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 computationFri, 06 Dec 2013 08:50:39 -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/06/t1386337865ptadqhx6um1j87c.htm/, Retrieved Fri, 29 Mar 2024 13:17:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231315, Retrieved Fri, 29 Mar 2024 13:17:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [] [2013-12-06 13:50:39] [02b53344bfc7e15f5310bf5039e578c4] [Current]
Feedback Forum

Post a new message
Dataseries X:
1 -4.813031 0.266482 0.02211 21.033 0.815285
1 -4.075192 0.33559 0.01929 19.085 0.819521
1 -4.443179 0.311173 0.01309 20.651 0.825288
1 -4.117501 0.334147 0.01353 20.644 0.819235
1 -3.747787 0.234513 0.01767 19.649 0.823484
1 -4.242867 0.299111 0.01222 21.378 0.825069
1 -5.634322 0.257682 0.00607 24.886 0.764112
1 -6.167603 0.183721 0.00344 26.892 0.763262
1 -5.498678 0.327769 0.0107 21.812 0.773587
1 -5.011879 0.325996 0.01022 21.862 0.798463
1 -5.24977 0.391002 0.01166 21.118 0.776156
1 -4.960234 0.363566 0.01141 21.414 0.79252
1 -6.547148 0.152813 0.00581 25.703 0.646846
1 -5.660217 0.254989 0.01041 24.889 0.665833
1 -6.105098 0.203653 0.00609 24.922 0.654027
1 -5.340115 0.210185 0.00839 25.175 0.658245
1 -5.44004 0.239764 0.01859 22.333 0.644692
1 -2.93107 0.434326 0.02919 20.376 0.605417
1 -3.949079 0.35787 0.0316 17.28 0.719467
1 -4.554466 0.340176 0.03365 17.153 0.68608
1 -4.095442 0.262564 0.03871 17.536 0.704087
1 -5.18696 0.237622 0.01849 19.493 0.698951
1 -4.330956 0.262384 0.0128 22.468 0.679834
1 -5.248776 0.210279 0.0184 20.422 0.686894
1 -5.557447 0.22089 0.01778 23.831 0.732479
1 -5.571843 0.236853 0.02887 22.066 0.737948
1 -6.18359 0.226278 0.01095 25.908 0.720916
1 -6.27169 0.196102 0.01328 25.119 0.726652
1 -7.120925 0.279789 0.00677 25.97 0.676258
1 -6.635729 0.209866 0.0117 25.678 0.723797
0 -7.3483 0.177551 0.00339 26.775 0.741367
0 -7.682587 0.173319 0.00167 30.94 0.742055
0 -7.067931 0.175181 0.00119 30.775 0.738703
0 -7.695734 0.17854 0.00072 32.684 0.742133
0 -7.964984 0.163519 0.00065 33.047 0.741899
0 -7.777685 0.170183 0.00135 31.732 0.742737
1 -6.149653 0.218037 0.00586 23.216 0.778834
1 -6.006414 0.196371 0.0034 24.951 0.783626
1 -6.452058 0.212294 0.00231 26.738 0.766209
1 -6.006647 0.266892 0.00265 26.31 0.758324
1 -6.647379 0.201095 0.00231 26.822 0.765623
1 -7.044105 0.063412 0.00257 26.453 0.759203
0 -7.31055 0.098648 0.0074 22.736 0.654172
0 -6.793547 0.158266 0.00675 23.145 0.634267
0 -7.057869 0.091608 0.00454 25.368 0.635285
0 -6.99582 0.102083 0.00476 25.032 0.638928
0 -7.156076 0.127642 0.00476 24.602 0.631653
0 -7.31951 0.200873 0.00432 26.805 0.635204
0 -6.439398 0.266392 0.00839 23.162 0.733659
0 -6.482096 0.264967 0.00462 24.971 0.754073
0 -6.650471 0.254498 0.00479 25.135 0.775933
0 -6.689151 0.291954 0.00474 25.03 0.760361
0 -7.072419 0.220434 0.00481 24.692 0.766204
0 -6.836811 0.269866 0.00484 25.429 0.785714
1 -4.649573 0.205558 0.01036 21.028 0.819032
1 -4.333543 0.221727 0.0118 20.767 0.811843
1 -4.438453 0.238298 0.00969 21.422 0.821364
1 -4.60826 0.290024 0.00681 22.817 0.817756
