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Description of Statistical Computation

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 computationWed, 20 Dec 2017 21:59:37 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/20/t15138043490wiz86moay9qnkp.htm/, Retrieved Tue, 14 May 2024 07:30:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=310579, Retrieved Tue, 14 May 2024 07:30:07 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact91

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-       [Kendall tau Correlation Matrix] [] [2017-12-20 20:59:37] [ddc578dfab8fb8809d20d480c2453c83] [Current]
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Dataset

Dataseries X:
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Histogram
Boxplots 
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10	5	6
13	3	9
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12	5	10
13	6	9
19	7	15
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10	3	9
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12	5	9
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19	7	19
14	8	10
16	6	12
15	5	9
15	8	11
19	7	17
12	5	9
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19	10	17
18	6	13
13	4	11
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14	5	7
20	7	17
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16	7	10
8	2	10
15	7	8
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19	5	18
17	8	14
20	6	16
15	7	11
19	10	16
21	8	17
23	10	20
16	9	14
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23	10	17
11	4	11
12	6	13
19	9	11
9	4	8
12	6	9
14	7	9
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15	4	10
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21	7	16
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12	2	10
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19	8	13
16	7	14
24	10	18
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13	5	10
12	4	9
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17	5	11
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17	5	14
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25	10	20
16	6	14
14	6	9
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20	8	15
16	7	14
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20	9	15
22	10	14
15	6	12
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6	3	6
16	9	11
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15	6	12
10	5	12
11	4	8
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12	6	8
15	6	12
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19	7	15
20	6	20
17	10	10
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19	8	14
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19	7	16
16	7	9
22	9	16
23	9	19
17	8	13
18	6	15
19	8	14
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12	2	11
17	6	14
19	8	15
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18	7	16
18	8	13
18	6	15
20	10	14
23	10	15
23	10	14
19	8	12
21	8	12
19	7	15
23	10	17
17	5	13
11	3	5
14	2	7
10	3	10
12	4	15
14	2	9
14	6	9
21	8	15
18	8	14
16	5	11
23	10	18
25	9	20
25	8	20
21	9	16
17	8	15
17	5	14
22	7	13
25	9	18
21	8	14
18	4	12
15	7	9
20	8	19
17	7	13
18	7	12
20	9	14
15	6	6
17	7	14
16	4	11
14	6	11
22	10	14
20	9	12
25	10	19
19	8	13
17	4	14
21	8	17
18	5	12
20	8	16
22	9	15
18	8	15
15	4	15
18	8	16
22	10	15
15	6	12
16	7	13
23	10	14
23	9	17
20	8	14
13	3	14
18	8	14
18	7	15
18	7	11
15	8	11
18	8	16
20	7	12
19	7	12
25	9	19
22	9	18
20	9	16
15	4	16
15	6	13
16	6	11
13	6	10
20	8	14
15	3	14
21	8	14
21	8	16
14	6	10
21	10	16
11	2	7
20	9	16
17	6	15
22	6	17
14	5	11
14	4	11
14	7	10
15	5	13
19	8	14
21	6	13
20	9	13
17	6	12
13	4	10
17	7	15
12	2	6
19	8	15
17	9	15
17	6	11
17	5	14
20	7	14
18	8	16
15	4	12
21	9	15
23	9	20
19	9	12
15	7	9
14	5	13
22	7	15
24	9	19
19	8	11
15	6	11
22	9	17
20	8	15
20	7	14
17	7	15
21	7	11
17	8	12
23	10	15
20	6	16
19	6	16

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310579&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=310579&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310579&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Correlations for all pairs of data series (method=pearson)
TevredenheidIntention_to_UsePerceived_Ease_of_Use
Tevredenheid10.7310.761
Intention_to_Use0.73110.55
Perceived_Ease_of_Use0.7610.551

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Tevredenheid & Intention_to_Use & Perceived_Ease_of_Use \tabularnewline
Tevredenheid & 1 & 0.731 & 0.761 \tabularnewline
Intention_to_Use & 0.731 & 1 & 0.55 \tabularnewline
Perceived_Ease_of_Use & 0.761 & 0.55 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310579&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Tevredenheid[/C][C]Intention_to_Use[/C][C]Perceived_Ease_of_Use[/C][/ROW]
[ROW][C]Tevredenheid[/C][C]1[/C][C]0.731[/C][C]0.761[/C][/ROW]
[ROW][C]Intention_to_Use[/C][C]0.731[/C][C]1[/C][C]0.55[/C][/ROW]
[ROW][C]Perceived_Ease_of_Use[/C][C]0.761[/C][C]0.55[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310579&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310579&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Correlations for all pairs of data series (method=pearson)
TevredenheidIntention_to_UsePerceived_Ease_of_Use
Tevredenheid10.7310.761
Intention_to_Use0.73110.55
Perceived_Ease_of_Use0.7610.551






