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Author's title

Author*Unverified author*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationTue, 11 Dec 2012 08:57:09 -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/11/t1355234238qggi58t8slebqor.htm/, Retrieved Fri, 29 Mar 2024 09:55:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198489, Retrieved Fri, 29 Mar 2024 09:55:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact117
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [WS10] [2011-12-09 08:45:50] [09e53a95f5780167f20e6b4304200573]
- R       [Kendall tau Correlation Matrix] [] [2012-12-11 13:57:09] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
293403	111	74	91256	123	119

277108	70	69	86997	64	64

264020	76	76	55709	101	100

260646	109	60	75741	104	104

246100	81	89	92046	135	135

244051	67	111	84607	130	124

241329	54	57	73586	93	93

234730	106	116	162365	159	155

234509	125	122	70817	125	120

233482	68	90	59635	81	78

233406	96	85	109104	117	117

228548	106	65	120087	205	198

223914	104	89	72631	115	110

223696	88	82	104911	115	114

223004	87	84	85224	147	137

213765	84	56	58233	150	150

210554	81	73	117986	126	124

202204	44	79	67271	61	56

199512	75	59	55071	82	82

195304	93	47	114425	152	145

191467	76	75	79194	109	104

191381	87	71	101653	210	212

191276	112	90	81493	151	141

190410	84	107	64664	96	94

188967	86	75	63717	98	94

188780	98	85	72369	98	98

185139	121	83	86281	128	126

185039	94	73	63958	100	98

184217	69	45	73795	74	74

181853	87	93	96750	92	91

181379	92	123	83038	101	96

181344	75	114	65196	109	108

179562	76	89	62932	116	116

178863	86	78	57637	88	87

178140	56	91	70111	83	78

176789	115	66	123328	149	149

176460	97	55	38885	122	122

175877	95	81	54628	96	95

175568	106	80	74482	105	102

174107	49	71	76168	95	91

173587	70	70	71170	97	95

173260	41	78	37238	16	15

172684	87	112	101773	103	102

167845	105	77	103646	145	145

167131	71	69	37048	56	56

167105	56	32	85903	75	71

166790	49	59	43460	46	46

164767	51	87	90257	81	80

162810	49	76	70027	83	80

162336	111	84	111436	153	151

161678	75	59	65911	87	83

158980	84	75	105965	123	122

157250	84	106	61704	104	104

156833	79	73	48204	85	85

155383	83	75	60029	99	99

154991	63	87	52295	99	98

154730	78	82	82204	98	98

151503	93	83	56316	99	98

146455	65	68	95556	127	128

143937	98	66	78792	140	139

142339	75	67	125410	144	142

142146	108	88	76013	152	139

142141	73	87	91939	61	61

142069	66	88	57231	83	82

141933	90	75	51370	100	99

139350	70	79	99518	89	88

139144	57	76	56530	75	75

137793	70	78	56699	77	77

136911	95	86	74349	117	103

136548	89	62	83042	158	157

135171	80	61	71181	82	82

134043	54	69	55901	57	54

131876	27	83	38417	36	36

131122	56	50	65724	89	89

130539	60	47	48821	66	66

130533	64	76	85168	78	79

130232	102	83	55027	107	105

129100	38	60	73713	87	87

128655	75	70	79774	111	108

128066	42	48	42564	80	80

127619	49	50	36311	52	50

127324	79	87	56733	104	101

126683	71	123	63262	72	71

126681	39	90	94137	67	66

125971	61	45	38439	71	71

125366	69	22	34497	68	68

122433	51	91	58425	66	66

121135	50	51	42051	69	68

119291	83	38	64102	123	120

118958	52	68	54506	61	58

118807	56	81	55827	70	70

118372	72	35	66477	142	145

116900	42	36	28340	58	57

116775	30	83	73087	124	112

115199	84	54	51360	87	87

114928	44	72	53009	96	91

114397	70	65	55064	87	85

113337	58	37	63016	68	68

111664	55	59	38650	98	98

108715	64	35	40671	80	78

107342	77	53	82043	116	111

107335	48	61	49319	65	64

