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R Software Module

rwasp_pairs.wasp

Title produced by software

Kendall tau Correlation Matrix

Date of computation

Tue, 13 Dec 2011 11:56:56 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/13/t13237954333357vkfb8zjjl2e.htm/, Retrieved Thu, 02 May 2024 21:10:28 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=154539, Retrieved Thu, 02 May 2024 21:10:28 +0000

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

-       [Kendall tau Correlation Matrix] [WS 10 - Kendall's...] [2011-12-13 16:56:56] [e1c4030d3eb0ab0fcc7a7b48aeaac474] [Current]

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2	13	12	30	33	13	16
1	8	8	32	35	11	15
2	14	12	30	35	12	13
2	14	11	33	25	13	14
1	13	11	36	39	12	17
1	16	13	37	37	12	13
1	14	11	31	31	13	12
1	13	10	36	28	12	9
2	15	7	40	38	15	25
1	13	10	31	32	11	13
2	16	12	24	32	13	10
1	20	15	46	46	12	13
1	17	12	40	40	12	9
1	15	15	27	33	12	14
2	16	12	32	25	15	26
1	16	10	41	37	13	12
1	12	10	28	33	13	11
2	9	8	34	33	12	19
2	15	11	31	35	11	12
2	17	14	38	39	11	9
1	12	12	37	36	13	15
1	10	11	34	37	10	15
2	11	6	33	43	12	23
2	16	12	38	27	13	20
1	16	14	27	31	10	0
2	15	11	36	33	12	15
1	13	8	37	35	13	8
2	14	12	35	36	12	12
1	19	15	44	39	11	11
1	16	13	41	31	11	18
2	17	14	29	34	14	19
1	10	12	31	29	12	13
1	15	7	32	37	14	22
1	14	11	35	30	12	12
1	14	7	36	32	12	15
2	16	12	28	31	13	16
1	17	12	34	34	15	16
1	15	12	36	30	12	13
2	17	13	33	33	16	11
2	14	15	35	37	10	16
1	10	9	34	33	13	14
2	14	9	38	28	12	11
2	16	11	35	32	12	20
2	18	14	40	40	16	16
1	15	12	35	39	12	12
1	16	15	32	28	16	17
1	16	12	33	33	13	11
1	10	6	31	36	10	12
2	8	5	32	35	14	14
1	17	13	35	34	13	13
1	14	11	32	35	12	14
1	12	11	26	30	13	19
2	10	6	38	35	16	17
1	14	12	45	37	12	11
1	12	10	36	40	12	12
1	16	6	37	34	13	12
1	16	12	33	37	13	14
1	15	14	35	38	11	15
2	11	6	32	27	14	18
1	16	11	32	27	16	16
2	8	6	32	27	16	16
1	17	14	33	39	14	19
1	16	12	37	37	14	17
1	15	12	40	32	14	15
2	8	8	35	27	14	13
1	13	10	30	35	10	16
1	14	11	36	40	13	17
1	13	7	34	32	14	16
1	16	12	34	36	17	13
2	12	9	37	35	12	15
1	19	13	34	31	12	16
1	19	14	37	34	12	10
1	12	6	43	36	15	19
1	14	12	39	40	10	11
2	15	6	29	33	13	17
1	13	14	41	38	12	19
2	16	12	32	33	13	15
2	10	10	34	35	14	15
1	15	10	34	30	12	17
1	16	12	35	31	13	13
1	15	11	41	42	14	17
2	11	10	32	33	10	12
2	9	7	39	35	12	27
1	16	12	33	33	13	12
1	12	12	30	31	10	15
2	14	12	32	36	13	18
1	14	10	41	32	13	19
1	13	10	24	43	12	21
2	15	12	35	33	12	13
2	17	12	39	34	15	16
2	14	12	32	36	12	13
2	9	9	28	33	16	20
2	11	11	31	32	15	17
1	9	10	36	36	10	10
2	7	5	39	39	13	18
1	13	10	33	30	0	11
2	15	10	36	34	10	18
1	12	12	31	34	12	14
2	15	11	33	36	14	11
2	14	9	33	31	12	14
1	15	15	33	27	13	12
2	9	9	39	28	14	22
1	16	12	35	37	11	12
1	16	16	37	36	11	12
1	14	10	29	31	12	15
2	14	14	34	31	9	13
2	13	10	35	31	13	13
1	14	11	36	34	13	16
2	16	12	29	36	12	12
1	16	14	35	30	14	16
1	13	10	35	37	12	15
2	12	9	36	29	10	19
2	16	12	38	37	11	15
1	16	11	36	38	14	13
1	16	12	37	38	12	9
2	10	7	32	33	13	14
2	14	16	34	34	13	14
2	12	11	29	32	9	12
2	12	12	38	36	13	17
1	12	9	34	30	11	11
1	12	9	33	34	12	17
1	19	15	42	42	13	15
2	14	10	32	24	12	15
1	13	11	31	29	12	11
1	17	14	34	32	11	14
2	16	12	39	31	12	14
1	15	12	38	37	12	14
1	12	12	36	34	13	14
1	8	11	32	35	14	13
1	10	9	37	34	13	14
1	16	11	36	33	12	10
2	10	6	34	31	15	17
2	16	12	34	32	13	11
1	10	12	34	37	14	13
1	18	14	38	39	12	14
1	12	8	33	31	11	14
2	16	15	5	0	12	18
2	10	9	28	30	11	18
2	15	9	33	30	14	18
1	17	11	41	43	13	14
2	16	12	30	31	12	12
2	14	10	31	33	14	16
2	12	11	34	31	13	17
2	11	10	33	38	11	13
2	15	12	37	32	16	16
1	7	11	34	38	13	15

