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Author

*The author of this computation has been verified*

R Software Module

rwasp_pairs.wasp

Title produced by software

Kendall tau Correlation Matrix

Date of computation

Mon, 12 Dec 2011 16:38:50 -0500

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/2011/Dec/12/t1323726187ejuln9ei9mws4xn.htm/, Retrieved Fri, 03 May 2024 10:26:14 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=154236, Retrieved Fri, 03 May 2024 10:26:14 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

117

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]
- RMP   [Kendall tau Correlation Matrix] [WS10 Pearson Corr...] [2011-12-11 18:59:03] [8501ca4b76170905b8a207a77f626994]
-    D      [Kendall tau Correlation Matrix] [WS10.1] [2011-12-12 21:38:50] [5ae3d23a633522d14794d358c652ae9c] [Current]
-   P         [Kendall tau Correlation Matrix] [WS10.2] [2011-12-12 21:51:45] [9e469a83342941fcd5c6dffbf184cd3a] 

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Dataseries X:

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Histogram

Boxplots

1	41	38	13	12	14
1	39	32	16	11	18
1	30	35	19	15	11
0	31	33	15	6	12
1	34	37	14	13	16
1	35	29	13	10	18
1	39	31	19	12	14
1	34	36	15	14	14
1	36	35	14	12	15
1	37	38	15	9	15
0	38	31	16	10	17
1	36	34	16	12	19
0	38	35	16	12	10
1	39	38	16	11	16
1	33	37	17	15	18
0	32	33	15	12	14
0	36	32	15	10	14
1	38	38	20	12	17
0	39	38	18	11	14
1	32	32	16	12	16
0	32	33	16	11	18
1	31	31	16	12	11
1	39	38	19	13	14
1	37	39	16	11	12
0	39	32	17	12	17
1	41	32	17	13	9
0	36	35	16	10	16
1	33	37	15	14	14
1	33	33	16	12	15
0	34	33	14	10	11
1	31	31	15	12	16
0	27	32	12	8	13
1	37	31	14	10	17
1	34	37	16	12	15
0	34	30	14	12	14
0	32	33	10	7	16
0	29	31	10	9	9
0	36	33	14	12	15
1	29	31	16	10	17
0	35	33	16	10	13
0	37	32	16	10	15
1	34	33	14	12	16
0	38	32	20	15	16
0	35	33	14	10	12
1	38	28	14	10	15
1	37	35	11	12	11
1	38	39	14	13	15
1	33	34	15	11	15
1	36	38	16	11	17
0	38	32	14	12	13
1	32	38	16	14	16
0	32	30	14	10	14
0	32	33	12	12	11
1	34	38	16	13	12
0	32	32	9	5	12
1	37	35	14	6	15
1	39	34	16	12	16
1	29	34	16	12	15
0	37	36	15	11	12
1	35	34	16	10	12
0	30	28	12	7	8
0	38	34	16	12	13
1	34	35	16	14	11
1	31	35	14	11	14
1	34	31	16	12	15
0	35	37	17	13	10
1	36	35	18	14	11
0	30	27	18	11	12
1	39	40	12	12	15
0	35	37	16	12	15
0	38	36	10	8	14
1	31	38	14	11	16
1	34	39	18	14	15
0	38	41	18	14	15
0	34	27	16	12	13
1	39	30	17	9	12
1	37	37	16	13	17
1	34	31	16	11	13
0	28	31	13	12	15
0	37	27	16	12	13
0	33	36	16	12	15
1	35	37	16	12	15
0	37	33	15	12	16
1	32	34	15	11	15
1	33	31	16	10	14
0	38	39	14	9	15
1	33	34	16	12	14
1	29	32	16	12	13
1	33	33	15	12	7
1	31	36	12	9	17
1	36	32	17	15	13
1	35	41	16	12	15
1	32	28	15	12	14
1	29	30	13	12	13
1	39	36	16	10	16
1	37	35	16	13	12
1	35	31	16	9	14
0	37	34	16	12	17
0	32	36	14	10	15
1	38	36	16	14	17
0	37	35	16	11	12
1	36	37	20	15	16
0	32	28	15	11	11
1	33	39	16	11	15
0	40	32	13	12	9
1	38	35	17	12	16
0	41	39	16	12	15
0	36	35	16	11	10
1	43	42	12	7	10
