Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationSun, 29 Nov 2015 17:26:59 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Nov/29/t1448818044t612v41vs4baxvx.htm/, Retrieved Wed, 15 May 2024 00:34:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284501, Retrieved Wed, 15 May 2024 00:34:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [] [2015-11-22 21:46:49] [32b17a345b130fdf5cc88718ed94a974]
- R PD    [Kendall tau Correlation Matrix] [Task 13 - Chapter 5] [2015-11-29 17:26:59] [39661ea0cc1af7d66f31b3ef3719ea7a] [Current]
Feedback Forum

Post a new message
Dataseries X:
41 13 38 12 14 12 53 32 9
39 16 32 11 18 11 83 51 9
30 19 35 15 11 14 66 42 9
31 15 33 6 12 12 67 41 9
34 14 37 13 16 21 76 46 9
35 13 29 10 18 12 78 47 9
39 19 31 12 14 22 53 37 9
34 15 36 14 14 11 80 49 9
36 14 35 12 15 10 74 45 9
37 15 38 9 15 13 76 47 9
38 16 31 10 17 10 79 49 9
36 16 34 12 19 8 54 33 9
38 16 35 12 10 15 67 42 9
39 16 38 11 16 14 54 33 9
33 17 37 15 18 10 87 53 9
32 15 33 12 14 14 58 36 9
36 15 32 10 14 14 75 45 9
38 20 38 12 17 11 88 54 9
39 18 38 11 14 10 64 41 9
32 16 32 12 16 13 57 36 9
32 16 33 11 18 9.5 66 41 9
31 16 31 12 11 14 68 44 9
39 19 38 13 14 12 54 33 9
37 16 39 11 12 14 56 37 9
39 17 32 12 17 11 86 52 9
41 17 32 13 9 9 80 47 9
36 16 35 10 16 11 76 43 9
33 15 37 14 14 15 69 44 9
33 16 33 12 15 14 78 45 9
34 14 33 10 11 13 67 44 9
31 15 31 12 16 9 80 49 9
27 12 32 8 13 15 54 33 9
37 14 31 10 17 10 71 43 9
34 16 37 12 15 11 84 54 9
34 14 30 12 14 13 74 42 9
32 10 33 7 16 8 71 44 9
29 10 31 9 9 20 63 37 9
36 14 33 12 15 12 71 43 9
29 16 31 10 17 10 76 46 9
35 16 33 10 13 10 69 42 9
37 16 32 10 15 9 74 45 9
34 14 33 12 16 14 75 44 9
38 20 32 15 16 8 54 33 9
35 14 33 10 12 14 52 31 9
38 14 28 10 15 11 69 42 9
37 11 35 12 11 13 68 40 9
38 14 39 13 15 9 65 43 9
33 15 34 11 15 11 75 46 9
36 16 38 11 17 15 74 42 9
38 14 32 12 13 11 75 45 9
32 16 38 14 16 10 72 44 9
32 14 30 10 14 14 67 40 9
32 12 33 12 11 18 63 37 9
34 16 38 13 12 14 62 46 9
32 9 32 5 12 11 63 36 9
37 14 35 6 15 14.5 76 47 9
39 16 34 12 16 13 74 45 9
29 16 34 12 15 9 67 42 9
37 15 36 11 12 10 73 43 9
35 16 34 10 12 15 70 43 9
30 12 28 7 8 20 53 32 9
38 16 34 12 13 12 77 45 9
34 16 35 14 11 12 80 48 9
31 14 35 11 14 14 52 31 9
34 16 31 12 15 13 54 33 9
35 17 37 13 10 11 80 49 10
36 18 35 14 11 17 66 42 10
30 18 27 11 12 12 73 41 10
39 12 40 12 15 13 63 38 10
35 16 37 12 15 14 69 42 10
38 10 36 8 14 13 67 44 10
31 14 38 11 16 15 54 33 10
34 18 39 14 15 13 81 48 10
38 18 41 14 15 10 69 40 10
34 16 27 12 13 11 84 50 10
39 17 30 9 12 19 80 49 10
37 16 37 13 17 13 70 43 10
34 16 31 11 13 17 69 44 10
28 13 31 12 15 13 77 47 10
37 16 27 12 13 9 54 33 10
33 16 36 12 15 11 79 46 10
35 16 37 12 15 9 71 45 10
37 15 33 12 16 12 73 43 10
32 15 34 11 15 12 72 44 10
33 16 31 10 14 13 77 47 10
38 14 39 9 15 13 75 45 10