1 -4.476755 0.262633 0.00786 22.603 0.813432
1 -4.609161 0.221711 0.01143 21.66 0.817396
0 -7.040508 0.066994 0.00871 25.554 0.678874
0 -7.293801 0.086372 0.00301 26.138 0.686264
0 -6.966321 0.095882 0.0034 25.856 0.694399
0 -7.24562 0.018689 0.00351 25.964 0.683296
0 -7.496264 0.056844 0.003 26.415 0.673636
0 -7.314237 0.006274 0.0042 24.547 0.681811
1 -5.409423 0.22685 0.02183 19.56 0.720908
1 -5.324574 0.20566 0.02659 19.979 0.729067
1 -5.86975 0.151814 0.04882 20.338 0.731444
1 -6.261141 0.120956 0.02431 21.718 0.727313
1 -5.720868 0.15883 0.02599 20.264 0.730387
1 -5.207985 0.224852 0.03361 18.57 0.733232
1 -5.79182 0.329066 0.00442 25.742 0.762959
1 -5.389129 0.306636 0.00623 24.178 0.789532
1 -5.31336 0.201861 0.00479 25.438 0.815908
1 -5.477592 0.315074 0.00472 25.197 0.807217
1 -5.775966 0.341169 0.00905 23.37 0.789977
1 -5.391029 0.250572 0.0042 25.82 0.81634
1 -5.115212 0.249494 0.01062 21.875 0.779612
1 -4.913885 0.265699 0.0222 19.2 0.790117
1 -4.441519 0.155097 0.01823 19.055 0.770466
1 -5.132032 0.210458 0.01825 19.659 0.778747
1 -5.022288 0.146948 0.01237 20.536 0.787896
1 -6.025367 0.078202 0.00882 22.244 0.772416
1 -5.288912 0.343073 0.0547 13.893 0.729586
1 -5.657899 0.315903 0.02782 16.176 0.727747
1 -6.366916 0.335753 0.03151 15.924 0.712199
1 -5.515071 0.299549 0.04824 13.922 0.740837
1 -5.783272 0.299793 0.04214 14.739 0.743937
1 -4.379411 0.375531 0.07223 11.866 0.745526
1 -4.508984 0.389232 0.08725 11.744 0.733165
1 -6.411497 0.207156 0.01658 19.664 0.71436
1 -5.952058 0.08784 0.01914 18.78 0.734504
1 -6.152551 0.17352 0.01211 20.969 0.69779
1 -6.251425 0.188056 0.0085 22.219 0.71217
1 -6.247076 0.180528 0.01018 21.693 0.705658
1 -6.41744 0.194627 0.00852 22.663 0.693429
1 -4.020042 0.265315 0.08151 15.338 0.714485
1 -5.159169 0.202146 0.10323 15.433 0.690892
1 -3.760348 0.242861 0.16744 12.435 0.674953
1 -3.700544 0.260481 0.31482 8.867 0.656846
1 -4.20273 0.310163 0.11843 15.06 0.643327
1 -3.269487 0.270641 0.2593 10.489 0.641418
1 -6.878393 0.089267 0.00495 26.759 0.722356
1 -7.111576 0.14478 0.00243 28.409 0.691483
1 -6.997403 0.210279 0.00578 27.421 0.719974
1 -6.981201 0.18455 0.00233 29.746 0.67793
1 -6.600023 0.249172 0.00659 26.833 0.700246
1 -6.739151 0.160686 0.00238 29.928 0.676066
1 -5.845099 0.278679 0.00947 21.934 0.740539
1 -5.25832 0.256454 0.00704 23.239 0.727863
1 -6.471427 0.184378 0.0083 22.407 0.712466
1 -4.876336 0.212054 0.01316 21.305 0.722085
1 -5.96304 0.250283 0.0062 23.671 0.722254
1 -6.729713 0.181701 0.01048 21.864 0.715121
1 -4.673241 0.261549 0.06051 23.693 0.662668
1 -6.051233 0.27328 0.01554 26.356 0.653823
1 -4.597834 0.372114 0.01802 25.69 0.676023
1 -4.913137 0.393056 0.00856 25.02 0.655239
1 -5.517173 0.389295 0.00681 24.581 0.58271
1 -6.186128 0.279933 0.0235 24.743 0.68413
1 -4.711007 0.281618 0.01161 27.166 0.656182
1 -5.418787 0.160267 0.01968 18.305 0.74148
1 -5.44514 0.142466 0.01813 18.784 0.732903
1 -5.944191 0.143359 0.0202 19.196 0.728421
1 -5.594275 0.12795 0.01874 18.857 0.735546
1 -5.540351 0.087165 0.01794 18.178 0.738245
