FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationFri, 15 Jan 2010 06:19:34 -0700
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/Jan/15/t1263561645b9kli99wvns7iqi.htm/, Retrieved Fri, 03 May 2024 11:12:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=72193, Retrieved Fri, 03 May 2024 11:12:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact175

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] [Some rev. stats] [2010-01-15 13:19:34] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
22	134	3.44	335.12	107.89	60.51
7	112	3.29	143.8	68.94	39.05
2	92	2.42	88.7	62.15	69.6
9	115	3.29	244.97	97.89	53.34
13	94	3.13	289.48	87.22	75.79
15	137	3.43	276.93	105.38	41.24
8	112	3.03	174.31	76.06	48.82
8	74	2.47	332.74	104.79	70.21
12	101	2.97	268.43	109.41	63.59
22	155	4.08	397.95	165.23	116.09
10	63	2.17	355.29	98.84	72.67
7	110	2.89	135.95	67.68	56.59
17	128	3.37	531.25	169.02	129.43
21	118	3.37	515.73	189.34	123.26
5	132	3.67	197.41	91.1	72.53
6	68	3.4	124.4	71.46	51.17
6	100	3.03	167.91	74.16	56.85
6	100	2.78	145.83	77.01	77.74
11	97	2.69	257.55	89.04	62.56
13	87	2.64	478.66	156.42	71.49
7	133	3.33	212.19	78.98	51.86
6	96	3.43	176.07	73.2	53.06
14	130	3.51	184.32	76.78	67.21
15	162	4.05	319	109.44	48.62
8	130	2.89	157.64	80.45	69.74
29	136	3.49	515.85	167.62	116.65
11	134	3.53	300.07	109.55	61.51
15	130	3.71	187.35	97.29	61.82
19	142	3.46	382.07	146.51	102.82
9	111	2.71	174.27	76.75	84.13
27	127	3.34	439.35	134.34	81.19
9	80	3.64	260.15	99.57	53.69
34	119	3.5	595.2	204.52	107.51
8	99	3.09	245.68	96.53	61.84
7	28	4.67	94.96	67.4	61.17
10	133	3.02	222.45	93.03	54.17
12	140	3.68	305.54	121.66	118.34
2	79	2.26	98	61.82	66.85
21	98	3.27	260.33	108.37	78.96
8	89	2.54	138.62	81.71	64.12
18	124	3.35	501.13	191.27	107.89
16	163	4.41	513.08	178.34	118.54
24	80	2.86	309.71	119.63	77.41
21	145	3.54	246.26	92.55	59.21
8	139	2.96	507.39	192.19	146.65
4	57	2.38	92.68	58.65	60.22
3	44	2.32	250.59	75.61	56.84
9	155	3.6	246.35	99.43	64
15	141	3.44	475.44	182.26	88.32
20	106	2.94	366.62	123.55	76.7
13	146	4.06	344.34	114.03	107.82
8	119	2.43	226.55	94.05	99.37
19	105	3.39	445.53	138.14	80.98
14	120	3.43	312.29	117.09	94.88
26	80	2.96	343.64	106.64	82.86
26	127	3.34	311.42	113.46	82.15
20	120	3.64	290.12	117.57	38.61
22	135	3.55	685.06	238.23	172.38
14	79	2.72	423.58	138	84.34
18	119	3.31	514.39	198.68	114.97
14	126	3.07	236.65	113.27	70.04
12	123	3.08	205.29	90.57	51.11
18	174	4.35	294.16	122.1	126.97
17	105	3.5	377.49	134.49	93.05
5	77	2.96	150.95	84.08	46.45
18	135	3.29	164.03	87.56	53.17
17	120	3.33	392.93	133.94	82.38
9	126	3.6	235.82	99.56	91.55
3	73	2.92	102.66	71.46	53.54
8	111	3	262.41	112.86	117.91
11	127	3.34	155.03	75.79	53.79
18	75	3.26	184.96	79.62	61.37
20	112	3.2	203.76	89.37	69.87
3	26	1.73	164.69	85.39	89.45
36	109	3.41	518.61	163.59	81.96
3	97	2.06	114.69	66.25	78.92
10	119	3.97	254.26	91.96	94.55
13	145	3.92	281.6	96.93	68.78
7	95	3.39	165.03	79.61	55.42
9	124	3.76	71.56	54.24	58.43
10	118	3.69	296.94	100.4	68.46
8	59	3.69	147.64	75.96	76.28
29	152	3.71	395.72	152.95	94.14
8	70	2.26	154.54	76.36	78.28
16	105	2.56	547.15	187.98	103.14
15	122	3.13	295.65	130.33	88.98
34	151	4.08	388.32	160.14	113.63
9	113	3.14	225.2	100.79	72.07
17	122	3.3	308.23	116.3	75.51
2	113	3.42	253.34	95.44	74.12
14	135	3.14	401.35	139.24	115.44
9	111	3.36	117.1	70	43.3
17	91	3.37	411.68	136.95	74.5
24	88	3.03	378.88	131.99	56.59
12	47	1.96	164.98	90.95	89.81
16	121	3.46	349.79	137.37	55.51
20	132	3.57	347.44	132.41	83.24
17	114	3.26	327.65	136.76	83.89
11	149	3.73	321.87	128.03	80.38
21	91	2.53	753.96	179.19	128.92
15	113	3.23	505.68	184.58	87.34
4	64	2.56	120.52	63.1	56.34
17	142	3.46	212.61	91.47	63.58
14	125	3.68	391.51	167.86	123.26
20	127	3.43	1723.73	480.42	286.45
26	161	4.13	535.05	227.26	211.92
12	102	2.83	322.52	109.14	55.23
6	124	3.26	153.85	77.5	50.62
6	136	3.4	165.93	97.49	73.63
9	75	2.14	187.08	89.21	43.71
23	122	3.3	340.21	130.73	119.58
14	116	3.14	459.75	153.54	154.4
13	87	3.48	182.55	81.2	58.27
11	96	3	193.58	88.22	60.33
16	165	4.23	308.04	123.44	88.37
26	164	3.57	561.19	167.28	109.61
17	87	3.35	324.6	102.51	63.91
6	71	2.45	303.42	120.15	79.75
8	136	4.12	217.82	88.99	66.69
28	76	3.62	261.71	84.64	81.66
21	141	3.92	355.99	133.12	75.11
10	66	3.47	160.58	76.48	66.08
38	89	2.97	203.16	80.28	62
10	113	3.23	279.98	96.59	73.7
22	131	3.54	228.72	96.83	64.92
8	132	3.38	231.58	76.99	49.62
24	44	2.2	616.34	212.42	130.76

