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Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationFri, 16 Dec 2011 14:57:59 -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/16/t1324065852w1726i1mtujym0t.htm/, Retrieved Sun, 05 May 2024 12:51:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=156127, Retrieved Sun, 05 May 2024 12:51:44 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Survey Scores] [Intrinsic Motivat...] [2010-10-12 11:18:40] [b98453cac15ba1066b407e146608df68]
- R PD  [Survey Scores] [] [2011-10-18 18:34:00] [77e355412ccdb651b3c7eae41c3da865]
- RMPD    [Kendall tau Correlation Matrix] [] [2011-12-16 19:42:01] [77e355412ccdb651b3c7eae41c3da865]
-    D        [Kendall tau Correlation Matrix] [] [2011-12-16 19:57:59] [2be7aedefc35278abdba659ba29c8de8] [Current]
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Dataseries X:
35.323	26	21	21
35.478	20	16	15
4.39	19	19	18
41.667	19	18	11
22.173	20	16	8
28.021	25	23	19
18.109	25	17	4
13.962	22	12	20
40.174	26	19	16
16.065	22	16	14
18.145	17	19	10
18.439	22	20	13
10.603	19	13	14
34.811	24	20	8
69.064	26	27	23
51.202	21	17	11
14.786	13	8	9
33.01	26	25	24
81.101	20	26	5
89.232	22	13	15
21.223	14	19	5
15.173	21	15	19
241.66	7	5	6
26.848	23	16	13
8.752	17	14	11
60.535	25	24	17
60.535	25	24	17
26.052	19	9	5
49.218	20	19	9
30.669	23	19	15
18.673	22	25	17
86	22	19	17
10.632	21	18	20
35.802	15	15	12
33.974	20	12	7
36.972	22	21	16
4.928	18	12	7
53.976	20	15	14
15.467	28	28	24
35.723	22	25	15
40.424	18	19	15
9.706	23	20	10
26.532	20	24	14
23.843	25	26	18
18.062	26	25	12
35.681	15	12	9
68.125	17	12	9
23.937	23	15	8
31.479	21	17	18
66.659	13	14	10
250.234	18	16	17
49.469	19	11	14
42.951	22	20	16
43.402	16	11	10
24.112	24	22	19
56.95	18	20	10
17.313	20	19	14
25.658	24	17	10
48.172	14	21	4
13.891	22	23	19
32.048	24	18	9
19.797	18	17	12
31.317	21	27	16
20.966	23	25	11
22.708	17	19	18
26.81	22	22	11
52.004	24	24	24
32.354	21	20	17
27.128	22	19	18
26.529	16	11	9
28.392	21	22	19
57.393	23	22	18
194.731	22	16	12
9.415	24	20	23
91.076	24	24	22
57.751	16	16	14
8.236	16	16	14
20.407	21	22	16
13.681	26	24	23
79.659	15	16	7
53.48	25	27	10
6.906	18	11	12
50.202	23	21	12
37.877	20	20	12
85.903	17	20	17
35.351	25	27	21
283.801	24	20	16
5.974	17	12	11
3.441	19	8	14
51.987	20	21	13
13.22	15	18	9
1.455	27	24	19
18.187	22	16	13
21.29	23	18	19
5.686	16	20	13
4.944	19	20	13
32.789	25	19	13
50.494	19	17	14
35.162	19	16	12
38.095	26	26	22
19.172	21	15	11
24.5	20	22	5
20.573	24	17	18
42.042	22	23	19
302.912	20	21	14
25.027	18	19	15
16.488	18	14	12
32.36	24	17	19
6.193	24	12	15
37.7	22	24	17
6.343	23	18	8
23.025	22	20	10
48.578	20	16	12
21.564	18	20	12
33.697	25	22	20
10.831	18	12	12
19.172	16	16	12
21.075	20	17	14
33.189	19	22	6
60.5	15	12	10
33.686	19	14	18
40.838	19	23	18
13.491	16	15	7
106.637	17	17	18
35.897	28	28	9
7.314	23	20	17
49.094	25	23	22
14.667	20	13	11
54.179	17	18	15
145.846	23	23	17
18.56	16	19	15
23.525	23	23	22
21.804	11	12	9
26.301	18	16	13
41.33	24	23	20
10.5	23	13	14
13.338	21	22	14
60.31	16	18	12
34.256	24	23	20
48.267	23	20	20
41.559	18	10	8
32.45	20	17	17
10.951	9	18	9
22.561	24	15	18
57.095	25	23	22
19.105	20	17	10
13.151	21	17	13
27.426	25	22	15
15.355	22	20	18
13.82	21	20	18
47.21	21	19	12
110.349	22	18	12
34.985	27	22	20
27.257	24	20	12
23.556	24	22	16
50.108	21	18	16
18.158	18	16	18
87.357	16	16	16
18.187	22	16	13
28.33	20	16	17
13.474	18	17	13
26.244	20	18	17