1 -5.825257 0.115697 0.01796 18.33 0.736964
1 -6.890021 0.152941 0.01724 26.842 0.699787
1 -5.892061 0.195976 0.00487 26.369 0.718839
1 -6.135296 0.20363 0.0161 23.949 0.724045
1 -6.112667 0.217013 0.01015 26.017 0.735136
1 -5.436135 0.254909 0.00903 23.389 0.721308
1 -6.448134 0.178713 0.00504 25.619 0.723096
1 -5.301321 0.320385 0.03031 17.06 0.744064
1 -5.333619 0.322044 0.02529 17.707 0.706687
1 -4.378916 0.300067 0.02278 19.013 0.708144
1 -4.654894 0.304107 0.0369 16.747 0.708617
1 -5.634576 0.306014 0.02629 17.366 0.701404
1 -5.866357 0.23307 0.01827 18.801 0.696049
1 -4.796845 0.397749 0.02485 18.54 0.685057
1 -5.410336 0.288917 0.04238 15.648 0.665945
1 -5.585259 0.310746 0.01728 18.702 0.661735
1 -5.898673 0.213353 0.0201 18.687 0.632631
1 -6.132663 0.220617 0.01049 20.68 0.630409
1 -5.456811 0.345238 0.01493 20.366 0.574282
1 -3.297668 0.414758 0.0753 12.359 0.793509
1 -4.276605 0.355736 0.06057 14.367 0.768974
1 -3.377325 0.335357 0.08069 12.298 0.764036
1 -4.892495 0.262281 0.07889 14.989 0.775708
1 -4.484303 0.340256 0.10952 12.529 0.762726
1 -2.434031 0.450493 0.21713 8.441 0.76832
1 -2.839756 0.356224 0.16265 9.449 0.754449
1 -4.865194 0.246404 0.04179 21.52 0.670475
1 -4.239028 0.175691 0.04611 21.824 0.659333
1 -3.583722 0.207914 0.02631 22.431 0.652025
1 -5.4351 0.230532 0.03191 22.953 0.623731
1 -3.444478 0.303214 0.10748 19.075 0.646786
1 -5.070096 0.280091 0.03828 21.534 0.627337
1 -5.498456 0.234196 0.02663 19.651 0.675865
1 -5.185987 0.259229 0.02073 20.437 0.694571
1 -5.283009 0.226528 0.0281 19.388 0.684373
1 -5.529833 0.24275 0.02707 18.954 0.719576
1 -5.617124 0.184896 0.01435 21.219 0.673086
1 -2.929379 0.396746 0.03882 18.447 0.674562
0 -6.816086 0.17227 0.0062 24.078 0.628232
0 -7.018057 0.176316 0.00533 24.679 0.62671
0 -7.517934 0.160414 0.0091 21.083 0.628058
0 -5.736781 0.164529 0.01337 19.269 0.725216
0 -7.169701 0.073298 0.00965 21.02 0.646167
0 -7.3045 0.171088 0.01049 21.528 0.646818
0 -6.323531 0.218885 0.00435 26.436 0.7567
0 -6.085567 0.192375 0.0043 26.55 0.776158
0 -5.943501 0.19215 0.00478 26.547 0.7667
0 -6.012559 0.229298 0.0059 25.445 0.756482
0 -5.966779 0.197938 0.00401 26.005 0.761255
0 -6.016891 0.109256 0.00415 26.143 0.763242
1 -6.486822 0.197919 0.0057 24.151 0.745957
1 -6.311987 0.182459 0.00488 24.412 0.762508
1 -5.711205 0.240875 0.0054 23.683 0.778349
1 -6.261446 0.183218 0.00611 23.133 0.75932
1 -5.704053 0.216204 0.00639 22.866 0.768845
1 -6.27717 0.109397 0.00595 23.008 0.75718
0 -5.61907 0.191576 0.00955 23.079 0.669565
0 -5.198864 0.206768 0.01179 22.085 0.656516
0 -5.592584 0.133917 0.00737 24.199 0.654331
0 -6.431119 0.15331 0.01397 23.958 0.667654
0 -6.359018 0.116636 0.0068 25.023 0.663884
0 -6.710219 0.149694 0.00703 24.775 0.659132
0 -6.934474 0.15989 0.04441 19.368 0.683761
0 -6.538586 0.121952 0.02764 19.517 0.657899
0 -6.195325 0.129303 0.0181 19.147 0.683244
0 -6.787197 0.158453 0.10715 17.883 0.655683
0 -6.744577 0.207454 0.07223 19.02 0.643956
0 -5.724056 0.190667 0.04398 21.209 0.664357