33 16 34 12 14 12 69 42 10
29 16 32 12 13 15 54 33 10
33 15 33 12 7 22 70 43 10
31 12 36 9 17 13 73 46 10
36 17 32 15 13 15 54 33 10
35 16 41 12 15 13 77 46 10
32 15 28 12 14 15 82 48 10
29 13 30 12 13 12.5 80 47 10
39 16 36 10 16 11 80 47 10
37 16 35 13 12 16 69 43 10
35 16 31 9 14 11 78 46 10
37 16 34 12 17 11 81 48 10
32 14 36 10 15 10 76 46 10
38 16 36 14 17 10 76 45 10
37 16 35 11 12 16 73 45 10
36 20 37 15 16 12 85 52 10
32 15 28 11 11 11 66 42 10
33 16 39 11 15 16 79 47 10
40 13 32 12 9 19 68 41 10
38 17 35 12 16 11 76 47 10
41 16 39 12 15 16 71 43 10
36 16 35 11 10 15 54 33 10
43 12 42 7 10 24 46 30 10
30 16 34 12 15 14 85 52 10
31 16 33 14 11 15 74 44 10
32 17 41 11 13 11 88 55 10
32 13 33 11 14 15 38 11 10
37 12 34 10 18 12 76 47 10
37 18 32 13 16 10 86 53 10
33 14 40 13 14 14 54 33 10
34 14 40 8 14 13 67 44 10
33 13 35 11 14 9 69 42 10
38 16 36 12 14 15 90 55 10
33 13 37 11 12 15 54 33 10
31 16 27 13 14 14 76 46 10
38 13 39 12 15 11 89 54 10
37 16 38 14 15 8 76 47 10
36 15 31 13 15 11 73 45 10
31 16 33 15 13 11 79 47 10
39 15 32 10 17 8 90 55 10
44 17 39 11 17 10 74 44 10
33 15 36 9 19 11 81 53 10
35 12 33 11 15 13 72 44 10
32 16 33 10 13 11 71 42 10
28 10 32 11 9 20 66 40 10
40 16 37 8 15 10 77 46 10
27 12 30 11 15 15 65 40 10
37 14 38 12 15 12 74 46 10
32 15 29 12 16 14 85 53 10
28 13 22 9 11 23 54 33 10
34 15 35 11 14 14 63 42 10
30 11 35 10 11 16 54 35 10
35 12 34 8 15 11 64 40 10
31 11 35 9 13 12 69 41 10
32 16 34 8 15 10 54 33 10
30 15 37 9 16 14 84 51 10
30 17 35 15 14 12 86 53 10
31 16 23 11 15 12 77 46 10
40 10 31 8 16 11 89 55 10
32 18 27 13 16 12 76 47 10
36 13 36 12 11 13 60 38 10
32 16 31 12 12 11 75 46 10
35 13 32 9 9 19 73 46 10
38 10 39 7 16 12 85 53 10
42 15 37 13 13 17 79 47 10
34 16 38 9 16 9 71 41 10
35 16 39 6 12 12 72 44 10
38 14 34 8 9 19 69 43 9
33 10 31 8 13 18 78 51 10
36 17 32 15 13 15 54 33 10
32 13 37 6 14 14 69 43 10
33 15 36 9 19 11 81 53 10
34 16 32 11 13 9 84 51 10
32 12 38 8 12 18 84 50 10
34 13 36 8 13 16 69 46 10
27 13 26 10 10 24 66 43 11
31 12 26 8 14 14 81 47 11
38 17 33 14 16 20 82 50 11
34 15 39 10 10 18 72 43 11
24 10 30 8 11 23 54 33 11
30 14 33 11 14 12 78 48 11
26 11 25 12 12 14 74 44 11
34 13 38 12 9 16 82 50 11
27 16 37 12 9 18 73 41 11
37 12 31 5 11 20 55 34 11
36 16 37 12 16 12 72 44 11
41 12 35 10 9 12 78 47 11
29 9 25 7 13 17 59 35 11
36 12 28 12 16 13 72 44 11
32 15 35 11 13 9 78 44 11
37 12 33 8 9 16 68 43 11
30 12 30 9 12 18 69 41 11
31 14 31 10 16 10 67 41 11
38 12 37 9 11 14 74 42 11
36 16 36 12 14 11 54 33 11
35 11 30 6 13 9 67 41 11
31 19 36 15 15 11 70 44 11
38 15 32 12 14 10 80 48 11
22 8 28 12 16 11 89 55 11
32 16 36 12 13 19 76 44 11
36 17 34 11 14 14 74 43 11
39 12 31 7 15 12 87 52 11
28 11 28 7 13 14 54 30 11
32 11 36 5 11 21 61 39 11
32 14 36 12 11 13 38 11 11
38 16 40 12 14 10 75 44 11
32 12 33 3 15 15 69 42 11
