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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, 09 Dec 2012 09:07:54 -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/2012/Dec/09/t1355062996ap0ik2xfhj9fdk6.htm/, Retrieved Sat, 20 Apr 2024 01:00:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197883, Retrieved Sat, 20 Apr 2024 01:00:42 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact91
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] [Ws 10: Pearson co...] [2011-12-10 19:14:19] [a9a952c1cbc7081c25fad93a34aab827]
- R         [Kendall tau Correlation Matrix] [ws10] [2012-12-09 14:07:54] [ed5689773f261aad7999fb516f38c1f9] [Current]
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Dataseries X:
0	255202	64	92	34
0	135248	59	58	30
0	207223	64	62	42
1	189326	95	108	34
1	141365	46	55	25
0	65295	27	8	31
0	439387	103	134	29
0	33186	19	1	18
0	183696	51	64	30
0	186657	38	77	29
1	276696	99	86	42
1	194414	98	96	50
0	141409	59	44	33
1	306730	68	108	46
1	192691	74	63	38
1	333497	164	160	52
0	261835	59	109	32
1	263451	130	86	35
1	157448	49	93	25
1	232190	73	126	42
0	245725	64	110	40
0	388603	92	86	35
0	156540	34	50	25
0	156189	47	92	46
0	189726	106	123	39
0	192167	106	81	35
1	249893	122	93	38
1	236812	76	113	35
1	143160	47	52	28
0	259667	54	113	37
0	243020	68	113	40
0	176062	67	44	42
0	286683	79	123	44
1	87485	33	38	33
0	329737	88	111	38
1	247082	51	77	37
0	378463	108	102	41
1	191653	75	74	32
0	114673	31	33	17
0	301596	167	107	39
0	284195	73	108	33
1	155568	60	66	35
1	177306	67	69	32
1	144595	51	62	35
0	140319	73	50	45
1	405267	135	91	38
1	78800	42	20	26
1	201970	69	101	45
1	302705	101	129	44
1	164733	50	93	40
1	194221	68	89	33
0	24188	24	8	4
0	346142	288	80	41
0	65029	17	21	18
0	101097	64	30	14
1	253745	51	86	36
0	273513	77	116	49
1	282220	160	106	32
1	280928	120	132	37
1	214872	74	75	32
0	342048	127	139	43
0	273924	108	121	25
1	195726	92	57	42
1	231162	80	67	37
0	209798	61	45	33
1	201345	60	88	28
0	180231	118	79	31
1	204441	129	75	40
0	197813	67	114	32
1	136421	60	127	25
1	216092	59	86	42
1	73566	32	22	23
0	213998	70	67	42
1	181728	50	77	38
0	148758	51	105	34
0	308343	71	121	39
1	251437	78	88	32
0	202388	102	78	37
0	173286	56	122	34
0	155529	58	66	33
0	132672	41	58	25
1	390163	102	134	45
0	145905	66	30	26
0	228012	88	103	40
1	80953	25	49	8
0	130805	47	26	27
1	135163	49	67	32
1	333790	168	59	37
1	271806	95	95	50
1	164235	99	156	41
1	234092	80	74	37
0	207158	69	137	38
0	156583	57	37	28
0	242395	68	111	36
1	261601	70	58	32
1	178489	35	78	32
0	204221	44	88	33
1	268066	69	152	35
1	327622	133	130	58
1	361799	101	145	27
0	247131	107	108	45
1	265849	58	138	37
0	162336	162	62	32
1	43287	14	13	19
0	172244	68	89	22
0	189021	121	86	35
0	227681	43	116	36
0	269329	81	157	36
0	106503	56	28	23
1	117891	77	83	40
1	287201	59	72	40
0	266805	78	134	42
0	23623	11	12	1
1	174954	69	120	36
0	61857	25	23	11
1	144889	43	83	40
1	347988	103	126	34
0	21054	16	4	0
1	224051	46	71	27
1	31414	19	18	8
1	278660	107	98	35
0	209481	58	68	44
0	156870	75	44	40
1	112933	46	29	28
0	38214	34	16	8
0	166011	35	61	36
1	316044	73	117	47
1	181578	56	46	48
1	358903	72	129	45
1	275578	91	139	48
1	368796	106	136	49
1	172464	31	66	35
1	94381	35	42	32
1	250563	290	75	36
1	382499	154	97	42
1	118010	42	49	35
1	365575	122	127	42
1	147989	72	55	34
1	231681	46	101	41
0	193119	77	80	36
