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Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationSat, 04 Oct 2014 17:58:58 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Oct/04/t1412441992r3a91hbct0dki5v.htm/, Retrieved Sun, 12 May 2024 13:46:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=238626, Retrieved Sun, 12 May 2024 13:46:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsAlessio De Looze
Estimated Impact104
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Harrell-Davis Quantiles] [] [2014-10-04 16:58:58] [072d4f39c76834f6beee313555a90f83] [Current]
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Dataseries X:
164,88
164,88
164,57
164,53
165,03
165,92
165,92
165,92
165,92
166,12
166,34
165,48
165,61
165,61
165,94
165,88
166,23
166,32
166,43
166,43
166,2
166,21
168,02
168,68
168,65
168,65
168,75
168,8
168,58
168,98
169
169
168,94
169,96
171,59
172,41
172,65
172,65
172,65
172,38
171,95
171,95
171,87
171,87
171,91
171,99
172,15
172,73
173,2
164,97
164,97
164,43
163,16
162,98
161,69
162,19
162
162,22
164,08
164,58
164,68




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=238626&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=238626&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=238626&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 time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Harrell-Davis Quantiles
quantilesvaluestandard error
0.01161.7702293255910.284805339411884
0.02161.8974787714810.281265627174338
0.03162.0489230806680.32593845633287
0.04162.2158890969420.418379943798544
0.05162.4000642337760.534163069260603
0.06162.6041821117330.646342661178127
0.07162.8266842185950.734626774696923
0.08163.0611626238420.78680145367277
0.09163.2983076457110.799388500607141
0.1163.5283469341450.775043922061135
0.11163.7429600390930.721422404667687
0.12163.9363759970330.648390457976331
0.13164.1057153281650.567214966845741
0.14164.2507658608340.487276898175343
0.15164.3734079552040.41650359242982
0.16164.4768896927820.359743874865342
0.17164.5651158853820.3189253748248
0.18164.6420627610380.293901021241618
0.19164.7113716351360.282515312804278
0.2164.7761221804260.281955374873924
0.21164.8387497967190.289342168168908
0.22164.9010564333260.302111876579383
0.23164.9642673595350.318215141765348
0.24165.0291006334810.335584411765123
0.25165.095833298150.352460423715975
0.26165.1643624132050.36701003665195
0.27165.2342667964210.37770023981187
0.28165.3048766405970.383159234810066
0.29165.3753548274750.382970014003268
0.3165.4447884187230.376763140990785
0.31165.5122839033030.365320934834554
0.32165.5770569446070.349242876776731
0.33165.6385072136760.329805280349866
0.34165.69627114710.308767582073267
0.35165.7502492828840.287782257917667
0.36165.8006091278950.268398885432509
0.37165.8477682805750.251842488599379
0.38165.8923650081570.240026023717039
0.39165.9352242356540.233420487625962
0.4165.9773258780120.233323538010638
0.41166.0197798964450.240358293918044
0.42166.06380891410.254979339671662
0.43166.110735406970.278049324808312
0.44166.1619672100110.309979783294614
0.45166.2189731325820.35124690895555
0.46166.2832404764430.401991628588602
0.47166.3562084927590.461910066395118
0.48166.4391761737470.529458965812121
0.49166.5331886463560.602733750748332
0.5166.6389127897690.678886587720355
