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Author*The author of this computation has been verified*
R Software ModulePatrick.Wessarwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationFri, 10 Dec 2010 12:28:14 +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/10/t12919840152a47kj3822aopd5.htm/, Retrieved Mon, 29 Apr 2024 14:00:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107605, Retrieved Mon, 29 Apr 2024 14:00:37 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116
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 pearsson] [2010-12-10 12:28:14] [e926a978b40506c05812140b9c5157ab] [Current]
-    D      [Kendall tau Correlation Matrix] [ws 10 pearsson] [2010-12-10 12:38:22] [4eaa304e6a28c475ba490fccf4c01ad3]
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Dataseries X:
0	1	24	14	11	12	24	26
1	1	25	11	7	8	25	23
1	0	17	6	17	8	30	25
0	1	18	12	10	8	19	23
1	0	16	10	12	7	22	29
1	1	20	10	11	4	25	25
1	1	16	11	11	11	23	21
1	1	18	16	12	7	17	22
1	1	17	11	13	7	21	25
0	1	23	13	14	12	19	24
1	1	30	12	16	10	19	18
1	1	18	12	10	8	16	15
0	1	15	11	11	8	23	22
0	1	12	4	15	4	27	28
1	1	21	9	9	9	22	20
0	1	20	8	17	7	22	24
1	1	27	15	11	9	23	21
0	1	34	16	18	11	21	20
1	1	21	9	14	13	19	21
0	1	31	14	10	8	18	23
0	1	19	11	11	8	20	28
1	1	16	8	15	9	23	24
1	1	20	9	15	6	25	24
0	1	21	9	13	9	19	24
0	1	22	9	16	9	24	23
1	1	17	9	13	6	22	23
0	1	24	10	9	6	25	29
1	1	25	16	18	16	26	24
1	1	26	11	18	5	29	18
1	1	25	8	12	7	32	25
1	1	17	9	17	9	25	21
0	1	32	16	9	6	29	26
0	1	33	11	9	6	28	22
0	0	32	12	18	12	28	22
0	1	25	12	12	7	29	23
0	1	29	14	18	10	26	30
1	1	22	9	14	9	25	23
0	1	18	10	15	8	14	17
1	1	17	9	16	5	25	23
0	1	20	10	10	8	26	23
0	1	15	12	11	8	20	25
1	1	20	14	14	10	18	24
0	1	33	14	9	6	32	24
1	1	23	14	17	7	25	21
0	1	26	16	5	4	23	24
0	1	18	9	12	8	21	24
1	1	20	10	12	8	20	28
1	1	11	6	6	4	15	16
0	1	28	8	24	20	30	20
1	1	26	13	12	8	24	29
1	1	22	10	12	8	26	27
0	1	17	8	14	6	24	22
0	1	12	7	7	4	22	28
0	1	17	9	12	9	24	25
1	0	19	12	14	7	24	28
0	1	18	13	8	9	24	24
0	1	10	10	11	5	19	23
0	1	29	11	9	5	31	30
0	1	31	8	11	8	22	24
0	1	9	13	10	6	19	25
1	0	20	11	11	8	25	25
1	1	28	8	12	7	20	22
1	1	19	9	9	7	21	23
1	1	29	15	18	11	23	23
1	1	26	9	15	6	25	25
1	1	23	10	12	8	20	21
0	1	13	14	13	6	21	25
1	1	21	12	14	9	22	24
0	1	19	12	10	8	23	29
1	1	28	11	13	6	25	22
1	1	23	14	13	10	25	27
1	0	18	6	11	8	17	26
0	1	21	12	13	8	19	22
1	1	20	8	16	10	25	24
1	1	21	10	11	5	26	24
1	1	28	12	16	14	27	22
0	1	26	14	14	8	17	24
1	1	10	5	8	6	19	24
0	0	16	11	9	5	17	23
0	1	22	10	15	6	22	20
0	1	19	9	11	10	21	27
1	1	31	10	21	12	32	26
0	1	31	16	14	9	21	25
1	1	29	13	18	12	21	21
0	1	19	9	12	7	18	21
1	1	22	10	13	8	18	19
0	1	15	7	12	6	19	21
1	1	20	9	19	10	20	16
0	1	23	14	11	10	20	29
1	1	24	9	13	10	19	15
1	1	25	14	15	11	22	21
1	1	13	8	12	7	14	19
1	1	28	8	16	12	18	24
1	0	25	7	18	11	35	17
1	1	9	6	8	11	29	23
0	1	17	11	9	6	20	19
0	1	25	14	15	9	22	24
1	1	15	8	6	6	20	25
0	1	19	20	8	7	19	25
1	0	15	8	10	4	22	24
1	1	20	11	11	8	24	26
1	1	18	10	14	9	21	26
1	1	33	14	11	8	26	25
1	1	16	9	12	8	16	21
0	1	17	9	11	5	23	26
1	1	16	8	9	4	18	23
0	1	21	10	12	8	16	23
0	1	26	13	20	10	26	22
1	1	18	12	13	9	21	13
1	1	22	13	12	13	22	15
1	1	30	14	9	9	23	14
1	1	24	14	24	20	21	10
1	1	29	16	11	6	27	24
1	1	31	9	17	9	25	19
1	0	20	9	11	7	21	20
1	1	20	7	11	9	26	22
