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Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationFri, 07 Dec 2012 09:39:16 -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/2012/Dec/07/t1354891174qfn04qwhox75fho.htm/, Retrieved Thu, 31 Oct 2024 22:48:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197404, Retrieved Thu, 31 Oct 2024 22:48:17 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128
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] [Kendall's tau Cor...] [2012-12-07 14:39:16] [e3d79eec5d0d9e3c05706137ffeca8bc] [Current]
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Dataseries X:
210907	1	1	24188	145
120982	1	1	18273	101
176508	1	1	14130	98
179321	1	0	32287	132
123185	1	1	8654	60
52746	1	1	9245	38
385534	1	1	33251	144
33170	1	1	1271	5
101645	1	1	5279	28
149061	1	1	27101	84
165446	1	0	16373	79
237213	1	1	19716	127
173326	1	0	17753	78
133131	1	1	9028	60
258873	1	1	18653	131
180083	1	0	8828	84
324799	1	0	29498	133
230964	1	1	27563	150
236785	1	0	18293	91
135473	1	1	22530	132
202925	1	0	15977	136
215147	1	1	35082	124
344297	1	1	16116	118
153935	1	1	15849	70
132943	1	0	16026	107
174724	1	1	26569	119
174415	1	0	24785	89
225548	1	1	17569	112
223632	1	1	23825	108
124817	1	0	7869	52
221698	1	1	14975	112
210767	1	0	37791	116
170266	1	1	9605	123
260561	1	1	27295	125
84853	1	0	2746	27
294424	1	0	34461	162
101011	1	0	8098	32
215641	1	0	4787	64
325107	1	1	24919	92
7176	1	0	603	0
167542	1	0	16329	83
106408	1	1	12558	41
96560	1	0	7784	47
265769	1	0	28522	120
269651	1	1	22265	105
149112	1	1	14459	79
175824	1	1	14526	65
152871	1	1	22240	70
111665	1	1	11802	55
116408	1	0	7623	39
362301	1	1	11912	67
78800	1	0	7935	21
183167	1	0	18220	127
277965	1	1	19199	152
150629	1	0	19918	113
168809	1	1	21884	99
24188	1	1	2694	7
329267	1	1	15808	141
65029	1	0	3597	21
101097	1	1	5296	35
218946	1	0	25239	109
244052	1	0	29801	133
341570	1	1	18450	123
103597	1	1	7132	26
233328	1	1	34861	230
256462	1	0	35940	166
206161	1	1	16688	68
311473	1	0	24683	147
235800	1	1	46230	179
177939	1	0	10387	61
207176	1	0	21436	101
196553	1	1	30546	108
174184	1	1	19746	90
143246	1	0	15977	114
187559	1	0	22583	103
187681	1	1	17274	142
119016	1	1	16469	79
182192	1	1	14251	88
73566	1	0	3007	25
194979	1	0	16851	83
167488	1	0	21113	113
143756	1	1	17401	118
275541	1	0	23958	110
243199	1	1	23567	129
182999	1	1	13065	51
135649	1	0	15358	93
152299	1	1	14587	76
120221	1	1	12770	49
346485	1	1	24021	118
145790	1	1	9648	38
193339	1	1	20537	141
80953	1	1	7905	58
122774	1	1	4527	27
130585	1	1	30495	91
112611	1	1	7117	48
286468	1	1	17719	63
241066	1	1	27056	56
148446	1	0	33473	144
204713	1	0	9758	73
182079	1	1	21115	168
140344	1	0	7236	64
220516	1	1	13790	97
243060	1	0	32902	117
162765	1	1	25131	100
182613	1	0	30910	149
232138	1	1	35947	187
265318	1	0	29848	127
85574	1	0	6943	37
310839	1	1	42705	245
225060	1	1	31808	87
232317	1	1	26675	177
144966	1	1	8435	49
43287	1	1	7409	49