35 16 37 11 11 16 62 41 11
32 13 32 10 15 14 72 44 11
37 15 38 12 12 12 70 44 11
34 16 31 9 14 19 79 48 11
33 16 37 12 14 15 87 53 11
33 14 33 9 8 19 62 37 11
26 16 32 12 13 13 77 44 11
30 16 30 12 9 17 69 44 11
24 14 30 10 15 12 69 40 11
34 11 31 9 17 11 75 42 11
34 12 32 12 13 14 54 35 11
33 15 34 8 15 11 72 43 11
34 15 36 11 15 13 74 45 11
35 16 37 11 14 12 85 55 11
35 16 36 12 16 15 52 31 11
36 11 33 10 13 14 70 44 11
34 15 33 10 16 12 84 50 11
34 12 33 12 9 17 64 40 11
41 12 44 12 16 11 84 53 11
32 15 39 11 11 18 87 54 11
30 15 32 8 10 13 79 49 11
35 16 35 12 11 17 67 40 11
28 14 25 10 15 13 65 41 11
33 17 35 11 17 11 85 52 11
39 14 34 10 14 12 83 52 11
36 13 35 8 8 22 61 36 11
36 15 39 12 15 14 82 52 11
35 13 33 12 11 12 76 46 11
38 14 36 10 16 12 58 31 11
33 15 32 12 10 17 72 44 11
31 12 32 9 15 9 72 44 11
34 13 36 9 9 21 38 11 11
32 8 36 6 16 10 78 46 11
31 14 32 10 19 11 54 33 11
33 14 34 9 12 12 63 34 11
34 11 33 9 8 23 66 42 11
34 12 35 9 11 13 70 43 11
34 13 30 6 14 12 71 43 11
33 10 38 10 9 16 67 44 11
32 16 34 6 15 9 58 36 11
41 18 33 14 13 17 72 46 11
34 13 32 10 16 9 72 44 11
36 11 31 10 11 14 70 43 11
37 4 30 6 12 17 76 50 11
36 13 27 12 13 13 50 33 11
29 16 31 12 10 11 72 43 11
37 10 30 7 11 12 72 44 11
27 12 32 8 12 10 88 53 11
35 12 35 11 8 19 53 34 11
28 10 28 3 12 16 58 35 11
35 13 33 6 12 16 66 40 11
37 15 31 10 15 14 82 53 11
29 12 35 8 11 20 69 42 11
32 14 35 9 13 15 68 43 11
36 10 32 9 14 23 44 29 11
19 12 21 8 10 20 56 36 11
21 12 20 9 12 16 53 30 11
31 11 34 7 15 14 70 42 11
33 10 32 7 13 17 78 47 11
36 12 34 6 13 11 71 44 11
33 16 32 9 13 13 72 45 11
37 12 33 10 12 17 68 44 11
34 14 33 11 12 15 67 43 11
35 16 37 12 9 21 75 43 11
31 14 32 8 9 18 62 40 11
37 13 34 11 15 15 67 41 11
35 4 30 3 10 8 83 52 11
27 15 30 11 14 12 64 38 11
34 11 38 12 15 12 68 41 11
40 11 36 7 7 22 62 39 11
29 14 32 9 14 12 72 43 11




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284501&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284501&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284501&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'George Udny Yule' @ yule.wessa.net







Correlations for all pairs of data series (method=pearson)
ConnectedLearningSeparateSoftwareHappinessDepressionSport1Sport2Month
Connected10.20.4550.1340.133-0.1360.1240.144-0.198
Learning0.210.2230.6230.249-0.2310.1430.125-0.324
Separate0.4550.22310.190.11-0.0990.10.107-0.114
Software0.1340.6230.1910.164-0.1640.1140.098-0.274
Happiness0.1330.2490.110.1641-0.5830.2870.263-0.247
Depression-0.136-0.231-0.099-0.164-0.5831-0.329-0.2830.234
Sport10.1240.1430.10.1140.287-0.32910.9530
Sport20.1440.1250.1070.0980.263-0.2830.9531-0.021
Month-0.198-0.324-0.114-0.274-0.2470.2340-0.0211

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Connected & Learning & Separate & Software & Happiness & Depression & Sport1 & Sport2 & Month \tabularnewline
