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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 computationWed, 04 Dec 2013 05:24:40 -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/2013/Dec/04/t13861527248xzp8ugf57jqm2y.htm/, Retrieved Wed, 24 Apr 2024 09:51:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230488, Retrieved Wed, 24 Apr 2024 09:51:40 +0000
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Original text written by user:Howard Van den Branden
IsPrivate?No (this computation is public)
User-defined keywordsHoward Van den Branden
Estimated Impact81
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 co...] [2013-12-04 10:24:40] [c48df00dfd28bb130a7db97d228aa375] [Current]
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Dataseries X:
41 38 13 12 14 12 32
39 32 16 11 18 11 51
30 35 19 15 11 14 42
31 33 15 6 12 12 41
34 37 14 13 16 21 46
35 29 13 10 18 12 47
39 31 19 12 14 22 37
34 36 15 14 14 11 49
36 35 14 12 15 10 45
37 38 15 9 15 13 47
38 31 16 10 17 10 49
36 34 16 12 19 8 33
38 35 16 12 10 15 42
39 38 16 11 16 14 33
33 37 17 15 18 10 53
32 33 15 12 14 14 36
36 32 15 10 14 14 45
38 38 20 12 17 11 54
39 38 18 11 14 10 41
32 32 16 12 16 13 36
32 33 16 11 18 9.5 41
31 31 16 12 11 14 44
39 38 19 13 14 12 33
37 39 16 11 12 14 37
39 32 17 12 17 11 52
41 32 17 13 9 9 47
36 35 16 10 16 11 43
33 37 15 14 14 15 44
33 33 16 12 15 14 45
34 33 14 10 11 13 44
31 31 15 12 16 9 49
27 32 12 8 13 15 33
37 31 14 10 17 10 43
34 37 16 12 15 11 54
34 30 14 12 14 13 42
32 33 10 7 16 8 44
29 31 10 9 9 20 37
36 33 14 12 15 12 43
29 31 16 10 17 10 46
35 33 16 10 13 10 42
37 32 16 10 15 9 45
34 33 14 12 16 14 44
38 32 20 15 16 8 33
35 33 14 10 12 14 31
38 28 14 10 15 11 42
37 35 11 12 11 13 40
38 39 14 13 15 9 43
33 34 15 11 15 11 46
36 38 16 11 17 15 42
38 32 14 12 13 11 45
32 38 16 14 16 10 44
32 30 14 10 14 14 40
32 33 12 12 11 18 37
34 38 16 13 12 14 46
32 32 9 5 12 11 36
37 35 14 6 15 14.5 47
39 34 16 12 16 13 45
29 34 16 12 15 9 42
37 36 15 11 12 10 43
35 34 16 10 12 15 43
30 28 12 7 8 20 32
38 34 16 12 13 12 45
34 35 16 14 11 12 48
31 35 14 11 14 14 31
34 31 16 12 15 13 33
35 37 17 13 10 11 49
36 35 18 14 11 17 42
30 27 18 11 12 12 41
39 40 12 12 15 13 38
35 37 16 12 15 14 42
38 36 10 8 14 13 44
31 38 14 11 16 15 33
34 39 18 14 15 13 48
38 41 18 14 15 10 40
34 27 16 12 13 11 50
39 30 17 9 12 19 49
37 37 16 13 17 13 43
34 31 16 11 13 17 44
28 31 13 12 15 13 47
37 27 16 12 13 9 33
33 36 16 12 15 11 46
35 37 16 12 15 9 45
37 33 15 12 16 12 43
32 34 15 11 15 12 44
33 31 16 10 14 13 47
38 39 14 9 15 13 45
33 34 16 12 14 12 42
29 32 16 12 13 15 33
33 33 15 12 7 22 43
31 36 12 9 17 13 46
36 32 17 15 13 15 33
35 41 16 12 15 13 46
32 28 15 12 14 15 48
29 30 13 12 13 12.5 47
39 36 16 10 16 11 47
37 35 16 13 12 16 43
35 31 16 9 14 11 46
37 34 16 12 17 11 48
32 36 14 10 15 10 46
38 36 16 14 17 10 45
37 35 16 11 12 16 45
36 37 20 15 16 12 52