155754	1	0	14993	73
164709	1	1	36867	177
201940	1	1	33835	94
235454	1	1	24164	117
220801	1	1	12607	60
99466	1	0	22609	55
92661	1	1	5892	39
133328	1	1	17014	64
61361	1	1	5394	26
125930	1	1	9178	64
100750	1	1	6440	58
224549	1	0	21916	95
82316	1	1	4011	25
102010	1	1	5818	26
101523	1	1	18647	76
243511	1	0	20556	129
22938	1	0	238	11
41566	1	1	70	2
152474	1	0	22392	101
61857	1	0	3913	28
99923	1	1	12237	36
132487	1	0	8388	89
317394	1	0	22120	193
21054	1	1	338	4
209641	1	1	11727	84
22648	1	0	3704	23
31414	1	1	3988	39
46698	1	0	3030	14
131698	1	1	13520	78
91735	1	0	1421	14
244749	1	1	20923	101
184510	1	1	20237	82
79863	1	0	3219	24
128423	1	0	3769	36
97839	1	0	12252	75
38214	1	1	1888	16
151101	1	1	14497	55
272458	1	0	28864	131
172494	1	1	21721	131
108043	1	1	4821	39
328107	1	1	33644	144
250579	1	1	15923	139
351067	1	1	42935	211
158015	1	1	18864	78
98866	1	1	4977	50
85439	0	0	7785	39
229242	0	0	17939	90
351619	0	0	23436	166
84207	0	1	325	12
120445	0	0	13539	57
324598	0	0	34538	133
131069	0	1	12198	69
204271	0	1	26924	119
165543	0	0	12716	119
141722	0	0	8172	65
116048	0	1	10855	61
250047	0	0	11932	49
299775	0	1	14300	101
195838	0	1	25515	196
173260	0	0	2805	15
254488	0	1	29402	136
104389	0	0	16440	89
136084	0	1	11221	40
199476	0	1	28732	123
92499	0	1	5250	21
224330	0	0	28608	163
135781	0	0	8092	29
74408	0	0	4473	35
81240	0	1	1572	13
14688	0	1	2065	5
181633	0	0	14817	96
271856	0	1	16714	151
7199	0	0	556	6
46660	0	0	2089	13
17547	0	1	2658	3
133368	0	1	10695	56
95227	0	1	1669	23
152601	0	1	16267	57
98146	0	1	7768	14
79619	0	0	7252	43
59194	0	1	6387	20
139942	0	1	18715	72
118612	0	0	7936	87
72880	0	0	8643	21
65475	0	0	7294	56
99643	0	0	4570	59
71965	0	0	7185	82
77272	0	1	10058	43
49289	0	1	2342	25
135131	0	1	8509	38
108446	0	0	13275	25
89746	0	0	6816	38
44296	0	0	1930	12
77648	0	1	8086	29
181528	0	0	10737	47
134019	0	0	8033	45
124064	0	0	7058	40
92630	0	1	6782	30
121848	0	0	5401	41
52915	0	1	6521	25
81872	0	1	10856	23
58981	0	0	2154	14
53515	0	1	6117	16
60812	0	0	5238	26
56375	0	0	4820	21
65490	0	1	5615	27
80949	0	0	4272	9
76302	0	1	8702	33
104011	0	0	15340	42
98104	0	0	8030	68
67989	0	0	9526	32
30989	0	0	1278	6
135458	0	1	4236	67
73504	0	0	3023	33
63123	0	0	7196	77
61254	0	1	3394	46
74914	0	1	6371	30
31774	0	0	1574	0
81437	0	0	9620	36
87186	0	0	6978	46
50090	0	1	4911	18
65745	0	0	8645	48
56653	0	0	8987	29
158399	0	0	5544	28
46455	0	0	3083	34
73624	0	0	6909	33
38395	0	0	3189	34
91899	0	0	6745	33
139526	0	1	16724	80
52164	0	1	4850	32
51567	0	1	7025	30
70551	0	0	6047	41
84856	0	0	7377	41
102538	0	1	9078	51
86678	0	1	4605	18
85709	0	0	3238	34
34662	0	0	8100	31
150580	0	0	9653	39
99611	0	1	8914	54
19349	0	1	786	14
99373	0	1	6700	24
86230	0	1	5788	24
30837	0	0	593	8
31706	0	0	4506	26
89806	0	0	6382	19
62088	0	0	5621	11
40151	0	1	3997	14
27634	0	0	520	1
76990	0	0	8891	39
37460	0	1	999	5
54157	0	0	7067	37
49862	0	0	4639	32
84337	0	1	5654	38
64175	0	1	6928	47
59382	0	0	1514	47
119308	0	1	9238	37
