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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, 16 Dec 2011 09:48:52 -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/t1324046942hps38zhcfvrs6ry.htm/, Retrieved Sun, 05 May 2024 13:22:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=156017, Retrieved Sun, 05 May 2024 13:22:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact111
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 18:04:16] [b98453cac15ba1066b407e146608df68]
- RMPD  [Kendall tau Correlation Matrix] [] [2011-12-13 08:49:16] [8fcdd1f5b88bf5ac5d2a0b8a91219b89]
-   PD    [Kendall tau Correlation Matrix] [] [2011-12-16 14:46:03] [8fcdd1f5b88bf5ac5d2a0b8a91219b89]
-    D      [Kendall tau Correlation Matrix] [] [2011-12-16 14:47:52] [8fcdd1f5b88bf5ac5d2a0b8a91219b89]
-    D          [Kendall tau Correlation Matrix] [] [2011-12-16 14:48:52] [888ed98a09d01be7e0be9dfdea403736] [Current]
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Dataseries X:
112285	210907	81	79	30
84786	120982	55	58	28
83123	176508	50	60	38
101193	179321	125	108	30
38361	123185	40	49	22
68504	52746	37	0	26
119182	385534	63	121	25
22807	33170	44	1	18
116174	149061	66	43	26
57635	165446	57	69	25
66198	237213	74	78	38
71701	173326	49	86	44
57793	133131	52	44	30
80444	258873	88	104	40
53855	180083	36	63	34
97668	324799	108	158	47
133824	230964	43	102	30
101481	236785	75	77	31
99645	135473	32	82	23
114789	202925	44	115	36
99052	215147	85	101	36
67654	344297	86	80	30
65553	153935	56	50	25
97500	132943	50	83	39
69112	174724	135	123	34
82753	174415	63	73	31
85323	225548	81	81	31
72654	223632	52	105	33
30727	124817	44	47	25
77873	221698	113	105	33
117478	210767	39	94	35
74007	170266	73	44	42
90183	260561	48	114	43
61542	84853	33	38	30
101494	294424	59	107	33
55813	215641	69	71	32
79215	325107	64	84	36
55461	167542	59	59	28
31081	106408	32	33	14
83122	265769	37	96	32
70106	269651	31	106	30
60578	149112	65	56	35
79892	152871	74	59	28
49810	111665	54	39	28
71570	116408	76	34	39
100708	362301	715	76	34
33032	78800	57	20	26
82875	183167	66	91	39
139077	277965	106	115	39
71595	150629	54	85	33
72260	168809	32	76	28
5950	24188	20	8	4
115762	329267	71	79	39
32551	65029	21	21	18
31701	101097	70	30	14
80670	218946	112	76	29
143558	244052	66	101	44
120733	233328	165	92	28
105195	256462	56	123	35
73107	206161	61	75	28
132068	311473	53	128	38
149193	235800	127	105	23
46821	177939	63	55	36
87011	207176	38	56	32
95260	196553	50	41	29
55183	174184	52	72	25
106671	143246	42	67	27
73511	187559	76	75	36
92945	187681	67	114	28
78664	119016	50	118	23
70054	182192	53	77	40
22618	73566	39	22	23
74011	194979	50	66	40
83737	167488	77	69	28
69094	143756	57	105	34
93133	275541	73	116	33
95536	243199	34	88	28
225920	182999	39	73	34
62133	135649	46	99	30
61370	152299	63	62	33
43836	120221	35	53	22
106117	346485	106	118	38
38692	145790	43	30	26
84651	193339	47	100	35
56622	80953	31	49	8
15986	122774	162	24	24
95364	130585	57	67	29
89691	286468	263	57	29
67267	241066	78	75	45
126846	148446	63	135	37
41140	204713	54	68	33
102860	182079	63	124	33
51715	140344	77	33	25
55801	220516	79	98	32
111813	243060	110	58	29
120293	162765	56	68	28
138599	182613	56	81	28
161647	232138	43	131	31
115929	265318	111	110	52
162901	310839	62	130	24
109825	225060	56	93	41
129838	232317	74	118	33
37510	144966	60	39	32
43750	43287	43	13	19
40652	155754	68	74	20
87771	164709	53	81	31
85872	201940	87	109	31
89275	235454	46	151	32
192565	99466	32	28	23
140867	100750	67	83	30
120662	224549	47	54	31
101338	243511	65	133	42
1168	22938	9	12	1
65567	152474	45	106	32
25162	61857	25	23	11
40735	132487	97	71	36
91413	317394	53	116	31
855	21054	2	4	0
97068	209641	52	62	24
14116	31414	22	18	8
76643	244749	144	98	33
110681	184510	60	64	40
92696	128423	89	32	38
94785	97839	42	25	24
8773	38214	52	16	8
83209	151101	98	48	35
93815	272458	99	100	43
86687	172494	52	46	43
105547	328107	125	129	41
103487	250579	106	130	38
213688	351067	95	136	45
71220	158015	40	59	31
56926	85439	43	32	28
91721	229242	128	63	31
115168	351619	142	95	40
111194	84207	73	14	30
135777	324598	128	113	37
51513	131069	61	47	30
74163	204271	73	92	35
51633	165543	148	70	32
75345	141722	64	19	27
98952	299775	97	91	31
102372	195838	50	111	31
37238	173260	37	41	21
103772	254488	50	120	39
123969	104389	105	135	41
135400	199476	46	87	32
130115	224330	52	131	39
6023	14688	0	4	0
64466	181633	48	47	30
54990	271856	91	109	37
1644	7199	0	7	0
6179	46660	7	12	5
3926	17547	3	0	1
34777	95227	70	37	32
73224	152601	36	46	24