32 28 15 11 11 11 42
33 39 16 11 15 16 47
40 32 13 12 9 19 41
38 35 17 12 16 11 47
41 39 16 12 15 16 43
36 35 16 11 10 15 33
43 42 12 7 10 24 30
30 34 16 12 15 14 52
31 33 16 14 11 15 44
32 41 17 11 13 11 55
32 33 13 11 14 15 11
37 34 12 10 18 12 47
37 32 18 13 16 10 53
33 40 14 13 14 14 33
34 40 14 8 14 13 44
33 35 13 11 14 9 42
38 36 16 12 14 15 55
33 37 13 11 12 15 33
31 27 16 13 14 14 46
38 39 13 12 15 11 54
37 38 16 14 15 8 47
36 31 15 13 15 11 45
31 33 16 15 13 11 47
39 32 15 10 17 8 55
44 39 17 11 17 10 44
33 36 15 9 19 11 53
35 33 12 11 15 13 44
32 33 16 10 13 11 42
28 32 10 11 9 20 40
40 37 16 8 15 10 46
27 30 12 11 15 15 40
37 38 14 12 15 12 46
32 29 15 12 16 14 53
28 22 13 9 11 23 33
34 35 15 11 14 14 42
30 35 11 10 11 16 35
35 34 12 8 15 11 40
31 35 11 9 13 12 41
32 34 16 8 15 10 33
30 37 15 9 16 14 51
30 35 17 15 14 12 53
31 23 16 11 15 12 46
40 31 10 8 16 11 55
32 27 18 13 16 12 47
36 36 13 12 11 13 38
32 31 16 12 12 11 46
35 32 13 9 9 19 46
38 39 10 7 16 12 53
42 37 15 13 13 17 47
34 38 16 9 16 9 41
35 39 16 6 12 12 44
38 34 14 8 9 19 43
33 31 10 8 13 18 51
36 32 17 15 13 15 33
32 37 13 6 14 14 43
33 36 15 9 19 11 53
34 32 16 11 13 9 51
32 38 12 8 12 18 50
34 36 13 8 13 16 46
27 26 13 10 10 24 43
31 26 12 8 14 14 47
38 33 17 14 16 20 50
34 39 15 10 10 18 43
24 30 10 8 11 23 33
30 33 14 11 14 12 48
26 25 11 12 12 14 44
34 38 13 12 9 16 50
27 37 16 12 9 18 41
37 31 12 5 11 20 34
36 37 16 12 16 12 44
41 35 12 10 9 12 47
29 25 9 7 13 17 35
36 28 12 12 16 13 44
32 35 15 11 13 9 44
37 33 12 8 9 16 43
30 30 12 9 12 18 41
31 31 14 10 16 10 41
38 37 12 9 11 14 42
36 36 16 12 14 11 33
35 30 11 6 13 9 41
31 36 19 15 15 11 44
38 32 15 12 14 10 48
22 28 8 12 16 11 55
32 36 16 12 13 19 44
36 34 17 11 14 14 43
39 31 12 7 15 12 52
28 28 11 7 13 14 30
32 36 11 5 11 21 39
32 36 14 12 11 13 11
38 40 16 12 14 10 44
32 33 12 3 15 15 42
35 37 16 11 11 16 41
32 32 13 10 15 14 44
37 38 15 12 12 12 44
34 31 16 9 14 19 48
33 37 16 12 14 15 53
33 33 14 9 8 19 37
26 32 16 12 13 13 44
30 30 16 12 9 17 44
24 30 14 10 15 12 40
34 31 11 9 17 11 42
34 32 12 12 13 14 35
33 34 15 8 15 11 43
34 36 15 11 15 13 45
35 37 16 11 14 12 55
35 36 16 12 16 15 31
36 33 11 10 13 14 44
34 33 15 10 16 12 50
34 33 12 12 9 17 40
41 44 12 12 16 11 53
32 39 15 11 11 18 54
30 32 15 8 10 13 49
35 35 16 12 11 17 40
28 25 14 10 15 13 41
33 35 17 11 17 11 52
39 34 14 10 14 12 52
36 35 13 8 8 22 36
36 39 15 12 15 14 52
35 33 13 12 11 12 46
38 36 14 10 16 12 31
33 32 15 12 10 17 44
31 32 12 9 15 9 44
34 36 13 9 9 21 11
32 36 8 6 16 10 46
31 32 14 10 19 11 33
33 34 14 9 12 12 34
34 33 11 9 8 23 42
34 35 12 9 11 13 43
34 30 13 6 14 12 43
33 38 10 10 9 16 44
32 34 16 6 15 9 36
41 33 18 14 13 17 46
34 32 13 10 16 9 44
36 31 11 10 11 14 43
37 30 4 6 12 17 50
36 27 13 12 13 13 33
29 31 16 12 10 11 43
37 30 10 7 11 12 44
27 32 12 8 12 10 53
35 35 12 11 8 19 34
28 28 10 3 12 16 35
35 33 13 6 12 16 40