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156127&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156127&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156127&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'Gertrude Mary Cox' @ cox.wessa.net







Correlations for all pairs of data series (method=kendall)
First_ClickI1I2I3
First_Click10.0290.1220.041
I10.02910.4420.385
I20.1220.44210.333
I30.0410.3850.3331

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & First_Click & I1 & I2 & I3 \tabularnewline
First_Click & 1 & 0.029 & 0.122 & 0.041 \tabularnewline
I1 & 0.029 & 1 & 0.442 & 0.385 \tabularnewline
I2 & 0.122 & 0.442 & 1 & 0.333 \tabularnewline
I3 & 0.041 & 0.385 & 0.333 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156127&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]First_Click[/C][C]I1[/C][C]I2[/C][C]I3[/C][/ROW]
[ROW][C]First_Click[/C][C]1[/C][C]0.029[/C][C]0.122[/C][C]0.041[/C][/ROW]
[ROW][C]I1[/C][C]0.029[/C][C]1[/C][C]0.442[/C][C]0.385[/C][/ROW]
[ROW][C]I2[/C][C]0.122[/C][C]0.442[/C][C]1[/C][C]0.333[/C][/ROW]
[ROW][C]I3[/C][C]0.041[/C][C]0.385[/C][C]0.333[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156127&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156127&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)
First_ClickI1I2I3
First_Click10.0290.1220.041
I10.02910.4420.385
I20.1220.44210.333
I30.0410.3850.3331







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
First_Click;I1-0.09270.03680.0287
p-value(0.2408)(0.6421)(0.6006)
First_Click;I2-0.0080.16820.1216
p-value(0.9195)(0.0324)(0.0259)
First_Click;I30.00360.05830.0408
p-value(0.9641)(0.4614)(0.4537)
I1;I20.59920.58520.4418
p-value(0)(0)(0)
I1;I30.52070.50180.3854
p-value(0)(0)(0)
I2;I30.44520.440.3331
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
First_Click;I1 & -0.0927 & 0.0368 & 0.0287 \tabularnewline
p-value & (0.2408) & (0.6421) & (0.6006) \tabularnewline
First_Click;I2 & -0.008 & 0.1682 & 0.1216 \tabularnewline
p-value & (0.9195) & (0.0324) & (0.0259) \tabularnewline
First_Click;I3 & 0.0036 & 0.0583 & 0.0408 \tabularnewline
p-value & (0.9641) & (0.4614) & (0.4537) \tabularnewline
I1;I2 & 0.5992 & 0.5852 & 0.4418 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
I1;I3 & 0.5207 & 0.5018 & 0.3854 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
I2;I3 & 0.4452 & 0.44 & 0.3331 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156127&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]First_Click;I1[/C][C]-0.0927[/C][C]0.0368[/C][C]0.0287[/C][/ROW]
[ROW][C]p-value[/C][C](0.2408)[/C][C](0.6421)[/C][C](0.6006)[/C][/ROW]
[ROW][C]First_Click;I2[/C][C]-0.008[/C][C]0.1682[/C][C]0.1216[/C][/ROW]
[ROW][C]p-value[/C][C](0.9195)[/C][C](0.0324)[/C][C](0.0259)[/C][/ROW]
[ROW][C]First_Click;I3[/C][C]0.0036[/C][C]0.0583[/C][C]0.0408[/C][/ROW]
[ROW][C]p-value[/C][C](0.9641)[/C][C](0.4614)[/C][C](0.4537)[/C][/ROW]
[ROW][C]I1;I2[/C][C]0.5992[/C][C]0.5852[/C][C]0.4418[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]I1;I3[/C][C]0.5207[/C][C]0.5018[/C][C]0.3854[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]I2;I3[/C][C]0.4452[/C][C]0.44[/C][C]0.3331[/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=156127&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156127&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
First_Click;I1-0.09270.03680.0287
p-value(0.2408)(0.6421)(0.6006)
First_Click;I2-0.0080.16820.1216
p-value(0.9195)(0.0324)(0.0259)
First_Click;I30.00360.05830.0408
p-value(0.9641)(0.4614)(0.4537)
I1;I20.59920.58520.4418
p-value(0)(0)(0)
I1;I30.52070.50180.3854
p-value(0)(0)(0)
I2;I30.44520.440.3331
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')