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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, 03 Dec 2013 14:40:06 -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/03/t1386099614zt208pd0fukxbp3.htm/, Retrieved Thu, 28 Mar 2024 10:43:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230394, Retrieved Thu, 28 Mar 2024 10:43:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [] [2013-12-03 19:40:06] [fa37975af643c4e4fccca077f5456344] [Current]
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Dataseries X:
119.992 157.302 74.997 0.00007 0.00554
122.4 148.65 113.819 0.00008 0.00696
116.682 131.111 111.555 0.00009 0.00781
116.676 137.871 111.366 0.00009 0.00698
116.014 141.781 110.655 0.00011 0.00908
120.552 131.162 113.787 0.00008 0.0075
120.267 137.244 114.82 0.00003 0.00202
107.332 113.84 104.315 0.00003 0.00182
95.73 132.068 91.754 0.00006 0.00332
95.056 120.103 91.226 0.00006 0.00332
88.333 112.24 84.072 0.00006 0.0033
91.904 115.871 86.292 0.00006 0.00336
136.926 159.866 131.276 0.00002 0.00153
139.173 179.139 76.556 0.00003 0.00208
152.845 163.305 75.836 0.00002 0.00149
142.167 217.455 83.159 0.00003 0.00203
144.188 349.259 82.764 0.00004 0.00292
168.778 232.181 75.603 0.00004 0.00387
153.046 175.829 68.623 0.00005 0.00432
156.405 189.398 142.822 0.00005 0.00399
153.848 165.738 65.782 0.00005 0.0045
153.88 172.86 78.128 0.00003 0.00267
167.93 193.221 79.068 0.00003 0.00247
173.917 192.735 86.18 0.00003 0.00258
163.656 200.841 76.779 0.00005 0.0039
104.4 206.002 77.968 0.00006 0.00375
171.041 208.313 75.501 0.00003 0.00234
146.845 208.701 81.737 0.00003 0.00275
155.358 227.383 80.055 0.00002 0.00176
162.568 198.346 77.63 0.00003 0.00253
197.076 206.896 192.055 0.00001 0.00168
199.228 209.512 192.091 0.00001 0.00138
198.383 215.203 193.104 0.00001 0.00135
202.266 211.604 197.079 0.000009 0.00107
203.184 211.526 196.16 0.000009 0.00106
201.464 210.565 195.708 0.00001 0.00115
177.876 192.921 168.013 0.00002 0.00241
176.17 185.604 163.564 0.00002 0.00218
180.198 201.249 175.456 0.00002 0.00166
187.733 202.324 173.015 0.00002 0.00182
186.163 197.724 177.584 0.00002 0.00175
184.055 196.537 166.977 0.00001 0.00147
237.226 247.326 225.227 0.00001 0.00182
241.404 248.834 232.483 0.00001 0.00173
243.439 250.912 232.435 0.000009 0.00137
242.852 255.034 227.911 0.000009 0.00139
245.51 262.09 231.848 0.00001 0.00148
252.455 261.487 182.786 0.000007 0.00113
122.188 128.611 115.765 0.00004 0.00203
122.964 130.049 114.676 0.00003 0.00155
124.445 135.069 117.495 0.00003 0.00167
126.344 134.231 112.773 0.00004 0.00169
128.001 138.052 122.08 0.00003 0.00166
129.336 139.867 118.604 0.00004 0.00183
108.807 134.656 102.874 0.00007 0.00486
