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Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationTue, 13 Dec 2011 11:45:29 -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/2011/Dec/13/t1323794759af6tlvgfixtbeff.htm/, Retrieved Thu, 02 May 2024 19:05:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=154524, Retrieved Thu, 02 May 2024 19:05:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact69
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [WS 10 - Pearson C...] [2011-12-13 16:45:29] [e1c4030d3eb0ab0fcc7a7b48aeaac474] [Current]
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Dataseries X:
2	13	12	30	33	13	16
NA	NA	NA	NA	NA	NA	NA
1	8	8	32	35	11	15
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
2	14	12	30	35	12	13
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
2	14	11	33	25	13	14
1	13	11	36	39	12	17
1	16	13	37	37	12	13
NA	NA	NA	NA	NA	NA	NA
1	14	11	31	31	13	12
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	13	10	36	28	12	9
2	15	7	40	38	15	25
1	13	10	31	32	11	13
NA	NA	NA	NA	NA	NA	NA
2	16	12	24	32	13	10
1	20	15	46	46	12	13
NA	NA	NA	NA	NA	NA	NA
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
NA	NA	NA	NA	NA	NA	NA
2	9	8	34	33	12	19
2	15	11	31	35	11	12
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
2	17	14	38	39	11	9
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	12	12	37	36	13	15
1	10	11	34	37	10	15
NA	NA	NA	NA	NA	NA	NA
2	11	6	33	43	12	23
2	16	12	38	27	13	20
1	16	14	27	31	10	0
NA	NA	NA	NA	NA	NA	NA
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
NA	NA	NA	NA	NA	NA	NA
1	16	13	41	31	11	18
NA	NA	NA	NA	NA	NA	NA
2	17	14	29	34	14	19
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	10	12	31	29	12	13
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
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
NA	NA	NA	NA	NA	NA	NA
1	17	12	34	34	15	16
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	15	12	36	30	12	13
NA	NA	NA	NA	NA	NA	NA
2	17	13	33	33	16	11
NA	NA	NA	NA	NA	NA	NA
2	14	15	35	37	10	16
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	10	9	34	33	13	14
NA	NA	NA	NA	NA	NA	NA
2	14	9	38	28	12	11
2	16	11	35	32	12	20
NA	NA	NA	NA	NA	NA	NA
2	18	14	40	40	16	16
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	15	12	35	39	12	12
NA	NA	NA	NA	NA	NA	NA
1	16	15	32	28	16	17
NA	NA	NA	NA	NA	NA	NA
1	16	12	33	33	13	11
NA	NA	NA	NA	NA	NA	NA
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
NA	NA	NA	NA	NA	NA	NA
1	12	11	26	30	13	19
NA	NA	NA	NA	NA	NA	NA
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
NA	NA	NA	NA	NA	NA	NA
1	15	14	35	38	11	15
2	11	6	32	27	14	18
1	16	11	32	27	16	16
NA	NA	NA	NA	NA	NA	NA
2	8	6	32	27	16	16
1	17	14	33	39	14	19
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	16	12	37	37	14	17
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
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
NA	NA	NA	NA	NA	NA	NA
1	16	12	34	36	17	13
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
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
NA	NA	NA	NA	NA	NA	NA
1	14	12	39	40	10	11
NA	NA	NA	NA	NA	NA	NA
2	15	6	29	33	13	17
1	13	14	41	38	12	19
2	16	12	32	33	13	15
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
2	10	10	34	35	14	15
NA	NA	NA	NA	NA	NA	NA
1	15	10	34	30	12	17
1	16	12	35	31	13	13
NA	NA	NA	NA	NA	NA	NA
1	15	11	41	42	14	17
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
2	11	10	32	33	10	12
2	9	7	39	35	12	27
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	16	12	33	33	13	12
NA	12	9	31	28	13	12
1	12	12	30	31	10	15
2	14	12	32	36	13	18
NA	NA	NA	NA	NA	NA	NA
1	14	10	41	32	13	19
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	13	10	24	43	12	21
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
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
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
2	11	11	31	32	15	17
1	9	10	36	36	10	10