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231315&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]5 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=231315&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231315&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 time5 seconds
R Server'George Udny Yule' @ yule.wessa.net







Correlations for all pairs of data series (method=pearson)
statusspread1spread2NHRHNRDFA
status10.5650.4550.189-0.3620.232
spread10.56510.6520.541-0.6730.196
spread20.4550.65210.318-0.4320.167
NHR0.1890.5410.3181-0.714-0.132
HNR-0.362-0.673-0.432-0.7141-0.009
DFA0.2320.1960.167-0.132-0.0091

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & status & spread1 & spread2 & NHR & HNR & DFA \tabularnewline
status & 1 & 0.565 & 0.455 & 0.189 & -0.362 & 0.232 \tabularnewline
spread1 & 0.565 & 1 & 0.652 & 0.541 & -0.673 & 0.196 \tabularnewline
spread2 & 0.455 & 0.652 & 1 & 0.318 & -0.432 & 0.167 \tabularnewline
NHR & 0.189 & 0.541 & 0.318 & 1 & -0.714 & -0.132 \tabularnewline
HNR & -0.362 & -0.673 & -0.432 & -0.714 & 1 & -0.009 \tabularnewline
DFA & 0.232 & 0.196 & 0.167 & -0.132 & -0.009 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231315&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]status[/C][C]spread1[/C][C]spread2[/C][C]NHR[/C][C]HNR[/C][C]DFA[/C][/ROW]
[ROW][C]status[/C][C]1[/C][C]0.565[/C][C]0.455[/C][C]0.189[/C][C]-0.362[/C][C]0.232[/C][/ROW]
[ROW][C]spread1[/C][C]0.565[/C][C]1[/C][C]0.652[/C][C]0.541[/C][C]-0.673[/C][C]0.196[/C][/ROW]
[ROW][C]spread2[/C][C]0.455[/C][C]0.652[/C][C]1[/C][C]0.318[/C][C]-0.432[/C][C]0.167[/C][/ROW]
[ROW][C]NHR[/C][C]0.189[/C][C]0.541[/C][C]0.318[/C][C]1[/C][C]-0.714[/C][C]-0.132[/C][/ROW]
[ROW][C]HNR[/C][C]-0.362[/C][C]-0.673[/C][C]-0.432[/C][C]-0.714[/C][C]1[/C][C]-0.009[/C][/ROW]
[ROW][C]DFA[/C][C]0.232[/C][C]0.196[/C][C]0.167[/C][C]-0.132[/C][C]-0.009[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231315&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231315&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)
statusspread1spread2NHRHNRDFA
status10.5650.4550.189-0.3620.232
spread10.56510.6520.541-0.6730.196
spread20.4550.65210.318-0.4320.167
NHR0.1890.5410.3181-0.714-0.132
HNR-0.362-0.673-0.432-0.7141-0.009
DFA0.2320.1960.167-0.132-0.0091







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
status;spread10.56480.59240.4849
p-value(0)(0)(0)
status;spread20.45480.4680.3831
p-value(0)(0)(0)
status;NHR0.18940.40760.3338
p-value(0.008)(0)(0)
status;HNR-0.3615-0.3551-0.2907
p-value(0)(0)(0)
status;DFA0.23170.22350.183
p-value(0.0011)(0.0017)(0.0018)
spread1;spread20.65240.64980.4654
p-value(0)(0)(0)
spread1;NHR0.54090.65930.4802
p-value(0)(0)(0)
spread1;HNR-0.6732-0.6277-0.4499
p-value(0)(0)(0)
spread1;DFA0.19570.21110.1526
p-value(0.0061)(0.0031)(0.0015)
spread2;NHR0.31810.4180.2877
p-value(0)(0)(0)
spread2;HNR-0.4316-0.3743-0.2553
p-value(0)(0)(0)
spread2;DFA0.16650.20040.1345
p-value(0.02)(0.005)(0.0052)
NHR;HNR-0.7141-0.866-0.7039
p-value(0)(0)(0)
NHR;DFA-0.1319-0.1755-0.1063
p-value(0.0661)(0.0141)(0.0273)
HNR;DFA-0.00870.0096-0.0034