109.86 126.358 104.437 0.00008 0.00539
110.417 131.067 103.37 0.00007 0.00514
117.274 129.916 110.402 0.00006 0.00469
116.879 131.897 108.153 0.00007 0.00493
114.847 271.314 104.68 0.00008 0.0052
209.144 237.494 109.379 0.00001 0.00152
223.365 238.987 98.664 0.00001 0.00151
222.236 231.345 205.495 0.00001 0.00144
228.832 234.619 223.634 0.00001 0.00155
229.401 252.221 221.156 0.000009 0.00113
228.969 239.541 113.201 0.00001 0.0014
140.341 159.774 67.021 0.00006 0.0044
136.969 166.607 66.004 0.00007 0.00463
143.533 162.215 65.809 0.00008 0.00467
148.09 162.824 67.343 0.00005 0.00354
142.729 162.408 65.476 0.00006 0.00419
136.358 176.595 65.75 0.00007 0.00478
120.08 139.71 111.208 0.00003 0.0022
112.014 588.518 107.024 0.00005 0.00329
110.793 128.101 107.316 0.00004 0.00283
110.707 122.611 105.007 0.00005 0.00289
112.876 148.826 106.981 0.00004 0.00289
110.568 125.394 106.821 0.00004 0.0028
95.385 102.145 90.264 0.00006 0.00332
100.77 115.697 85.545 0.0001 0.00576
96.106 108.664 84.51 0.00007 0.00415
95.605 107.715 87.549 0.00007 0.00371
100.96 110.019 95.628 0.00006 0.00348
98.804 102.305 87.804 0.00004 0.00258
176.858 205.56 75.344 0.00004 0.0042
180.978 200.125 155.495 0.00002 0.00244
178.222 202.45 141.047 0.00002 0.00194
176.281 227.381 125.61 0.00003 0.00312
173.898 211.35 74.677 0.00003 0.00254
179.711 225.93 144.878 0.00004 0.00419
166.605 206.008 78.032 0.00004 0.00453
151.955 163.335 147.226 0.00003 0.00227
148.272 164.989 142.299 0.00003 0.00256
152.125 161.469 76.596 0.00003 0.00226
157.821 172.975 68.401 0.00002 0.00196
157.447 163.267 149.605 0.00002 0.00197
159.116 168.913 144.811 0.00002 0.00184
125.036 143.946 116.187 0.0001 0.00623
125.791 140.557 96.206 0.00011 0.00655
126.512 141.756 99.77 0.00015 0.0099
125.641 141.068 116.346 0.00026 0.01522
128.451 150.449 75.632 0.00012 0.00909
139.224 586.567 66.157 0.00022 0.01628
150.258 154.609 75.349 0.00002 0.00136
154.003 160.267 128.621 0.00001 0.001
149.689 160.368 133.608 0.00002 0.00134
155.078 163.736 144.148 0.00001 0.00092
151.884 157.765 133.751 0.00002 0.00122
151.989 157.339 132.857 0.00001 0.00096
193.03 208.9 80.297 0.00004 0.00389
200.714 223.982 89.686 0.00003 0.00337
208.519 220.315 199.02 0.00003 0.00339
204.664 221.3 189.621 0.00004 0.00485
210.141 232.706 185.258 0.00003 0.0028
206.327 226.355 92.02 0.00002 0.00246
151.872 492.892 69.085 0.00006 0.00385
158.219 442.557 71.948 0.00003 0.00207
170.756 450.247 79.032 0.00003 0.00261
178.285 442.824 82.063 0.00003 0.00194
217.116 233.481 93.978 0.00002 0.00128
128.94 479.697 88.251 0.00005 0.00314
176.824 215.293 83.961 0.00003 0.00221
138.19 203.522 83.34 0.00005 0.00398
182.018 197.173 79.187 0.00005 0.00449