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72193&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]5 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=72193&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72193&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 time5 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( MRT , NFM )0.2443801136664746.74881111148995e-05
tau( MRT , FmpC )0.2377247336973000.000104287863381902
tau( MRT , AFL )0.5235789872612370
tau( MRT , LpM )0.5071691805728150
tau( MRT , LpC )0.2967488445358411.18123957504324e-06
tau( NFM , FmpC )0.5028027316292590
tau( NFM , AFL )0.2378883117184477.81735371648828e-05
tau( NFM , LpM )0.2824707933324532.7333529730722e-06
tau( NFM , LpC )0.1668565107862050.005602617730746
tau( FmpC , AFL )0.1622681227466520.0069954088206794
tau( FmpC , LpM )0.1741920471068910.00379066846217002
tau( FmpC , LpC )0.08352710928508160.165094799757073
tau( AFL , LpM )0.813699145392570
tau( AFL , LpC )0.4766250037236331.99840144432528e-15
tau( LpM , LpC )0.5135320967591030

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( MRT , NFM ) & 0.244380113666474 & 6.74881111148995e-05 \tabularnewline
tau( MRT , FmpC ) & 0.237724733697300 & 0.000104287863381902 \tabularnewline
tau( MRT , AFL ) & 0.523578987261237 & 0 \tabularnewline
tau( MRT , LpM ) & 0.507169180572815 & 0 \tabularnewline
tau( MRT , LpC ) & 0.296748844535841 & 1.18123957504324e-06 \tabularnewline
tau( NFM , FmpC ) & 0.502802731629259 & 0 \tabularnewline
tau( NFM , AFL ) & 0.237888311718447 & 7.81735371648828e-05 \tabularnewline
tau( NFM , LpM ) & 0.282470793332453 & 2.7333529730722e-06 \tabularnewline
tau( NFM , LpC ) & 0.166856510786205 & 0.005602617730746 \tabularnewline
tau( FmpC , AFL ) & 0.162268122746652 & 0.0069954088206794 \tabularnewline
tau( FmpC , LpM ) & 0.174192047106891 & 0.00379066846217002 \tabularnewline
tau( FmpC , LpC ) & 0.0835271092850816 & 0.165094799757073 \tabularnewline
tau( AFL , LpM ) & 0.81369914539257 & 0 \tabularnewline
tau( AFL , LpC ) & 0.476625003723633 & 1.99840144432528e-15 \tabularnewline
tau( LpM , LpC ) & 0.513532096759103 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72193&T=1