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154539&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154539&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154539&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	1 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Correlations for all pairs of data series (method=kendall)
	Gender	Learning	Software	Connected	Separate	Happiness	Depression
Gender	1	-0.114	-0.139	-0.143	-0.184	0.122	0.215
Learning	-0.114	1	0.534	0.156	0.085	0.046	-0.13
Software	-0.139	0.534	1	0.068	0.101	-0.078	-0.159
Connected	-0.143	0.156	0.068	1	0.287	0.021	-0.009
Separate	-0.184	0.085	0.101	0.287	1	-0.051	-0.048
Happiness	0.122	0.046	-0.078	0.021	-0.051	1	0.25
Depression	0.215	-0.13	-0.159	-0.009	-0.048	0.25	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Gender & Learning & Software & Connected & Separate & Happiness & Depression \tabularnewline
Gender & 1 & -0.114 & -0.139 & -0.143 & -0.184 & 0.122 & 0.215 \tabularnewline
Learning & -0.114 & 1 & 0.534 & 0.156 & 0.085 & 0.046 & -0.13 \tabularnewline
Software & -0.139 & 0.534 & 1 & 0.068 & 0.101 & -0.078 & -0.159 \tabularnewline
Connected & -0.143 & 0.156 & 0.068 & 1 & 0.287 & 0.021 & -0.009 \tabularnewline
Separate & -0.184 & 0.085 & 0.101 & 0.287 & 1 & -0.051 & -0.048 \tabularnewline
Happiness & 0.122 & 0.046 & -0.078 & 0.021 & -0.051 & 1 & 0.25 \tabularnewline
Depression & 0.215 & -0.13 & -0.159 & -0.009 & -0.048 & 0.25 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154539&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]Software[/C][C]Connected[/C][C]Separate[/C][C]Happiness[/C][C]Depression[/C][/ROW]
[ROW][C]Gender[/C][C]1[/C][C]-0.114[/C][C]-0.139[/C][C]-0.143[/C][C]-0.184[/C][C]0.122[/C][C]0.215[/C][/ROW]
[ROW][C]Learning[/C][C]-0.114[/C][C]1[/C][C]0.534[/C][C]0.156[/C][C]0.085[/C][C]0.046[/C][C]-0.13[/C][/ROW]
[ROW][C]Software[/C][C]-0.139[/C][C]0.534[/C][C]1[/C][C]0.068[/C][C]0.101[/C][C]-0.078[/C][C]-0.159[/C][/ROW]
[ROW][C]Connected[/C][C]-0.143[/C][C]0.156[/C][C]0.068[/C][C]1[/C][C]0.287[/C][C]0.021[/C][C]-0.009[/C][/ROW]
[ROW][C]Separate[/C][C]-0.184[/C][C]0.085[/C][C]0.101[/C][C]0.287[/C][C]1[/C][C]-0.051[/C][C]-0.048[/C][/ROW]
[ROW][C]Happiness[/C][C]0.122[/C][C]0.046[/C][C]-0.078[/C][C]0.021[/C][C]-0.051[/C][C]1[/C][C]0.25[/C][/ROW]