156.239 195.107 79.82 0.00004 0.00395
145.174 198.109 80.637 0.00005 0.00422
138.145 197.238 81.114 0.00004 0.00327
166.888 198.966 79.512 0.00004 0.00351
119.031 127.533 109.216 0.00004 0.00192
120.078 126.632 105.667 0.00002 0.00135
120.289 128.143 100.209 0.00004 0.00238
120.256 125.306 104.773 0.00003 0.00205
119.056 125.213 86.795 0.00003 0.0017
118.747 123.723 109.836 0.00003 0.00171
106.516 112.777 93.105 0.00006 0.00319
110.453 127.611 105.554 0.00004 0.00315
113.4 133.344 107.816 0.00004 0.00283
113.166 130.27 100.673 0.00004 0.00312
112.239 126.609 104.095 0.00004 0.0029
116.15 131.731 109.815 0.00003 0.00232
170.368 268.796 79.543 0.00003 0.00269
208.083 253.792 91.802 0.00004 0.00428
198.458 219.29 148.691 0.00002 0.00215
202.805 231.508 86.232 0.00002 0.00211
202.544 241.35 164.168 0.00001 0.00133
223.361 263.872 87.638 0.00002 0.00188
169.774 191.759 151.451 0.00009 0.00946
183.52 216.814 161.34 0.00008 0.00819
188.62 216.302 165.982 0.00009 0.01027
202.632 565.74 177.258 0.00008 0.00963
186.695 211.961 149.442 0.0001 0.01154
192.818 224.429 168.793 0.00016 0.01958
198.116 233.099 174.478 0.00014 0.01699
121.345 139.644 98.25 0.00006 0.00332
119.1 128.442 88.833 0.00006 0.003
117.87 127.349 95.654 0.00005 0.003
122.336 142.369 94.794 0.00006 0.00339
117.963 134.209 100.757 0.00015 0.00718
126.144 154.284 97.543 0.00008 0.00454
127.93 138.752 112.173 0.00005 0.00318
114.238 124.393 77.022 0.00005 0.00316
115.322 135.738 107.802 0.00005 0.00329
114.554 126.778 91.121 0.00006 0.0034
112.15 131.669 97.527 0.00005 0.00284
102.273 142.83 85.902 0.00009 0.00461
236.2 244.663 102.137 0.00001 0.00153
237.323 243.709 229.256 0.00001 0.00159
260.105 264.919 237.303 0.00001 0.00186
197.569 217.627 90.794 0.00004 0.00448
240.301 245.135 219.783 0.00002 0.00283
244.99 272.21 239.17 0.00002 0.00237
112.547 133.374 105.715 0.00003 0.0019
110.739 113.597 100.139 0.00003 0.002
113.715 116.443 96.913 0.00003 0.00203
117.004 144.466 99.923 0.00003 0.00218
115.38 123.109 108.634 0.00003 0.00199
116.388 129.038 108.97 0.00003 0.00213
151.737 190.204 129.859 0.00002 0.00162
148.79 158.359 138.99 0.00002 0.00186
148.143 155.982 135.041 0.00003 0.00231
150.44 163.441 144.736 0.00003 0.00233
148.462 161.078 141.998 0.00003 0.00235
149.818 163.417 144.786 0.00002 0.00198
117.226 123.925 106.656 0.00004 0.0027
116.848 217.552 99.503 0.00005 0.00346
116.286 177.291 96.983 0.00003 0.00192
116.556 592.03 86.228 0.00004 0.00263
116.342 581.289 94.246 0.00002 0.00148
114.563 119.167 86.647 0.00003 0.00184
201.774 262.707 78.228 0.00003 0.00396
174.188 230.978 94.261 0.00003 0.00259
209.516 253.017 89.488 0.00003 0.00292