[TABLE]
[ROW][C]Kendall tau rank correlations for all pairs of data series[/C][/ROW]
[ROW][C]pair[/C][C]tau[/C][C]p-value[/C][/ROW]
[ROW][C]tau( MRT , NFM )[/C][C]0.244380113666474[/C][C]6.74881111148995e-05[/C][/ROW]
[ROW][C]tau( MRT , FmpC )[/C][C]0.237724733697300[/C][C]0.000104287863381902[/C][/ROW]
[ROW][C]tau( MRT , AFL )[/C][C]0.523578987261237[/C][C]0[/C][/ROW]
[ROW][C]tau( MRT , LpM )[/C][C]0.507169180572815[/C][C]0[/C][/ROW]
[ROW][C]tau( MRT , LpC )[/C][C]0.296748844535841[/C][C]1.18123957504324e-06[/C][/ROW]
[ROW][C]tau( NFM , FmpC )[/C][C]0.502802731629259[/C][C]0[/C][/ROW]
[ROW][C]tau( NFM , AFL )[/C][C]0.237888311718447[/C][C]7.81735371648828e-05[/C][/ROW]
[ROW][C]tau( NFM , LpM )[/C][C]0.282470793332453[/C][C]2.7333529730722e-06[/C][/ROW]
[ROW][C]tau( NFM , LpC )[/C][C]0.166856510786205[/C][C]0.005602617730746[/C][/ROW]
[ROW][C]tau( FmpC , AFL )[/C][C]0.162268122746652[/C][C]0.0069954088206794[/C][/ROW]
[ROW][C]tau( FmpC , LpM )[/C][C]0.174192047106891[/C][C]0.00379066846217002[/C][/ROW]
[ROW][C]tau( FmpC , LpC )[/C][C]0.0835271092850816[/C][C]0.165094799757073[/C][/ROW]
[ROW][C]tau( AFL , LpM )[/C][C]0.81369914539257[/C][C]0[/C][/ROW]
[ROW][C]tau( AFL , LpC )[/C][C]0.476625003723633[/C][C]1.99840144432528e-15[/C][/ROW]
[ROW][C]tau( LpM , LpC )[/C][C]0.513532096759103[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72193&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72193&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:

Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( MRT , NFM )0.2443801136664746.74881111148995e-05
tau( MRT , FmpC )0.2377247336973000.000104287863381902
tau( MRT , AFL )0.5235789872612370
tau( MRT , LpM )0.5071691805728150
tau( MRT , LpC )0.2967488445358411.18123957504324e-06
tau( NFM , FmpC )0.5028027316292590
tau( NFM , AFL )0.2378883117184477.81735371648828e-05
tau( NFM , LpM )0.2824707933324532.7333529730722e-06
tau( NFM , LpC )0.1668565107862050.005602617730746
tau( FmpC , AFL )0.1622681227466520.0069954088206794
tau( FmpC , LpM )0.1741920471068910.00379066846217002
tau( FmpC , LpC )0.08352710928508160.165094799757073
tau( AFL , LpM )0.813699145392570
tau( AFL , LpC )0.4766250037236331.99840144432528e-15
tau( LpM , LpC )0.5135320967591030


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
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='kendall')
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$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Kendall tau rank correlations for all pairs of data series',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'tau',1,TRUE)
a<-table.element(a,'p-value',1,TRUE)
a<-table.row.end(a)
n <- length(y[,1])
n
cor.test(y[1,],y[2,],method='kendall')
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste('tau(',dimnames(t(x))[[2]][i])
dum <- paste(dum,',')
dum <- paste(dum,dimnames(t(x))[[2]][j])
dum <- paste(dum,')')
a<-table.element(a,dum,header=TRUE)
r <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,r$estimate)
a<-table.element(a,r$p.value)
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable.tab')