0.51166.7565182339170.754274729261876
0.52166.8855832884590.825008270621458
0.53167.0250455521470.886625265905572
0.54167.173213467150.935047652427909
0.55167.3278481549250.967406039692325
0.56167.4863154987190.981306320620937
0.57167.645798207110.976205826926099
0.58167.8035483330240.95301673487051
0.59167.9571540826150.914371216303477
0.6168.1047917996590.864561191488325
0.61168.2454350027420.808821072788947
0.62168.378996705160.753260229936858
0.63168.5063878013910.704924514093631
0.64168.6294817494960.670010378729465
0.65168.7509831229510.654808364494461
0.66168.8742044999980.663439587078833
0.67169.0027629389810.696782595912527
0.68169.1402146699160.752985709406211
0.69169.2896551371590.827194263433464
0.7169.4533208439770.911921659215507
0.71169.6322380075540.998953360658322
0.72169.8259680537241.07887112650195
0.73170.0324981267291.1427283285383
0.74170.2483133183691.1824962145532
0.75170.4686654104361.19244692303834
0.76170.6880226677391.16934252641889
0.77170.9006518062141.11383831633459
0.78171.1012540740851.02978277582586
0.79171.2855601245840.924110059731419
0.8171.4507887207960.8059910374732
0.81171.5958939943570.685133020414986
0.82171.7215617733020.571064458785723
0.83171.8299598772510.471530152417532
0.84171.9242903831760.392106969633768
0.85172.0082242499520.334932909021396
0.86172.0853140728930.298665014596598
0.87172.1584779098960.278286640144158
0.88172.2296304348770.267010374595119
0.89172.2995158103380.257907879396446
0.9172.3677797254960.245853181321814
0.91172.4333136383860.227539348529627
0.92172.4949130656210.202273166567988
0.93172.5522986709550.172105545647128
0.94172.6074959854640.142460469173558
0.95172.6662984747460.123902539756329
0.96172.7387692000580.133933507512159
0.97172.836389576350.186104947988871
0.98172.9628255556420.276562627400497
0.99173.0994569975570.382596734863646

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 161.770229325591 & 0.284805339411884 \tabularnewline
0.02 & 161.897478771481 & 0.281265627174338 \tabularnewline
0.03 & 162.048923080668 & 0.32593845633287 \tabularnewline
0.04 & 162.215889096942 & 0.418379943798544 \tabularnewline
0.05 & 162.400064233776 & 0.534163069260603 \tabularnewline
0.06 & 162.604182111733 & 0.646342661178127 \tabularnewline
0.07 & 162.826684218595 & 0.734626774696923 \tabularnewline
0.08 & 163.061162623842 & 0.78680145367277 \tabularnewline
0.09 & 163.298307645711 & 0.799388500607141 \tabularnewline
0.1 & 163.528346934145 & 0.775043922061135 \tabularnewline
0.11 & 163.742960039093 & 0.721422404667687 \tabularnewline
0.12 & 163.936375997033 & 0.648390457976331 \tabularnewline
0.13 & 164.105715328165 & 0.567214966845741 \tabularnewline
0.14 & 164.250765860834 & 0.487276898175343 \tabularnewline
0.15 & 164.373407955204 & 0.41650359242982 \tabularnewline
0.16 & 164.476889692782 & 0.359743874865342 \tabularnewline
0.17 & 164.565115885382 & 0.3189253748248 \tabularnewline
0.18 & 164.642062761038 & 0.293901021241618 \tabularnewline
0.19 & 164.711371635136 & 0.282515312804278 \tabularnewline
0.2 & 164.776122180426 & 0.281955374873924 \tabularnewline
0.21 & 164.838749796719 & 0.289342168168908 \tabularnewline
0.22 & 164.901056433326 & 0.302111876579383 \tabularnewline
0.23 & 164.964267359535 & 0.318215141765348 \tabularnewline
0.24 & 165.029100633481 & 0.335584411765123 \tabularnewline