0	189020	108	29	32
0	341958	106	95	33
1	222060	79	120	35
0	173260	63	41	21
0	274787	91	128	42
1	130908	52	142	49
0	204009	75	88	33
0	262412	94	170	39
0	1	0	0	0
0	14688	10	4	0
0	98	1	0	0
0	455	2	0	0
1	0	0	0	0
0	0	0	0	0
1	195765	75	56	33
0	334258	129	121	47
0	0	0	0	0
0	203	4	0	0
0	7199	5	7	0
1	46660	20	12	5
1	17547	5	0	1
0	107465	38	37	38
1	969	2	0	0
1	179994	58	47	28




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197883&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197883&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197883&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' @ jenkins.wessa.net







Correlations for all pairs of data series (method=pearson)
GeslachtTime_in_RFCLoginsBlogged_computationsReviewed_compendiums
Geslacht10.1380.1010.1490.203
Time_in_RFC0.13810.7070.7980.749
Logins0.1010.70710.5380.583
Blogged_computations0.1490.7980.53810.734
Reviewed_compendiums0.2030.7490.5830.7341

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Geslacht & Time_in_RFC & Logins & Blogged_computations & Reviewed_compendiums \tabularnewline
Geslacht & 1 & 0.138 & 0.101 & 0.149 & 0.203 \tabularnewline
Time_in_RFC & 0.138 & 1 & 0.707 & 0.798 & 0.749 \tabularnewline
Logins & 0.101 & 0.707 & 1 & 0.538 & 0.583 \tabularnewline
Blogged_computations & 0.149 & 0.798 & 0.538 & 1 & 0.734 \tabularnewline
Reviewed_compendiums & 0.203 & 0.749 & 0.583 & 0.734 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197883&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Geslacht[/C][C]Time_in_RFC[/C][C]Logins[/C][C]Blogged_computations[/C][C]Reviewed_compendiums[/C][/ROW]
[ROW][C]Geslacht[/C][C]1[/C][C]0.138[/C][C]0.101[/C][C]0.149[/C][C]0.203[/C][/ROW]
[ROW][C]Time_in_RFC[/C][C]0.138[/C][C]1[/C][C]0.707[/C][C]0.798[/C][C]0.749[/C][/ROW]
[ROW][C]Logins[/C][C]0.101[/C][C]0.707[/C][C]1[/C][C]0.538[/C][C]0.583[/C][/ROW]
[ROW][C]Blogged_computations[/C][C]0.149[/C][C]0.798[/C][C]0.538[/C][C]1[/C][C]0.734[/C][/ROW]
[ROW][C]Reviewed_compendiums[/C][C]0.203[/C][C]0.749[/C][C]0.583[/C][C]0.734[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197883&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197883&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)
GeslachtTime_in_RFCLoginsBlogged_computationsReviewed_compendiums
Geslacht10.1380.1010.1490.203
Time_in_RFC0.13810.7070.7980.749
Logins0.1010.70710.5380.583
Blogged_computations0.1490.7980.53810.734
Reviewed_compendiums0.2030.7490.5830.7341







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Geslacht;Time_in_RFC0.1380.13090.1072
p-value(0.078)(0.0949)(0.0948)
Geslacht;Logins0.10060.10020.0825
p-value(0.1998)(0.2017)(0.2007)
Geslacht;Blogged_computations0.14910.13190.1085
p-value(0.0568)(0.0922)(0.0922)
Geslacht;Reviewed_compendiums0.20320.17510.146
p-value(0.0091)(0.0249)(0.0254)
Time_in_RFC;Logins0.70740.7820.6071
p-value(0)(0)(0)
Time_in_RFC;Blogged_computations0.79830.77980.6095
p-value(0)(0)(0)
Time_in_RFC;Reviewed_compendiums0.74890.65630.5015
p-value(0)(0)(0)
Logins;Blogged_computations0.53830.64650.4777
p-value(0)(0)(0)
Logins;Reviewed_compendiums0.58340.59990.4467
p-value(0)(0)(0)
Blogged_computations;Reviewed_compendiums0.73360.64990.4945
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
Geslacht;Time_in_RFC & 0.138 & 0.1309 & 0.1072 \tabularnewline