Connected & 1 & 0.2 & 0.455 & 0.134 & 0.133 & -0.136 & 0.124 & 0.144 & -0.198 \tabularnewline
Learning & 0.2 & 1 & 0.223 & 0.623 & 0.249 & -0.231 & 0.143 & 0.125 & -0.324 \tabularnewline
Separate & 0.455 & 0.223 & 1 & 0.19 & 0.11 & -0.099 & 0.1 & 0.107 & -0.114 \tabularnewline
Software & 0.134 & 0.623 & 0.19 & 1 & 0.164 & -0.164 & 0.114 & 0.098 & -0.274 \tabularnewline
Happiness & 0.133 & 0.249 & 0.11 & 0.164 & 1 & -0.583 & 0.287 & 0.263 & -0.247 \tabularnewline
Depression & -0.136 & -0.231 & -0.099 & -0.164 & -0.583 & 1 & -0.329 & -0.283 & 0.234 \tabularnewline
Sport1 & 0.124 & 0.143 & 0.1 & 0.114 & 0.287 & -0.329 & 1 & 0.953 & 0 \tabularnewline
Sport2 & 0.144 & 0.125 & 0.107 & 0.098 & 0.263 & -0.283 & 0.953 & 1 & -0.021 \tabularnewline
Month & -0.198 & -0.324 & -0.114 & -0.274 & -0.247 & 0.234 & 0 & -0.021 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284501&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Connected[/C][C]Learning[/C][C]Separate[/C][C]Software[/C][C]Happiness[/C][C]Depression[/C][C]Sport1[/C][C]Sport2[/C][C]Month[/C][/ROW]
[ROW][C]Connected[/C][C]1[/C][C]0.2[/C][C]0.455[/C][C]0.134[/C][C]0.133[/C][C]-0.136[/C][C]0.124[/C][C]0.144[/C][C]-0.198[/C][/ROW]
[ROW][C]Learning[/C][C]0.2[/C][C]1[/C][C]0.223[/C][C]0.623[/C][C]0.249[/C][C]-0.231[/C][C]0.143[/C][C]0.125[/C][C]-0.324[/C][/ROW]
[ROW][C]Separate[/C][C]0.455[/C][C]0.223[/C][C]1[/C][C]0.19[/C][C]0.11[/C][C]-0.099[/C][C]0.1[/C][C]0.107[/C][C]-0.114[/C][/ROW]
[ROW][C]Software[/C][C]0.134[/C][C]0.623[/C][C]0.19[/C][C]1[/C][C]0.164[/C][C]-0.164[/C][C]0.114[/C][C]0.098[/C][C]-0.274[/C][/ROW]
[ROW][C]Happiness[/C][C]0.133[/C][C]0.249[/C][C]0.11[/C][C]0.164[/C][C]1[/C][C]-0.583[/C][C]0.287[/C][C]0.263[/C][C]-0.247[/C][/ROW]
[ROW][C]Depression[/C][C]-0.136[/C][C]-0.231[/C][C]-0.099[/C][C]-0.164[/C][C]-0.583[/C][C]1[/C][C]-0.329[/C][C]-0.283[/C][C]0.234[/C][/ROW]
[ROW][C]Sport1[/C][C]0.124[/C][C]0.143[/C][C]0.1[/C][C]0.114[/C][C]0.287[/C][C]-0.329[/C][C]1[/C][C]0.953[/C][C]0[/C][/ROW]
[ROW][C]Sport2[/C][C]0.144[/C][C]0.125[/C][C]0.107[/C][C]0.098[/C][C]0.263[/C][C]-0.283[/C][C]0.953[/C][C]1[/C][C]-0.021[/C][/ROW]
[ROW][C]Month[/C][C]-0.198[/C][C]-0.324[/C][C]-0.114[/C][C]-0.274[/C][C]-0.247[/C][C]0.234[/C][C]0[/C][C]-0.021[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284501&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284501&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)
ConnectedLearningSeparateSoftwareHappinessDepressionSport1Sport2Month
Connected10.20.4550.1340.133-0.1360.1240.144-0.198
Learning0.210.2230.6230.249-0.2310.1430.125-0.324
Separate0.4550.22310.190.11-0.0990.10.107-0.114
Software0.1340.6230.1910.164-0.1640.1140.098-0.274
Happiness0.1330.2490.110.1641-0.5830.2870.263-0.247
Depression-0.136-0.231-0.099-0.164-0.5831-0.329-0.2830.234
