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Author

*The author of this computation has been verified*

R Software Module

Patrick.Wessarwasp_pairs.wasp

Title produced by software

Kendall tau Correlation Matrix

Date of computation

Thu, 16 Dec 2010 21:25:58 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/16/t12925346856mcvvlblbsnajgv.htm/, Retrieved Fri, 03 May 2024 13:51:23 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=111291, Retrieved Fri, 03 May 2024 13:51:23 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

150

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Multiple Regression] [Multiple Regressi...] [2010-12-14 23:59:54] [2843717cd92615903379c14ebee3c5df]
-    D  [Multiple Regression] [Multiple Regressi...] [2010-12-15 18:56:10] [2843717cd92615903379c14ebee3c5df]
-    D    [Multiple Regression] [Multiple Regressi...] [2010-12-15 22:44:30] [2843717cd92615903379c14ebee3c5df]
- RMPD      [Kendall tau Correlation Matrix] [Pearson Correlati...] [2010-12-16 18:18:52] [2843717cd92615903379c14ebee3c5df]
-   P           [Kendall tau Correlation Matrix] [Kendall's tau Cor...] [2010-12-16 21:25:58] [dfb0309aec67f282200eef05efe0d5bd] [Current]

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Dataseries X:

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0	13	26	9	15	25	25
0	16	20	9	15	25	24
0	19	21	9	14	19	21
1	15	31	14	10	18	23
0	14	21	8	10	18	17
0	13	18	8	12	22	19
0	19	26	11	18	29	18
0	15	22	10	12	26	27
0	14	22	9	14	25	23
0	15	29	15	18	23	23
1	16	15	14	9	23	29
0	16	16	11	11	23	21
1	16	24	14	11	24	26
0	17	17	6	17	30	25
1	15	19	20	8	19	25
1	15	22	9	16	24	23
0	20	31	10	21	32	26
1	18	28	8	24	30	20
0	16	38	11	21	29	29
1	16	26	14	14	17	24
0	19	25	11	7	25	23
0	16	25	16	18	26	24
1	17	29	14	18	26	30
0	17	28	11	13	25	22
1	16	15	11	11	23	22
0	15	18	12	13	21	13
1	14	21	9	13	19	24
0	15	25	7	18	35	17
1	12	23	13	14	19	24
0	14	23	10	12	20	21
0	16	19	9	9	21	23
1	14	18	9	12	21	24
1	10	26	16	5	23	24
1	14	18	12	10	19	23
0	16	18	6	11	17	26
1	16	28	14	11	24	24
1	16	17	14	12	15	21
0	14	29	10	12	25	23
1	20	12	4	15	27	28
1	14	25	12	12	29	23
