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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 computationSun, 18 Dec 2011 07:54:18 -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/18/t1324212877p5hyl9l7osnjubh.htm/, Retrieved Sun, 05 May 2024 10:47:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=156798, Retrieved Sun, 05 May 2024 10:47:37 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact94
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [] [2010-12-05 17:44:33] [b98453cac15ba1066b407e146608df68]
- RMPD    [Kendall tau Correlation Matrix] [Pearson Correlati...] [2011-12-18 12:54:18] [e1aba6efa0fba8dc2a9839c208d0186e] [Current]
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Dataseries X:
140824	165	186099	38
110459	135	113854	34
105079	121	99776	42
112098	148	106194	38
43929	73	100792	27
76173	49	47552	35
187326	185	250931	33
22807	5	6853	18
144408	125	115466	34
66485	93	110896	33
79089	154	169351	46
81625	98	94853	55
68788	70	72591	37
103297	148	101345	55
69446	100	113713	44
114948	150	165354	59
167949	197	164263	36
125081	114	135213	39
125818	169	111669	29
136588	200	134163	51
112431	148	140303	49
103037	140	150773	39
82317	74	111848	25
118906	128	102509	52
83515	140	96785	45
104581	116	116136	38
103129	147	158376	41
83243	132	153990	43
37110	70	64057	32
113344	144	230054	41
139165	155	184531	47
86652	165	114198	50
112302	161	198299	48
69652	31	33750	37
119442	199	189723	43
69867	78	100826	42
101629	121	188355	44
70168	112	104470	36
31081	41	58391	17
103925	158	164808	42
92622	123	134097	39
79011	104	80238	41
93487	94	133252	36
64520	73	54518	47
93473	52	121850	45
114360	71	79367	41
33032	21	56968	26
96125	155	106314	52
151911	174	191889	47
89256	136	104864	45
95671	128	160791	40
5950	7	15049	4
149695	165	191179	44
32551	21	25109	18
31701	35	45824	14
100087	137	129711	37
169707	174	210012	61
150491	257	194679	39
120192	207	197680	42
95893	103	81180	36
151715	171	197765	49
176225	279	214738	28
59900	83	96252	43
104767	130	124527	42
114799	131	153242	37
72128	126	145707	30
143592	158	113963	35
89626	138	134904	44
131072	200	114268	36
126817	104	94333	28
81351	111	102204	45
22618	26	23824	23
88977	115	111563	45
92059	127	91313	38
81897	140	89770	38
108146	121	100125	46
126372	183	165278	36
249771	68	181712	41
71154	112	80906	38
71571	103	75881	37
55918	63	83963	28
160141	166	175721	45
38692	38	68580	26
102812	163	136323	44
56622	59	55792	8
15986	27	25157	27
123534	108	100922	38
108535	88	118845	37
93879	92	170492	57
144551	170	81716	45
56750	98	115750	37
127654	205	105590	40
65594	96	92795	31
59938	107	82390	36
146975	150	135599	40
143372	123	111542	36
168553	176	162519	35
183500	213	211381	39
165986	208	189944	65
184923	307	226168	30
140358	125	117495	51
149959	208	195894	41
57224	73	80684	36
43750	49	19630	19
48029	82	88634	23
104978	206	139292	44
100046	112	128602	40
101047	139	135848	40
197426	60	178377	30
160902	70	106330	41
147172	112	178303	40
109432	142	116938	45
1168	11	5841	1
83248	130	106020	40
25162	31	24610	11
45724	132	74151	45
110529	219	232241	38
855	4	6622	0
101382	102	127097	30
14116	39	13155	8
89506	125	160501	39
135356	121	91502	48
116066	42	24469	48
144244	111	88229	29
8773	16	13983	8
102153	70	80716	43
117440	162	157384	52
104128	173	122975	53
134238	171	191469	48
134047	172	231257	48
279488	254	258287	50
79756	90	122531	40
66089	50	61394	36
102070	113	86480	40
146760	187	195791	46
154771	16	18284	42
165933	175	147581	46
64593	90	72558	39
92280	140	147341	41
67150	145	114651	46
128692	141	100187	32
124089	125	130332	39
125386	241	134218	39
37238	16	10901	21
140015	175	145758	45
150047	132	75767	50
154451	154	134969	36
156349	198	169216	44
0	0	0	0
6023	5	7953	0
0	0	0	0
0	0	0	0
0	0	0	0
0	0	0	0
84601	125	105406	37
68946	174	174586	52
0	0	0	0
0	0	0	0
1644	6	4245	0
6179	13	21509	5
3926	3	7670	1
52789	35	15673	43
0	0	0	0
100350	80	75882	34