37 31 15 10 15 14 53
29 35 12 8 11 20 42
32 35 14 9 13 15 43
36 32 10 9 14 23 29
19 21 12 8 10 20 36
21 20 12 9 12 16 30
31 34 11 7 15 14 42
33 32 10 7 13 17 47
36 34 12 6 13 11 44
33 32 16 9 13 13 45
37 33 12 10 12 17 44
34 33 14 11 12 15 43
35 37 16 12 9 21 43
31 32 14 8 9 18 40
37 34 13 11 15 15 41
35 30 4 3 10 8 52
27 30 15 11 14 12 38
34 38 11 12 15 12 41
40 36 11 7 7 22 39
29 32 14 9 14 12 43
   




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 9 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230488&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230488&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230488&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 time9 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Correlations for all pairs of data series (method=pearson)
ConnectedSeparateLearningSoftwareHappinessDepressionSport2
Connected10.4550.20.1340.133-0.1360.144
Separate0.45510.2230.190.11-0.0990.107
Learning0.20.22310.6230.249-0.2310.125
Software0.1340.190.62310.164-0.1640.098
Happiness0.1330.110.2490.1641-0.5830.263
Depression-0.136-0.099-0.231-0.164-0.5831-0.283
Sport20.1440.1070.1250.0980.263-0.2831

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Connected & Separate & Learning & Software & Happiness & Depression & Sport2 \tabularnewline
Connected & 1 & 0.455 & 0.2 & 0.134 & 0.133 & -0.136 & 0.144 \tabularnewline
Separate & 0.455 & 1 & 0.223 & 0.19 & 0.11 & -0.099 & 0.107 \tabularnewline
Learning & 0.2 & 0.223 & 1 & 0.623 & 0.249 & -0.231 & 0.125 \tabularnewline
Software & 0.134 & 0.19 & 0.623 & 1 & 0.164 & -0.164 & 0.098 \tabularnewline
Happiness & 0.133 & 0.11 & 0.249 & 0.164 & 1 & -0.583 & 0.263 \tabularnewline
Depression & -0.136 & -0.099 & -0.231 & -0.164 & -0.583 & 1 & -0.283 \tabularnewline
Sport2 & 0.144 & 0.107 & 0.125 & 0.098 & 0.263 & -0.283 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230488&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Connected[/C][C]Separate[/C][C]Learning[/C][C]Software[/C][C]Happiness[/C][C]Depression[/C][C]Sport2[/C][/ROW]
[ROW][C]Connected[/C][C]1[/C][C]0.455[/C][C]0.2[/C][C]0.134[/C][C]0.133[/C][C]-0.136[/C][C]0.144[/C][/ROW]
[ROW][C]Separate[/C][C]0.455[/C][C]1[/C][C]0.223[/C][C]0.19[/C][C]0.11[/C][C]-0.099[/C][C]0.107[/C][/ROW]
[ROW][C]Learning[/C][C]0.2[/C][C]0.223[/C][C]1[/C][C]0.623[/C][C]0.249[/C][C]-0.231[/C][C]0.125[/C][/ROW]
[ROW][C]Software[/C][C]0.134[/C][C]0.19[/C][C]0.623[/C][C]1[/C][C]0.164[/C][C]-0.164[/C][C]0.098[/C][/ROW]
[ROW][C]Happiness[/C][C]0.133[/C][C]0.11[/C][C]0.249[/C][C]0.164[/C][C]1[/C][C]-0.583[/C][C]0.263[/C][/ROW]
[ROW][C]Depression[/C][C]-0.136[/C][C]-0.099[/C][C]-0.231[/C][C]-0.164[/C][C]-0.583[/C][C]1[/C][C]-0.283[/C][/ROW]
[ROW][C]Sport2[/C][C]0.144[/C][C]0.107[/C][C]0.125[/C][C]0.098[/C][C]0.263[/C][C]-0.283[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230488&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230488&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)