0	14	28	12	16	27	22
0	11	20	14	14	18	24
0	15	17	9	17	25	21
0	16	17	9	13	22	23
1	14	20	10	10	26	23
0	16	31	14	17	23	20
1	14	21	10	12	16	23
1	12	19	9	13	27	21
0	16	23	14	13	25	27
1	9	15	8	11	14	12
0	14	24	9	13	19	15
0	16	28	8	12	20	22
0	16	16	9	12	16	21
1	15	19	9	12	18	21
0	16	21	9	9	22	20
1	12	21	15	7	21	24
1	16	20	8	17	22	24
0	16	16	10	12	22	29
0	14	25	8	12	32	25
0	16	30	14	9	23	14
1	17	29	11	9	31	30
0	18	22	10	13	18	19
1	18	19	12	10	23	29
0	12	33	14	11	26	25
1	16	17	9	12	24	25
1	10	9	13	10	19	25
0	14	14	15	13	14	16
0	18	15	8	6	20	25
1	18	12	7	7	22	28
1	16	21	10	13	24	24
0	16	20	10	11	25	25
0	16	29	13	18	21	21
1	13	33	11	9	28	22
1	16	21	8	9	24	20
1	16	15	12	11	20	25
1	20	19	9	11	21	27
0	16	23	10	15	23	21
1	15	20	11	8	13	13
0	15	20	11	11	24	26
0	16	18	10	14	21	26
1	14	31	16	14	21	25
0	15	18	16	12	17	22
0	12	13	8	12	14	19
0	17	9	6	8	29	23
0	16	20	11	11	25	25
0	15	18	12	10	16	15
0	13	23	14	17	25	21
0	16	17	9	16	25	23
0	16	17	11	13	21	25
0	16	16	8	15	23	24
1	16	31	8	11	22	24
1	14	15	7	12	19	21
0	16	28	16	16	24	24
1	16	26	13	20	26	22
0	20	20	8	16	25	24
1	15	19	11	11	20	28
0	16	25	14	15	22	21
1	13	18	10	15	14	17
0	17	20	10	12	20	28
1	16	33	14	9	32	24
0	12	24	14	24	21	10
0	16	22	10	15	22	20
0	16	32	12	18	28	22
0	17	31	9	17	25	19
1	13	13	16	12	17	22
0	12	18	8	15	21	22
1	18	17	9	11	23	26
0	14	29	16	11	27	24
0	14	22	13	15	22	22
0	13	18	13	12	19	20
0	16	22	8	14	20	20
0	13	25	14	11	17	15
0	16	20	11	20	24	20
0	13	20	9	11	21	20
0	16	17	8	12	21	24
0	15	21	13	17	23	22
0	16	26	13	12	24	29
1	15	10	10	11	19	23
0	17	15	8	10	22	24
0	15	20	7	11	26	22
0	12	14	11	12	17	16
1	16	16	11	9	17	23
1	10	23	14	8	19	27
0	16	11	6	6	15	16
1	14	19	10	12	17	21
0	15	30	9	15	27	26
1	13	21	12	13	19	22
1	15	20	11	17	21	23
0	11	22	14	14	25	19
0	12	30	12	16	19	18
0	16	28	8	16	18	24
1	15	23	14	11	20	29
0	17	23	8	11	15	22
1	16	21	11	16	20	24
0	10	30	12	15	29	22
0	18	22	9	14	19	12
1	13	32	16	9	29	26
0	15	22	11	13	24	18
1	16	15	11	11	23	22
0	16	21	12	14	22	24
0	14	27	15	11	23	21
0	10	22	13	12	22	15
0	17	9	6	8	29	23
0	13	29	11	7	26	22
0	15	20	7	11	26	22
0	16	16	8	13	21	24
0	12	16	8	9	18	23
0	13	16	9	12	10	13

