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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software ModulePatrick.Wessarwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationMon, 13 Dec 2010 20:31:06 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/13/t1292273081dw6pozxbujqtd8s.htm/, Retrieved Mon, 06 May 2024 19:33:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109186, Retrieved Mon, 06 May 2024 19:33:10 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120

Tree of Dependent Computations

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]
- R PD    [Kendall tau Correlation Matrix] [Workshop 10; Pear...] [2010-12-13 20:31:06] [50e0b5177c9c80b42996aa89930b928a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	236,67	107,11	8,92
2	258,1	122,23	9,32
3	241,52	134,69	8,9
4	190,71	128,79	8,53
5	200,32	126,16	8,51
6	223,41	119,98	9,03
7	201,38	108,45	9,6
8	211,83	108,43	9,88
9	224,41	98,17	10,81
10	211,57	106,09	11,61
11	194,77	108,81	11,81
12	201,86	103,03	13,93
13	225	124,36	16,19
14	278,9	118,52	18,05
15	259,74	112,2	17,08
16	230,45	114,71	17,46
17	238,26	107,96	16,9
18	250,14	101,21	15,69
19	263,81	102,77	15,86
20	247,22	112,13	12,98
21	229,81	109,36	12,31
22	224,27	110,91	11,51
23	213,23	123,57	11,73
24	239,57	129,95	11,7
25	249,7	124,46	10,9
26	212,5	122,34	10,57
27	203,27	116,61	10,37
28	192,05	114,59	9,59
29	190,04	112,52	9,09
30	202,05	118,67	9,26
31	211,91	116,8	9,9
32	210,39	123,63	9,61
33	231,25	128,04	9,85
34	224,3	134,57	9,99
35	209,64	130,33	9,9
36	206,05	136,47	10,45
37	229,7	139,05	11,66
38	264,67	158,21	13,61
39	246,29	148,07	12,88
40	260,91	137,74	12,52
41	265,14	139,74	10,93
42	284,52	144,08	12,07
43	287,48	145,35	13,21
44	321,9	145,77	13,68
45	321,59	140,56	14,02
46	282,39	121,41	11,7
47	241	120,44	11,83
48	228,48	116,97	11,32
49	261,59	128,03	12,24
50	270	128,51	13,31
51	262,86	127,76	12,93
52	277,41	134,58	13,47
53	288	147,64	15,47
54	287,14	144,46	16,58
55	337,65	137,6	17,8
56	328,38	146,87	21,72
57	374,41	145,67	23,45
58	344,77	151,95	23,16
59	361,05	150,23	22,77
60	374,22	155,86	24,9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109186&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109186&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109186&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Correlations for all pairs of data series (method=pearson)
MonthTeaCoffeeSugar
Month10.6870.7140.518
Tea0.68710.6580.808
Coffee0.7140.65810.414
Sugar0.5180.8080.4141

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Month & Tea & Coffee & Sugar \tabularnewline
Month & 1 & 0.687 & 0.714 & 0.518 \tabularnewline
Tea & 0.687 & 1 & 0.658 & 0.808 \tabularnewline
Coffee & 0.714 & 0.658 & 1 & 0.414 \tabularnewline
Sugar & 0.518 & 0.808 & 0.414 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109186&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Month[/C][C]Tea[/C][C]Coffee[/C][C]Sugar[/C][/ROW]
[ROW][C]Month[/C][C]1[/C][C]0.687[/C][C]0.714[/C][C]0.518[/C][/ROW]
[ROW][C]Tea[/C][C]0.687[/C][C]1[/C][C]0.658[/C][C]0.808[/C][/ROW]
[ROW][C]Coffee[/C][C]0.714[/C][C]0.658[/C][C]1[/C][C]0.414[/C][/ROW]
[ROW][C]Sugar[/C][C]0.518[/C][C]0.808[/C][C]0.414[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109186&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109186&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)
MonthTeaCoffeeSugar
Month10.6870.7140.518
Tea0.68710.6580.808
Coffee0.7140.65810.414
Sugar0.5180.8080.4141






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Month;Tea0.6870.65190.4757
p-value(0)(0)(0)
Month;Coffee0.71350.70820.5311
p-value(0)(0)(0)
Month;Sugar0.51750.51780.3912
p-value(0)(0)(0)
Tea;Coffee0.65810.59780.4271
p-value(0)(0)(0)
Tea;Sugar0.80840.73210.5642
p-value(0)(0)(0)
Coffee;Sugar0.41410.31320.2329
p-value(0.001)(0.0148)(0.0086)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Month;Tea & 0.687 & 0.6519 & 0.4757 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Month;Coffee & 0.7135 & 0.7082 & 0.5311 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Month;Sugar & 0.5175 & 0.5178 & 0.3912 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Tea;Coffee & 0.6581 & 0.5978 & 0.4271 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Tea;Sugar & 0.8084 & 0.7321 & 0.5642 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Coffee;Sugar & 0.4141 & 0.3132 & 0.2329 \tabularnewline
p-value & (0.001) & (0.0148) & (0.0086) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109186&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]Month;Tea[/C][C]0.687[/C][C]0.6519[/C][C]0.4757[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Month;Coffee[/C][C]0.7135[/C][C]0.7082[/C][C]0.5311[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Month;Sugar[/C][C]0.5175[/C][C]0.5178[/C][C]0.3912[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Tea;Coffee[/C][C]0.6581[/C][C]0.5978[/C][C]0.4271[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Tea;Sugar[/C][C]0.8084[/C][C]0.7321[/C][C]0.5642[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Coffee;Sugar[/C][C]0.4141[/C][C]0.3132[/C][C]0.2329[/C][/ROW]
[ROW][C]p-value[/C][C](0.001)[/C][C](0.0148)[/C][C](0.0086)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109186&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109186&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
Month;Tea0.6870.65190.4757
p-value(0)(0)(0)
Month;Coffee0.71350.70820.5311
p-value(0)(0)(0)
Month;Sugar0.51750.51780.3912
p-value(0)(0)(0)
Tea;Coffee0.65810.59780.4271
p-value(0)(0)(0)
Tea;Sugar0.80840.73210.5642
p-value(0)(0)(0)
Coffee;Sugar0.41410.31320.2329
p-value(0.001)(0.0148)(0.0086)


Figures (Output of Computation)

Input Parameters & R Code

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')