[ROW][C]Depression[/C][C]0.215[/C][C]-0.13[/C][C]-0.159[/C][C]-0.009[/C][C]-0.048[/C][C]0.25[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154539&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154539&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	Software	Connected	Separate	Happiness	Depression
Gender	1	-0.114	-0.139	-0.143	-0.184	0.122	0.215
Learning	-0.114	1	0.534	0.156	0.085	0.046	-0.13
Software	-0.139	0.534	1	0.068	0.101	-0.078	-0.159
Connected	-0.143	0.156	0.068	1	0.287	0.021	-0.009
Separate	-0.184	0.085	0.101	0.287	1	-0.051	-0.048
Happiness	0.122	0.046	-0.078	0.021	-0.051	1	0.25
Depression	0.215	-0.13	-0.159	-0.009	-0.048	0.25	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
Gender;Learning	-0.156	-0.1325	-0.1142
p-value	(0.0601)	(0.111)	(0.1107)
Gender;Software	-0.1846	-0.1596	-0.1391
p-value	(0.0257)	(0.0543)	(0.0546)
Gender;Connected	-0.1887	-0.1693	-0.1433
p-value	(0.0226)	(0.0411)	(0.0415)
Gender;Separate	-0.2414	-0.2169	-0.1836
p-value	(0.0033)	(0.0085)	(0.009)
Gender;Happiness	0.1434	0.1371	0.1219
p-value	(0.0843)	(0.0988)	(0.0986)
Gender;Depression	0.2757	0.2517	0.2146
p-value	(8e-04)	(0.0022)	(0.0024)
Learning;Software	0.6309	0.6601	0.5336
p-value	(0)	(0)	(0)
Learning;Connected	0.1576	0.2143	0.1562
p-value	(0.0574)	(0.0094)	(0.0101)
Learning;Separate	0.0822	0.1127	0.0853
p-value	(0.3241)	(0.1757)	(0.1598)
Learning;Happiness	0.0294	0.0551	0.0456
p-value	(0.7245)	(0.5092)	(0.4744)
Learning;Depression	-0.1884	-0.1757	-0.1304
p-value	(0.0228)	(0.0339)	(0.0328)
Software;Connected	0.0018	0.0926	0.0683
p-value	(0.9827)	(0.2662)	(0.2656)
Software;Separate	0.0273	0.1348	0.1006
p-value	(0.7439)	(0.1046)	(0.1008)
Software;Happiness	-0.102	-0.0984	-0.0784
p-value	(0.2206)	(0.2374)	(0.2234)
Software;Depression	-0.27	-0.2143	-0.1586
p-value	(0.001)	(0.0094)	(0.0102)
Connected;Separate	0.5598	0.3843	0.2873
p-value	(0)	(0)	(0)
Connected;Happiness	0.0599	0.0308	0.0215
p-value	(0.4726)	(0.7124)	(0.7313)
Connected;Depression	-0.0062	-0.0113	-0.0094
p-value	(0.9412)	(0.8927)	(0.8752)
Separate;Happiness	-0.0227	-0.0712	-0.0512
p-value	(0.7857)	(0.3928)	(0.4127)
Separate;Depression	-0.0613	-0.0614	-0.0479
p-value	(0.4622)	(0.4616)	(0.4244)
Happiness;Depression	0.3022	0.3278	0.2502
p-value	(2e-04)	(1e-04)	(1e-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 & -0.156 & -0.1325 & -0.1142 \tabularnewline
p-value & (0.0601) & (0.111) & (0.1107) \tabularnewline
Gender;Software & -0.1846 & -0.1596 & -0.1391 \tabularnewline