p-value(0.9043)(0.8941)(0.9431)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
status;spread1 & 0.5648 & 0.5924 & 0.4849 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
status;spread2 & 0.4548 & 0.468 & 0.3831 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
status;NHR & 0.1894 & 0.4076 & 0.3338 \tabularnewline
p-value & (0.008) & (0) & (0) \tabularnewline
status;HNR & -0.3615 & -0.3551 & -0.2907 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
status;DFA & 0.2317 & 0.2235 & 0.183 \tabularnewline
p-value & (0.0011) & (0.0017) & (0.0018) \tabularnewline
spread1;spread2 & 0.6524 & 0.6498 & 0.4654 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
spread1;NHR & 0.5409 & 0.6593 & 0.4802 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
spread1;HNR & -0.6732 & -0.6277 & -0.4499 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
spread1;DFA & 0.1957 & 0.2111 & 0.1526 \tabularnewline
p-value & (0.0061) & (0.0031) & (0.0015) \tabularnewline
spread2;NHR & 0.3181 & 0.418 & 0.2877 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
spread2;HNR & -0.4316 & -0.3743 & -0.2553 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
spread2;DFA & 0.1665 & 0.2004 & 0.1345 \tabularnewline
p-value & (0.02) & (0.005) & (0.0052) \tabularnewline
NHR;HNR & -0.7141 & -0.866 & -0.7039 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
NHR;DFA & -0.1319 & -0.1755 & -0.1063 \tabularnewline
p-value & (0.0661) & (0.0141) & (0.0273) \tabularnewline
HNR;DFA & -0.0087 & 0.0096 & -0.0034 \tabularnewline
p-value & (0.9043) & (0.8941) & (0.9431) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231315&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]status;spread1[/C][C]0.5648[/C][C]0.5924[/C][C]0.4849[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]status;spread2[/C][C]0.4548[/C][C]0.468[/C][C]0.3831[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]status;NHR[/C][C]0.1894[/C][C]0.4076[/C][C]0.3338[/C][/ROW]
[ROW][C]p-value[/C][C](0.008)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]status;HNR[/C][C]-0.3615[/C][C]-0.3551[/C][C]-0.2907[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]status;DFA[/C][C]0.2317[/C][C]0.2235[/C][C]0.183[/C][/ROW]
[ROW][C]p-value[/C][C](0.0011)[/C][C](0.0017)[/C][C](0.0018)[/C][/ROW]
[ROW][C]spread1;spread2[/C][C]0.6524[/C][C]0.6498[/C][C]0.4654[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]spread1;NHR[/C][C]0.5409[/C][C]0.6593[/C][C]0.4802[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]spread1;HNR[/C][C]-0.6732[/C][C]-0.6277[/C][C]-0.4499[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]spread1;DFA[/C][C]0.1957[/C][C]0.2111[/C][C]0.1526[/C][/ROW]
[ROW][C]p-value[/C][C](0.0061)[/C][C](0.0031)[/C][C](0.0015)[/C][/ROW]
[ROW][C]spread2;NHR[/C][C]0.3181[/C][C]0.418[/C][C]0.2877[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]spread2;HNR[/C][C]-0.4316[/C][C]-0.3743[/C][C]-0.2553[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]spread2;DFA[/C][C]0.1665[/C][C]0.2004[/C][C]0.1345[/C][/ROW]
[ROW][C]p-value[/C][C](0.02)[/C][C](0.005)[/C][C](0.0052)[/C][/ROW]