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111291&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]4 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=111291&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111291&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Correlations for all pairs of data series (method=kendall)
	Gender	Learning	Concern	Doubts	Expectations	Standards	Organization
Gender	1	-0.058	-0.08	0.137	-0.227	-0.106	0.233
Learning	-0.058	1	-0.044	-0.213	0.061	0.167	0.213
Concern	-0.08	-0.044	1	0.293	0.214	0.302	0.014
Doubts	0.137	-0.213	0.293	1	0.012	-0.006	0.05
Expectations	-0.227	0.061	0.214	0.012	1	0.154	-0.104
Standards	-0.106	0.167	0.302	-0.006	0.154	1	0.211
Organization	0.233	0.213	0.014	0.05	-0.104	0.211	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Gender & Learning & Concern & Doubts & Expectations & Standards & Organization \tabularnewline
Gender & 1 & -0.058 & -0.08 & 0.137 & -0.227 & -0.106 & 0.233 \tabularnewline
Learning & -0.058 & 1 & -0.044 & -0.213 & 0.061 & 0.167 & 0.213 \tabularnewline
Concern & -0.08 & -0.044 & 1 & 0.293 & 0.214 & 0.302 & 0.014 \tabularnewline
Doubts & 0.137 & -0.213 & 0.293 & 1 & 0.012 & -0.006 & 0.05 \tabularnewline
Expectations & -0.227 & 0.061 & 0.214 & 0.012 & 1 & 0.154 & -0.104 \tabularnewline
Standards & -0.106 & 0.167 & 0.302 & -0.006 & 0.154 & 1 & 0.211 \tabularnewline
Organization & 0.233 & 0.213 & 0.014 & 0.05 & -0.104 & 0.211 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111291&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Gender[/C][C]Learning[/C][C]Concern[/C][C]Doubts[/C][C]Expectations[/C][C]Standards[/C][C]Organization[/C][/ROW]
[ROW][C]Gender[/C][C]1[/C][C]-0.058[/C][C]-0.08[/C][C]0.137[/C][C]-0.227[/C][C]-0.106[/C][C]0.233[/C][/ROW]
[ROW][C]Learning[/C][C]-0.058[/C][C]1[/C][C]-0.044[/C][C]-0.213[/C][C]0.061[/C][C]0.167[/C][C]0.213[/C][/ROW]
[ROW][C]Concern[/C][C]-0.08[/C][C]-0.044[/C][C]1[/C][C]0.293[/C][C]0.214[/C][C]0.302[/C][C]0.014[/C][/ROW]
[ROW][C]Doubts[/C][C]0.137[/C][C]-0.213[/C][C]0.293[/C][C]1[/C][C]0.012[/C][C]-0.006[/C][C]0.05[/C][/ROW]
[ROW][C]Expectations[/C][C]-0.227[/C][C]0.061[/C][C]0.214[/C][C]0.012[/C][C]1[/C][C]0.154[/C][C]-0.104[/C][/ROW]
[ROW][C]Standards[/C][C]-0.106[/C][C]0.167[/C][C]0.302[/C][C]-0.006[/C][C]0.154[/C][C]1[/C][C]0.211[/C][/ROW]
[ROW][C]Organization[/C][C]0.233[/C][C]0.213[/C][C]0.014[/C][C]0.05[/C][C]-0.104[/C][C]0.211[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111291&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111291&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)
	Gender	Learning	Concern	Doubts	Expectations	Standards	Organization
Gender	1	-0.058	-0.08	0.137	-0.227	-0.106	0.233
Learning	-0.058	1	-0.044	-0.213	0.061	0.167	0.213
Concern	-0.08	-0.044	1	0.293	0.214	0.302	0.014
Doubts	0.137	-0.213	0.293	1	0.012	-0.006	0.05
Expectations	-0.227	0.061	0.214	0.012	1	0.154	-0.104
Standards	-0.106	0.167	0.302	-0.006	0.154	1	0.211
Organization	0.233	0.213	0.014	0.05	-0.104	0.211	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
