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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 10:03:04 -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/t1324566229krb8kn17wzf3nqx.htm/, Retrieved Fri, 03 May 2024 11:30:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=159556, Retrieved Fri, 03 May 2024 11:30:48 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact106
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] [] [2011-12-15 18:41:33] [145a13cc95845961a3828fae7139a7eb]
- R         [Kendall tau Correlation Matrix] [] [2011-12-22 15:03:04] [5a15ab6cc81a4d08ac9d21b238bcb336] [Current]
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Dataseries X:
0	129988	81	20	18
0	130358	46	38	17
0	7215	18	0	0
1	112914	86	49	22
1	219904	126	76	30
1	402036	218	104	31
1	117604	50	37	19
0	131822	50	57	25
1	99729	38	42	30
1	256310	86	62	26
1	113066	69	50	20
1	165392	62	66	30
0	78240	90	38	15
0	152673	84	48	22
0	134368	47	42	17
0	125769	67	47	19
0	123467	50	71	28
1	56232	47	0	12
1	108458	79	50	28
0	22762	21	12	13
0	48633	50	16	14
0	182081	83	77	27
1	140857	59	29	25
0	93773	46	38	30
0	133398	78	50	21
0	113933	23	33	17
0	153851	139	49	22
1	140711	75	59	28
0	303844	105	55	26
1	163810	38	42	17
1	123344	40	40	23
0	157640	39	51	20
1	103274	90	45	16
0	193500	105	73	20
0	178768	43	51	21
0	0	1	0	0
1	181412	55	46	27
1	92342	47	44	14
1	100023	41	31	29
1	178277	50	71	31
1	145067	58	61	19
1	114146	50	28	30
0	86039	25	21	23
1	125481	66	42	21
1	95535	42	44	22
1	129221	78	40	21
0	61554	26	15	32
0	168048	82	46	20
1	159121	75	43	26
0	129362	51	47	25
1	48188	28	12	22
0	95461	56	46	19
0	229864	64	56	24
0	191094	68	47	26
1	161082	51	50	27
0	111388	47	35	10
1	172614	58	45	26
1	63205	18	25	23
1	109102	56	47	21
1	137303	74	28	34
1	125304	50	48	29
1	88620	65	32	19
0	95808	48	28	19
1	83419	29	31	23
0	101723	25	13	22
0	94982	37	38	29
0	143566	61	48	31
1	113325	63	68	21
0	81518	32	32	21
1	31970	15	5	21
1	192268	102	53	15
1	91261	55	33	9
0	80820	56	54	23
1	85829	59	37	18
1	116322	53	52	31
1	56544	32	0	25
0	118838	52	52	25
1	118781	80	51	22
1	60138	23	16	21
0	73422	66	33	26
0	67751	58	48	22
1	225857	54	35	26
1	51185	24	24	20
0	97181	32	37	25
0	45100	39	17	19
1	115801	43	32	22
1	186310	190	55	25
0	71960	86	39	22
0	80105	48	31	21
0	107728	42	26	21
1	98707	33	37	23
1	136234	67	66	22
0	136781	52	35	21
1	105863	52	24	12
1	49164	33	22	13
0	189493	93	42	32
0	169406	50	86	24
0	19349	12	13	1
1	160819	87	21	24
0	109510	53	32	25
0	43803	25	8	4
1	47062	19	38	15
1	110845	44	45	21
0	92517	52	24	23
1	58660	36	23	12
1	27676	22	2	16
1	98550	32	52	24
0	43646	24	5	9
0	0	0	0	0
0	75566	28	43	25
0	57359	48	18	17
1	104330	36	44	18
1	70369	47	45	21
0	65494	56	29	17
0	3616	5	0	0
1	0	0	0	0
1	143931	37	32	20
1	117946	66	65	26
0	137332	85	26	27
0	84336	33	24	20
1	43410	19	7	1
0	137585	60	62	25
1	79015	34	30	14
1	101354	46	49	27
1	57586	38	3	12
1	19764	12	10	2
1	105757	42	42	16
0	103651	25	23	23
0	113402	35	40	28
0	11796	9	1	2
0	7627	9	0	0
1	121085	49	29	17
1	6836	3	0	1
0	139563	46	46	17
0	5118	3	5	0
1	40248	16	8	4
0	0	0	0	0
1	95079	42	21	25
0	80763	32	21	26
1	7131	4	0	0
1	4194	11	0	0
0	60378	20	15	15
1	109173	44	47	20
1	83484	16	17	19




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=159556&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=159556&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159556&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=pearson)
GeslachtTime_in_RFCLoginsBlogged_computationsReviewed_compendiums
Geslacht10.0720.0690.070.073
Time_in_RFC0.07210.7730.7930.656
Logins0.0690.77310.6840.517
Blogged_computations0.070.7930.68410.655
Reviewed_compendiums0.0730.6560.5170.6551

\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 & 0.072 & 0.069 & 0.07 & 0.073 \tabularnewline
Time_in_RFC & 0.072 & 1 & 0.773 & 0.793 & 0.656 \tabularnewline
Logins & 0.069 & 0.773 & 1 & 0.684 & 0.517 \tabularnewline
Blogged_computations & 0.07 & 0.793 & 0.684 & 1 & 0.655 \tabularnewline
Reviewed_compendiums & 0.073 & 0.656 & 0.517 & 0.655 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159556&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]0.072[/C][C]0.069[/C][C]0.07[/C][C]0.073[/C][/ROW]
[ROW][C]Time_in_RFC[/C][C]0.072[/C][C]1[/C][C]0.773[/C][C]0.793[/C][C]0.656[/C][/ROW]
[ROW][C]Logins[/C][C]0.069[/C][C]0.773[/C][C]1[/C][C]0.684[/C][C]0.517[/C][/ROW]
[ROW][C]Blogged_computations[/C][C]0.07[/C][C]0.793[/C][C]0.684[/C][C]1[/C][C]0.655[/C][/ROW]
[ROW][C]Reviewed_compendiums[/C][C]0.073[/C][C]0.656[/C][C]0.517[/C][C]0.655[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159556&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159556&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
Geslacht10.0720.0690.070.073
Time_in_RFC0.07210.7730.7930.656
Logins0.0690.77310.6840.517
Blogged_computations0.070.7930.68410.655
Reviewed_compendiums0.0730.6560.5170.6551