p-value & (0.0257) & (0.0543) & (0.0546) \tabularnewline
Gender;Connected & -0.1887 & -0.1693 & -0.1433 \tabularnewline
p-value & (0.0226) & (0.0411) & (0.0415) \tabularnewline
Gender;Separate & -0.2414 & -0.2169 & -0.1836 \tabularnewline
p-value & (0.0033) & (0.0085) & (0.009) \tabularnewline
Gender;Happiness & 0.1434 & 0.1371 & 0.1219 \tabularnewline
p-value & (0.0843) & (0.0988) & (0.0986) \tabularnewline
Gender;Depression & 0.2757 & 0.2517 & 0.2146 \tabularnewline
p-value & (8e-04) & (0.0022) & (0.0024) \tabularnewline
Learning;Software & 0.6309 & 0.6601 & 0.5336 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Learning;Connected & 0.1576 & 0.2143 & 0.1562 \tabularnewline
p-value & (0.0574) & (0.0094) & (0.0101) \tabularnewline
Learning;Separate & 0.0822 & 0.1127 & 0.0853 \tabularnewline
p-value & (0.3241) & (0.1757) & (0.1598) \tabularnewline
Learning;Happiness & 0.0294 & 0.0551 & 0.0456 \tabularnewline
p-value & (0.7245) & (0.5092) & (0.4744) \tabularnewline
Learning;Depression & -0.1884 & -0.1757 & -0.1304 \tabularnewline
p-value & (0.0228) & (0.0339) & (0.0328) \tabularnewline
Software;Connected & 0.0018 & 0.0926 & 0.0683 \tabularnewline
p-value & (0.9827) & (0.2662) & (0.2656) \tabularnewline
Software;Separate & 0.0273 & 0.1348 & 0.1006 \tabularnewline
p-value & (0.7439) & (0.1046) & (0.1008) \tabularnewline
Software;Happiness & -0.102 & -0.0984 & -0.0784 \tabularnewline
p-value & (0.2206) & (0.2374) & (0.2234) \tabularnewline
Software;Depression & -0.27 & -0.2143 & -0.1586 \tabularnewline
p-value & (0.001) & (0.0094) & (0.0102) \tabularnewline
Connected;Separate & 0.5598 & 0.3843 & 0.2873 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Connected;Happiness & 0.0599 & 0.0308 & 0.0215 \tabularnewline
p-value & (0.4726) & (0.7124) & (0.7313) \tabularnewline
Connected;Depression & -0.0062 & -0.0113 & -0.0094 \tabularnewline
p-value & (0.9412) & (0.8927) & (0.8752) \tabularnewline
Separate;Happiness & -0.0227 & -0.0712 & -0.0512 \tabularnewline
p-value & (0.7857) & (0.3928) & (0.4127) \tabularnewline
Separate;Depression & -0.0613 & -0.0614 & -0.0479 \tabularnewline
p-value & (0.4622) & (0.4616) & (0.4244) \tabularnewline
Happiness;Depression & 0.3022 & 0.3278 & 0.2502 \tabularnewline
p-value & (2e-04) & (1e-04) & (1e-04) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154539&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]-0.156[/C][C]-0.1325[/C][C]-0.1142[/C][/ROW]