0.25 & 165.09583329815 & 0.352460423715975 \tabularnewline
0.26 & 165.164362413205 & 0.36701003665195 \tabularnewline
0.27 & 165.234266796421 & 0.37770023981187 \tabularnewline
0.28 & 165.304876640597 & 0.383159234810066 \tabularnewline
0.29 & 165.375354827475 & 0.382970014003268 \tabularnewline
0.3 & 165.444788418723 & 0.376763140990785 \tabularnewline
0.31 & 165.512283903303 & 0.365320934834554 \tabularnewline
0.32 & 165.577056944607 & 0.349242876776731 \tabularnewline
0.33 & 165.638507213676 & 0.329805280349866 \tabularnewline
0.34 & 165.6962711471 & 0.308767582073267 \tabularnewline
0.35 & 165.750249282884 & 0.287782257917667 \tabularnewline
0.36 & 165.800609127895 & 0.268398885432509 \tabularnewline
0.37 & 165.847768280575 & 0.251842488599379 \tabularnewline
0.38 & 165.892365008157 & 0.240026023717039 \tabularnewline
0.39 & 165.935224235654 & 0.233420487625962 \tabularnewline
0.4 & 165.977325878012 & 0.233323538010638 \tabularnewline
0.41 & 166.019779896445 & 0.240358293918044 \tabularnewline
0.42 & 166.0638089141 & 0.254979339671662 \tabularnewline
0.43 & 166.11073540697 & 0.278049324808312 \tabularnewline
0.44 & 166.161967210011 & 0.309979783294614 \tabularnewline
0.45 & 166.218973132582 & 0.35124690895555 \tabularnewline
0.46 & 166.283240476443 & 0.401991628588602 \tabularnewline
0.47 & 166.356208492759 & 0.461910066395118 \tabularnewline
0.48 & 166.439176173747 & 0.529458965812121 \tabularnewline
0.49 & 166.533188646356 & 0.602733750748332 \tabularnewline
0.5 & 166.638912789769 & 0.678886587720355 \tabularnewline
0.51 & 166.756518233917 & 0.754274729261876 \tabularnewline
0.52 & 166.885583288459 & 0.825008270621458 \tabularnewline
0.53 & 167.025045552147 & 0.886625265905572 \tabularnewline
0.54 & 167.17321346715 & 0.935047652427909 \tabularnewline
0.55 & 167.327848154925 & 0.967406039692325 \tabularnewline
0.56 & 167.486315498719 & 0.981306320620937 \tabularnewline
0.57 & 167.64579820711 & 0.976205826926099 \tabularnewline
0.58 & 167.803548333024 & 0.95301673487051 \tabularnewline
0.59 & 167.957154082615 & 0.914371216303477 \tabularnewline
0.6 & 168.104791799659 & 0.864561191488325 \tabularnewline
0.61 & 168.245435002742 & 0.808821072788947 \tabularnewline
0.62 & 168.37899670516 & 0.753260229936858 \tabularnewline
0.63 & 168.506387801391 & 0.704924514093631 \tabularnewline
0.64 & 168.629481749496 & 0.670010378729465 \tabularnewline
0.65 & 168.750983122951 & 0.654808364494461 \tabularnewline
0.66 & 168.874204499998 & 0.663439587078833 \tabularnewline
0.67 & 169.002762938981 & 0.696782595912527 \tabularnewline
0.68 & 169.140214669916 & 0.752985709406211 \tabularnewline
0.69 & 169.289655137159 & 0.827194263433464 \tabularnewline
0.7 & 169.453320843977 & 0.911921659215507 \tabularnewline
0.71 & 169.632238007554 & 0.998953360658322 \tabularnewline
0.72 & 169.825968053724 & 1.07887112650195 \tabularnewline
0.73 & 170.032498126729 & 1.1427283285383 \tabularnewline
0.74 & 170.248313318369 & 1.1824962145532 \tabularnewline
0.75 & 170.468665410436 & 1.19244692303834 \tabularnewline
0.76 & 170.688022667739 & 1.16934252641889 \tabularnewline
0.77 & 170.900651806214 & 1.11383831633459 \tabularnewline
0.78 & 171.101254074085 & 1.02978277582586 \tabularnewline
0.79 & 171.285560124584 & 0.924110059731419 \tabularnewline
0.8 & 171.450788720796 & 0.8059910374732 \tabularnewline