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156798&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156798&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156798&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'Gertrude Mary Cox' @ cox.wessa.net







Correlations for all pairs of data series (method=pearson)
CharactersHyperlinksSecondsReviewed_Compendiums
Characters10.7640.7940.677
Hyperlinks0.76410.8510.674
Seconds0.7940.85110.673
Reviewed_Compendiums0.6770.6740.6731

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Characters & Hyperlinks & Seconds & Reviewed_Compendiums \tabularnewline
Characters & 1 & 0.764 & 0.794 & 0.677 \tabularnewline
Hyperlinks & 0.764 & 1 & 0.851 & 0.674 \tabularnewline
Seconds & 0.794 & 0.851 & 1 & 0.673 \tabularnewline
Reviewed_Compendiums & 0.677 & 0.674 & 0.673 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156798&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Characters[/C][C]Hyperlinks[/C][C]Seconds[/C][C]Reviewed_Compendiums[/C][/ROW]
[ROW][C]Characters[/C][C]1[/C][C]0.764[/C][C]0.794[/C][C]0.677[/C][/ROW]
[ROW][C]Hyperlinks[/C][C]0.764[/C][C]1[/C][C]0.851[/C][C]0.674[/C][/ROW]
[ROW][C]Seconds[/C][C]0.794[/C][C]0.851[/C][C]1[/C][C]0.673[/C][/ROW]
[ROW][C]Reviewed_Compendiums[/C][C]0.677[/C][C]0.674[/C][C]0.673[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156798&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156798&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=pearson)
CharactersHyperlinksSecondsReviewed_Compendiums
Characters10.7640.7940.677
Hyperlinks0.76410.8510.674
Seconds0.7940.85110.673
Reviewed_Compendiums0.6770.6740.6731







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Characters;Hyperlinks0.76390.75320.602
p-value(0)(0)(0)
Characters;Seconds0.79360.74910.5804
p-value(0)(0)(0)
Characters;Reviewed_Compendiums0.67740.51490.3785
p-value(0)(0)(0)
Hyperlinks;Seconds0.85090.82460.6638
p-value(0)(0)(0)
Hyperlinks;Reviewed_Compendiums0.67360.59070.4463
p-value(0)(0)(0)
Seconds;Reviewed_Compendiums0.67250.54890.41
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
Characters;Hyperlinks & 0.7639 & 0.7532 & 0.602 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Characters;Seconds & 0.7936 & 0.7491 & 0.5804 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Characters;Reviewed_Compendiums & 0.6774 & 0.5149 & 0.3785 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Hyperlinks;Seconds & 0.8509 & 0.8246 & 0.6638 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Hyperlinks;Reviewed_Compendiums & 0.6736 & 0.5907 & 0.4463 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Seconds;Reviewed_Compendiums & 0.6725 & 0.5489 & 0.41 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156798&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]Characters;Hyperlinks[/C][C]0.7639[/C][C]0.7532[/C][C]0.602[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Characters;Seconds[/C][C]0.7936[/C][C]0.7491[/C][C]0.5804[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Characters;Reviewed_Compendiums[/C][C]0.6774[/C][C]0.5149[/C][C]0.3785[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Hyperlinks;Seconds[/C][C]0.8509[/C][C]0.8246[/C][C]0.6638[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Hyperlinks;Reviewed_Compendiums[/C][C]0.6736[/C][C]0.5907[/C][C]0.4463[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Seconds;Reviewed_Compendiums[/C][C]0.6725[/C][C]0.5489[/C][C]0.41[/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=156798&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156798&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
Characters;Hyperlinks0.76390.75320.602
p-value(0)(0)(0)
Characters;Seconds0.79360.74910.5804
p-value(0)(0)(0)
Characters;Reviewed_Compendiums0.67740.51490.3785
p-value(0)(0)(0)
Hyperlinks;Seconds0.85090.82460.6638
p-value(0)(0)(0)
Hyperlinks;Reviewed_Compendiums0.67360.59070.4463
p-value(0)(0)(0)
Seconds;Reviewed_Compendiums0.67250.54890.41
p-value(0)(0)(0)



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