106539	36	68	77411	63	63

105615	57	70	202316	51	48

105410	62	72	89041	88	86

105324	42	71	26982	46	46

103012	30	37	29467	28	26

102531	46	63	40001	64	63

101324	81	104	70780	103	100

100885	39	29	49288	49	48

100672	38	69	50466	55	55

99946	106	80	99501	125	119

99768	24	62	15430	27	27

99246	27	63	37361	52	51

98599	48	55	36252	46	44

98030	30	41	31701	35	35

94763	94	75	56979	100	99

93340	41	63	43448	60	60

93125	30	29	50838	37	36

91185	57	66	21067	67	67

90961	42	78	63785	49	49

90938	40	51	37137	43	42

89318	75	78	44970	82	81

88817	70	60	46765	56	56

84944	54	72	54565	90	89

84572	43	82	72571	84	84

84256	97	58	59155	76	75

80953	49	27	56622	59	58

78800	20	66	33032	21	21

78776	30	18	26998	34	34

75812	28	57	35606	30	30

75426	3	19	47261	36	33

74398	41	30	31258	51	51

74112	28	54	174949	52	52

73567	37	31	23238	18	18

69471	22	63	22618	26	25

68948	31	47	35838	45	43

67746	18	35	62832	58	56

67507	101	112	78956	49	49

65029	21	61	32551	21	21

64320	16	56	62147	24	23

61857	23	30	25162	31	28

61499	28	75	36990	15	15

50999	2	66	63989	8	8

46660	12	13	6179	13	13

43287	13	64	43750	49	49

38214	16	21	8773	16	16

35523	0	53	52491	33	33

32750	1	22	22807	5	5

31414	18	9	14116	39	39

24188	8	7	5950	7	7

22938	12	0	1168	11	11

21054	4	0	855	4	4

17547	0	4	3926	3	3

14688	4	0	6023	5	5

7199	7	0	1644	6	6

969	0	0	0	0	0

455	0	0	0	0	0

203	0	0	0	0	0

98	0	0	0	0	0

0	0	0	0	0	0

0	0	0	0	0	0

0	0	0	0	0	0

0	0	0	0	0	0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=198489&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=198489&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198489&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 time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Correlations for all pairs of data series (method=pearson)
YX1X2X3X4X5
Y10.7750.6770.6270.7510.75
X10.77510.6850.6390.8570.857
X20.6770.68510.6190.6130.609
X30.6270.6390.61910.7070.705
X40.7510.8570.6130.70710.999
X50.750.8570.6090.7050.9991

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Y & X1 & X2 & X3 & X4 & X5 \tabularnewline
Y & 1 & 0.775 & 0.677 & 0.627 & 0.751 & 0.75 \tabularnewline
X1 & 0.775 & 1 & 0.685 & 0.639 & 0.857 & 0.857 \tabularnewline
X2 & 0.677 & 0.685 & 1 & 0.619 & 0.613 & 0.609 \tabularnewline
X3 & 0.627 & 0.639 & 0.619 & 1 & 0.707 & 0.705 \tabularnewline
X4 & 0.751 & 0.857 & 0.613 & 0.707 & 1 & 0.999 \tabularnewline
X5 & 0.75 & 0.857 & 0.609 & 0.705 & 0.999 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198489&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Y[/C][C]X1[/C][C]X2[/C][C]X3[/C][C]X4[/C][C]X5[/C][/ROW]
[ROW][C]Y[/C][C]1[/C][C]0.775[/C][C]0.677[/C][C]0.627[/C][C]0.751[/C][C]0.75[/C][/ROW]
[ROW][C]X1[/C][C]0.775[/C][C]1[/C][C]0.685[/C][C]0.639[/C][C]0.857[/C][C]0.857[/C][/ROW]
[ROW][C]X2[/C][C]0.677[/C][C]0.685[/C][C]1[/C][C]0.619[/C][C]0.613[/C][C]0.609[/C][/ROW]
[ROW][C]X3[/C][C]0.627[/C][C]0.639[/C][C]0.619[/C][C]1[/C][C]0.707[/C][C]0.705[/C][/ROW]
[ROW][C]X4[/C][C]0.751[/C][C]0.857[/C][C]0.613[/C][C]0.707[/C][C]1[/C][C]0.999[/C][/ROW]
[ROW][C]X5[/C][C]0.75[/C][C]0.857[/C][C]0.609[/C][C]0.705[/C][C]0.999[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198489&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198489&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)
YX1X2X3X4X5
Y10.7750.6770.6270.7510.75
X10.77510.6850.6390.8570.857
X20.6770.68510.6190.6130.609
X30.6270.6390.61910.7070.705
X40.7510.8570.6130.70710.999
X50.750.8570.6090.7050.9991