1	30	34	16	12	15
1	31	33	16	14	11
1	32	41	17	11	13
1	37	34	12	10	18
0	37	32	18	13	16
1	33	40	14	13	14
1	34	40	14	8	14
1	33	35	13	11	14
1	38	36	16	12	14
0	33	37	13	11	12
1	31	27	16	13	14
1	38	39	13	12	15
1	37	38	16	14	15
1	36	31	15	13	15
1	31	33	16	15	13
0	39	32	15	10	17
1	44	39	17	11	17
1	33	36	15	9	19
1	35	33	12	11	15
0	32	33	16	10	13
0	28	32	10	11	9
1	40	37	16	8	15
0	27	30	12	11	15
0	37	38	14	12	15
1	32	29	15	12	16
0	28	22	13	9	11
0	34	35	15	11	14
1	30	35	11	10	11
1	35	34	12	8	15
0	31	35	11	9	13
1	32	34	16	8	15
0	30	37	15	9	16
1	30	35	17	15	14
0	31	23	16	11	15
1	40	31	10	8	16
1	32	27	18	13	16
0	36	36	13	12	11
0	32	31	16	12	12
0	35	32	13	9	9
1	38	39	10	7	16
1	42	37	15	13	13
0	34	38	16	9	16
1	35	39	16	6	12
1	38	34	14	8	9
1	33	31	10	8	13
1	32	37	13	6	14
1	33	36	15	9	19
1	34	32	16	11	13
1	32	38	12	8	12
0	27	26	13	10	10
0	31	26	12	8	14
0	38	33	17	14	16
1	34	39	15	10	10
0	24	30	10	8	11
0	30	33	14	11	14
1	26	25	11	12	12
1	34	38	13	12	9
0	27	37	16	12	9
0	37	31	12	5	11
1	36	37	16	12	16
0	41	35	12	10	9
1	29	25	9	7	13
1	36	28	12	12	16
0	32	35	15	11	13
1	37	33	12	8	9
0	30	30	12	9	12
1	31	31	14	10	16
1	38	37	12	9	11
1	36	36	16	12	14
0	35	30	11	6	13
0	31	36	19	15	15
0	38	32	15	12	14
1	22	28	8	12	16
1	32	36	16	12	13
0	36	34	17	11	14
1	39	31	12	7	15
0	28	28	11	7	13
0	32	36	11	5	11
1	32	36	14	12	11
1	38	40	16	12	14
1	32	33	12	3	15
1	35	37	16	11	11
1	32	32	13	10	15
0	37	38	15	12	12
1	34	31	16	9	14
1	33	37	16	12	14
0	33	33	14	9	8
0	30	30	16	12	9
0	24	30	14	10	15
0	34	31	11	9	17
0	34	32	12	12	13
1	33	34	15	8	15
1	34	36	15	11	15
1	35	37	16	11	14
0	35	36	16	12	16
0	36	33	11	10	13
0	34	33	15	10	16
1	34	33	12	12	9
0	41	44	12	12	16
0	32	39	15	11	11
0	30	32	15	8	10
1	35	35	16	12	11
0	28	25	14	10	15
1	33	35	17	11	17
1	39	34	14	10	14
0	36	35	13	8	8
1	36	39	15	12	15
0	35	33	13	12	11
0	38	36	14	10	16
1	33	32	15	12	10
0	31	32	12	9	15
1	32	36	8	6	16
0	31	32	14	10	19
0	33	34	14	9	12
0	34	33	11	9	8
0	34	35	12	9	11
1	34	30	13	6	14
0	33	38	10	10	9
0	32	34	16	6	15
1	41	33	18	14	13
1	34	32	13	10	16
0	36	31	11	10	11
0	37	30	4	6	12
0	36	27	13	12	13
1	29	31	16	12	10
0	37	30	10	7	11
0	27	32	12	8	12
0	35	35	12	11	8
0	28	28	10	3	12
0	35	33	13	6	12
0	29	35	12	8	11
0	32	35	14	9	13
1	36	32	10	9	14
1	19	21	12	8	10
1	21	20	12	9	12
0	31	34	11	7	15
0	33	32	10	7	13
1	36	34	12	6	13
1	33	32	16	9	13
0	37	33	12	10	12
0	34	33	14	11	12
0	35	37	16	12	9
1	31	32	14	8	9
1	37	34	13	11	15
1	35	30	4	3	10
1	27	30	15	11	14
0	34	38	11	12	15
0	40	36	11	7	7
0	29	32	14	9	14
0	38	34	15	12	8
1	34	33	14	8	10
0	21	27	13	11	13
0	36	32	11	8	13
1	38	34	15	10	13
0	30	29	11	8	8
0	35	35	13	7	12
1	30	27	13	8	13
1	36	33	16	10	12
0	34	38	13	8	10
1	35	36	16	12	13
0	34	33	16	14	12
0	32	39	12	7	9
1	33	29	7	6	15
0	33	32	16	11	13
1	26	34	5	4	13
0	35	38	16	9	13
0	21	17	4	5	15
0	38	35	12	9	15
0	35	32	15	11	14
1	33	34	14	12	15
0	37	36	11	9	11
0	38	31	16	12	15
1	34	35	15	10	14
0	27	29	12	9	13
1	16	22	6	6	12
0	40	41	16	10	16
0	36	36	10	9	16
1	42	42	15	13	9
1	30	33	14	12	14