0.81 & 171.595893994357 & 0.685133020414986 \tabularnewline
0.82 & 171.721561773302 & 0.571064458785723 \tabularnewline
0.83 & 171.829959877251 & 0.471530152417532 \tabularnewline
0.84 & 171.924290383176 & 0.392106969633768 \tabularnewline
0.85 & 172.008224249952 & 0.334932909021396 \tabularnewline
0.86 & 172.085314072893 & 0.298665014596598 \tabularnewline
0.87 & 172.158477909896 & 0.278286640144158 \tabularnewline
0.88 & 172.229630434877 & 0.267010374595119 \tabularnewline
0.89 & 172.299515810338 & 0.257907879396446 \tabularnewline
0.9 & 172.367779725496 & 0.245853181321814 \tabularnewline
0.91 & 172.433313638386 & 0.227539348529627 \tabularnewline
0.92 & 172.494913065621 & 0.202273166567988 \tabularnewline
0.93 & 172.552298670955 & 0.172105545647128 \tabularnewline
0.94 & 172.607495985464 & 0.142460469173558 \tabularnewline
0.95 & 172.666298474746 & 0.123902539756329 \tabularnewline
0.96 & 172.738769200058 & 0.133933507512159 \tabularnewline
0.97 & 172.83638957635 & 0.186104947988871 \tabularnewline
0.98 & 172.962825555642 & 0.276562627400497 \tabularnewline
0.99 & 173.099456997557 & 0.382596734863646 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=238626&T=1

[TABLE]
[ROW][C]Harrell-Davis Quantiles[/C][/ROW]
[ROW][C]quantiles[/C][C]value[/C][C]standard error[/C][/ROW]
[ROW][C]0.01[/C][C]161.770229325591[/C][C]0.284805339411884[/C][/ROW]
[ROW][C]0.02[/C][C]161.897478771481[/C][C]0.281265627174338[/C][/ROW]
[ROW][C]0.03[/C][C]162.048923080668[/C][C]0.32593845633287[/C][/ROW]
[ROW][C]0.04[/C][C]162.215889096942[/C][C]0.418379943798544[/C][/ROW]
[ROW][C]0.05[/C][C]162.400064233776[/C][C]0.534163069260603[/C][/ROW]
[ROW][C]0.06[/C][C]162.604182111733[/C][C]0.646342661178127[/C][/ROW]
[ROW][C]0.07[/C][C]162.826684218595[/C][C]0.734626774696923[/C][/ROW]
[ROW][C]0.08[/C][C]163.061162623842[/C][C]0.78680145367277[/C][/ROW]
[ROW][C]0.09[/C][C]163.298307645711[/C][C]0.799388500607141[/C][/ROW]
[ROW][C]0.1[/C][C]163.528346934145[/C][C]0.775043922061135[/C][/ROW]
[ROW][C]0.11[/C][C]163.742960039093[/C][C]0.721422404667687[/C][/ROW]
[ROW][C]0.12[/C][C]163.936375997033[/C][C]0.648390457976331[/C][/ROW]
[ROW][C]0.13[/C][C]164.105715328165[/C][C]0.567214966845741[/C][/ROW]
[ROW][C]0.14[/C][C]164.250765860834[/C][C]0.487276898175343[/C][/ROW]
[ROW][C]0.15[/C][C]164.373407955204[/C][C]0.41650359242982[/C][/ROW]
[ROW][C]0.16[/C][C]164.476889692782[/C][C]0.359743874865342[/C][/ROW]
[ROW][C]0.17[/C][C]164.565115885382[/C][C]0.3189253748248[/C][/ROW]
[ROW][C]0.18[/C][C]164.642062761038[/C][C]0.293901021241618[/C][/ROW]
[ROW][C]0.19[/C][C]164.711371635136[/C][C]0.282515312804278[/C][/ROW]
[ROW][C]0.2[/C][C]164.776122180426[/C][C]0.281955374873924[/C][/ROW]
[ROW][C]0.21[/C][C]164.838749796719[/C][C]0.289342168168908[/C][/ROW]
[ROW][C]0.22[/C][C]164.901056433326[/C][C]0.302111876579383[/C][/ROW]
[ROW][C]0.23[/C][C]164.964267359535[/C][C]0.318215141765348[/C][/ROW]
[ROW][C]0.24[/C][C]165.029100633481[/C][C]0.335584411765123[/C][/ROW]
[ROW][C]0.25[/C][C]165.09583329815[/C][C]0.352460423715975[/C][/ROW]
[ROW][C]0.26[/C][C]165.164362413205[/C][C]0.36701003665195[/C][/ROW]
[ROW][C]0.27[/C][C]165.234266796421[/C][C]0.37770023981187[/C][/ROW]
[ROW][C]0.28[/C][C]165.304876640597[/C][C]0.383159234810066[/C][/ROW]
[ROW][C]0.29[/C][C]165.375354827475[/C][C]0.382970014003268[/C][/ROW]