76702	0	0	8204	51
103425	0	0	5926	45
70344	0	1	5785	21
43410	0	0	4	1
104838	0	1	5930	42
62215	0	0	3710	26
69304	0	0	705	21
53117	0	0	443	4
19764	0	0	2416	10
86680	0	1	7747	43
84105	0	0	5432	34
77945	0	0	4913	31
89113	0	1	2650	19
91005	0	0	2370	34
40248	0	1	775	6
64187	0	0	5576	11
50857	0	0	1352	24
56613	0	1	3080	16
62792	0	1	10205	72




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 3 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197404&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197404&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197404&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 time3 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Correlations for all pairs of data series (method=kendall)
timepopgenderreviewsblogs
time10.4110.1210.6390.665
pop0.41110.1970.3920.403
gender0.1210.19710.1320.098
reviews0.6390.3920.13210.716
blogs0.6650.4030.0980.7161

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & time & pop & gender & reviews & blogs \tabularnewline
time & 1 & 0.411 & 0.121 & 0.639 & 0.665 \tabularnewline
pop & 0.411 & 1 & 0.197 & 0.392 & 0.403 \tabularnewline
gender & 0.121 & 0.197 & 1 & 0.132 & 0.098 \tabularnewline
reviews & 0.639 & 0.392 & 0.132 & 1 & 0.716 \tabularnewline
blogs & 0.665 & 0.403 & 0.098 & 0.716 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197404&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]time[/C][C]pop[/C][C]gender[/C][C]reviews[/C][C]blogs[/C][/ROW]
[ROW][C]time[/C][C]1[/C][C]0.411[/C][C]0.121[/C][C]0.639[/C][C]0.665[/C][/ROW]
[ROW][C]pop[/C][C]0.411[/C][C]1[/C][C]0.197[/C][C]0.392[/C][C]0.403[/C][/ROW]
[ROW][C]gender[/C][C]0.121[/C][C]0.197[/C][C]1[/C][C]0.132[/C][C]0.098[/C][/ROW]
[ROW][C]reviews[/C][C]0.639[/C][C]0.392[/C][C]0.132[/C][C]1[/C][C]0.716[/C][/ROW]
[ROW][C]blogs[/C][C]0.665[/C][C]0.403[/C][C]0.098[/C][C]0.716[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197404&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197404&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)
timepopgenderreviewsblogs
time10.4110.1210.6390.665
pop0.41110.1970.3920.403
gender0.1210.19710.1320.098
reviews0.6390.3920.13210.716
blogs0.6650.4030.0980.7161







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
time;pop0.46380.50230.4108
p-value(0)(0)(0)
time;gender0.14090.14830.1213
p-value(0.0167)(0.0117)(0.012)
time;reviews0.78230.8410.639
p-value(0)(0)(0)
time;blogs0.81380.85720.6648
p-value(0)(0)(0)
pop;gender0.19660.19660.1966
p-value(8e-04)(8e-04)(9e-04)
pop;reviews0.47190.47910.3919
p-value(0)(0)(0)
pop;blogs0.46390.4910.4029
p-value(0)(0)(0)
gender;reviews0.14460.16080.1315
p-value(0.014)(0.0062)(0.0064)
gender;blogs0.12750.11960.0982
p-value(0.0305)(0.0425)(0.0427)
reviews;blogs0.87570.89430.7156
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
time;pop & 0.4638 & 0.5023 & 0.4108 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
