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Author

*The author of this computation has been verified*

R Software Module

Patrick.Wessarwasp_pairs.wasp

Title produced by software

Kendall tau Correlation Matrix

Date of computation

Sun, 12 Dec 2010 13:27:16 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/12/t1292160523lcy94u4sabpynwt.htm/, Retrieved Tue, 07 May 2024 11:39:35 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108434, Retrieved Tue, 07 May 2024 11:39:35 +0000

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User-defined keywords

Estimated Impact

129

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]
F   PD    [Kendall tau Correlation Matrix] [Ws 10 - Pearson C...] [2010-12-12 13:27:16] [0829c729852d8a4b1b0c41cf0848af95] [Current]
-    D      [Kendall tau Correlation Matrix] [PAPER - Pearson C...] [2010-12-19 17:13:40] [603e2f5305d3a2a4e062624458fa1155] 

Feedback Forum

2010-12-20 17:54:50 [00c625c7d009d84797af914265b614f9] [reply] 
Correct, 
De pearson correlation matrix gaat uit van normaliteit. We kunnen duidelijk zien aan de figuur dat deze assumptie niet voldaan is (daarom beter Kendall Tau matrix gebruiken). 
De prijs van water en de prijs van meel hebben de grootste invloed op de prijs van het brood. Ook de brood - tarwe correlatie is significant verschillend van 0 (P-value = 0.0033; dus de kans dat we ons vergissen bij het verwerpen van de nulhypothese is ook zeer klein) 

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Dataseries X:

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104,37	1	167.16	101,56	100,93
104,89	2	179.84	102,13	101,18
105,15	3	174.44	102,39	101,11
105,72	4	180.35	102,42	102,42
106,38	5	193.17	103,87	102,37
106,40	6	195.16	104,44	101,95
106,47	7	202.43	104,97	102,20
106,59	8	189.91	105,17	103,35
106,76	9	195.98	105,35	103,65
107,35	10	212.09	104,65	102,06
107,81	11	205.81	106,62	102,66
108,03	12	204.31	107,05	102,32
109,08	1	196.07	112,30	102,21
109,86	2	199.98	114,70	102,33
110,29	3	199.1	115,40	104,41
110,34	4	198.31	115,64	104,33
110,59	5	195.72	115,66	105,27
110,64	6	223.04	114,50	105,34
110,83	7	238.41	115,14	104,88
111,51	8	259.73	115,41	105,49
113,32	9	326.54	119,32	105,90
115,89	10	335.15	124,77	105,39
116,51	11	321.81	130,96	104,40
117,44	12	368.62	141,02	106,19
118,25	1	369.59	150,60	106,54
118,65	2	425	151,10	108,26
118,52	3	439.72	157,19	106,95
119,07	4	362.23	157,28	108,32
119,12	5	328.76	156,54	108,35
119,28	6	348.55	159,62	109,29
119,30	7	328.18	163,77	109,46
119,44	8	329.34	165,08	109,50
119,57	9	295.55	164,75	109,84
119,93	10	237.38	163,93	108,73
120,03	11	226.85	157,51	109,38
119,66	12	220.14	153,36	109,97
119,46	1	239.36	156,83	111,10
119,48	2	224.69	154,98	110,53
119,56	3	230.98	155,02	110,23
119,43	4	233.47	153,34	109,41
119,57	5	256.7	153,19	108,94
119,59	6	253.41	152,80	109,81
119,50	7	224.95	152,97	109,20
119,54	8	210.37	152,96	109,45
119,56	9	191.09	152,35	110,61
119,61	10	198.85	151,88	109,44
119,64	11	211.04	150,27	109,77
119,60	12	206.25	148,80	108,04
119,71	1	201.19	149,28	109,65
119,72	2	194.37	148,64	111,69
119,66	3	191.08	150,36	111,65
119,76	4	192.87	149,69	112,04
119,80	5	181.61	152,94	111,42
119,88	6	157.67	155,18	112,25
119,78	7	196.14	156,32	111,46
120,08	8	246.35	156,25	111,62
120,22	9	271.9 	155,52	111,77