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156017&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156017&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156017&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'Herman Ole Andreas Wold' @ wold.wessa.net







Correlations for all pairs of data series (method=kendall)
Total_sizeTime_RFCPR_viewBloggedReviewed
Total_size10.4450.2320.4710.325
Time_RFC0.44510.3540.5710.432
PR_view0.2320.35410.2740.34
Blogged0.4710.5710.27410.437
Reviewed0.3250.4320.340.4371

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Total_size & Time_RFC & PR_view & Blogged & Reviewed \tabularnewline
Total_size & 1 & 0.445 & 0.232 & 0.471 & 0.325 \tabularnewline
Time_RFC & 0.445 & 1 & 0.354 & 0.571 & 0.432 \tabularnewline
PR_view & 0.232 & 0.354 & 1 & 0.274 & 0.34 \tabularnewline
Blogged & 0.471 & 0.571 & 0.274 & 1 & 0.437 \tabularnewline
Reviewed & 0.325 & 0.432 & 0.34 & 0.437 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156017&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Total_size[/C][C]Time_RFC[/C][C]PR_view[/C][C]Blogged[/C][C]Reviewed[/C][/ROW]
[ROW][C]Total_size[/C][C]1[/C][C]0.445[/C][C]0.232[/C][C]0.471[/C][C]0.325[/C][/ROW]
[ROW][C]Time_RFC[/C][C]0.445[/C][C]1[/C][C]0.354[/C][C]0.571[/C][C]0.432[/C][/ROW]
[ROW][C]PR_view[/C][C]0.232[/C][C]0.354[/C][C]1[/C][C]0.274[/C][C]0.34[/C][/ROW]
[ROW][C]Blogged[/C][C]0.471[/C][C]0.571[/C][C]0.274[/C][C]1[/C][C]0.437[/C][/ROW]
[ROW][C]Reviewed[/C][C]0.325[/C][C]0.432[/C][C]0.34[/C][C]0.437[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156017&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156017&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)
Total_sizeTime_RFCPR_viewBloggedReviewed
Total_size10.4450.2320.4710.325
Time_RFC0.44510.3540.5710.432
PR_view0.2320.35410.2740.34
Blogged0.4710.5710.27410.437
Reviewed0.3250.4320.340.4371