p-value & (0.078) & (0.0949) & (0.0948) \tabularnewline
Geslacht;Logins & 0.1006 & 0.1002 & 0.0825 \tabularnewline
p-value & (0.1998) & (0.2017) & (0.2007) \tabularnewline
Geslacht;Blogged_computations & 0.1491 & 0.1319 & 0.1085 \tabularnewline
p-value & (0.0568) & (0.0922) & (0.0922) \tabularnewline
Geslacht;Reviewed_compendiums & 0.2032 & 0.1751 & 0.146 \tabularnewline
p-value & (0.0091) & (0.0249) & (0.0254) \tabularnewline
Time_in_RFC;Logins & 0.7074 & 0.782 & 0.6071 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time_in_RFC;Blogged_computations & 0.7983 & 0.7798 & 0.6095 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time_in_RFC;Reviewed_compendiums & 0.7489 & 0.6563 & 0.5015 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Logins;Blogged_computations & 0.5383 & 0.6465 & 0.4777 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Logins;Reviewed_compendiums & 0.5834 & 0.5999 & 0.4467 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Blogged_computations;Reviewed_compendiums & 0.7336 & 0.6499 & 0.4945 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197883&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]Geslacht;Time_in_RFC[/C][C]0.138[/C][C]0.1309[/C][C]0.1072[/C][/ROW]
[ROW][C]p-value[/C][C](0.078)[/C][C](0.0949)[/C][C](0.0948)[/C][/ROW]
[ROW][C]Geslacht;Logins[/C][C]0.1006[/C][C]0.1002[/C][C]0.0825[/C][/ROW]
[ROW][C]p-value[/C][C](0.1998)[/C][C](0.2017)[/C][C](0.2007)[/C][/ROW]
[ROW][C]Geslacht;Blogged_computations[/C][C]0.1491[/C][C]0.1319[/C][C]0.1085[/C][/ROW]
[ROW][C]p-value[/C][C](0.0568)[/C][C](0.0922)[/C][C](0.0922)[/C][/ROW]
[ROW][C]Geslacht;Reviewed_compendiums[/C][C]0.2032[/C][C]0.1751[/C][C]0.146[/C][/ROW]
[ROW][C]p-value[/C][C](0.0091)[/C][C](0.0249)[/C][C](0.0254)[/C][/ROW]
[ROW][C]Time_in_RFC;Logins[/C][C]0.7074[/C][C]0.782[/C][C]0.6071[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time_in_RFC;Blogged_computations[/C][C]0.7983[/C][C]0.7798[/C][C]0.6095[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time_in_RFC;Reviewed_compendiums[/C][C]0.7489[/C][C]0.6563[/C][C]0.5015[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;Blogged_computations[/C][C]0.5383[/C][C]0.6465[/C][C]0.4777[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;Reviewed_compendiums[/C][C]0.5834[/C][C]0.5999[/C][C]0.4467[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Blogged_computations;Reviewed_compendiums[/C][C]0.7336[/C][C]0.6499[/C][C]0.4945[/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=197883&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197883&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
Geslacht;Time_in_RFC0.1380.13090.1072
p-value(0.078)(0.0949)(0.0948)
Geslacht;Logins0.10060.10020.0825
p-value(0.1998)(0.2017)(0.2007)
Geslacht;Blogged_computations0.14910.13190.1085
p-value(0.0568)(0.0922)(0.0922)
Geslacht;Reviewed_compendiums0.20320.17510.146
p-value(0.0091)(0.0249)(0.0254)
Time_in_RFC;Logins0.70740.7820.6071
p-value(0)(0)(0)
Time_in_RFC;Blogged_computations0.79830.77980.6095
p-value(0)(0)(0)
Time_in_RFC;Reviewed_compendiums0.74890.65630.5015
p-value(0)(0)(0)
Logins;Blogged_computations0.53830.64650.4777
p-value(0)(0)(0)
Logins;Reviewed_compendiums0.58340.59990.4467
p-value(0)(0)(0)
Blogged_computations;Reviewed_compendiums0.73360.64990.4945
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')