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108434&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108434&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108434&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Correlations for all pairs of data series (method=pearson)
	Brood	Maand	Tarwe	Meel	Water
Brood	1	0.104	0.383	0.974	0.937
Maand	0.104	1	0.053	0.05	0.039
Tarwe	0.383	0.053	1	0.403	0.162
Meel	0.974	0.05	0.403	1	0.917
Water	0.937	0.039	0.162	0.917	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Brood & Maand & Tarwe & Meel & Water \tabularnewline
Brood & 1 & 0.104 & 0.383 & 0.974 & 0.937 \tabularnewline
Maand & 0.104 & 1 & 0.053 & 0.05 & 0.039 \tabularnewline
Tarwe & 0.383 & 0.053 & 1 & 0.403 & 0.162 \tabularnewline
Meel & 0.974 & 0.05 & 0.403 & 1 & 0.917 \tabularnewline
Water & 0.937 & 0.039 & 0.162 & 0.917 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108434&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Brood[/C][C]Maand[/C][C]Tarwe[/C][C]Meel[/C][C]Water[/C][/ROW]
[ROW][C]Brood[/C][C]1[/C][C]0.104[/C][C]0.383[/C][C]0.974[/C][C]0.937[/C][/ROW]
[ROW][C]Maand[/C][C]0.104[/C][C]1[/C][C]0.053[/C][C]0.05[/C][C]0.039[/C][/ROW]
[ROW][C]Tarwe[/C][C]0.383[/C][C]0.053[/C][C]1[/C][C]0.403[/C][C]0.162[/C][/ROW]
[ROW][C]Meel[/C][C]0.974[/C][C]0.05[/C][C]0.403[/C][C]1[/C][C]0.917[/C][/ROW]
[ROW][C]Water[/C][C]0.937[/C][C]0.039[/C][C]0.162[/C][C]0.917[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108434&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108434&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)
	Brood	Maand	Tarwe	Meel	Water
Brood	1	0.104	0.383	0.974	0.937
Maand	0.104	1	0.053	0.05	0.039
Tarwe	0.383	0.053	1	0.403	0.162
Meel	0.974	0.05	0.403	1	0.917
Water	0.937	0.039	0.162	0.917	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
Brood;Maand	0.1039	0.1766	0.1617
p-value	(0.4418)	(0.1889)	(0.0852)
Brood;Tarwe	0.3831	0.1971	0.1286
p-value	(0.0033)	(0.1417)	(0.1582)
Brood;Meel	0.9736	0.7739	0.614
p-value	(0)	(0)	(0)
Brood;Water	0.9369	0.9189	0.7796
p-value	(0)	(0)	(0)
Maand;Tarwe	0.0526	0.2048	0.1402
p-value	(0.6976)	(0.1264)	(0.1354)
Maand;Meel	0.0495	0.0968	0.0831
p-value	(0.7144)	(0.4737)	(0.3762)
Maand;Water	0.0391	0.0275	0.0286
p-value	(0.7728)	(0.8392)	(0.761)
Tarwe;Meel	0.4034	0.5545	0.4048
p-value	(0.0019)	(0)	(0)
Tarwe;Water	0.1617	0.1646	0.1115
p-value	(0.2295)	(0.2203)	(0.2205)
Meel;Water	0.9174	0.7696	0.589
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
Brood;Maand & 0.1039 & 0.1766 & 0.1617 \tabularnewline
p-value & (0.4418) & (0.1889) & (0.0852) \tabularnewline
Brood;Tarwe & 0.3831 & 0.1971 & 0.1286 \tabularnewline
p-value & (0.0033) & (0.1417) & (0.1582) \tabularnewline
Brood;Meel & 0.9736 & 0.7739 & 0.614 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Brood;Water & 0.9369 & 0.9189 & 0.7796 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Maand;Tarwe & 0.0526 & 0.2048 & 0.1402 \tabularnewline