174.688 240.005 74.287 0.00008 0.00564
198.764 396.961 74.904 0.00004 0.0039
214.289 260.277 77.973 0.00003 0.00317
  




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 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 & 9 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230394&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230394&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230394&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'George Udny Yule' @ yule.wessa.net







Correlations for all pairs of data series (method=pearson)
MDVP:Fo(Hz)MDVP:Fhi(Hz)MDVP:Flo(Hz)MDVP:Jitter(Abs)MDVP:PPQ
MDVP:Fo(Hz)10.4010.597-0.382-0.112
MDVP:Fhi(Hz)0.40110.085-0.0290.091
MDVP:Flo(Hz)0.5970.0851-0.278-0.096
MDVP:Jitter(Abs)-0.382-0.029-0.27810.898
MDVP:PPQ-0.1120.091-0.0960.8981

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & MDVP:Fo(Hz) & MDVP:Fhi(Hz) & MDVP:Flo(Hz) & MDVP:Jitter(Abs) & MDVP:PPQ \tabularnewline
MDVP:Fo(Hz) & 1 & 0.401 & 0.597 & -0.382 & -0.112 \tabularnewline
MDVP:Fhi(Hz) & 0.401 & 1 & 0.085 & -0.029 & 0.091 \tabularnewline
MDVP:Flo(Hz) & 0.597 & 0.085 & 1 & -0.278 & -0.096 \tabularnewline
MDVP:Jitter(Abs) & -0.382 & -0.029 & -0.278 & 1 & 0.898 \tabularnewline
MDVP:PPQ & -0.112 & 0.091 & -0.096 & 0.898 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230394&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]MDVP:Fo(Hz)[/C][C]MDVP:Fhi(Hz)[/C][C]MDVP:Flo(Hz)[/C][C]MDVP:Jitter(Abs)[/C][C]MDVP:PPQ[/C][/ROW]
[ROW][C]MDVP:Fo(Hz)[/C][C]1[/C][C]0.401[/C][C]0.597[/C][C]-0.382[/C][C]-0.112[/C][/ROW]
[ROW][C]MDVP:Fhi(Hz)[/C][C]0.401[/C][C]1[/C][C]0.085[/C][C]-0.029[/C][C]0.091[/C][/ROW]
[ROW][C]MDVP:Flo(Hz)[/C][C]0.597[/C][C]0.085[/C][C]1[/C][C]-0.278[/C][C]-0.096[/C][/ROW]
[ROW][C]MDVP:Jitter(Abs)[/C][C]-0.382[/C][C]-0.029[/C][C]-0.278[/C][C]1[/C][C]0.898[/C][/ROW]
[ROW][C]MDVP:PPQ[/C][C]-0.112[/C][C]0.091[/C][C]-0.096[/C][C]0.898[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230394&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230394&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)
MDVP:Fo(Hz)MDVP:Fhi(Hz)MDVP:Flo(Hz)MDVP:Jitter(Abs)MDVP:PPQ
MDVP:Fo(Hz)10.4010.597-0.382-0.112
MDVP:Fhi(Hz)0.40110.085-0.0290.091
MDVP:Flo(Hz)0.5970.0851-0.278-0.096
MDVP:Jitter(Abs)-0.382-0.029-0.27810.898
MDVP:PPQ-0.1120.091-0.0960.8981







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
MDVP:Fo(Hz);MDVP:Fhi(Hz)0.4010.79560.6603
p-value(0)(0)(0)
MDVP:Fo(Hz);MDVP:Flo(Hz)0.59650.32360.2695
p-value(0)(0)(0)
MDVP:Fo(Hz);MDVP:Jitter(Abs)-0.382-0.5664-0.4232
p-value(0)(0)(0)
MDVP:Fo(Hz);MDVP:PPQ-0.1122-0.2982-0.2032
p-value(0.1185)(0)(0)
MDVP:Fhi(Hz);MDVP:Flo(Hz)0.0850.09560.1234
p-value(0.2377)(0.1835)(0.0104)