ConnectedSeparateLearningSoftwareHappinessDepressionSport2
Connected10.4550.20.1340.133-0.1360.144
Separate0.45510.2230.190.11-0.0990.107
Learning0.20.22310.6230.249-0.2310.125
Software0.1340.190.62310.164-0.1640.098
Happiness0.1330.110.2490.1641-0.5830.263
Depression-0.136-0.099-0.231-0.164-0.5831-0.283
Sport20.1440.1070.1250.0980.263-0.2831







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Connected;Separate0.45510.33880.2521
p-value(0)(0)(0)
Connected;Learning0.19960.18150.1373
p-value(0.0011)(0.0031)(0.0026)
Connected;Software0.13390.14890.111
p-value(0.0296)(0.0155)(0.015)
Connected;Happiness0.13280.15240.1127
p-value(0.031)(0.0132)(0.0125)
Connected;Depression-0.1364-0.1382-0.102
p-value(0.0267)(0.0247)(0.0222)
Connected;Sport20.14390.15010.1089
p-value(0.0193)(0.0146)(0.0133)
Separate;Learning0.22270.21370.1602
p-value(3e-04)(5e-04)(5e-04)
Separate;Software0.18970.20020.1481
p-value(0.002)(0.0011)(0.0012)
Separate;Happiness0.10990.11550.0815
p-value(0.0747)(0.061)(0.0715)
Separate;Depression-0.0993-0.0482-0.0358
p-value(0.1073)(0.4351)(0.4229)
Separate;Sport20.10730.08480.0607
p-value(0.082)(0.1693)(0.1687)
Learning;Software0.62340.58320.4726
p-value(0)(0)(0)
Learning;Happiness0.24860.23950.1798
p-value(0)(1e-04)(1e-04)
Learning;Depression-0.2309-0.2491-0.1892
p-value(2e-04)(0)(0)
Learning;Sport20.1250.19710.1494
p-value(0.0424)(0.0013)(9e-04)
Software;Happiness0.16420.15230.1123
p-value(0.0075)(0.0132)(0.0154)
Software;Depression-0.1636-0.1296-0.0961
p-value(0.0077)(0.0353)(0.0361)
Software;Sport20.09760.13280.0985
p-value(0.1137)(0.031)(0.0294)
Happiness;Depression-0.5829-0.5407-0.4228
p-value(0)(0)(0)
Happiness;Sport20.26330.29750.2184
p-value(0)(0)(0)
Depression;Sport2-0.2829-0.2823-0.2045
p-value(0)(0)(0)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Connected;Separate & 0.4551 & 0.3388 & 0.2521 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Connected;Learning & 0.1996 & 0.1815 & 0.1373 \tabularnewline
p-value & (0.0011) & (0.0031) & (0.0026) \tabularnewline
Connected;Software & 0.1339 & 0.1489 & 0.111 \tabularnewline
p-value & (0.0296) & (0.0155) & (0.015) \tabularnewline
Connected;Happiness & 0.1328 & 0.1524 & 0.1127 \tabularnewline
p-value & (0.031) & (0.0132) & (0.0125) \tabularnewline
Connected;Depression & -0.1364 & -0.1382 & -0.102 \tabularnewline
p-value & (0.0267) & (0.0247) & (0.0222) \tabularnewline
Connected;Sport2 & 0.1439 & 0.1501 & 0.1089 \tabularnewline
p-value & (0.0193) & (0.0146) & (0.0133) \tabularnewline
Separate;Learning & 0.2227 & 0.2137 & 0.1602 \tabularnewline
p-value & (3e-04) & (5e-04) & (5e-04) \tabularnewline
Separate;Software & 0.1897 & 0.2002 & 0.1481 \tabularnewline
p-value & (0.002) & (0.0011) & (0.0012) \tabularnewline
Separate;Happiness & 0.1099 & 0.1155 & 0.0815 \tabularnewline
p-value & (0.0747) & (0.061) & (0.0715) \tabularnewline
