Free Statistics

of Irreproducible Research!

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 computationWed, 16 Dec 2009 05:00:43 -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/Dec/16/t1260964935nftkapp904xg0ql.htm/, Retrieved Tue, 30 Apr 2024 19:26:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68250, Retrieved Tue, 30 Apr 2024 19:26:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact142
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [Kendall Tau Ameri...] [2008-12-10 14:54:10] [b87cf4f6ac665e4d6a88fc8d9f2625f6]
-  M      [Kendall tau Correlation Matrix] [] [2009-12-16 12:00:43] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum

Post a new message
Dataseries X:
358.59	122.36
362.96	123.33
362.42	123.04
364.97	124.53
364.04	125.13
361.06	125.85
358.48	126.50
352.96	126.53
359.59	127.07
360.39	124.55
357.40	124.90
362.93	124.32
364.55	122.84
365.73	123.31
364.70	123.31
364.65	124.87
359.43	124.64
362.14	124.73
356.97	124.90
354.82	124.04
353.17	123.28
357.06	123.86
356.18	122.29
355.01	124.09
355.65	124.54
357.31	125.65
357.07	125.70
357.91	125.53
358.48	125.61
358.97	125.55
351.77	125.41
352.16	127.60
359.08	124.68
360.35	124.41
359.53	126.43
359.30	126.38
358.41	125.78
359.68	124.70
355.31	125.07
357.08	125.25
349.71	126.58
354.13	127.13
345.49	125.82
341.69	123.70
344.25	124.39
340.17	123.70
342.47	124.42
344.43	121.05
333.23	121.02
339.72	123.23
342.61	121.32
346.36	120.91
339.09	120.72
339.73	123.31
341.12	119.58
335.94	119.53
333.46	120.59
335.66	118.63
341.12	118.47
342.21	111.81
342.62	114.71
346.06	117.34
344.43	115.77
346.65	118.38
343.74	117.84
335.67	118.83
342.75	120.02
341.77	116.21
345.84	117.08
346.52	120.20
350.79	119.83
345.44	118.92
345.87	118.03
338.48	117.71
337.21	119.55
340.81	116.13
339.86	115.97
342.86	115.99
343.33	114.96
341.73	116.46
351.38	116.55
351.13	113.05
345.99	117.44
347.55	118.84
346.02	117.06
345.29	117.54
347.03	119.31
348.01	118.72
345.48	121.55
349.40	122.61
351.05	121.53
349.70	123.31
350.86	124.07
354.45	123.59
355.30	122.97
357.48	123.22
355.24	123.04
351.79	122.96
355.22	122.81
351.02	122.81
350.28	122.62
350.17	120.82
348.16	119.41
340.30	121.56
343.75	121.59
344.71	118.50
344.13	118.77
342.14	118.86
345.04	117.60
346.02	119.90
346.43	121.83
347.07	121.84
339.33	122.12
339.10	122.12
337.19	121.36
339.58	119.66
327.85	119.32
326.81	120.36
321.73	117.06
320.45	117.48
327.69	115.60
323.95	113.86
320.47	116.92
322.13	117.75
316.34	117.75
314.78	115.31
308.90	116.28
308.62	115.22
314.41	115.65
306.88	115.11
310.60	118.67
321.60	118.04
321.50	116.50
325.68	119.78
324.35	119.95
320.01	120.37
326.88	119.79
332.39	119.43
331.48	121.06
332.62	121.74
324.79	121.09
327.12	122.97
328.91	120.50
328.37	117.18
324.83	115.03
325.90	113.36
326.18	112.59
328.94	111.65
333.78	111.98
328.06	114.87
325.87	114.67
325.41	114.09
318.86	114.77
319.13	117.05
310.16	117.22
311.73	113.18
306.54	110.95
311.16	112.14
311.98	112.72
306.72	110.01
308.05	110.29
300.76	110.74
301.90	110.32
293.09	105.89
292.76	108.97
294.58	109.34
289.90	106.57
296.69	99.49
297.21	101.81
293.31	104.29
296.25	109.73
298.60	105.06
296.87	107.97
301.02	108.13
304.73	109.86
301.92	108.95
295.72	111.20
293.18	110.69
298.35	106.10
297.99	105.68
299.85	104.12
299.85	104.71
304.45	104.30
299.45	103.52
298.14	107.76
298.78	107.80
297.02	107.30
301.33	108.64
294.96	105.03
296.69	108.30
300.73	107.21
301.96	109.27
297.38	109.50
293.87	111.68
285.96	111.80
285.41	111.75
283.70	106.68
284.76	106.37
277.11	105.76
274.73	109.01