Sport10.1240.1430.10.1140.287-0.32910.9530
Sport20.1440.1250.1070.0980.263-0.2830.9531-0.021
Month-0.198-0.324-0.114-0.274-0.2470.2340-0.0211







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Connected;Learning0.19960.18150.1373
p-value(0.0011)(0.0031)(0.0026)
Connected;Separate0.45510.33880.2521
p-value(0)(0)(0)
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;Sport10.12390.12690.0929
p-value(0.0443)(0.0394)(0.0328)
Connected;Sport20.14390.15010.1089
p-value(0.0193)(0.0146)(0.0133)
Connected;Month-0.1983-0.1734-0.1388
p-value(0.0012)(0.0047)(0.005)
Learning;Separate0.22270.21370.1602
p-value(3e-04)(5e-04)(5e-04)
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;Sport10.14320.22030.1662
p-value(0.02)(3e-04)(2e-04)
Learning;Sport20.1250.19710.1494
p-value(0.0424)(0.0013)(9e-04)
Learning;Month-0.3239-0.3259-0.2666
p-value(0)(0)(0)
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;Sport10.10.06860.0491
p-value(0.1049)(0.2666)(0.2598)
Separate;Sport20.10730.08480.0607
p-value(0.082)(0.1693)(0.1687)
Separate;Month-0.1142-0.1065-0.0832
p-value(0.0639)(0.0841)(0.0929)
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;Sport10.11390.13560.1001
p-value(0.0647)(0.0276)(0.0253)
Software;Sport20.09760.13280.0985
p-value(0.1137)(0.031)(0.0294)
Software;Month-0.2739-0.2778-0.228
p-value(0)(0)(0)
Happiness;Depression-0.5829-0.5407-0.4228
p-value(0)(0)(0)
Happiness;Sport10.28710.33210.2409
p-value(0)(0)(0)
Happiness;Sport20.26330.29750.2184
p-value(0)(0)(0)
Happiness;Month-0.2467-0.2475-0.2043
p-value(1e-04)(0)(0)
Depression;Sport1-0.3294-0.3248-0.233
p-value(0)(0)(0)
Depression;Sport2-0.2829-0.2823-0.2045
p-value(0)(0)(0)
Depression;Month0.23380.23090.1886
p-value(1e-04)(2e-04)(1e-04)
Sport1;Sport20.9530.94570.8488
p-value(0)(0)(0)
Sport1;Month3e-04-0.0068-0.0049
p-value(0.9957)(0.913)(0.9193)
Sport2;Month-0.0209-0.0272-0.02
p-value(0.7358)(0.6594)(0.6835)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Connected;Learning & 0.1996 & 0.1815 & 0.1373 \tabularnewline
p-value & (0.0011) & (0.0031) & (0.0026) \tabularnewline
Connected;Separate & 0.4551 & 0.3388 & 0.2521 \tabularnewline
p-value & (0) & (0) & (0) \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;Sport1 & 0.1239 & 0.1269 & 0.0929 \tabularnewline
p-value & (0.0443) & (0.0394) & (0.0328) \tabularnewline
Connected;Sport2 & 0.1439 & 0.1501 & 0.1089 \tabularnewline
p-value & (0.0193) & (0.0146) & (0.0133) \tabularnewline
Connected;Month & -0.1983 & -0.1734 & -0.1388 \tabularnewline
p-value & (0.0012) & (0.0047) & (0.005) \tabularnewline
Learning;Separate & 0.2227 & 0.2137 & 0.1602 \tabularnewline
p-value & (3e-04) & (5e-04) & (5e-04) \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;Sport1 & 0.1432 & 0.2203 & 0.1662 \tabularnewline
p-value & (0.02) & (3e-04) & (2e-04) \tabularnewline
