika , Azië ) & 0.103270223752151 & 0.164312961371562 \tabularnewline
tau( Amerika , Oceanïe ) & 0.264216142172531 & 0.000379029756218285 \tabularnewline
tau( Amerika , Werkloosheid ) & -0.258175559380379 & 0.000507476907299231 \tabularnewline
tau( Azië , Oceanïe ) & 0.282596395541055 & 0.000143809006700080 \tabularnewline
tau( Azië , Werkloosheid ) & 0.445783132530121 & 1.93421345606737e-09 \tabularnewline
tau( Oceanïe , Werkloosheid ) & 0.127513007744135 & 0.0862862715998693 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33827&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( Europa , Afrika )[/C][C]0.175921941831217[/C][C]0.0178784722634078[/C][/ROW]
[ROW][C]tau( Europa , Amerika )[/C][C]0.154640655729696[/C][C]0.0373224213063887[/C][/ROW]
[ROW][C]tau( Europa , Azië )[/C][C]0.589585431399862[/C][C]1.99840144432528e-15[/C][/ROW]
[ROW][C]tau( Europa , Oceanïe )[/C][C]0.257647695901045[/C][C]0.000529366338130277[/C][/ROW]
[ROW][C]tau( Europa , Werkloosheid )[/C][C]0.222349736902624[/C][C]0.00275422732937836[/C][/ROW]
[ROW][C]tau( Afrika , Amerika )[/C][C]0.309899582342015[/C][C]3.01677366598696e-05[/C][/ROW]
[ROW][C]tau( Afrika , Azië )[/C][C]0.0292682938878569[/C][C]0.693550935272995[/C][/ROW]
[ROW][C]tau( Afrika , Oceanïe )[/C][C]0.106865882835096[/C][C]0.150666063850880[/C][/ROW]
[ROW][C]tau( Afrika , Werkloosheid )[/C][C]-0.200286952291413[/C][C]0.0070077634806467[/C][/ROW]
[ROW][C]tau( Amerika , Azië )[/C][C]0.103270223752151[/C][C]0.164312961371562[/C][/ROW]
[ROW][C]tau( Amerika , Oceanïe )[/C][C]0.264216142172531[/C][C]0.000379029756218285[/C][/ROW]
[ROW][C]tau( Amerika , Werkloosheid )[/C][C]-0.258175559380379[/C][C]0.000507476907299231[/C][/ROW]
[ROW][C]tau( Azië , Oceanïe )[/C][C]0.282596395541055[/C][C]0.000143809006700080[/C][/ROW]
[ROW][C]tau( Azië , Werkloosheid )[/C][C]0.445783132530121[/C][C]1.93421345606737e-09[/C][/ROW]
[ROW][C]tau( Oceanïe , Werkloosheid )[/C][C]0.127513007744135[/C][C]0.0862862715998693[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33827&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33827&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( Europa , Afrika )0.1759219418312170.0178784722634078
tau( Europa , Amerika )0.1546406557296960.0373224213063887
tau( Europa , Azië )0.5895854313998621.99840144432528e-15
tau( Europa , Oceanïe )0.2576476959010450.000529366338130277
tau( Europa , Werkloosheid )0.2223497369026240.00275422732937836
tau( Afrika , Amerika )0.3098995823420153.01677366598696e-05
tau( Afrika , Azië )0.02926829388785690.693550935272995
tau( Afrika , Oceanïe )0.1068658828350960.150666063850880
tau( Afrika , Werkloosheid )-0.2002869522914130.0070077634806467
tau( Amerika , Azië )0.1032702237521510.164312961371562
tau( Amerika , Oceanïe )0.2642161421725310.000379029756218285
tau( Amerika , Werkloosheid )-0.2581755593803790.000507476907299231
tau( Azië , Oceanïe )0.2825963955410550.000143809006700080
tau( Azië , Werkloosheid )0.4457831325301211.93421345606737e-09
tau( Oceanïe , Werkloosheid )0.1275130077441350.0862862715998693



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')