274.73	109.01
274.73	109.01
274.73	109.01
274.69	107.69
275.42	105.19
264.15	105.48
276.24	102.22
268.88	100.54
277.97	105.00
280.49	105.44
281.09	107.89
276.16	108.64
272.58	106.70
270.94	109.10
284.31	105.23
283.94	108.41
284.18	108.80
282.83	110.39
283.84	110.22
282.71	110.86
279.29	108.58
280.70	107.70
274.47	106.62
273.44	109.84
275.49	107.16
279.46	107.26
280.19	108.70
288.21	109.85
284.80	109.41
281.41	112.36
283.39	111.03
287.97	110.67
290.77	109.21
290.60	113.58
289.67	113.88
289.84	114.08
298.55	112.33
296.07	113.92
297.14	114.41
295.34	114.57
296.25	115.35
294.30	113.13
296.15	113.29
296.49	112.56
298.05	113.06
301.03	113.46
300.52	115.39
301.50	116.62
296.93	117.04
289.84	117.42
291.44	115.62
286.88	115.16
286.74	115.69
288.93	112.85
292.19	114.05
295.39	112.00
295.86	113.74
293.36	116.26
292.86	118.63
292.73	116.49
296.73	118.23
285.02	116.83
285.24	118.82
288.62	114.36
283.36	112.02
285.84	113.24
291.48	109.75
291.41	110.33
287.77	112.86
284.97	113.04
286.05	113.80
278.19	110.90
281.21	109.96
277.92	108.69
280.08	108.84
269.24	108.47
268.48	108.07
268.83	107.94
269.54	108.11
262.37	108.11
265.12	106.81
265.34	105.58
263.32	105.61
267.18	106.52
260.75	103.86
261.78	104.60
257.27	104.73
255.63	105.12
251.39	104.76
259.49	103.85
261.18	103.83
261.65	103.22
262.01	101.64
265.23	102.13
268.10	104.33
262.27	104.92
263.59	107.78
257.85	104.49
265.69	102.80
271.15	102.86
266.69	104.51
265.77	104.73
262.32	102.58
270.48	99.93
273.03	101.41
269.13	101.05
280.65	99.86
282.75	101.11
281.44	100.89
281.99	101.09
282.86	98.31
287.21	98.08
283.11	99.55
280.66	99.62
282.39	97.37
280.83	98.16
284.71	97.98
279.99	98.15
283.50	97.10
284.88	97.24
288.60	96.70
284.80	96.64
287.20	100.65
286.22	96.75
286.54	97.74
279.58	97.92
283.08	98.34
288.88	93.84
280.18	97.80
284.16	96.20
290.57	95.99
286.82	95.18
273.00	95.95
278.69	92.23
264.54	91.78
271.92	92.97
283.60	89.76
269.25	92.88
263.58	96.23
264.16	95.79
268.85	93.97
269.67	93.90
249.41	93.60
268.99	93.96
268.65	88.69
260.16	88.57
256.55	85.62
251.47	86.25
234.93	85.33
232.96	83.33
215.49	77.78
213.68	78.70
236.07	72.05
235.41	80.75
214.77	81.41
225.85	82.65
224.64	75.85
238.26	75.70
232.44	78.25
222.50	77.41
225.28	76.84
220.49	74.25
216.86	74.95
234.70	68.78
230.06	73.21
238.27	73.26
238.56	78.67
242.70	75.63
249.14	74.99
234.89	83.87
227.78	79.62
234.04	80.13
230.70	79.76
230.17	78.20
218.23	78.05
232.20	79.05
220.76	73.32
215.60	75.17
217.69	73.26
204.35	73.72
191.44	73.57
203.84	70.60
211.86	71.25
210.57	74.22
219.57	73.32
219.98	73.01
226.01	74.21
207.04	75.32
212.52	71.73
217.92	71.94
210.45	72.94
218.53	72.47
223.32	71.94
218.76	74.30
217.63	74.30




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68250&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68250&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68250&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'Gwilym Jenkins' @ 72.249.127.135







Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( Arabia , Asia )0.7429155418092820

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( Arabia , Asia ) & 0.742915541809282 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68250&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( Arabia , Asia )[/C][C]0.742915541809282[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68250&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68250&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( Arabia , Asia )0.7429155418092820



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')