[ROW][C]NHR;HNR[/C][C]-0.7141[/C][C]-0.866[/C][C]-0.7039[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]NHR;DFA[/C][C]-0.1319[/C][C]-0.1755[/C][C]-0.1063[/C][/ROW]
[ROW][C]p-value[/C][C](0.0661)[/C][C](0.0141)[/C][C](0.0273)[/C][/ROW]
[ROW][C]HNR;DFA[/C][C]-0.0087[/C][C]0.0096[/C][C]-0.0034[/C][/ROW]
[ROW][C]p-value[/C][C](0.9043)[/C][C](0.8941)[/C][C](0.9431)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231315&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231315&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
status;spread10.56480.59240.4849
p-value(0)(0)(0)
status;spread20.45480.4680.3831
p-value(0)(0)(0)
status;NHR0.18940.40760.3338
p-value(0.008)(0)(0)
status;HNR-0.3615-0.3551-0.2907
p-value(0)(0)(0)
status;DFA0.23170.22350.183
p-value(0.0011)(0.0017)(0.0018)
spread1;spread20.65240.64980.4654
p-value(0)(0)(0)
spread1;NHR0.54090.65930.4802
p-value(0)(0)(0)
spread1;HNR-0.6732-0.6277-0.4499
p-value(0)(0)(0)
spread1;DFA0.19570.21110.1526
p-value(0.0061)(0.0031)(0.0015)
spread2;NHR0.31810.4180.2877
p-value(0)(0)(0)
spread2;HNR-0.4316-0.3743-0.2553
p-value(0)(0)(0)
spread2;DFA0.16650.20040.1345
p-value(0.02)(0.005)(0.0052)
NHR;HNR-0.7141-0.866-0.7039
p-value(0)(0)(0)
NHR;DFA-0.1319-0.1755-0.1063
p-value(0.0661)(0.0141)(0.0273)
HNR;DFA-0.00870.0096-0.0034
p-value(0.9043)(0.8941)(0.9431)







Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.010.80.870.87
0.020.870.930.87
0.030.870.930.93
0.040.870.930.93
0.050.870.930.93
0.060.870.930.93
0.070.930.930.93
0.080.930.930.93
0.090.930.930.93
0.10.930.930.93

\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 & 0.8 & 0.87 & 0.87 \tabularnewline
0.02 & 0.87 & 0.93 & 0.87 \tabularnewline
0.03 & 0.87 & 0.93 & 0.93 \tabularnewline
0.04 & 0.87 & 0.93 & 0.93 \tabularnewline
0.05 & 0.87 & 0.93 & 0.93 \tabularnewline
0.06 & 0.87 & 0.93 & 0.93 \tabularnewline
0.07 & 0.93 & 0.93 & 0.93 \tabularnewline
0.08 & 0.93 & 0.93 & 0.93 \tabularnewline
0.09 & 0.93 & 0.93 & 0.93 \tabularnewline
0.1 & 0.93 & 0.93 & 0.93 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231315&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]0.8[/C][C]0.87[/C][C]0.87[/C][/ROW]
[ROW][C]0.02[/C][C]0.87[/C][C]0.93[/C][C]0.87[/C][/ROW]
[ROW][C]0.03[/C][C]0.87[/C][C]0.93[/C][C]0.93[/C][/ROW]
[ROW][C]0.04[/C][C]0.87[/C][C]0.93[/C][C]0.93[/C][/ROW]
[ROW][C]0.05[/C][C]0.87[/C][C]0.93[/C][C]0.93[/C][/ROW]
[ROW][C]0.06[/C][C]0.87[/C][C]0.93[/C][C]0.93[/C][/ROW]
[ROW][C]0.07[/C][C]0.93[/C][C]0.93[/C][C]0.93[/C][/ROW]
[ROW][C]0.08[/C][C]0.93[/C][C]0.93[/C][C]0.93[/C][/ROW]
[ROW][C]0.09[/C][C]0.93[/C][C]0.93[/C][C]0.93[/C][/ROW]
[ROW][C]0.1[/C][C]0.93[/C][C]0.93[/C][C]0.93[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231315&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231315&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
0.010.80.870.87
0.020.870.930.87
0.030.870.930.93
0.040.870.930.93
0.050.870.930.93
0.060.870.930.93
0.070.930.930.93
0.080.930.930.93
0.090.930.930.93
0.10.930.930.93



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')