1	1	28	16	16	8	24	24
1	1	17	9	13	6	19	21
0	1	28	14	11	8	24	24
1	1	31	16	19	16	17	20
70	110	2607	1309	1538	996	2707	2752




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107605&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107605&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107605&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'George Udny Yule' @ 72.249.76.132







Correlations for all pairs of data series (method=pearson)
genderbrowsercomdoapepcpso
gender10.9960.9970.9960.9970.9970.9970.997
browser0.99610.9990.9990.9990.9990.9990.999
com0.9970.9991110.99911
doa0.9960.999110.9990.99911
pe0.9970.99910.9991110.999
pc0.9970.9990.9990.999110.9990.999
ps0.9970.9991110.99911
o0.9970.999110.9990.99911

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & gender & browser & com & doa & pe & pc & ps & o \tabularnewline
gender & 1 & 0.996 & 0.997 & 0.996 & 0.997 & 0.997 & 0.997 & 0.997 \tabularnewline
browser & 0.996 & 1 & 0.999 & 0.999 & 0.999 & 0.999 & 0.999 & 0.999 \tabularnewline
com & 0.997 & 0.999 & 1 & 1 & 1 & 0.999 & 1 & 1 \tabularnewline
doa & 0.996 & 0.999 & 1 & 1 & 0.999 & 0.999 & 1 & 1 \tabularnewline
pe & 0.997 & 0.999 & 1 & 0.999 & 1 & 1 & 1 & 0.999 \tabularnewline
pc & 0.997 & 0.999 & 0.999 & 0.999 & 1 & 1 & 0.999 & 0.999 \tabularnewline
ps & 0.997 & 0.999 & 1 & 1 & 1 & 0.999 & 1 & 1 \tabularnewline
o & 0.997 & 0.999 & 1 & 1 & 0.999 & 0.999 & 1 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107605&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]gender[/C][C]browser[/C][C]com[/C][C]doa[/C][C]pe[/C][C]pc[/C][C]ps[/C][C]o[/C][/ROW]
[ROW][C]gender[/C][C]1[/C][C]0.996[/C][C]0.997[/C][C]0.996[/C][C]0.997[/C][C]0.997[/C][C]0.997[/C][C]0.997[/C][/ROW]
[ROW][C]browser[/C][C]0.996[/C][C]1[/C][C]0.999[/C][C]0.999[/C][C]0.999[/C][C]0.999[/C][C]0.999[/C][C]0.999[/C][/ROW]
[ROW][C]com[/C][C]0.997[/C][C]0.999[/C][C]1[/C][C]1[/C][C]1[/C][C]0.999[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]doa[/C][C]0.996[/C][C]0.999[/C][C]1[/C][C]1[/C][C]0.999[/C][C]0.999[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]pe[/C][C]0.997[/C][C]0.999[/C][C]1[/C][C]0.999[/C][C]1[/C][C]1[/C][C]1[/C][C]0.999[/C][/ROW]
[ROW][C]pc[/C][C]0.997[/C][C]0.999[/C][C]0.999[/C][C]0.999[/C][C]1[/C][C]1[/C][C]0.999[/C][C]0.999[/C][/ROW]
[ROW][C]ps[/C][C]0.997[/C][C]0.999[/C][C]1[/C][C]1[/C][C]1[/C][C]0.999[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]o[/C][C]0.997[/C][C]0.999[/C][C]1[/C][C]1[/C][C]0.999[/C][C]0.999[/C][C]1[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107605&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107605&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)
genderbrowsercomdoapepcpso
gender10.9960.9970.9960.9970.9970.9970.997
browser0.99610.9990.9990.9990.9990.9990.999
com0.9970.9991110.99911
doa0.9960.999110.9990.99911
pe0.9970.99910.9991110.999
pc0.9970.9990.9990.999110.9990.999
ps0.9970.9991110.99911
o0.9970.999110.9990.99911







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
gender;browser0.9963-0.0661-0.0666
p-value(0)(0.4713)(0.4621)
gender;com0.99660.0240.02
p-value(0)(0.7941)(0.7932)
gender;doa0.9964-0.1334-0.1153
p-value(0)(0.1447)(0.14)
gender;pe0.99690.2130.1821
p-value(0)(0.019)(0.0188)