MDVP:Fhi(Hz);MDVP:Jitter(Abs)-0.0292-0.3633-0.2605
p-value(0.6853)(0)(0)
MDVP:Fhi(Hz);MDVP:PPQ0.0911-0.1178-0.0795
p-value(0.2052)(0.1009)(0.099)
MDVP:Flo(Hz);MDVP:Jitter(Abs)-0.2778-0.4079-0.2952
p-value(1e-04)(0)(0)
MDVP:Flo(Hz);MDVP:PPQ-0.0958-0.3751-0.2607
p-value(0.1827)(0)(0)
MDVP:Jitter(Abs);MDVP:PPQ0.89780.90980.777
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
MDVP:Fo(Hz);MDVP:Fhi(Hz) & 0.401 & 0.7956 & 0.6603 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
MDVP:Fo(Hz);MDVP:Flo(Hz) & 0.5965 & 0.3236 & 0.2695 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
MDVP:Fo(Hz);MDVP:Jitter(Abs) & -0.382 & -0.5664 & -0.4232 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
MDVP:Fo(Hz);MDVP:PPQ & -0.1122 & -0.2982 & -0.2032 \tabularnewline
p-value & (0.1185) & (0) & (0) \tabularnewline
MDVP:Fhi(Hz);MDVP:Flo(Hz) & 0.085 & 0.0956 & 0.1234 \tabularnewline
p-value & (0.2377) & (0.1835) & (0.0104) \tabularnewline
MDVP:Fhi(Hz);MDVP:Jitter(Abs) & -0.0292 & -0.3633 & -0.2605 \tabularnewline
p-value & (0.6853) & (0) & (0) \tabularnewline
MDVP:Fhi(Hz);MDVP:PPQ & 0.0911 & -0.1178 & -0.0795 \tabularnewline
p-value & (0.2052) & (0.1009) & (0.099) \tabularnewline
MDVP:Flo(Hz);MDVP:Jitter(Abs) & -0.2778 & -0.4079 & -0.2952 \tabularnewline
p-value & (1e-04) & (0) & (0) \tabularnewline
MDVP:Flo(Hz);MDVP:PPQ & -0.0958 & -0.3751 & -0.2607 \tabularnewline
p-value & (0.1827) & (0) & (0) \tabularnewline
MDVP:Jitter(Abs);MDVP:PPQ & 0.8978 & 0.9098 & 0.777 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230394&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]MDVP:Fo(Hz);MDVP:Fhi(Hz)[/C][C]0.401[/C][C]0.7956[/C][C]0.6603[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]MDVP:Fo(Hz);MDVP:Flo(Hz)[/C][C]0.5965[/C][C]0.3236[/C][C]0.2695[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]MDVP:Fo(Hz);MDVP:Jitter(Abs)[/C][C]-0.382[/C][C]-0.5664[/C][C]-0.4232[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]MDVP:Fo(Hz);MDVP:PPQ[/C][C]-0.1122[/C][C]-0.2982[/C][C]-0.2032[/C][/ROW]
[ROW][C]p-value[/C][C](0.1185)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]MDVP:Fhi(Hz);MDVP:Flo(Hz)[/C][C]0.085[/C][C]0.0956[/C][C]0.1234[/C][/ROW]
[ROW][C]p-value[/C][C](0.2377)[/C][C](0.1835)[/C][C](0.0104)[/C][/ROW]
[ROW][C]MDVP:Fhi(Hz);MDVP:Jitter(Abs)[/C][C]-0.0292[/C][C]-0.3633[/C][C]-0.2605[/C][/ROW]
[ROW][C]p-value[/C][C](0.6853)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]MDVP:Fhi(Hz);MDVP:PPQ[/C][C]0.0911[/C][C]-0.1178[/C][C]-0.0795[/C][/ROW]
[ROW][C]p-value[/C][C](0.2052)[/C][C](0.1009)[/C][C](0.099)[/C][/ROW]
[ROW][C]MDVP:Flo(Hz);MDVP:Jitter(Abs)[/C][C]-0.2778[/C][C]-0.4079[/C][C]-0.2952[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]MDVP:Flo(Hz);MDVP:PPQ[/C][C]-0.0958[/C][C]-0.3751[/C][C]-0.2607[/C][/ROW]