Learning;Sport2 & 0.125 & 0.1971 & 0.1494 \tabularnewline
p-value & (0.0424) & (0.0013) & (9e-04) \tabularnewline
Learning;Month & -0.3239 & -0.3259 & -0.2666 \tabularnewline
p-value & (0) & (0) & (0) \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;Sport1 & 0.1 & 0.0686 & 0.0491 \tabularnewline
p-value & (0.1049) & (0.2666) & (0.2598) \tabularnewline
Separate;Sport2 & 0.1073 & 0.0848 & 0.0607 \tabularnewline
p-value & (0.082) & (0.1693) & (0.1687) \tabularnewline
Separate;Month & -0.1142 & -0.1065 & -0.0832 \tabularnewline
p-value & (0.0639) & (0.0841) & (0.0929) \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;Sport1 & 0.1139 & 0.1356 & 0.1001 \tabularnewline
p-value & (0.0647) & (0.0276) & (0.0253) \tabularnewline
Software;Sport2 & 0.0976 & 0.1328 & 0.0985 \tabularnewline
p-value & (0.1137) & (0.031) & (0.0294) \tabularnewline
Software;Month & -0.2739 & -0.2778 & -0.228 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Happiness;Depression & -0.5829 & -0.5407 & -0.4228 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Happiness;Sport1 & 0.2871 & 0.3321 & 0.2409 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Happiness;Sport2 & 0.2633 & 0.2975 & 0.2184 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Happiness;Month & -0.2467 & -0.2475 & -0.2043 \tabularnewline
p-value & (1e-04) & (0) & (0) \tabularnewline
Depression;Sport1 & -0.3294 & -0.3248 & -0.233 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Depression;Sport2 & -0.2829 & -0.2823 & -0.2045 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Depression;Month & 0.2338 & 0.2309 & 0.1886 \tabularnewline
p-value & (1e-04) & (2e-04) & (1e-04) \tabularnewline
Sport1;Sport2 & 0.953 & 0.9457 & 0.8488 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Sport1;Month & 3e-04 & -0.0068 & -0.0049 \tabularnewline
p-value & (0.9957) & (0.913) & (0.9193) \tabularnewline
Sport2;Month & -0.0209 & -0.0272 & -0.02 \tabularnewline
p-value & (0.7358) & (0.6594) & (0.6835) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284501&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;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;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;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;Sport1[/C][C]0.1239[/C][C]0.1269[/C][C]0.0929[/C][/ROW]
[ROW][C]p-value[/C][C](0.0443)[/C][C](0.0394)[/C][C](0.0328)[/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]Connected;Month[/C][C]-0.1983[/C][C]-0.1734[/C][C]-0.1388[/C][/ROW]
[ROW][C]p-value[/C][C](0.0012)[/C][C](0.0047)[/C][C](0.005)[/C][/ROW]
[ROW][C]Learning;Separate[/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]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;Sport1[/C][C]0.1432[/C][C]0.2203[/C][C]0.1662[/C][/ROW]