[ROW][C]p-value[/C][C](0.0601)[/C][C](0.111)[/C][C](0.1107)[/C][/ROW]
[ROW][C]Gender;Software[/C][C]-0.1846[/C][C]-0.1596[/C][C]-0.1391[/C][/ROW]
[ROW][C]p-value[/C][C](0.0257)[/C][C](0.0543)[/C][C](0.0546)[/C][/ROW]
[ROW][C]Gender;Connected[/C][C]-0.1887[/C][C]-0.1693[/C][C]-0.1433[/C][/ROW]
[ROW][C]p-value[/C][C](0.0226)[/C][C](0.0411)[/C][C](0.0415)[/C][/ROW]
[ROW][C]Gender;Separate[/C][C]-0.2414[/C][C]-0.2169[/C][C]-0.1836[/C][/ROW]
[ROW][C]p-value[/C][C](0.0033)[/C][C](0.0085)[/C][C](0.009)[/C][/ROW]
[ROW][C]Gender;Happiness[/C][C]0.1434[/C][C]0.1371[/C][C]0.1219[/C][/ROW]
[ROW][C]p-value[/C][C](0.0843)[/C][C](0.0988)[/C][C](0.0986)[/C][/ROW]
[ROW][C]Gender;Depression[/C][C]0.2757[/C][C]0.2517[/C][C]0.2146[/C][/ROW]
[ROW][C]p-value[/C][C](8e-04)[/C][C](0.0022)[/C][C](0.0024)[/C][/ROW]
[ROW][C]Learning;Software[/C][C]0.6309[/C][C]0.6601[/C][C]0.5336[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Learning;Connected[/C][C]0.1576[/C][C]0.2143[/C][C]0.1562[/C][/ROW]
[ROW][C]p-value[/C][C](0.0574)[/C][C](0.0094)[/C][C](0.0101)[/C][/ROW]
[ROW][C]Learning;Separate[/C][C]0.0822[/C][C]0.1127[/C][C]0.0853[/C][/ROW]
[ROW][C]p-value[/C][C](0.3241)[/C][C](0.1757)[/C][C](0.1598)[/C][/ROW]
[ROW][C]Learning;Happiness[/C][C]0.0294[/C][C]0.0551[/C][C]0.0456[/C][/ROW]
[ROW][C]p-value[/C][C](0.7245)[/C][C](0.5092)[/C][C](0.4744)[/C][/ROW]
[ROW][C]Learning;Depression[/C][C]-0.1884[/C][C]-0.1757[/C][C]-0.1304[/C][/ROW]
[ROW][C]p-value[/C][C](0.0228)[/C][C](0.0339)[/C][C](0.0328)[/C][/ROW]
[ROW][C]Software;Connected[/C][C]0.0018[/C][C]0.0926[/C][C]0.0683[/C][/ROW]
[ROW][C]p-value[/C][C](0.9827)[/C][C](0.2662)[/C][C](0.2656)[/C][/ROW]
[ROW][C]Software;Separate[/C][C]0.0273[/C][C]0.1348[/C][C]0.1006[/C][/ROW]
[ROW][C]p-value[/C][C](0.7439)[/C][C](0.1046)[/C][C](0.1008)[/C][/ROW]
[ROW][C]Software;Happiness[/C][C]-0.102[/C][C]-0.0984[/C][C]-0.0784[/C][/ROW]
[ROW][C]p-value[/C][C](0.2206)[/C][C](0.2374)[/C][C](0.2234)[/C][/ROW]
[ROW][C]Software;Depression[/C][C]-0.27[/C][C]-0.2143[/C][C]-0.1586[/C][/ROW]
[ROW][C]p-value[/C][C](0.001)[/C][C](0.0094)[/C][C](0.0102)[/C][/ROW]
[ROW][C]Connected;Separate[/C][C]0.5598[/C][C]0.3843[/C][C]0.2873[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Connected;Happiness[/C][C]0.0599[/C][C]0.0308[/C][C]0.0215[/C][/ROW]
[ROW][C]p-value[/C][C](0.4726)[/C][C](0.7124)[/C][C](0.7313)[/C][/ROW]