p-value & (0.6976) & (0.1264) & (0.1354) \tabularnewline
Maand;Meel & 0.0495 & 0.0968 & 0.0831 \tabularnewline
p-value & (0.7144) & (0.4737) & (0.3762) \tabularnewline
Maand;Water & 0.0391 & 0.0275 & 0.0286 \tabularnewline
p-value & (0.7728) & (0.8392) & (0.761) \tabularnewline
Tarwe;Meel & 0.4034 & 0.5545 & 0.4048 \tabularnewline
p-value & (0.0019) & (0) & (0) \tabularnewline
Tarwe;Water & 0.1617 & 0.1646 & 0.1115 \tabularnewline
p-value & (0.2295) & (0.2203) & (0.2205) \tabularnewline
Meel;Water & 0.9174 & 0.7696 & 0.589 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108434&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]Brood;Maand[/C][C]0.1039[/C][C]0.1766[/C][C]0.1617[/C][/ROW]
[ROW][C]p-value[/C][C](0.4418)[/C][C](0.1889)[/C][C](0.0852)[/C][/ROW]
[ROW][C]Brood;Tarwe[/C][C]0.3831[/C][C]0.1971[/C][C]0.1286[/C][/ROW]
[ROW][C]p-value[/C][C](0.0033)[/C][C](0.1417)[/C][C](0.1582)[/C][/ROW]
[ROW][C]Brood;Meel[/C][C]0.9736[/C][C]0.7739[/C][C]0.614[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Brood;Water[/C][C]0.9369[/C][C]0.9189[/C][C]0.7796[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Maand;Tarwe[/C][C]0.0526[/C][C]0.2048[/C][C]0.1402[/C][/ROW]
[ROW][C]p-value[/C][C](0.6976)[/C][C](0.1264)[/C][C](0.1354)[/C][/ROW]
[ROW][C]Maand;Meel[/C][C]0.0495[/C][C]0.0968[/C][C]0.0831[/C][/ROW]
[ROW][C]p-value[/C][C](0.7144)[/C][C](0.4737)[/C][C](0.3762)[/C][/ROW]
[ROW][C]Maand;Water[/C][C]0.0391[/C][C]0.0275[/C][C]0.0286[/C][/ROW]
[ROW][C]p-value[/C][C](0.7728)[/C][C](0.8392)[/C][C](0.761)[/C][/ROW]
[ROW][C]Tarwe;Meel[/C][C]0.4034[/C][C]0.5545[/C][C]0.4048[/C][/ROW]
[ROW][C]p-value[/C][C](0.0019)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Tarwe;Water[/C][C]0.1617[/C][C]0.1646[/C][C]0.1115[/C][/ROW]
[ROW][C]p-value[/C][C](0.2295)[/C][C](0.2203)[/C][C](0.2205)[/C][/ROW]
[ROW][C]Meel;Water[/C][C]0.9174[/C][C]0.7696[/C][C]0.589[/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=108434&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108434&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
pair	Pearson r	Spearman rho	Kendall tau
Brood;Maand	0.1039	0.1766	0.1617
p-value	(0.4418)	(0.1889)	(0.0852)
Brood;Tarwe	0.3831	0.1971	0.1286
p-value	(0.0033)	(0.1417)	(0.1582)
Brood;Meel	0.9736	0.7739	0.614
p-value	(0)	(0)	(0)
Brood;Water	0.9369	0.9189	0.7796
p-value	(0)	(0)	(0)
Maand;Tarwe	0.0526	0.2048	0.1402
p-value	(0.6976)	(0.1264)	(0.1354)
Maand;Meel	0.0495	0.0968	0.0831
p-value	(0.7144)	(0.4737)	(0.3762)
Maand;Water	0.0391	0.0275	0.0286
p-value	(0.7728)	(0.8392)	(0.761)
Tarwe;Meel	0.4034	0.5545	0.4048
p-value	(0.0019)	(0)	(0)
Tarwe;Water	0.1617	0.1646	0.1115
p-value	(0.2295)	(0.2203)	(0.2205)
Meel;Water	0.9174	0.7696	0.589
p-value	(0)	(0)	(0)

Figure 1

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code