[ROW][C]p-value[/C][C](0.02)[/C][C](3e-04)[/C][C](2e-04)[/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]Learning;Month[/C][C]-0.3239[/C][C]-0.3259[/C][C]-0.2666[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/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;Sport1[/C][C]0.1[/C][C]0.0686[/C][C]0.0491[/C][/ROW]
[ROW][C]p-value[/C][C](0.1049)[/C][C](0.2666)[/C][C](0.2598)[/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]Separate;Month[/C][C]-0.1142[/C][C]-0.1065[/C][C]-0.0832[/C][/ROW]
[ROW][C]p-value[/C][C](0.0639)[/C][C](0.0841)[/C][C](0.0929)[/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;Sport1[/C][C]0.1139[/C][C]0.1356[/C][C]0.1001[/C][/ROW]
[ROW][C]p-value[/C][C](0.0647)[/C][C](0.0276)[/C][C](0.0253)[/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]Software;Month[/C][C]-0.2739[/C][C]-0.2778[/C][C]-0.228[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/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;Sport1[/C][C]0.2871[/C][C]0.3321[/C][C]0.2409[/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]Happiness;Month[/C][C]-0.2467[/C][C]-0.2475[/C][C]-0.2043[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Depression;Sport1[/C][C]-0.3294[/C][C]-0.3248[/C][C]-0.233[/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]
[ROW][C]Depression;Month[/C][C]0.2338[/C][C]0.2309[/C][C]0.1886[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](2e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Sport1;Sport2[/C][C]0.953[/C][C]0.9457[/C][C]0.8488[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Sport1;Month[/C][C]3e-04[/C][C]-0.0068[/C][C]-0.0049[/C][/ROW]
[ROW][C]p-value[/C][C](0.9957)[/C][C](0.913)[/C][C](0.9193)[/C][/ROW]
[ROW][C]Sport2;Month[/C][C]-0.0209[/C][C]-0.0272[/C][C]-0.02[/C][/ROW]
[ROW][C]p-value[/C][C](0.7358)[/C][C](0.6594)[/C][C](0.6835)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284501&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284501&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;Learning0.19960.18150.1373
p-value(0.0011)(0.0031)(0.0026)
Connected;Separate0.45510.33880.2521
p-value(0)(0)(0)
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;Sport10.12390.12690.0929
p-value(0.0443)(0.0394)(0.0328)
Connected;Sport20.14390.15010.1089
p-value(0.0193)(0.0146)(0.0133)
Connected;Month-0.1983-0.1734-0.1388
p-value(0.0012)(0.0047)(0.005)
Learning;Separate0.22270.21370.1602
p-value(3e-04)(5e-04)(5e-04)
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;Sport10.14320.22030.1662
p-value(0.02)(3e-04)(2e-04)
Learning;Sport20.1250.19710.1494
p-value(0.0424)(0.0013)(9e-04)
Learning;Month-0.3239-0.3259-0.2666
p-value(0)(0)(0)
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;Sport10.10.06860.0491
p-value(0.1049)(0.2666)(0.2598)
Separate;Sport20.10730.08480.0607
p-value(0.082)(0.1693)(0.1687)
Separate;Month-0.1142-0.1065-0.0832
p-value(0.0639)(0.0841)(0.0929)