Separate;Depression & -0.0993 & -0.0482 & -0.0358 \tabularnewline
p-value & (0.1073) & (0.4351) & (0.4229) \tabularnewline
Separate;Sport2 & 0.1073 & 0.0848 & 0.0607 \tabularnewline
p-value & (0.082) & (0.1693) & (0.1687) \tabularnewline
Learning;Software & 0.6234 & 0.5832 & 0.4726 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Learning;Happiness & 0.2486 & 0.2395 & 0.1798 \tabularnewline
p-value & (0) & (1e-04) & (1e-04) \tabularnewline
Learning;Depression & -0.2309 & -0.2491 & -0.1892 \tabularnewline
p-value & (2e-04) & (0) & (0) \tabularnewline
Learning;Sport2 & 0.125 & 0.1971 & 0.1494 \tabularnewline
p-value & (0.0424) & (0.0013) & (9e-04) \tabularnewline
Software;Happiness & 0.1642 & 0.1523 & 0.1123 \tabularnewline
p-value & (0.0075) & (0.0132) & (0.0154) \tabularnewline
Software;Depression & -0.1636 & -0.1296 & -0.0961 \tabularnewline
p-value & (0.0077) & (0.0353) & (0.0361) \tabularnewline
Software;Sport2 & 0.0976 & 0.1328 & 0.0985 \tabularnewline
p-value & (0.1137) & (0.031) & (0.0294) \tabularnewline
Happiness;Depression & -0.5829 & -0.5407 & -0.4228 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Happiness;Sport2 & 0.2633 & 0.2975 & 0.2184 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Depression;Sport2 & -0.2829 & -0.2823 & -0.2045 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230488&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]Connected;Separate[/C][C]0.4551[/C][C]0.3388[/C][C]0.2521[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Connected;Learning[/C][C]0.1996[/C][C]0.1815[/C][C]0.1373[/C][/ROW]
[ROW][C]p-value[/C][C](0.0011)[/C][C](0.0031)[/C][C](0.0026)[/C][/ROW]
[ROW][C]Connected;Software[/C][C]0.1339[/C][C]0.1489[/C][C]0.111[/C][/ROW]
[ROW][C]p-value[/C][C](0.0296)[/C][C](0.0155)[/C][C](0.015)[/C][/ROW]
[ROW][C]Connected;Happiness[/C][C]0.1328[/C][C]0.1524[/C][C]0.1127[/C][/ROW]
[ROW][C]p-value[/C][C](0.031)[/C][C](0.0132)[/C][C](0.0125)[/C][/ROW]
[ROW][C]Connected;Depression[/C][C]-0.1364[/C][C]-0.1382[/C][C]-0.102[/C][/ROW]
[ROW][C]p-value[/C][C](0.0267)[/C][C](0.0247)[/C][C](0.0222)[/C][/ROW]
[ROW][C]Connected;Sport2[/C][C]0.1439[/C][C]0.1501[/C][C]0.1089[/C][/ROW]
[ROW][C]p-value[/C][C](0.0193)[/C][C](0.0146)[/C][C](0.0133)[/C][/ROW]
[ROW][C]Separate;Learning[/C][C]0.2227[/C][C]0.2137[/C][C]0.1602[/C][/ROW]
[ROW][C]p-value[/C][C](3e-04)[/C][C](5e-04)[/C][C](5e-04)[/C][/ROW]
[ROW][C]Separate;Software[/C][C]0.1897[/C][C]0.2002[/C][C]0.1481[/C][/ROW]
[ROW][C]p-value[/C][C](0.002)[/C][C](0.0011)[/C][C](0.0012)[/C][/ROW]
[ROW][C]Separate;Happiness[/C][C]0.1099[/C][C]0.1155[/C][C]0.0815[/C][/ROW]
[ROW][C]p-value[/C][C](0.0747)[/C][C](0.061)[/C][C](0.0715)[/C][/ROW]
[ROW][C]Separate;Depression[/C][C]-0.0993[/C][C]-0.0482[/C][C]-0.0358[/C][/ROW]
[ROW][C]p-value[/C][C](0.1073)[/C][C](0.4351)[/C][C](0.4229)[/C][/ROW]
[ROW][C]Separate;Sport2[/C][C]0.1073[/C][C]0.0848[/C][C]0.0607[/C][/ROW]