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Herman Ole Andreas Wold' @ wold.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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154236&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154236&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154236&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	2 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Correlations for all pairs of data series (method=pearson)
	Gender	Connected	Separate	Learning	Software	Happiness
Gender	1	0.06	0.139	0.158	0.168	0.214
Connected	0.06	1	0.524	0.298	0.201	0.114
Separate	0.139	0.524	1	0.297	0.23	0.085
Learning	0.158	0.298	0.297	1	0.655	0.218
Software	0.168	0.201	0.23	0.655	1	0.161
Happiness	0.214	0.114	0.085	0.218	0.161	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Gender & Connected & Separate & Learning & Software & Happiness \tabularnewline
Gender & 1 & 0.06 & 0.139 & 0.158 & 0.168 & 0.214 \tabularnewline
Connected & 0.06 & 1 & 0.524 & 0.298 & 0.201 & 0.114 \tabularnewline
Separate & 0.139 & 0.524 & 1 & 0.297 & 0.23 & 0.085 \tabularnewline
Learning & 0.158 & 0.298 & 0.297 & 1 & 0.655 & 0.218 \tabularnewline
Software & 0.168 & 0.201 & 0.23 & 0.655 & 1 & 0.161 \tabularnewline
Happiness & 0.214 & 0.114 & 0.085 & 0.218 & 0.161 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154236&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Gender[/C][C]Connected[/C][C]Separate[/C][C]Learning[/C][C]Software[/C][C]Happiness[/C][/ROW]
[ROW][C]Gender[/C][C]1[/C][C]0.06[/C][C]0.139[/C][C]0.158[/C][C]0.168[/C][C]0.214[/C][/ROW]
[ROW][C]Connected[/C][C]0.06[/C][C]1[/C][C]0.524[/C][C]0.298[/C][C]0.201[/C][C]0.114[/C][/ROW]
[ROW][C]Separate[/C][C]0.139[/C][C]0.524[/C][C]1[/C][C]0.297[/C][C]0.23[/C][C]0.085[/C][/ROW]
[ROW][C]Learning[/C][C]0.158[/C][C]0.298[/C][C]0.297[/C][C]1[/C][C]0.655[/C][C]0.218[/C][/ROW]
[ROW][C]Software[/C][C]0.168[/C][C]0.201[/C][C]0.23[/C][C]0.655[/C][C]1[/C][C]0.161[/C][/ROW]
[ROW][C]Happiness[/C][C]0.214[/C][C]0.114[/C][C]0.085[/C][C]0.218[/C][C]0.161[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154236&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154236&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)
	Gender	Connected	Separate	Learning	Software	Happiness
Gender	1	0.06	0.139	0.158	0.168	0.214
Connected	0.06	1	0.524	0.298	0.201	0.114
Separate	0.139	0.524	1	0.297	0.23	0.085
Learning	0.158	0.298	0.297	1	0.655	0.218
Software	0.168	0.201	0.23	0.655	1	0.161
Happiness	0.214	0.114	0.085	0.218	0.161	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
Gender;Connected	0.0603	0.0548	0.0465
p-value	(0.3081)	(0.3537)	(0.3528)
Gender;Separate	0.1395	0.1582	0.1342
p-value	(0.0179)	(0.0072)	(0.0074)
Gender;Learning	0.1583	0.1977	0.1721
p-value	(0.0071)	(7e-04)	(8e-04)
Gender;Software	0.1681	0.199	0.1732
p-value	(0.0042)	(7e-04)	(7e-04)
Gender;Happiness	0.2141	0.2084	0.1797
p-value	(3e-04)	(4e-04)	(4e-04)