Gender;Learning	-0.062	-0.0657	-0.0579
p-value	(0.4538)	(0.4272)	(0.4254)
Gender;Concern	-0.0878	-0.0959	-0.0805
p-value	(0.2884)	(0.2462)	(0.2449)
Gender;Doubts	0.1587	0.1594	0.1373
p-value	(0.054)	(0.0529)	(0.0532)
Gender;Expectations	-0.2198	-0.266	-0.2274
p-value	(0.0073)	(0.0011)	(0.0013)
Gender;Standards	-0.1046	-0.1251	-0.1056
p-value	(0.2057)	(0.1299)	(0.1295)
Gender;Organization	0.2647	0.2736	0.233
p-value	(0.0012)	(8e-04)	(9e-04)
Learning;Concern	-0.0231	-0.0516	-0.0436
p-value	(0.7807)	(0.5337)	(0.4742)
Learning;Doubts	-0.3008	-0.2808	-0.2127
p-value	(2e-04)	(5e-04)	(7e-04)
Learning;Expectations	0.1385	0.0821	0.0608
p-value	(0.0931)	(0.3212)	(0.3274)
Learning;Standards	0.2349	0.2256	0.1674
p-value	(0.0041)	(0.0058)	(0.0064)
Learning;Organization	0.289	0.2778	0.2132
p-value	(4e-04)	(6e-04)	(6e-04)
Concern;Doubts	0.3776	0.3866	0.2932
p-value	(0)	(0)	(0)
Concern;Expectations	0.3212	0.2812	0.2144
p-value	(1e-04)	(5e-04)	(3e-04)
Concern;Standards	0.42	0.4094	0.3016
p-value	(0)	(0)	(0)
Concern;Organization	0.069	0.0226	0.0136
p-value	(0.4044)	(0.7848)	(0.8176)
Doubts;Expectations	0.0128	0.0188	0.0121
p-value	(0.8769)	(0.821)	(0.8426)
Doubts;Standards	-0.0458	-0.0095	-0.0059
p-value	(0.5802)	(0.9087)	(0.9212)
Doubts;Organization	0.0516	0.07	0.0498
p-value	(0.5336)	(0.3981)	(0.4111)
Expectations;Standards	0.2573	0.2013	0.1545
p-value	(0.0016)	(0.0142)	(0.0095)
Expectations;Organization	-0.1086	-0.1402	-0.1045
p-value	(0.1889)	(0.0893)	(0.0822)
Standards;Organization	0.3552	0.2916	0.2112
p-value	(0)	(3e-04)	(4e-04)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Gender;Learning & -0.062 & -0.0657 & -0.0579 \tabularnewline
p-value & (0.4538) & (0.4272) & (0.4254) \tabularnewline
Gender;Concern & -0.0878 & -0.0959 & -0.0805 \tabularnewline
p-value & (0.2884) & (0.2462) & (0.2449) \tabularnewline
Gender;Doubts & 0.1587 & 0.1594 & 0.1373 \tabularnewline
p-value & (0.054) & (0.0529) & (0.0532) \tabularnewline
Gender;Expectations & -0.2198 & -0.266 & -0.2274 \tabularnewline
p-value & (0.0073) & (0.0011) & (0.0013) \tabularnewline
Gender;Standards & -0.1046 & -0.1251 & -0.1056 \tabularnewline
p-value & (0.2057) & (0.1299) & (0.1295) \tabularnewline
Gender;Organization & 0.2647 & 0.2736 & 0.233 \tabularnewline
p-value & (0.0012) & (8e-04) & (9e-04) \tabularnewline
Learning;Concern & -0.0231 & -0.0516 & -0.0436 \tabularnewline
p-value & (0.7807) & (0.5337) & (0.4742) \tabularnewline
Learning;Doubts & -0.3008 & -0.2808 & -0.2127 \tabularnewline
p-value & (2e-04) & (5e-04) & (7e-04) \tabularnewline
Learning;Expectations & 0.1385 & 0.0821 & 0.0608 \tabularnewline
p-value & (0.0931) & (0.3212) & (0.3274) \tabularnewline
Learning;Standards & 0.2349 & 0.2256 & 0.1674 \tabularnewline
p-value & (0.0041) & (0.0058) & (0.0064) \tabularnewline
Learning;Organization & 0.289 & 0.2778 & 0.2132 \tabularnewline
p-value & (4e-04) & (6e-04) & (6e-04) \tabularnewline
Concern;Doubts & 0.3776 & 0.3866 & 0.2932 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Concern;Expectations & 0.3212 & 0.2812 & 0.2144 \tabularnewline