[ROW][C]p-value[/C][C](0.082)[/C][C](0.1693)[/C][C](0.1687)[/C][/ROW]
[ROW][C]Learning;Software[/C][C]0.6234[/C][C]0.5832[/C][C]0.4726[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Learning;Happiness[/C][C]0.2486[/C][C]0.2395[/C][C]0.1798[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Learning;Depression[/C][C]-0.2309[/C][C]-0.2491[/C][C]-0.1892[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Learning;Sport2[/C][C]0.125[/C][C]0.1971[/C][C]0.1494[/C][/ROW]
[ROW][C]p-value[/C][C](0.0424)[/C][C](0.0013)[/C][C](9e-04)[/C][/ROW]
[ROW][C]Software;Happiness[/C][C]0.1642[/C][C]0.1523[/C][C]0.1123[/C][/ROW]
[ROW][C]p-value[/C][C](0.0075)[/C][C](0.0132)[/C][C](0.0154)[/C][/ROW]
[ROW][C]Software;Depression[/C][C]-0.1636[/C][C]-0.1296[/C][C]-0.0961[/C][/ROW]
[ROW][C]p-value[/C][C](0.0077)[/C][C](0.0353)[/C][C](0.0361)[/C][/ROW]
[ROW][C]Software;Sport2[/C][C]0.0976[/C][C]0.1328[/C][C]0.0985[/C][/ROW]
[ROW][C]p-value[/C][C](0.1137)[/C][C](0.031)[/C][C](0.0294)[/C][/ROW]
[ROW][C]Happiness;Depression[/C][C]-0.5829[/C][C]-0.5407[/C][C]-0.4228[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Happiness;Sport2[/C][C]0.2633[/C][C]0.2975[/C][C]0.2184[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Depression;Sport2[/C][C]-0.2829[/C][C]-0.2823[/C][C]-0.2045[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230488&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230488&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
Connected;Separate0.45510.33880.2521
p-value(0)(0)(0)
Connected;Learning0.19960.18150.1373
p-value(0.0011)(0.0031)(0.0026)
Connected;Software0.13390.14890.111
p-value(0.0296)(0.0155)(0.015)
Connected;Happiness0.13280.15240.1127
p-value(0.031)(0.0132)(0.0125)
Connected;Depression-0.1364-0.1382-0.102
p-value(0.0267)(0.0247)(0.0222)
Connected;Sport20.14390.15010.1089
p-value(0.0193)(0.0146)(0.0133)
Separate;Learning0.22270.21370.1602
p-value(3e-04)(5e-04)(5e-04)
Separate;Software0.18970.20020.1481
p-value(0.002)(0.0011)(0.0012)
Separate;Happiness0.10990.11550.0815
p-value(0.0747)(0.061)(0.0715)
Separate;Depression-0.0993-0.0482-0.0358
p-value(0.1073)(0.4351)(0.4229)
Separate;Sport20.10730.08480.0607
p-value(0.082)(0.1693)(0.1687)
Learning;Software0.62340.58320.4726
p-value(0)(0)(0)
Learning;Happiness0.24860.23950.1798
p-value(0)(1e-04)(1e-04)
Learning;Depression-0.2309-0.2491-0.1892
p-value(2e-04)(0)(0)
Learning;Sport20.1250.19710.1494
p-value(0.0424)(0.0013)(9e-04)
Software;Happiness0.16420.15230.1123
p-value(0.0075)(0.0132)(0.0154)
Software;Depression-0.1636-0.1296-0.0961
p-value(0.0077)(0.0353)(0.0361)
Software;Sport20.09760.13280.0985
p-value(0.1137)(0.031)(0.0294)
Happiness;Depression-0.5829-0.5407-0.4228
p-value(0)(0)(0)
Happiness;Sport20.26330.29750.2184
p-value(0)(0)(0)
Depression;Sport2-0.2829-0.2823-0.2045
p-value(0)(0)(0)







Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.010.570.520.52
0.020.620.710.71