[ROW][C]Connected;Depression[/C][C]-0.0062[/C][C]-0.0113[/C][C]-0.0094[/C][/ROW]
[ROW][C]p-value[/C][C](0.9412)[/C][C](0.8927)[/C][C](0.8752)[/C][/ROW]
[ROW][C]Separate;Happiness[/C][C]-0.0227[/C][C]-0.0712[/C][C]-0.0512[/C][/ROW]
[ROW][C]p-value[/C][C](0.7857)[/C][C](0.3928)[/C][C](0.4127)[/C][/ROW]
[ROW][C]Separate;Depression[/C][C]-0.0613[/C][C]-0.0614[/C][C]-0.0479[/C][/ROW]
[ROW][C]p-value[/C][C](0.4622)[/C][C](0.4616)[/C][C](0.4244)[/C][/ROW]
[ROW][C]Happiness;Depression[/C][C]0.3022[/C][C]0.3278[/C][C]0.2502[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154539&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154539&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	-0.156	-0.1325	-0.1142
p-value	(0.0601)	(0.111)	(0.1107)
Gender;Software	-0.1846	-0.1596	-0.1391
p-value	(0.0257)	(0.0543)	(0.0546)
Gender;Connected	-0.1887	-0.1693	-0.1433
p-value	(0.0226)	(0.0411)	(0.0415)
Gender;Separate	-0.2414	-0.2169	-0.1836
p-value	(0.0033)	(0.0085)	(0.009)
Gender;Happiness	0.1434	0.1371	0.1219
p-value	(0.0843)	(0.0988)	(0.0986)
Gender;Depression	0.2757	0.2517	0.2146
p-value	(8e-04)	(0.0022)	(0.0024)
Learning;Software	0.6309	0.6601	0.5336
p-value	(0)	(0)	(0)
Learning;Connected	0.1576	0.2143	0.1562
p-value	(0.0574)	(0.0094)	(0.0101)
Learning;Separate	0.0822	0.1127	0.0853
p-value	(0.3241)	(0.1757)	(0.1598)
Learning;Happiness	0.0294	0.0551	0.0456
p-value	(0.7245)	(0.5092)	(0.4744)
Learning;Depression	-0.1884	-0.1757	-0.1304
p-value	(0.0228)	(0.0339)	(0.0328)
Software;Connected	0.0018	0.0926	0.0683
p-value	(0.9827)	(0.2662)	(0.2656)
Software;Separate	0.0273	0.1348	0.1006
p-value	(0.7439)	(0.1046)	(0.1008)
Software;Happiness	-0.102	-0.0984	-0.0784
p-value	(0.2206)	(0.2374)	(0.2234)
Software;Depression	-0.27	-0.2143	-0.1586
p-value	(0.001)	(0.0094)	(0.0102)
Connected;Separate	0.5598	0.3843	0.2873
p-value	(0)	(0)	(0)
Connected;Happiness	0.0599	0.0308	0.0215
p-value	(0.4726)	(0.7124)	(0.7313)
Connected;Depression	-0.0062	-0.0113	-0.0094
p-value	(0.9412)	(0.8927)	(0.8752)
Separate;Happiness	-0.0227	-0.0712	-0.0512
p-value	(0.7857)	(0.3928)	(0.4127)
Separate;Depression	-0.0613	-0.0614	-0.0479
p-value	(0.4622)	(0.4616)	(0.4244)
Happiness;Depression	0.3022	0.3278	0.2502
p-value	(2e-04)	(1e-04)	(1e-04)

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = kendall ;

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