NA	NA	NA	NA	NA	NA	NA
2	7	5	39	39	13	18
1	13	10	33	30	0	11
2	15	10	36	34	10	18
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
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
NA	NA	NA	NA	NA	NA	NA
1	16	12	35	37	11	12
1	16	16	37	36	11	12
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	14	10	29	31	12	15
NA	NA	NA	NA	NA	NA	NA
2	14	14	34	31	9	13
NA	NA	NA	NA	NA	NA	NA
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
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
2	12	9	36	29	10	19
2	16	12	38	37	11	15
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	16	11	36	38	14	13
1	16	12	37	38	12	9
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
2	10	7	32	33	13	14
NA	NA	NA	NA	NA	NA	NA
2	14	16	34	34	13	14
2	12	11	29	32	9	12
2	12	12	38	36	13	17
NA	NA	NA	NA	NA	NA	NA
1	12	9	34	30	11	11
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	12	9	33	34	12	17
1	19	15	42	42	13	15
2	14	10	32	24	12	15
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	13	11	31	29	12	11
NA	NA	NA	NA	NA	NA	NA
1	17	14	34	32	11	14
2	16	12	39	31	12	14
1	15	12	38	37	12	14
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	12	12	36	34	13	14
1	8	11	32	35	14	13
1	10	9	37	34	13	14
NA	NA	NA	NA	NA	NA	NA
1	16	11	36	33	12	10
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
2	10	6	34	31	15	17
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
2	16	12	34	32	13	11
1	10	12	34	37	14	13
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	18	14	38	39	12	14
1	12	8	33	31	11	14
NA	NA	NA	NA	NA	NA	NA
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
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
2	16	12	30	31	12	12
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
2	14	10	31	33	14	16
2	12	11	34	31	13	17
2	11	10	33	38	11	13
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
2	15	12	37	32	16	16
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
1	7	11	34	38	13	15
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA
NA	NA	NA	NA	NA	NA	NA




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'AstonUniversity' @ aston.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 & 3 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154524&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154524&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154524&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'AstonUniversity' @ aston.wessa.net







Correlations for all pairs of data series (method=pearson)
GenderLearningSoftwareConnectedSeparateHappinessDepression
Gender1-0.156-0.185-0.189-0.2410.1430.276
Learning-0.15610.6320.160.0870.028-0.184
Software-0.1850.63210.0060.033-0.103-0.265
Connected-0.1890.160.00610.5620.059-0.003
Separate-0.2410.0870.0330.5621-0.025-0.055
Happiness0.1430.028-0.1030.059-0.02510.3
Depression0.276-0.184-0.265-0.003-0.0550.31

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Gender & Learning & Software & Connected & Separate & Happiness & Depression \tabularnewline
Gender & 1 & -0.156 & -0.185 & -0.189 & -0.241 & 0.143 & 0.276 \tabularnewline
Learning & -0.156 & 1 & 0.632 & 0.16 & 0.087 & 0.028 & -0.184 \tabularnewline
Software & -0.185 & 0.632 & 1 & 0.006 & 0.033 & -0.103 & -0.265 \tabularnewline
Connected & -0.189 & 0.16 & 0.006 & 1 & 0.562 & 0.059 & -0.003 \tabularnewline
Separate & -0.241 & 0.087 & 0.033 & 0.562 & 1 & -0.025 & -0.055 \tabularnewline
Happiness & 0.143 & 0.028 & -0.103 & 0.059 & -0.025 & 1 & 0.3 \tabularnewline
Depression & 0.276 & -0.184 & -0.265 & -0.003 & -0.055 & 0.3 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154524&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/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]-0.156[/C][C]-0.185[/C][C]-0.189[/C][C]-0.241[/C][C]0.143[/C][C]0.276[/C][/ROW]
[ROW][C]Learning[/C][C]-0.156[/C][C]1[/C][C]0.632[/C][C]0.16[/C][C]0.087[/C][C]0.028[/C][C]-0.184[/C][/ROW]