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;Sport10.11390.13560.1001
p-value(0.0647)(0.0276)(0.0253)
Software;Sport20.09760.13280.0985
p-value(0.1137)(0.031)(0.0294)
Software;Month-0.2739-0.2778-0.228
p-value(0)(0)(0)
Happiness;Depression-0.5829-0.5407-0.4228
p-value(0)(0)(0)
Happiness;Sport10.28710.33210.2409
p-value(0)(0)(0)
Happiness;Sport20.26330.29750.2184
p-value(0)(0)(0)
Happiness;Month-0.2467-0.2475-0.2043
p-value(1e-04)(0)(0)
Depression;Sport1-0.3294-0.3248-0.233
p-value(0)(0)(0)
Depression;Sport2-0.2829-0.2823-0.2045
p-value(0)(0)(0)
Depression;Month0.23380.23090.1886
p-value(1e-04)(2e-04)(1e-04)
Sport1;Sport20.9530.94570.8488
p-value(0)(0)(0)
Sport1;Month3e-04-0.0068-0.0049
p-value(0.9957)(0.913)(0.9193)
Sport2;Month-0.0209-0.0272-0.02
p-value(0.7358)(0.6594)(0.6835)







Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.010.560.560.56
0.020.610.670.67
0.030.670.720.75
0.040.690.810.81
0.050.750.810.81
0.060.750.810.81
0.070.810.830.81
0.080.830.830.83
0.090.860.860.83
0.10.860.860.86

\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 & 0.56 & 0.56 & 0.56 \tabularnewline
0.02 & 0.61 & 0.67 & 0.67 \tabularnewline
0.03 & 0.67 & 0.72 & 0.75 \tabularnewline
0.04 & 0.69 & 0.81 & 0.81 \tabularnewline
0.05 & 0.75 & 0.81 & 0.81 \tabularnewline
0.06 & 0.75 & 0.81 & 0.81 \tabularnewline
0.07 & 0.81 & 0.83 & 0.81 \tabularnewline
0.08 & 0.83 & 0.83 & 0.83 \tabularnewline
0.09 & 0.86 & 0.86 & 0.83 \tabularnewline
0.1 & 0.86 & 0.86 & 0.86 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284501&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]0.56[/C][C]0.56[/C][C]0.56[/C][/ROW]
[ROW][C]0.02[/C][C]0.61[/C][C]0.67[/C][C]0.67[/C][/ROW]
[ROW][C]0.03[/C][C]0.67[/C][C]0.72[/C][C]0.75[/C][/ROW]
[ROW][C]0.04[/C][C]0.69[/C][C]0.81[/C][C]0.81[/C][/ROW]
[ROW][C]0.05[/C][C]0.75[/C][C]0.81[/C][C]0.81[/C][/ROW]
[ROW][C]0.06[/C][C]0.75[/C][C]0.81[/C][C]0.81[/C][/ROW]
[ROW][C]0.07[/C][C]0.81[/C][C]0.83[/C][C]0.81[/C][/ROW]
[ROW][C]0.08[/C][C]0.83[/C][C]0.83[/C][C]0.83[/C][/ROW]
[ROW][C]0.09[/C][C]0.86[/C][C]0.86[/C][C]0.83[/C][/ROW]
[ROW][C]0.1[/C][C]0.86[/C][C]0.86[/C][C]0.86[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284501&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284501&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
0.010.560.560.56
0.020.610.670.67
0.030.670.720.75
0.040.690.810.81
0.050.750.810.81
0.060.750.810.81
0.070.810.830.81
0.080.830.830.83
0.090.860.860.83
0.10.860.860.86



Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = TRUE ;
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$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
x <- na.omit(x)
y <- t(na.omit(t(y)))
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
n
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$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')