[ROW][C]p-value[/C][C](0.1827)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]MDVP:Jitter(Abs);MDVP:PPQ[/C][C]0.8978[/C][C]0.9098[/C][C]0.777[/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=230394&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230394&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
MDVP:Fo(Hz);MDVP:Fhi(Hz)0.4010.79560.6603
p-value(0)(0)(0)
MDVP:Fo(Hz);MDVP:Flo(Hz)0.59650.32360.2695
p-value(0)(0)(0)
MDVP:Fo(Hz);MDVP:Jitter(Abs)-0.382-0.5664-0.4232
p-value(0)(0)(0)
MDVP:Fo(Hz);MDVP:PPQ-0.1122-0.2982-0.2032
p-value(0.1185)(0)(0)
MDVP:Fhi(Hz);MDVP:Flo(Hz)0.0850.09560.1234
p-value(0.2377)(0.1835)(0.0104)
MDVP:Fhi(Hz);MDVP:Jitter(Abs)-0.0292-0.3633-0.2605
p-value(0.6853)(0)(0)
MDVP:Fhi(Hz);MDVP:PPQ0.0911-0.1178-0.0795
p-value(0.2052)(0.1009)(0.099)
MDVP:Flo(Hz);MDVP:Jitter(Abs)-0.2778-0.4079-0.2952
p-value(1e-04)(0)(0)
MDVP:Flo(Hz);MDVP:PPQ-0.0958-0.3751-0.2607
p-value(0.1827)(0)(0)
MDVP:Jitter(Abs);MDVP:PPQ0.89780.90980.777
p-value(0)(0)(0)







Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.010.50.80.8
0.020.50.80.9
0.030.50.80.9
0.040.50.80.9
0.050.50.80.9
0.060.50.80.9
0.070.50.80.9
0.080.50.80.9
0.090.50.80.9
0.10.50.81

\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 & 0.5 & 0.8 & 0.8 \tabularnewline
0.02 & 0.5 & 0.8 & 0.9 \tabularnewline
0.03 & 0.5 & 0.8 & 0.9 \tabularnewline
0.04 & 0.5 & 0.8 & 0.9 \tabularnewline
0.05 & 0.5 & 0.8 & 0.9 \tabularnewline
0.06 & 0.5 & 0.8 & 0.9 \tabularnewline
0.07 & 0.5 & 0.8 & 0.9 \tabularnewline
0.08 & 0.5 & 0.8 & 0.9 \tabularnewline
0.09 & 0.5 & 0.8 & 0.9 \tabularnewline
0.1 & 0.5 & 0.8 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230394&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]0.5[/C][C]0.8[/C][C]0.8[/C][/ROW]
[ROW][C]0.02[/C][C]0.5[/C][C]0.8[/C][C]0.9[/C][/ROW]
[ROW][C]0.03[/C][C]0.5[/C][C]0.8[/C][C]0.9[/C][/ROW]
[ROW][C]0.04[/C][C]0.5[/C][C]0.8[/C][C]0.9[/C][/ROW]
[ROW][C]0.05[/C][C]0.5[/C][C]0.8[/C][C]0.9[/C][/ROW]
[ROW][C]0.06[/C][C]0.5[/C][C]0.8[/C][C]0.9[/C][/ROW]
[ROW][C]0.07[/C][C]0.5[/C][C]0.8[/C][C]0.9[/C][/ROW]
[ROW][C]0.08[/C][C]0.5[/C][C]0.8[/C][C]0.9[/C][/ROW]
[ROW][C]0.09[/C][C]0.5[/C][C]0.8[/C][C]0.9[/C][/ROW]
[ROW][C]0.1[/C][C]0.5[/C][C]0.8[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230394&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230394&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
0.010.50.80.8
0.020.50.80.9
0.030.50.80.9
0.040.50.80.9
0.050.50.80.9
0.060.50.80.9
0.070.50.80.9
0.080.50.80.9
0.090.50.80.9
0.10.50.81



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')