[ROW][C]Software[/C][C]-0.185[/C][C]0.632[/C][C]1[/C][C]0.006[/C][C]0.033[/C][C]-0.103[/C][C]-0.265[/C][/ROW]
[ROW][C]Connected[/C][C]-0.189[/C][C]0.16[/C][C]0.006[/C][C]1[/C][C]0.562[/C][C]0.059[/C][C]-0.003[/C][/ROW]
[ROW][C]Separate[/C][C]-0.241[/C][C]0.087[/C][C]0.033[/C][C]0.562[/C][C]1[/C][C]-0.025[/C][C]-0.055[/C][/ROW]
[ROW][C]Happiness[/C][C]0.143[/C][C]0.028[/C][C]-0.103[/C][C]0.059[/C][C]-0.025[/C][C]1[/C][C]0.3[/C][/ROW]
[ROW][C]Depression[/C][C]0.276[/C][C]-0.184[/C][C]-0.265[/C][C]-0.003[/C][C]-0.055[/C][C]0.3[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154524&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154524&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)
GenderLearningSoftwareConnectedSeparateHappinessDepression
Gender1-0.156-0.185-0.189-0.2410.1430.276
Learning-0.15610.6320.160.0870.028-0.184
Software-0.1850.63210.0060.033-0.103-0.265
Connected-0.1890.160.00610.5620.059-0.003
Separate-0.2410.0870.0330.5621-0.025-0.055
Happiness0.1430.028-0.1030.059-0.02510.3
Depression0.276-0.184-0.265-0.003-0.0550.31







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall 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;Happiness0.14340.13710.1219
p-value(0.0843)(0.0988)(0.0986)
Gender;Depression0.27570.25170.2146
p-value(8e-04)(0.0022)(0.0024)
Learning;Software0.63220.6620.5355
p-value(0)(0)(0)
Learning;Connected0.16030.21860.159
p-value(0.0524)(0.0078)(0.0086)
Learning;Separate0.08690.11950.0906
p-value(0.2952)(0.1494)(0.1336)
Learning;Happiness0.02820.05050.0413
p-value(0.7342)(0.5435)(0.5151)
Learning;Depression-0.1843-0.1693-0.1258
p-value(0.0254)(0.0404)(0.0388)
Software;Connected0.00560.09870.0726
p-value(0.946)(0.2342)(0.2345)
Software;Separate0.03340.14360.1075
p-value(0.688)(0.0826)(0.0783)
Software;Happiness-0.1031-0.1026-0.0819
p-value(0.214)(0.2164)(0.2017)
Software;Depression-0.2649-0.2056-0.1521
p-value(0.0012)(0.0125)(0.0134)
Connected;Separate0.56180.39010.291
p-value(0)(0)(0)
Connected;Happiness0.05860.02750.0196
p-value(0.4808)(0.7406)(0.7534)
Connected;Depression-0.0025-0.0037-0.0033
p-value(0.976)(0.9641)(0.9555)
Separate;Happiness-0.0246-0.0765-0.0554
p-value(0.7677)(0.3569)(0.3743)
Separate;Depression-0.0549-0.0513-0.0405
p-value(0.5088)(0.5374)(0.4981)
Happiness;Depression0.30030.32350.2469
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 & 0.6322 & 0.662 & 0.5355 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Learning;Connected & 0.1603 & 0.2186 & 0.159 \tabularnewline
p-value & (0.0524) & (0.0078) & (0.0086) \tabularnewline
Learning;Separate & 0.0869 & 0.1195 & 0.0906 \tabularnewline
p-value & (0.2952) & (0.1494) & (0.1336) \tabularnewline
Learning;Happiness & 0.0282 & 0.0505 & 0.0413 \tabularnewline
p-value & (0.7342) & (0.5435) & (0.5151) \tabularnewline
Learning;Depression & -0.1843 & -0.1693 & -0.1258 \tabularnewline
p-value & (0.0254) & (0.0404) & (0.0388) \tabularnewline
Software;Connected & 0.0056 & 0.0987 & 0.0726 \tabularnewline
p-value & (0.946) & (0.2342) & (0.2345) \tabularnewline
Software;Separate & 0.0334 & 0.1436 & 0.1075 \tabularnewline
p-value & (0.688) & (0.0826) & (0.0783) \tabularnewline
Software;Happiness & -0.1031 & -0.1026 & -0.0819 \tabularnewline
p-value & (0.214) & (0.2164) & (0.2017) \tabularnewline
Software;Depression & -0.2649 & -0.2056 & -0.1521 \tabularnewline
p-value & (0.0012) & (0.0125) & (0.0134) \tabularnewline
Connected;Separate & 0.5618 & 0.3901 & 0.291 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Connected;Happiness & 0.0586 & 0.0275 & 0.0196 \tabularnewline
p-value & (0.4808) & (0.7406) & (0.7534) \tabularnewline
Connected;Depression & -0.0025 & -0.0037 & -0.0033 \tabularnewline
p-value & (0.976) & (0.9641) & (0.9555) \tabularnewline
Separate;Happiness & -0.0246 & -0.0765 & -0.0554 \tabularnewline
p-value & (0.7677) & (0.3569) & (0.3743) \tabularnewline