time;gender & 0.1409 & 0.1483 & 0.1213 \tabularnewline
p-value & (0.0167) & (0.0117) & (0.012) \tabularnewline
time;reviews & 0.7823 & 0.841 & 0.639 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
time;blogs & 0.8138 & 0.8572 & 0.6648 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
pop;gender & 0.1966 & 0.1966 & 0.1966 \tabularnewline
p-value & (8e-04) & (8e-04) & (9e-04) \tabularnewline
pop;reviews & 0.4719 & 0.4791 & 0.3919 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
pop;blogs & 0.4639 & 0.491 & 0.4029 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
gender;reviews & 0.1446 & 0.1608 & 0.1315 \tabularnewline
p-value & (0.014) & (0.0062) & (0.0064) \tabularnewline
gender;blogs & 0.1275 & 0.1196 & 0.0982 \tabularnewline
p-value & (0.0305) & (0.0425) & (0.0427) \tabularnewline
reviews;blogs & 0.8757 & 0.8943 & 0.7156 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197404&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]time;pop[/C][C]0.4638[/C][C]0.5023[/C][C]0.4108[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]time;gender[/C][C]0.1409[/C][C]0.1483[/C][C]0.1213[/C][/ROW]
[ROW][C]p-value[/C][C](0.0167)[/C][C](0.0117)[/C][C](0.012)[/C][/ROW]
[ROW][C]time;reviews[/C][C]0.7823[/C][C]0.841[/C][C]0.639[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]time;blogs[/C][C]0.8138[/C][C]0.8572[/C][C]0.6648[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]pop;gender[/C][C]0.1966[/C][C]0.1966[/C][C]0.1966[/C][/ROW]
[ROW][C]p-value[/C][C](8e-04)[/C][C](8e-04)[/C][C](9e-04)[/C][/ROW]
[ROW][C]pop;reviews[/C][C]0.4719[/C][C]0.4791[/C][C]0.3919[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]pop;blogs[/C][C]0.4639[/C][C]0.491[/C][C]0.4029[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]gender;reviews[/C][C]0.1446[/C][C]0.1608[/C][C]0.1315[/C][/ROW]
[ROW][C]p-value[/C][C](0.014)[/C][C](0.0062)[/C][C](0.0064)[/C][/ROW]
[ROW][C]gender;blogs[/C][C]0.1275[/C][C]0.1196[/C][C]0.0982[/C][/ROW]
[ROW][C]p-value[/C][C](0.0305)[/C][C](0.0425)[/C][C](0.0427)[/C][/ROW]
[ROW][C]reviews;blogs[/C][C]0.8757[/C][C]0.8943[/C][C]0.7156[/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=197404&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197404&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
time;pop0.46380.50230.4108
p-value(0)(0)(0)
time;gender0.14090.14830.1213
p-value(0.0167)(0.0117)(0.012)
time;reviews0.78230.8410.639
p-value(0)(0)(0)
time;blogs0.81380.85720.6648
p-value(0)(0)(0)
pop;gender0.19660.19660.1966
p-value(8e-04)(8e-04)(9e-04)
pop;reviews0.47190.47910.3919
p-value(0)(0)(0)
pop;blogs0.46390.4910.4029
p-value(0)(0)(0)
gender;reviews0.14460.16080.1315
p-value(0.014)(0.0062)(0.0064)
gender;blogs0.12750.11960.0982
p-value(0.0305)(0.0425)(0.0427)
reviews;blogs0.87570.89430.7156
p-value(0)(0)(0)



Parameters (Session):
par1 = 2 ; par2 = none ; par3 = 3 ; par4 = no ;
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')