Connected;Separate	0.5244	0.3741	0.2786
p-value	(0)	(0)	(0)
Connected;Learning	0.2981	0.2166	0.1644
p-value	(0)	(2e-04)	(2e-04)
Connected;Software	0.2006	0.1796	0.1331
p-value	(6e-04)	(0.0022)	(0.0023)
Connected;Happiness	0.1144	0.1435	0.1058
p-value	(0.0525)	(0.0148)	(0.0142)
Separate;Learning	0.2966	0.2392	0.1791
p-value	(0)	(0)	(0)
Separate;Software	0.2304	0.2125	0.1578
p-value	(1e-04)	(3e-04)	(3e-04)
Separate;Happiness	0.0854	0.1038	0.0737
p-value	(0.1482)	(0.0786)	(0.0879)
Learning;Software	0.6547	0.5986	0.4848
p-value	(0)	(0)	(0)
Learning;Happiness	0.2183	0.2333	0.1749
p-value	(2e-04)	(1e-04)	(1e-04)
Software;Happiness	0.1614	0.1585	0.1179
p-value	(0.006)	(0.007)	(0.0078)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Gender;Connected & 0.0603 & 0.0548 & 0.0465 \tabularnewline
p-value & (0.3081) & (0.3537) & (0.3528) \tabularnewline
Gender;Separate & 0.1395 & 0.1582 & 0.1342 \tabularnewline
p-value & (0.0179) & (0.0072) & (0.0074) \tabularnewline
Gender;Learning & 0.1583 & 0.1977 & 0.1721 \tabularnewline
p-value & (0.0071) & (7e-04) & (8e-04) \tabularnewline
Gender;Software & 0.1681 & 0.199 & 0.1732 \tabularnewline
p-value & (0.0042) & (7e-04) & (7e-04) \tabularnewline
Gender;Happiness & 0.2141 & 0.2084 & 0.1797 \tabularnewline
p-value & (3e-04) & (4e-04) & (4e-04) \tabularnewline
Connected;Separate & 0.5244 & 0.3741 & 0.2786 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Connected;Learning & 0.2981 & 0.2166 & 0.1644 \tabularnewline
p-value & (0) & (2e-04) & (2e-04) \tabularnewline
Connected;Software & 0.2006 & 0.1796 & 0.1331 \tabularnewline
p-value & (6e-04) & (0.0022) & (0.0023) \tabularnewline
Connected;Happiness & 0.1144 & 0.1435 & 0.1058 \tabularnewline
p-value & (0.0525) & (0.0148) & (0.0142) \tabularnewline
Separate;Learning & 0.2966 & 0.2392 & 0.1791 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Separate;Software & 0.2304 & 0.2125 & 0.1578 \tabularnewline
p-value & (1e-04) & (3e-04) & (3e-04) \tabularnewline
Separate;Happiness & 0.0854 & 0.1038 & 0.0737 \tabularnewline
p-value & (0.1482) & (0.0786) & (0.0879) \tabularnewline
Learning;Software & 0.6547 & 0.5986 & 0.4848 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Learning;Happiness & 0.2183 & 0.2333 & 0.1749 \tabularnewline
p-value & (2e-04) & (1e-04) & (1e-04) \tabularnewline
Software;Happiness & 0.1614 & 0.1585 & 0.1179 \tabularnewline
p-value & (0.006) & (0.007) & (0.0078) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154236&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;Connected[/C][C]0.0603[/C][C]0.0548[/C][C]0.0465[/C][/ROW]
[ROW][C]p-value[/C][C](0.3081)[/C][C](0.3537)[/C][C](0.3528)[/C][/ROW]
[ROW][C]Gender;Separate[/C][C]0.1395[/C][C]0.1582[/C][C]0.1342[/C][/ROW]
[ROW][C]p-value[/C][C](0.0179)[/C][C](0.0072)[/C][C](0.0074)[/C][/ROW]
[ROW][C]Gender;Learning[/C][C]0.1583[/C][C]0.1977[/C][C]0.1721[/C][/ROW]
[ROW][C]p-value[/C][C](0.0071)[/C][C](7e-04)[/C][C](8e-04)[/C][/ROW]