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Geslacht;Time_in_RFC0.07150.05540.0454
p-value(0.3941)(0.5097)(0.5078)
Geslacht;Logins0.06930.03730.0308
p-value(0.4092)(0.657)(0.6554)
Geslacht;Blogged_computations0.06990.06650.055
p-value(0.4049)(0.4287)(0.4268)
Geslacht;Reviewed_compendiums0.07290.0530.0443
p-value(0.3851)(0.5284)(0.5265)
Time_in_RFC;Logins0.77270.74240.5728
p-value(0)(0)(0)
Time_in_RFC;Blogged_computations0.79310.77510.5991
p-value(0)(0)(0)
Time_in_RFC;Reviewed_compendiums0.65550.59280.439
p-value(0)(0)(0)
Logins;Blogged_computations0.68430.70580.5316
p-value(0)(0)(0)
Logins;Reviewed_compendiums0.51730.47810.3478
p-value(0)(0)(0)
Blogged_computations;Reviewed_compendiums0.65520.55930.4185
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 & 0.0715 & 0.0554 & 0.0454 \tabularnewline
p-value & (0.3941) & (0.5097) & (0.5078) \tabularnewline
Geslacht;Logins & 0.0693 & 0.0373 & 0.0308 \tabularnewline
p-value & (0.4092) & (0.657) & (0.6554) \tabularnewline
Geslacht;Blogged_computations & 0.0699 & 0.0665 & 0.055 \tabularnewline
p-value & (0.4049) & (0.4287) & (0.4268) \tabularnewline
Geslacht;Reviewed_compendiums & 0.0729 & 0.053 & 0.0443 \tabularnewline
p-value & (0.3851) & (0.5284) & (0.5265) \tabularnewline
Time_in_RFC;Logins & 0.7727 & 0.7424 & 0.5728 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time_in_RFC;Blogged_computations & 0.7931 & 0.7751 & 0.5991 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time_in_RFC;Reviewed_compendiums & 0.6555 & 0.5928 & 0.439 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Logins;Blogged_computations & 0.6843 & 0.7058 & 0.5316 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Logins;Reviewed_compendiums & 0.5173 & 0.4781 & 0.3478 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Blogged_computations;Reviewed_compendiums & 0.6552 & 0.5593 & 0.4185 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159556&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]0.0715[/C][C]0.0554[/C][C]0.0454[/C][/ROW]
[ROW][C]p-value[/C][C](0.3941)[/C][C](0.5097)[/C][C](0.5078)[/C][/ROW]
[ROW][C]Geslacht;Logins[/C][C]0.0693[/C][C]0.0373[/C][C]0.0308[/C][/ROW]
[ROW][C]p-value[/C][C](0.4092)[/C][C](0.657)[/C][C](0.6554)[/C][/ROW]
[ROW][C]Geslacht;Blogged_computations[/C][C]0.0699[/C][C]0.0665[/C][C]0.055[/C][/ROW]
[ROW][C]p-value[/C][C](0.4049)[/C][C](0.4287)[/C][C](0.4268)[/C][/ROW]
[ROW][C]Geslacht;Reviewed_compendiums[/C][C]0.0729[/C][C]0.053[/C][C]0.0443[/C][/ROW]
[ROW][C]p-value[/C][C](0.3851)[/C][C](0.5284)[/C][C](0.5265)[/C][/ROW]
[ROW][C]Time_in_RFC;Logins[/C][C]0.7727[/C][C]0.7424[/C][C]0.5728[/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]0.7931[/C][C]0.7751[/C][C]0.5991[/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]0.6555[/C][C]0.5928[/C][C]0.439[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;Blogged_computations[/C][C]0.6843[/C][C]0.7058[/C][C]0.5316[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;Reviewed_compendiums[/C][C]0.5173[/C][C]0.4781[/C][C]0.3478[/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]0.6552[/C][C]0.5593[/C][C]0.4185[/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=159556&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159556&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_RFC0.07150.05540.0454
p-value(0.3941)(0.5097)(0.5078)
Geslacht;Logins0.06930.03730.0308
p-value(0.4092)(0.657)(0.6554)
Geslacht;Blogged_computations0.06990.06650.055
p-value(0.4049)(0.4287)(0.4268)
Geslacht;Reviewed_compendiums0.07290.0530.0443
p-value(0.3851)(0.5284)(0.5265)
Time_in_RFC;Logins0.77270.74240.5728
p-value(0)(0)(0)
Time_in_RFC;Blogged_computations0.79310.77510.5991
p-value(0)(0)(0)
Time_in_RFC;Reviewed_compendiums0.65550.59280.439
p-value(0)(0)(0)
Logins;Blogged_computations0.68430.70580.5316
p-value(0)(0)(0)
Logins;Reviewed_compendiums0.51730.47810.3478
p-value(0)(0)(0)
Blogged_computations;Reviewed_compendiums0.65520.55930.4185
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')