gender;pc0.99680.16760.1454
p-value(0)(0.0661)(0.0645)
gender;ps0.99690.07730.0654
p-value(0)(0.3997)(0.395)
gender;o0.9966-0.1941-0.1667
p-value(0)(0.0329)(0.0318)
browser;com0.99940.17210.1445
p-value(0)(0.0592)(0.058)
browser;doa0.99940.20590.1774
p-value(0)(0.0235)(0.0232)
browser;pe0.99930.04020.0341
p-value(0)(0.6615)(0.6603)
browser;pc0.99920.11170.0968
p-value(0)(0.2224)(0.2188)
browser;ps0.9994-0.0188-0.0164
p-value(0)(0.8376)(0.8317)
browser;o0.9995-0.0345-0.0299
p-value(0)(0.7072)(0.6998)
com;doa0.99970.49460.3817
p-value(0)(0)(0)
com;pe0.99960.32140.2475
p-value(0)(3e-04)(2e-04)
com;pc0.99950.38890.3004
p-value(0)(0)(0)
com;ps0.99970.3740.279
p-value(0)(0)(0)
com;o0.9996-0.0499-0.0362
p-value(0)(0.5864)(0.5797)
doa;pe0.99940.06550.0426
p-value(0)(0.4755)(0.5248)
doa;pc0.99940.25190.1939
p-value(0)(0.0053)(0.0043)
doa;ps0.99960.04640.0358
p-value(0)(0.6135)(0.5897)
doa;o0.99960.08370.0581
p-value(0)(0.3612)(0.3864)
pe;pc0.99970.49390.3848
p-value(0)(0)(0)
pe;ps0.99960.16370.1263
p-value(0)(0.0729)(0.0554)
pe;o0.9995-0.1953-0.149
p-value(0)(0.0318)(0.0251)
pc;ps0.99940.05060.0385
p-value(0)(0.5814)(0.5651)
pc;o0.9993-0.1737-0.1288
p-value(0)(0.0567)(0.0565)
ps;o0.99980.26750.1928
p-value(0)(0.003)(0.0035)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
gender;browser & 0.9963 & -0.0661 & -0.0666 \tabularnewline
p-value & (0) & (0.4713) & (0.4621) \tabularnewline
gender;com & 0.9966 & 0.024 & 0.02 \tabularnewline
p-value & (0) & (0.7941) & (0.7932) \tabularnewline
gender;doa & 0.9964 & -0.1334 & -0.1153 \tabularnewline
p-value & (0) & (0.1447) & (0.14) \tabularnewline
gender;pe & 0.9969 & 0.213 & 0.1821 \tabularnewline
p-value & (0) & (0.019) & (0.0188) \tabularnewline
gender;pc & 0.9968 & 0.1676 & 0.1454 \tabularnewline
p-value & (0) & (0.0661) & (0.0645) \tabularnewline
gender;ps & 0.9969 & 0.0773 & 0.0654 \tabularnewline
p-value & (0) & (0.3997) & (0.395) \tabularnewline
gender;o & 0.9966 & -0.1941 & -0.1667 \tabularnewline
p-value & (0) & (0.0329) & (0.0318) \tabularnewline
browser;com & 0.9994 & 0.1721 & 0.1445 \tabularnewline
p-value & (0) & (0.0592) & (0.058) \tabularnewline
browser;doa & 0.9994 & 0.2059 & 0.1774 \tabularnewline
p-value & (0) & (0.0235) & (0.0232) \tabularnewline
browser;pe & 0.9993 & 0.0402 & 0.0341 \tabularnewline
p-value & (0) & (0.6615) & (0.6603) \tabularnewline
browser;pc & 0.9992 & 0.1117 & 0.0968 \tabularnewline
p-value & (0) & (0.2224) & (0.2188) \tabularnewline
browser;ps & 0.9994 & -0.0188 & -0.0164 \tabularnewline
p-value & (0) & (0.8376) & (0.8317) \tabularnewline
browser;o & 0.9995 & -0.0345 & -0.0299 \tabularnewline
p-value & (0) & (0.7072) & (0.6998) \tabularnewline
com;doa & 0.9997 & 0.4946 & 0.3817 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
com;pe & 0.9996 & 0.3214 & 0.2475 \tabularnewline
p-value & (0) & (3e-04) & (2e-04) \tabularnewline
com;pc & 0.9995 & 0.3889 & 0.3004 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
com;ps & 0.9997 & 0.374 & 0.279 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
com;o & 0.9996 & -0.0499 & -0.0362 \tabularnewline
p-value & (0) & (0.5864) & (0.5797) \tabularnewline
doa;pe & 0.9994 & 0.0655 & 0.0426 \tabularnewline
p-value & (0) & (0.4755) & (0.5248) \tabularnewline