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Total_size;Time_RFC0.59180.59760.4447
p-value(0)(0)(0)
Total_size;PR_view0.19080.32950.2316
p-value(0.017)(0)(0)
Total_size;Blogged0.61730.6360.4708
p-value(0)(0)(0)
Total_size;Reviewed0.56060.4470.3245
p-value(0)(0)(0)
Time_RFC;PR_view0.4190.49630.3537
p-value(0)(0)(0)
Time_RFC;Blogged0.74820.73920.5711
p-value(0)(0)(0)
Time_RFC;Reviewed0.65690.58590.4323
p-value(0)(0)(0)
PR_view;Blogged0.20140.39150.2745
p-value(0.0117)(0)(0)
PR_view;Reviewed0.27470.46570.3395
p-value(5e-04)(0)(0)
Blogged;Reviewed0.63810.58740.4373
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
Total_size;Time_RFC & 0.5918 & 0.5976 & 0.4447 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Total_size;PR_view & 0.1908 & 0.3295 & 0.2316 \tabularnewline
p-value & (0.017) & (0) & (0) \tabularnewline
Total_size;Blogged & 0.6173 & 0.636 & 0.4708 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Total_size;Reviewed & 0.5606 & 0.447 & 0.3245 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time_RFC;PR_view & 0.419 & 0.4963 & 0.3537 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time_RFC;Blogged & 0.7482 & 0.7392 & 0.5711 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time_RFC;Reviewed & 0.6569 & 0.5859 & 0.4323 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PR_view;Blogged & 0.2014 & 0.3915 & 0.2745 \tabularnewline
p-value & (0.0117) & (0) & (0) \tabularnewline
PR_view;Reviewed & 0.2747 & 0.4657 & 0.3395 \tabularnewline
p-value & (5e-04) & (0) & (0) \tabularnewline
Blogged;Reviewed & 0.6381 & 0.5874 & 0.4373 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156017&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]Total_size;Time_RFC[/C][C]0.5918[/C][C]0.5976[/C][C]0.4447[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Total_size;PR_view[/C][C]0.1908[/C][C]0.3295[/C][C]0.2316[/C][/ROW]
[ROW][C]p-value[/C][C](0.017)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Total_size;Blogged[/C][C]0.6173[/C][C]0.636[/C][C]0.4708[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Total_size;Reviewed[/C][C]0.5606[/C][C]0.447[/C][C]0.3245[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time_RFC;PR_view[/C][C]0.419[/C][C]0.4963[/C][C]0.3537[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time_RFC;Blogged[/C][C]0.7482[/C][C]0.7392[/C][C]0.5711[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time_RFC;Reviewed[/C][C]0.6569[/C][C]0.5859[/C][C]0.4323[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PR_view;Blogged[/C][C]0.2014[/C][C]0.3915[/C][C]0.2745[/C][/ROW]
[ROW][C]p-value[/C][C](0.0117)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PR_view;Reviewed[/C][C]0.2747[/C][C]0.4657[/C][C]0.3395[/C][/ROW]
[ROW][C]p-value[/C][C](5e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Blogged;Reviewed[/C][C]0.6381[/C][C]0.5874[/C][C]0.4373[/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=156017&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156017&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
Total_size;Time_RFC0.59180.59760.4447
p-value(0)(0)(0)
Total_size;PR_view0.19080.32950.2316
p-value(0.017)(0)(0)
Total_size;Blogged0.61730.6360.4708
p-value(0)(0)(0)
Total_size;Reviewed0.56060.4470.3245
p-value(0)(0)(0)
Time_RFC;PR_view0.4190.49630.3537
p-value(0)(0)(0)
Time_RFC;Blogged0.74820.73920.5711
p-value(0)(0)(0)
Time_RFC;Reviewed0.65690.58590.4323
p-value(0)(0)(0)
PR_view;Blogged0.20140.39150.2745
p-value(0.0117)(0)(0)
PR_view;Reviewed0.27470.46570.3395
p-value(5e-04)(0)(0)
Blogged;Reviewed0.63810.58740.4373
p-value(0)(0)(0)



Parameters (Session):
par1 = 2 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
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')