[ROW][C]Gender;Software[/C][C]0.1681[/C][C]0.199[/C][C]0.1732[/C][/ROW]
[ROW][C]p-value[/C][C](0.0042)[/C][C](7e-04)[/C][C](7e-04)[/C][/ROW]
[ROW][C]Gender;Happiness[/C][C]0.2141[/C][C]0.2084[/C][C]0.1797[/C][/ROW]
[ROW][C]p-value[/C][C](3e-04)[/C][C](4e-04)[/C][C](4e-04)[/C][/ROW]
[ROW][C]Connected;Separate[/C][C]0.5244[/C][C]0.3741[/C][C]0.2786[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Connected;Learning[/C][C]0.2981[/C][C]0.2166[/C][C]0.1644[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](2e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]Connected;Software[/C][C]0.2006[/C][C]0.1796[/C][C]0.1331[/C][/ROW]
[ROW][C]p-value[/C][C](6e-04)[/C][C](0.0022)[/C][C](0.0023)[/C][/ROW]
[ROW][C]Connected;Happiness[/C][C]0.1144[/C][C]0.1435[/C][C]0.1058[/C][/ROW]
[ROW][C]p-value[/C][C](0.0525)[/C][C](0.0148)[/C][C](0.0142)[/C][/ROW]
[ROW][C]Separate;Learning[/C][C]0.2966[/C][C]0.2392[/C][C]0.1791[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Separate;Software[/C][C]0.2304[/C][C]0.2125[/C][C]0.1578[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](3e-04)[/C][C](3e-04)[/C][/ROW]
[ROW][C]Separate;Happiness[/C][C]0.0854[/C][C]0.1038[/C][C]0.0737[/C][/ROW]
[ROW][C]p-value[/C][C](0.1482)[/C][C](0.0786)[/C][C](0.0879)[/C][/ROW]
[ROW][C]Learning;Software[/C][C]0.6547[/C][C]0.5986[/C][C]0.4848[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Learning;Happiness[/C][C]0.2183[/C][C]0.2333[/C][C]0.1749[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Software;Happiness[/C][C]0.1614[/C][C]0.1585[/C][C]0.1179[/C][/ROW]
[ROW][C]p-value[/C][C](0.006)[/C][C](0.007)[/C][C](0.0078)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154236&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154236&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;Connected	0.0603	0.0548	0.0465
p-value	(0.3081)	(0.3537)	(0.3528)
Gender;Separate	0.1395	0.1582	0.1342
p-value	(0.0179)	(0.0072)	(0.0074)
Gender;Learning	0.1583	0.1977	0.1721
p-value	(0.0071)	(7e-04)	(8e-04)
Gender;Software	0.1681	0.199	0.1732
p-value	(0.0042)	(7e-04)	(7e-04)
Gender;Happiness	0.2141	0.2084	0.1797
p-value	(3e-04)	(4e-04)	(4e-04)
Connected;Separate	0.5244	0.3741	0.2786
p-value	(0)	(0)	(0)
Connected;Learning	0.2981	0.2166	0.1644
p-value	(0)	(2e-04)	(2e-04)
Connected;Software	0.2006	0.1796	0.1331
p-value	(6e-04)	(0.0022)	(0.0023)
Connected;Happiness	0.1144	0.1435	0.1058
p-value	(0.0525)	(0.0148)	(0.0142)
Separate;Learning	0.2966	0.2392	0.1791
p-value	(0)	(0)	(0)
Separate;Software	0.2304	0.2125	0.1578
p-value	(1e-04)	(3e-04)	(3e-04)
Separate;Happiness	0.0854	0.1038	0.0737
p-value	(0.1482)	(0.0786)	(0.0879)
Learning;Software	0.6547	0.5986	0.4848
p-value	(0)	(0)	(0)
Learning;Happiness	0.2183	0.2333	0.1749
p-value	(2e-04)	(1e-04)	(1e-04)
Software;Happiness	0.1614	0.1585	0.1179
p-value	(0.006)	(0.007)	(0.0078)

Figure 1

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code