doa;pc & 0.9994 & 0.2519 & 0.1939 \tabularnewline
p-value & (0) & (0.0053) & (0.0043) \tabularnewline
doa;ps & 0.9996 & 0.0464 & 0.0358 \tabularnewline
p-value & (0) & (0.6135) & (0.5897) \tabularnewline
doa;o & 0.9996 & 0.0837 & 0.0581 \tabularnewline
p-value & (0) & (0.3612) & (0.3864) \tabularnewline
pe;pc & 0.9997 & 0.4939 & 0.3848 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
pe;ps & 0.9996 & 0.1637 & 0.1263 \tabularnewline
p-value & (0) & (0.0729) & (0.0554) \tabularnewline
pe;o & 0.9995 & -0.1953 & -0.149 \tabularnewline
p-value & (0) & (0.0318) & (0.0251) \tabularnewline
pc;ps & 0.9994 & 0.0506 & 0.0385 \tabularnewline
p-value & (0) & (0.5814) & (0.5651) \tabularnewline
pc;o & 0.9993 & -0.1737 & -0.1288 \tabularnewline
p-value & (0) & (0.0567) & (0.0565) \tabularnewline
ps;o & 0.9998 & 0.2675 & 0.1928 \tabularnewline
p-value & (0) & (0.003) & (0.0035) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107605&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]gender;browser[/C][C]0.9963[/C][C]-0.0661[/C][C]-0.0666[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.4713)[/C][C](0.4621)[/C][/ROW]
[ROW][C]gender;com[/C][C]0.9966[/C][C]0.024[/C][C]0.02[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.7941)[/C][C](0.7932)[/C][/ROW]
[ROW][C]gender;doa[/C][C]0.9964[/C][C]-0.1334[/C][C]-0.1153[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.1447)[/C][C](0.14)[/C][/ROW]
[ROW][C]gender;pe[/C][C]0.9969[/C][C]0.213[/C][C]0.1821[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.019)[/C][C](0.0188)[/C][/ROW]
[ROW][C]gender;pc[/C][C]0.9968[/C][C]0.1676[/C][C]0.1454[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.0661)[/C][C](0.0645)[/C][/ROW]
[ROW][C]gender;ps[/C][C]0.9969[/C][C]0.0773[/C][C]0.0654[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.3997)[/C][C](0.395)[/C][/ROW]
[ROW][C]gender;o[/C][C]0.9966[/C][C]-0.1941[/C][C]-0.1667[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.0329)[/C][C](0.0318)[/C][/ROW]
[ROW][C]browser;com[/C][C]0.9994[/C][C]0.1721[/C][C]0.1445[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.0592)[/C][C](0.058)[/C][/ROW]
[ROW][C]browser;doa[/C][C]0.9994[/C][C]0.2059[/C][C]0.1774[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.0235)[/C][C](0.0232)[/C][/ROW]
[ROW][C]browser;pe[/C][C]0.9993[/C][C]0.0402[/C][C]0.0341[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.6615)[/C][C](0.6603)[/C][/ROW]
[ROW][C]browser;pc[/C][C]0.9992[/C][C]0.1117[/C][C]0.0968[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.2224)[/C][C](0.2188)[/C][/ROW]
[ROW][C]browser;ps[/C][C]0.9994[/C][C]-0.0188[/C][C]-0.0164[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.8376)[/C][C](0.8317)[/C][/ROW]
[ROW][C]browser;o[/C][C]0.9995[/C][C]-0.0345[/C][C]-0.0299[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.7072)[/C][C](0.6998)[/C][/ROW]
[ROW][C]com;doa[/C][C]0.9997[/C][C]0.4946[/C][C]0.3817[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]com;pe[/C][C]0.9996[/C][C]0.3214[/C][C]0.2475[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](3e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]com;pc[/C][C]0.9995[/C][C]0.3889[/C][C]0.3004[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]com;ps[/C][C]0.9997[/C][C]0.374[/C][C]0.279[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]com;o[/C][C]0.9996[/C][C]-0.0499[/C][C]-0.0362[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.5864)[/C][C](0.5797)[/C][/ROW]