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Y;X10.77540.75890.5916
p-value(0)(0)(0)
Y;X20.67660.62190.4575
p-value(0)(0)(0)
Y;X30.62670.67980.5073
p-value(0)(0)(0)
Y;X40.75130.76760.5924
p-value(0)(0)(0)
Y;X50.75050.76550.5899
p-value(0)(0)(0)
X1;X20.68450.62040.4521
p-value(0)(0)(0)
X1;X30.63860.68530.5135
p-value(0)(0)(0)
X1;X40.85690.870.7057
p-value(0)(0)(0)
X1;X50.85690.87090.7059
p-value(0)(0)(0)
X2;X30.61930.61380.4502
p-value(0)(0)(0)
X2;X40.61310.59390.431
p-value(0)(0)(0)
X2;X50.60870.58440.4243
p-value(0)(0)(0)
X3;X40.70690.76470.5966
p-value(0)(0)(0)
X3;X50.70510.75960.5924
p-value(0)(0)(0)
X4;X50.99860.99870.9809
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
Y;X1 & 0.7754 & 0.7589 & 0.5916 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Y;X2 & 0.6766 & 0.6219 & 0.4575 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Y;X3 & 0.6267 & 0.6798 & 0.5073 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Y;X4 & 0.7513 & 0.7676 & 0.5924 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Y;X5 & 0.7505 & 0.7655 & 0.5899 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X1;X2 & 0.6845 & 0.6204 & 0.4521 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X1;X3 & 0.6386 & 0.6853 & 0.5135 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X1;X4 & 0.8569 & 0.87 & 0.7057 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X1;X5 & 0.8569 & 0.8709 & 0.7059 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X2;X3 & 0.6193 & 0.6138 & 0.4502 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X2;X4 & 0.6131 & 0.5939 & 0.431 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X2;X5 & 0.6087 & 0.5844 & 0.4243 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X3;X4 & 0.7069 & 0.7647 & 0.5966 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X3;X5 & 0.7051 & 0.7596 & 0.5924 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X4;X5 & 0.9986 & 0.9987 & 0.9809 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198489&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]Y;X1[/C][C]0.7754[/C][C]0.7589[/C][C]0.5916[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Y;X2[/C][C]0.6766[/C][C]0.6219[/C][C]0.4575[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Y;X3[/C][C]0.6267[/C][C]0.6798[/C][C]0.5073[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Y;X4[/C][C]0.7513[/C][C]0.7676[/C][C]0.5924[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Y;X5[/C][C]0.7505[/C][C]0.7655[/C][C]0.5899[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X1;X2[/C][C]0.6845[/C][C]0.6204[/C][C]0.4521[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X1;X3[/C][C]0.6386[/C][C]0.6853[/C][C]0.5135[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X1;X4[/C][C]0.8569[/C][C]0.87[/C][C]0.7057[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X1;X5[/C][C]0.8569[/C][C]0.8709[/C][C]0.7059[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X2;X3[/C][C]0.6193[/C][C]0.6138[/C][C]0.4502[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X2;X4[/C][C]0.6131[/C][C]0.5939[/C][C]0.431[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X2;X5[/C][C]0.6087[/C][C]0.5844[/C][C]0.4243[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X3;X4[/C][C]0.7069[/C][C]0.7647[/C][C]0.5966[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X3;X5[/C][C]0.7051[/C][C]0.7596[/C][C]0.5924[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X4;X5[/C][C]0.9986[/C][C]0.9987[/C][C]0.9809[/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=198489&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198489&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
Y;X10.77540.75890.5916
p-value(0)(0)(0)
Y;X20.67660.62190.4575
p-value(0)(0)(0)
Y;X30.62670.67980.5073
p-value(0)(0)(0)
Y;X40.75130.76760.5924
p-value(0)(0)(0)
Y;X50.75050.76550.5899
p-value(0)(0)(0)
X1;X20.68450.62040.4521
p-value(0)(0)(0)
X1;X30.63860.68530.5135
p-value(0)(0)(0)
X1;X40.85690.870.7057
p-value(0)(0)(0)
X1;X50.85690.87090.7059
p-value(0)(0)(0)
X2;X30.61930.61380.4502
p-value(0)(0)(0)
X2;X40.61310.59390.431
p-value(0)(0)(0)
X2;X50.60870.58440.4243
p-value(0)(0)(0)
X3;X40.70690.76470.5966
p-value(0)(0)(0)
X3;X50.70510.75960.5924
p-value(0)(0)(0)
X4;X50.99860.99870.9809
p-value(0)(0)(0)



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')