Separate;Depression & -0.0549 & -0.0513 & -0.0405 \tabularnewline
p-value & (0.5088) & (0.5374) & (0.4981) \tabularnewline
Happiness;Depression & 0.3003 & 0.3235 & 0.2469 \tabularnewline
p-value & (2e-04) & (1e-04) & (1e-04) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154524&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]0.6322[/C][C]0.662[/C][C]0.5355[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Learning;Connected[/C][C]0.1603[/C][C]0.2186[/C][C]0.159[/C][/ROW]
[ROW][C]p-value[/C][C](0.0524)[/C][C](0.0078)[/C][C](0.0086)[/C][/ROW]
[ROW][C]Learning;Separate[/C][C]0.0869[/C][C]0.1195[/C][C]0.0906[/C][/ROW]
[ROW][C]p-value[/C][C](0.2952)[/C][C](0.1494)[/C][C](0.1336)[/C][/ROW]
[ROW][C]Learning;Happiness[/C][C]0.0282[/C][C]0.0505[/C][C]0.0413[/C][/ROW]
[ROW][C]p-value[/C][C](0.7342)[/C][C](0.5435)[/C][C](0.5151)[/C][/ROW]
[ROW][C]Learning;Depression[/C][C]-0.1843[/C][C]-0.1693[/C][C]-0.1258[/C][/ROW]
[ROW][C]p-value[/C][C](0.0254)[/C][C](0.0404)[/C][C](0.0388)[/C][/ROW]
[ROW][C]Software;Connected[/C][C]0.0056[/C][C]0.0987[/C][C]0.0726[/C][/ROW]
[ROW][C]p-value[/C][C](0.946)[/C][C](0.2342)[/C][C](0.2345)[/C][/ROW]
[ROW][C]Software;Separate[/C][C]0.0334[/C][C]0.1436[/C][C]0.1075[/C][/ROW]
[ROW][C]p-value[/C][C](0.688)[/C][C](0.0826)[/C][C](0.0783)[/C][/ROW]
[ROW][C]Software;Happiness[/C][C]-0.1031[/C][C]-0.1026[/C][C]-0.0819[/C][/ROW]
[ROW][C]p-value[/C][C](0.214)[/C][C](0.2164)[/C][C](0.2017)[/C][/ROW]
[ROW][C]Software;Depression[/C][C]-0.2649[/C][C]-0.2056[/C][C]-0.1521[/C][/ROW]
[ROW][C]p-value[/C][C](0.0012)[/C][C](0.0125)[/C][C](0.0134)[/C][/ROW]
[ROW][C]Connected;Separate[/C][C]0.5618[/C][C]0.3901[/C][C]0.291[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Connected;Happiness[/C][C]0.0586[/C][C]0.0275[/C][C]0.0196[/C][/ROW]
[ROW][C]p-value[/C][C](0.4808)[/C][C](0.7406)[/C][C](0.7534)[/C][/ROW]
[ROW][C]Connected;Depression[/C][C]-0.0025[/C][C]-0.0037[/C][C]-0.0033[/C][/ROW]
[ROW][C]p-value[/C][C](0.976)[/C][C](0.9641)[/C][C](0.9555)[/C][/ROW]
[ROW][C]Separate;Happiness[/C][C]-0.0246[/C][C]-0.0765[/C][C]-0.0554[/C][/ROW]
[ROW][C]p-value[/C][C](0.7677)[/C][C](0.3569)[/C][C](0.3743)[/C][/ROW]
[ROW][C]Separate;Depression[/C][C]-0.0549[/C][C]-0.0513[/C][C]-0.0405[/C][/ROW]
[ROW][C]p-value[/C][C](0.5088)[/C][C](0.5374)[/C][C](0.4981)[/C][/ROW]
[ROW][C]Happiness;Depression[/C][C]0.3003[/C][C]0.3235[/C][C]0.2469[/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=154524&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154524&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;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;Happiness0.14340.13710.1219
p-value(0.0843)(0.0988)(0.0986)
Gender;Depression0.27570.25170.2146
p-value(8e-04)(0.0022)(0.0024)
Learning;Software0.63220.6620.5355
p-value(0)(0)(0)
Learning;Connected0.16030.21860.159
p-value(0.0524)(0.0078)(0.0086)
Learning;Separate0.08690.11950.0906
p-value(0.2952)(0.1494)(0.1336)
Learning;Happiness0.02820.05050.0413
p-value(0.7342)(0.5435)(0.5151)
Learning;Depression-0.1843-0.1693-0.1258
p-value(0.0254)(0.0404)(0.0388)
Software;Connected0.00560.09870.0726
p-value(0.946)(0.2342)(0.2345)
Software;Separate0.03340.14360.1075
p-value(0.688)(0.0826)(0.0783)
Software;Happiness-0.1031-0.1026-0.0819
p-value(0.214)(0.2164)(0.2017)
Software;Depression-0.2649-0.2056-0.1521
p-value(0.0012)(0.0125)(0.0134)
Connected;Separate0.56180.39010.291
p-value(0)(0)(0)
Connected;Happiness0.05860.02750.0196
p-value(0.4808)(0.7406)(0.7534)
Connected;Depression-0.0025-0.0037-0.0033
p-value(0.976)(0.9641)(0.9555)
Separate;Happiness-0.0246-0.0765-0.0554
p-value(0.7677)(0.3569)(0.3743)
Separate;Depression-0.0549-0.0513-0.0405
p-value(0.5088)(0.5374)(0.4981)
Happiness;Depression0.30030.32350.2469
p-value(2e-04)(1e-04)(1e-04)



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')