p-value & (1e-04) & (5e-04) & (3e-04) \tabularnewline
Concern;Standards & 0.42 & 0.4094 & 0.3016 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Concern;Organization & 0.069 & 0.0226 & 0.0136 \tabularnewline
p-value & (0.4044) & (0.7848) & (0.8176) \tabularnewline
Doubts;Expectations & 0.0128 & 0.0188 & 0.0121 \tabularnewline
p-value & (0.8769) & (0.821) & (0.8426) \tabularnewline
Doubts;Standards & -0.0458 & -0.0095 & -0.0059 \tabularnewline
p-value & (0.5802) & (0.9087) & (0.9212) \tabularnewline
Doubts;Organization & 0.0516 & 0.07 & 0.0498 \tabularnewline
p-value & (0.5336) & (0.3981) & (0.4111) \tabularnewline
Expectations;Standards & 0.2573 & 0.2013 & 0.1545 \tabularnewline
p-value & (0.0016) & (0.0142) & (0.0095) \tabularnewline
Expectations;Organization & -0.1086 & -0.1402 & -0.1045 \tabularnewline
p-value & (0.1889) & (0.0893) & (0.0822) \tabularnewline
Standards;Organization & 0.3552 & 0.2916 & 0.2112 \tabularnewline
p-value & (0) & (3e-04) & (4e-04) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111291&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;Learning[/C][C]-0.062[/C][C]-0.0657[/C][C]-0.0579[/C][/ROW]
[ROW][C]p-value[/C][C](0.4538)[/C][C](0.4272)[/C][C](0.4254)[/C][/ROW]
[ROW][C]Gender;Concern[/C][C]-0.0878[/C][C]-0.0959[/C][C]-0.0805[/C][/ROW]
[ROW][C]p-value[/C][C](0.2884)[/C][C](0.2462)[/C][C](0.2449)[/C][/ROW]
[ROW][C]Gender;Doubts[/C][C]0.1587[/C][C]0.1594[/C][C]0.1373[/C][/ROW]
[ROW][C]p-value[/C][C](0.054)[/C][C](0.0529)[/C][C](0.0532)[/C][/ROW]
[ROW][C]Gender;Expectations[/C][C]-0.2198[/C][C]-0.266[/C][C]-0.2274[/C][/ROW]
[ROW][C]p-value[/C][C](0.0073)[/C][C](0.0011)[/C][C](0.0013)[/C][/ROW]
[ROW][C]Gender;Standards[/C][C]-0.1046[/C][C]-0.1251[/C][C]-0.1056[/C][/ROW]
[ROW][C]p-value[/C][C](0.2057)[/C][C](0.1299)[/C][C](0.1295)[/C][/ROW]
[ROW][C]Gender;Organization[/C][C]0.2647[/C][C]0.2736[/C][C]0.233[/C][/ROW]
[ROW][C]p-value[/C][C](0.0012)[/C][C](8e-04)[/C][C](9e-04)[/C][/ROW]
[ROW][C]Learning;Concern[/C][C]-0.0231[/C][C]-0.0516[/C][C]-0.0436[/C][/ROW]
[ROW][C]p-value[/C][C](0.7807)[/C][C](0.5337)[/C][C](0.4742)[/C][/ROW]
[ROW][C]Learning;Doubts[/C][C]-0.3008[/C][C]-0.2808[/C][C]-0.2127[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](5e-04)[/C][C](7e-04)[/C][/ROW]
[ROW][C]Learning;Expectations[/C][C]0.1385[/C][C]0.0821[/C][C]0.0608[/C][/ROW]
[ROW][C]p-value[/C][C](0.0931)[/C][C](0.3212)[/C][C](0.3274)[/C][/ROW]
[ROW][C]Learning;Standards[/C][C]0.2349[/C][C]0.2256[/C][C]0.1674[/C][/ROW]
[ROW][C]p-value[/C][C](0.0041)[/C][C](0.0058)[/C][C](0.0064)[/C][/ROW]
[ROW][C]Learning;Organization[/C][C]0.289[/C][C]0.2778[/C][C]0.2132[/C][/ROW]
[ROW][C]p-value[/C][C](4e-04)[/C][C](6e-04)[/C][C](6e-04)[/C][/ROW]
[ROW][C]Concern;Doubts[/C][C]0.3776[/C][C]0.3866[/C][C]0.2932[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Concern;Expectations[/C][C]0.3212[/C][C]0.2812[/C][C]0.2144[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](5e-04)[/C][C](3e-04)[/C][/ROW]