[ROW][C]doa;pe[/C][C]0.9994[/C][C]0.0655[/C][C]0.0426[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.4755)[/C][C](0.5248)[/C][/ROW]
[ROW][C]doa;pc[/C][C]0.9994[/C][C]0.2519[/C][C]0.1939[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.0053)[/C][C](0.0043)[/C][/ROW]
[ROW][C]doa;ps[/C][C]0.9996[/C][C]0.0464[/C][C]0.0358[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.6135)[/C][C](0.5897)[/C][/ROW]
[ROW][C]doa;o[/C][C]0.9996[/C][C]0.0837[/C][C]0.0581[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.3612)[/C][C](0.3864)[/C][/ROW]
[ROW][C]pe;pc[/C][C]0.9997[/C][C]0.4939[/C][C]0.3848[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]pe;ps[/C][C]0.9996[/C][C]0.1637[/C][C]0.1263[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.0729)[/C][C](0.0554)[/C][/ROW]
[ROW][C]pe;o[/C][C]0.9995[/C][C]-0.1953[/C][C]-0.149[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.0318)[/C][C](0.0251)[/C][/ROW]
[ROW][C]pc;ps[/C][C]0.9994[/C][C]0.0506[/C][C]0.0385[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.5814)[/C][C](0.5651)[/C][/ROW]
[ROW][C]pc;o[/C][C]0.9993[/C][C]-0.1737[/C][C]-0.1288[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.0567)[/C][C](0.0565)[/C][/ROW]
[ROW][C]ps;o[/C][C]0.9998[/C][C]0.2675[/C][C]0.1928[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.003)[/C][C](0.0035)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107605&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107605&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
gender;browser0.9963-0.0661-0.0666
p-value(0)(0.4713)(0.4621)
gender;com0.99660.0240.02
p-value(0)(0.7941)(0.7932)
gender;doa0.9964-0.1334-0.1153
p-value(0)(0.1447)(0.14)
gender;pe0.99690.2130.1821
p-value(0)(0.019)(0.0188)
gender;pc0.99680.16760.1454
p-value(0)(0.0661)(0.0645)
gender;ps0.99690.07730.0654
p-value(0)(0.3997)(0.395)
gender;o0.9966-0.1941-0.1667
p-value(0)(0.0329)(0.0318)
browser;com0.99940.17210.1445
p-value(0)(0.0592)(0.058)
browser;doa0.99940.20590.1774
p-value(0)(0.0235)(0.0232)
browser;pe0.99930.04020.0341
p-value(0)(0.6615)(0.6603)
browser;pc0.99920.11170.0968
p-value(0)(0.2224)(0.2188)
browser;ps0.9994-0.0188-0.0164
p-value(0)(0.8376)(0.8317)
browser;o0.9995-0.0345-0.0299
p-value(0)(0.7072)(0.6998)
com;doa0.99970.49460.3817
p-value(0)(0)(0)
com;pe0.99960.32140.2475
p-value(0)(3e-04)(2e-04)
com;pc0.99950.38890.3004
p-value(0)(0)(0)
com;ps0.99970.3740.279
p-value(0)(0)(0)
com;o0.9996-0.0499-0.0362
p-value(0)(0.5864)(0.5797)
doa;pe0.99940.06550.0426
p-value(0)(0.4755)(0.5248)
doa;pc0.99940.25190.1939
p-value(0)(0.0053)(0.0043)
doa;ps0.99960.04640.0358
p-value(0)(0.6135)(0.5897)
doa;o0.99960.08370.0581
p-value(0)(0.3612)(0.3864)
pe;pc0.99970.49390.3848
p-value(0)(0)(0)
pe;ps0.99960.16370.1263
p-value(0)(0.0729)(0.0554)
pe;o0.9995-0.1953-0.149
p-value(0)(0.0318)(0.0251)
pc;ps0.99940.05060.0385
p-value(0)(0.5814)(0.5651)
pc;o0.9993-0.1737-0.1288
p-value(0)(0.0567)(0.0565)
ps;o0.99980.26750.1928
p-value(0)(0.003)(0.0035)



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')