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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, 22 Dec 2011 12:47:04 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/22/t1324576103ej0ss72yefenhff.htm/, Retrieved Fri, 03 May 2024 07:00:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=159779, Retrieved Fri, 03 May 2024 07:00:13 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact73
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [Paper deel 3a] [2011-12-22 17:47:04] [02ed7fa8d7b1f39a2d911dce6cf09d8a] [Current]
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Dataseries X:
162687	115	73	23975
201906	76	56	85634
7215	1	0	1929
159169	158	69	36294
257045	125	116	72255
531611	278	138	189748
191582	93	76	61834
195674	59	107	68167
177020	87	50	38462
330255	130	81	101219
121844	158	58	43270
203938	120	91	76183
117344	87	41	31476
220751	264	100	62157
174005	51	61	46261
156326	85	74	50063
145178	100	147	64483
90025	72	45	2341
179935	147	110	48149
47066	49	41	12743
106192	40	37	18743
241285	99	84	97057
200429	127	67	17675
149513	165	69	33106
159763	41	58	53311
207078	160	60	42754
213771	92	88	59056
201536	59	75	101621
408668	89	98	118120
217892	90	67	79572
182286	76	84	42744
188748	116	62	65931
137978	92	35	38575
265732	362	74	28795
236546	88	93	94440
0	0	0	0
230761	63	87	38229
132807	138	39	31972
161703	270	101	40071
253254	64	135	132480
269329	96	76	62797
161273	62	118	40429
107181	35	76	45545
213097	66	65	57568
139667	56	97	39019
171124	41	70	53866
81407	49	63	38345
250888	121	96	50210
239807	113	112	80947
172743	190	82	43461
48188	37	39	14812
169355	52	69	37819
335398	89	93	102738
241518	73	76	54509
200137	50	117	62956
159913	77	31	55411
223936	58	65	50611
101694	75	78	26692
157258	32	87	60056
211586	59	85	25155
181076	71	119	42840
150518	91	65	39358
141491	87	60	47241
130108	48	67	49611
166420	63	94	41833
125440	41	100	48930
195043	86	135	110600
138708	152	71	52235
116552	49	78	53986
31970	40	42	4105
277661	135	42	59331
167284	86	16	47796
135926	62	86	38302
119629	91	41	14063
171518	95	131	54414
108949	82	91	9903
183471	112	102	53987
159966	70	91	88937
101646	78	46	21928
84971	105	60	29487
88882	49	69	35334
304603	60	95	57596
75101	49	17	29750
145043	132	61	41029
95827	49	55	12416
173931	71	55	51158
243037	102	124	79935
115367	74	73	26552
125839	49	73	25807
164078	74	67	50620
158931	59	66	61467
190348	91	77	65292
152856	68	83	55516
146159	81	55	42006
62535	33	27	26273
245267	166	115	90248
199841	97	85	61476
19349	15	0	9604
247280	105	83	45108
164457	61	90	47232
72128	11	4	3439
104253	45	60	30553
151090	89	74	24751
147990	72	55	34458
87448	27	24	24649
27676	59	17	2342
170326	127	105	52739
132148	48	20	6245
0	0	0	0
95778	58	51	35381
109001	57	76	19595
158833	60	61	50848
150013	77	70	39443
89887	71	38	27023
3616	5	0	0
0	0	0	0
211648	73	81	61022
166048	76	78	63528
177948	124	76	34835
136061	56	89	37172
43410	63	3	13
184277	92	87	62548
109873	58	55	31334
151230	64	73	20839
60493	29	32	5084
19764	19	4	9927
177559	64	70	53229
140281	79	102	29877
164249	104	109	37310
11796	22	1	0
10674	7	0	0
151322	37	39	50067
6836	5	0	0
174712	48	45	47708
5118	1	0	0
40248	34	7	6012
0	0	0	0
127628	53	86	27749
88837	44	52	47555
7131	0	0	0
9056	18	1	1336
88589	52	49	11017
144470	56	72	55184
111408	50	56	43485




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

\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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159779&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159779&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159779&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'AstonUniversity' @ aston.wessa.net







Correlations for all pairs of data series (method=kendall)
BEJM
B10.490.5230.638
E0.4910.390.358
J0.5230.3910.498
M0.6380.3580.4981

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & B & E & J & M \tabularnewline
B & 1 & 0.49 & 0.523 & 0.638 \tabularnewline
E & 0.49 & 1 & 0.39 & 0.358 \tabularnewline
J & 0.523 & 0.39 & 1 & 0.498 \tabularnewline
M & 0.638 & 0.358 & 0.498 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159779&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]B[/C][C]E[/C][C]J[/C][C]M[/C][/ROW]
[ROW][C]B[/C][C]1[/C][C]0.49[/C][C]0.523[/C][C]0.638[/C][/ROW]
[ROW][C]E[/C][C]0.49[/C][C]1[/C][C]0.39[/C][C]0.358[/C][/ROW]
[ROW][C]J[/C][C]0.523[/C][C]0.39[/C][C]1[/C][C]0.498[/C][/ROW]
[ROW][C]M[/C][C]0.638[/C][C]0.358[/C][C]0.498[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159779&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159779&T=1

As an alternative you can also use a QR Code:  

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

Correlations for all pairs of data series (method=kendall)
BEJM
B10.490.5230.638
E0.4910.390.358
J0.5230.3910.498
M0.6380.3580.4981







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
B;E0.60850.66070.49
p-value(0)(0)(0)
B;J0.72150.69490.523
p-value(0)(0)(0)
B;M0.84560.80970.6382
p-value(0)(0)(0)
E;J0.49880.5330.3898
p-value(0)(0)(0)
E;M0.43470.50430.3576
p-value(0)(0)(0)
J;M0.70110.66740.4977
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
B;E & 0.6085 & 0.6607 & 0.49 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
B;J & 0.7215 & 0.6949 & 0.523 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
B;M & 0.8456 & 0.8097 & 0.6382 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
E;J & 0.4988 & 0.533 & 0.3898 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
E;M & 0.4347 & 0.5043 & 0.3576 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
J;M & 0.7011 & 0.6674 & 0.4977 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159779&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]B;E[/C][C]0.6085[/C][C]0.6607[/C][C]0.49[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]B;J[/C][C]0.7215[/C][C]0.6949[/C][C]0.523[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]B;M[/C][C]0.8456[/C][C]0.8097[/C][C]0.6382[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]E;J[/C][C]0.4988[/C][C]0.533[/C][C]0.3898[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]E;M[/C][C]0.4347[/C][C]0.5043[/C][C]0.3576[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]J;M[/C][C]0.7011[/C][C]0.6674[/C][C]0.4977[/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=159779&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159779&T=2

As an alternative you can also use a 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
B;E0.60850.66070.49
p-value(0)(0)(0)
B;J0.72150.69490.523
p-value(0)(0)(0)
B;M0.84560.80970.6382
p-value(0)(0)(0)
E;J0.49880.5330.3898
p-value(0)(0)(0)
E;M0.43470.50430.3576
p-value(0)(0)(0)
J;M0.70110.66740.4977
p-value(0)(0)(0)



Parameters (Session):
par1 = kendall ;
Parameters (R input):
par1 = kendall ;
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')