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Tevredenheid;Intention_to_Use0.7310.69960.5705
p-value(0)(0)(0)
Tevredenheid;Perceived_Ease_of_Use0.76110.72090.5824
p-value(0)(0)(0)
Intention_to_Use;Perceived_Ease_of_Use0.55040.51850.405
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
Tevredenheid;Intention_to_Use & 0.731 & 0.6996 & 0.5705 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Tevredenheid;Perceived_Ease_of_Use & 0.7611 & 0.7209 & 0.5824 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Intention_to_Use;Perceived_Ease_of_Use & 0.5504 & 0.5185 & 0.405 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310579&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]Tevredenheid;Intention_to_Use[/C][C]0.731[/C][C]0.6996[/C][C]0.5705[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Tevredenheid;Perceived_Ease_of_Use[/C][C]0.7611[/C][C]0.7209[/C][C]0.5824[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Intention_to_Use;Perceived_Ease_of_Use[/C][C]0.5504[/C][C]0.5185[/C][C]0.405[/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=310579&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310579&T=2

As an alternative you can also use a QR Code:  
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
Tevredenheid;Intention_to_Use0.7310.69960.5705
p-value(0)(0)(0)
Tevredenheid;Perceived_Ease_of_Use0.76110.72090.5824
p-value(0)(0)(0)
Intention_to_Use;Perceived_Ease_of_Use0.55040.51850.405
p-value(0)(0)(0)






Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.01111
0.02111
0.03111
0.04111
0.05111
0.06111
0.07111
0.08111
0.09111
0.1111

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Correlation Tests \tabularnewline
Number of significant by total number of Correlations \tabularnewline
Type I error & Pearson r & Spearman rho & Kendall tau \tabularnewline
0.01 & 1 & 1 & 1 \tabularnewline
0.02 & 1 & 1 & 1 \tabularnewline
0.03 & 1 & 1 & 1 \tabularnewline
0.04 & 1 & 1 & 1 \tabularnewline
0.05 & 1 & 1 & 1 \tabularnewline
0.06 & 1 & 1 & 1 \tabularnewline
0.07 & 1 & 1 & 1 \tabularnewline
0.08 & 1 & 1 & 1 \tabularnewline
0.09 & 1 & 1 & 1 \tabularnewline
0.1 & 1 & 1 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310579&T=3

[TABLE]
[ROW][C]Meta Analysis of Correlation Tests[/C][/ROW]
[ROW][C]Number of significant by total number of Correlations[/C][/ROW]
[ROW][C]Type I error[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]0.01[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.02[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.03[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.04[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.05[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.06[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.07[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.08[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.09[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.1[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310579&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310579&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.01111
0.02111
0.03111
0.04111
0.05111
0.06111
0.07111
0.08111
0.09111
0.1111


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par4 = 0 ; par5 = 0 ; par6 = 12 ;
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$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
x <- na.omit(x)
y <- t(na.omit(t(y)))
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
print(n)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$estimate,3))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
ncorrs <- (n*n -n)/2
mycorrs <- array(0, dim=c(10,3))
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)
for (iii in 1:10) {
iiid100 <- iii / 100
if (rp$p.value < iiid100) mycorrs[iii, 1] = mycorrs[iii, 1] + 1
if (rs$p.value < iiid100) mycorrs[iii, 2] = mycorrs[iii, 2] + 1
if (rk$p.value < iiid100) mycorrs[iii, 3] = mycorrs[iii, 3] + 1
}
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Correlation Tests',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of significant by total number of Correlations',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Type I error',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)
for (iii in 1:10) {
iiid100 <- iii / 100
a<-table.row.start(a)
a<-table.element(a,round(iiid100,2),header=T)
a<-table.element(a,round(mycorrs[iii,1]/ncorrs,2))
a<-table.element(a,round(mycorrs[iii,2]/ncorrs,2))
a<-table.element(a,round(mycorrs[iii,3]/ncorrs,2))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')