[ROW][C]Concern;Standards[/C][C]0.42[/C][C]0.4094[/C][C]0.3016[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Concern;Organization[/C][C]0.069[/C][C]0.0226[/C][C]0.0136[/C][/ROW]
[ROW][C]p-value[/C][C](0.4044)[/C][C](0.7848)[/C][C](0.8176)[/C][/ROW]
[ROW][C]Doubts;Expectations[/C][C]0.0128[/C][C]0.0188[/C][C]0.0121[/C][/ROW]
[ROW][C]p-value[/C][C](0.8769)[/C][C](0.821)[/C][C](0.8426)[/C][/ROW]
[ROW][C]Doubts;Standards[/C][C]-0.0458[/C][C]-0.0095[/C][C]-0.0059[/C][/ROW]
[ROW][C]p-value[/C][C](0.5802)[/C][C](0.9087)[/C][C](0.9212)[/C][/ROW]
[ROW][C]Doubts;Organization[/C][C]0.0516[/C][C]0.07[/C][C]0.0498[/C][/ROW]
[ROW][C]p-value[/C][C](0.5336)[/C][C](0.3981)[/C][C](0.4111)[/C][/ROW]
[ROW][C]Expectations;Standards[/C][C]0.2573[/C][C]0.2013[/C][C]0.1545[/C][/ROW]
[ROW][C]p-value[/C][C](0.0016)[/C][C](0.0142)[/C][C](0.0095)[/C][/ROW]
[ROW][C]Expectations;Organization[/C][C]-0.1086[/C][C]-0.1402[/C][C]-0.1045[/C][/ROW]
[ROW][C]p-value[/C][C](0.1889)[/C][C](0.0893)[/C][C](0.0822)[/C][/ROW]
[ROW][C]Standards;Organization[/C][C]0.3552[/C][C]0.2916[/C][C]0.2112[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](3e-04)[/C][C](4e-04)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111291&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111291&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
pair	Pearson r	Spearman rho	Kendall tau
Gender;Learning	-0.062	-0.0657	-0.0579
p-value	(0.4538)	(0.4272)	(0.4254)
Gender;Concern	-0.0878	-0.0959	-0.0805
p-value	(0.2884)	(0.2462)	(0.2449)
Gender;Doubts	0.1587	0.1594	0.1373
p-value	(0.054)	(0.0529)	(0.0532)
Gender;Expectations	-0.2198	-0.266	-0.2274
p-value	(0.0073)	(0.0011)	(0.0013)
Gender;Standards	-0.1046	-0.1251	-0.1056
p-value	(0.2057)	(0.1299)	(0.1295)
Gender;Organization	0.2647	0.2736	0.233
p-value	(0.0012)	(8e-04)	(9e-04)
Learning;Concern	-0.0231	-0.0516	-0.0436
p-value	(0.7807)	(0.5337)	(0.4742)
Learning;Doubts	-0.3008	-0.2808	-0.2127
p-value	(2e-04)	(5e-04)	(7e-04)
Learning;Expectations	0.1385	0.0821	0.0608
p-value	(0.0931)	(0.3212)	(0.3274)
Learning;Standards	0.2349	0.2256	0.1674
p-value	(0.0041)	(0.0058)	(0.0064)
Learning;Organization	0.289	0.2778	0.2132
p-value	(4e-04)	(6e-04)	(6e-04)
Concern;Doubts	0.3776	0.3866	0.2932
p-value	(0)	(0)	(0)
Concern;Expectations	0.3212	0.2812	0.2144
p-value	(1e-04)	(5e-04)	(3e-04)
Concern;Standards	0.42	0.4094	0.3016
p-value	(0)	(0)	(0)
Concern;Organization	0.069	0.0226	0.0136
p-value	(0.4044)	(0.7848)	(0.8176)
Doubts;Expectations	0.0128	0.0188	0.0121
p-value	(0.8769)	(0.821)	(0.8426)
Doubts;Standards	-0.0458	-0.0095	-0.0059
p-value	(0.5802)	(0.9087)	(0.9212)
Doubts;Organization	0.0516	0.07	0.0498
p-value	(0.5336)	(0.3981)	(0.4111)
Expectations;Standards	0.2573	0.2013	0.1545
p-value	(0.0016)	(0.0142)	(0.0095)
Expectations;Organization	-0.1086	-0.1402	-0.1045
p-value	(0.1889)	(0.0893)	(0.0822)
Standards;Organization	0.3552	0.2916	0.2112
p-value	(0)	(3e-04)	(4e-04)

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 2 ; par2 = quantiles ; par3 = 2 ; 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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code