0.030.710.760.81
0.040.760.860.86
0.050.810.860.86
0.060.810.860.86
0.070.810.90.86
0.080.860.90.9
0.090.90.90.9
0.10.90.90.9

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Correlation Tests \tabularnewline
Number of significant by total number of Correlations \tabularnewline
Type I error & Pearson r & Spearman rho & Kendall tau \tabularnewline
0.01 & 0.57 & 0.52 & 0.52 \tabularnewline
0.02 & 0.62 & 0.71 & 0.71 \tabularnewline
0.03 & 0.71 & 0.76 & 0.81 \tabularnewline
0.04 & 0.76 & 0.86 & 0.86 \tabularnewline
0.05 & 0.81 & 0.86 & 0.86 \tabularnewline
0.06 & 0.81 & 0.86 & 0.86 \tabularnewline
0.07 & 0.81 & 0.9 & 0.86 \tabularnewline
0.08 & 0.86 & 0.9 & 0.9 \tabularnewline
0.09 & 0.9 & 0.9 & 0.9 \tabularnewline
0.1 & 0.9 & 0.9 & 0.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230488&T=3

[TABLE]
[ROW][C]Meta Analysis of Correlation Tests[/C][/ROW]
[ROW][C]Number of significant by total number of Correlations[/C][/ROW]
[ROW][C]Type I error[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]0.01[/C][C]0.57[/C][C]0.52[/C][C]0.52[/C][/ROW]
[ROW][C]0.02[/C][C]0.62[/C][C]0.71[/C][C]0.71[/C][/ROW]
[ROW][C]0.03[/C][C]0.71[/C][C]0.76[/C][C]0.81[/C][/ROW]
[ROW][C]0.04[/C][C]0.76[/C][C]0.86[/C][C]0.86[/C][/ROW]
[ROW][C]0.05[/C][C]0.81[/C][C]0.86[/C][C]0.86[/C][/ROW]
[ROW][C]0.06[/C][C]0.81[/C][C]0.86[/C][C]0.86[/C][/ROW]
[ROW][C]0.07[/C][C]0.81[/C][C]0.9[/C][C]0.86[/C][/ROW]
[ROW][C]0.08[/C][C]0.86[/C][C]0.9[/C][C]0.9[/C][/ROW]
[ROW][C]0.09[/C][C]0.9[/C][C]0.9[/C][C]0.9[/C][/ROW]
[ROW][C]0.1[/C][C]0.9[/C][C]0.9[/C][C]0.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230488&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230488&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.010.570.520.52
0.020.620.710.71
0.030.710.760.81
0.040.760.860.86
0.050.810.860.86
0.060.810.860.86
0.070.810.90.86
0.080.860.90.9
0.090.90.90.9
0.10.90.90.9



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')
ncorrs <- (n*n -n)/2
mycorrs <- array(0, dim=c(10,3))
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)
for (iii in 1:10) {
iiid100 <- iii / 100
if (rp$p.value < iiid100) mycorrs[iii, 1] = mycorrs[iii, 1] + 1
if (rs$p.value < iiid100) mycorrs[iii, 2] = mycorrs[iii, 2] + 1
if (rk$p.value < iiid100) mycorrs[iii, 3] = mycorrs[iii, 3] + 1
}
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Correlation Tests',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of significant by total number of Correlations',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Type I error',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)
for (iii in 1:10) {
iiid100 <- iii / 100
a<-table.row.start(a)
a<-table.element(a,round(iiid100,2),header=T)
a<-table.element(a,round(mycorrs[iii,1]/ncorrs,2))
a<-table.element(a,round(mycorrs[iii,2]/ncorrs,2))
a<-table.element(a,round(mycorrs[iii,3]/ncorrs,2))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')