[ROW][C]0.3[/C][C]165.444788418723[/C][C]0.376763140990785[/C][/ROW]
[ROW][C]0.31[/C][C]165.512283903303[/C][C]0.365320934834554[/C][/ROW]
[ROW][C]0.32[/C][C]165.577056944607[/C][C]0.349242876776731[/C][/ROW]
[ROW][C]0.33[/C][C]165.638507213676[/C][C]0.329805280349866[/C][/ROW]
[ROW][C]0.34[/C][C]165.6962711471[/C][C]0.308767582073267[/C][/ROW]
[ROW][C]0.35[/C][C]165.750249282884[/C][C]0.287782257917667[/C][/ROW]
[ROW][C]0.36[/C][C]165.800609127895[/C][C]0.268398885432509[/C][/ROW]
[ROW][C]0.37[/C][C]165.847768280575[/C][C]0.251842488599379[/C][/ROW]
[ROW][C]0.38[/C][C]165.892365008157[/C][C]0.240026023717039[/C][/ROW]
[ROW][C]0.39[/C][C]165.935224235654[/C][C]0.233420487625962[/C][/ROW]
[ROW][C]0.4[/C][C]165.977325878012[/C][C]0.233323538010638[/C][/ROW]
[ROW][C]0.41[/C][C]166.019779896445[/C][C]0.240358293918044[/C][/ROW]
[ROW][C]0.42[/C][C]166.0638089141[/C][C]0.254979339671662[/C][/ROW]
[ROW][C]0.43[/C][C]166.11073540697[/C][C]0.278049324808312[/C][/ROW]
[ROW][C]0.44[/C][C]166.161967210011[/C][C]0.309979783294614[/C][/ROW]
[ROW][C]0.45[/C][C]166.218973132582[/C][C]0.35124690895555[/C][/ROW]
[ROW][C]0.46[/C][C]166.283240476443[/C][C]0.401991628588602[/C][/ROW]
[ROW][C]0.47[/C][C]166.356208492759[/C][C]0.461910066395118[/C][/ROW]
[ROW][C]0.48[/C][C]166.439176173747[/C][C]0.529458965812121[/C][/ROW]
[ROW][C]0.49[/C][C]166.533188646356[/C][C]0.602733750748332[/C][/ROW]
[ROW][C]0.5[/C][C]166.638912789769[/C][C]0.678886587720355[/C][/ROW]
[ROW][C]0.51[/C][C]166.756518233917[/C][C]0.754274729261876[/C][/ROW]
[ROW][C]0.52[/C][C]166.885583288459[/C][C]0.825008270621458[/C][/ROW]
[ROW][C]0.53[/C][C]167.025045552147[/C][C]0.886625265905572[/C][/ROW]
[ROW][C]0.54[/C][C]167.17321346715[/C][C]0.935047652427909[/C][/ROW]
[ROW][C]0.55[/C][C]167.327848154925[/C][C]0.967406039692325[/C][/ROW]
[ROW][C]0.56[/C][C]167.486315498719[/C][C]0.981306320620937[/C][/ROW]
[ROW][C]0.57[/C][C]167.64579820711[/C][C]0.976205826926099[/C][/ROW]
[ROW][C]0.58[/C][C]167.803548333024[/C][C]0.95301673487051[/C][/ROW]
[ROW][C]0.59[/C][C]167.957154082615[/C][C]0.914371216303477[/C][/ROW]
[ROW][C]0.6[/C][C]168.104791799659[/C][C]0.864561191488325[/C][/ROW]
[ROW][C]0.61[/C][C]168.245435002742[/C][C]0.808821072788947[/C][/ROW]
[ROW][C]0.62[/C][C]168.37899670516[/C][C]0.753260229936858[/C][/ROW]
[ROW][C]0.63[/C][C]168.506387801391[/C][C]0.704924514093631[/C][/ROW]
[ROW][C]0.64[/C][C]168.629481749496[/C][C]0.670010378729465[/C][/ROW]
[ROW][C]0.65[/C][C]168.750983122951[/C][C]0.654808364494461[/C][/ROW]
[ROW][C]0.66[/C][C]168.874204499998[/C][C]0.663439587078833[/C][/ROW]
[ROW][C]0.67[/C][C]169.002762938981[/C][C]0.696782595912527[/C][/ROW]
[ROW][C]0.68[/C][C]169.140214669916[/C][C]0.752985709406211[/C][/ROW]
[ROW][C]0.69[/C][C]169.289655137159[/C][C]0.827194263433464[/C][/ROW]
[ROW][C]0.7[/C][C]169.453320843977[/C][C]0.911921659215507[/C][/ROW]
[ROW][C]0.71[/C][C]169.632238007554[/C][C]0.998953360658322[/C][/ROW]
[ROW][C]0.72[/C][C]169.825968053724[/C][C]1.07887112650195[/C][/ROW]
[ROW][C]0.73[/C][C]170.032498126729[/C][C]1.1427283285383[/C][/ROW]
[ROW][C]0.74[/C][C]170.248313318369[/C][C]1.1824962145532[/C][/ROW]
[ROW][C]0.75[/C][C]170.468665410436[/C][C]1.19244692303834[/C][/ROW]
[ROW][C]0.76[/C][C]170.688022667739[/C][C]1.16934252641889[/C][/ROW]
[ROW][C]0.77[/C][C]170.900651806214[/C][C]1.11383831633459[/C][/ROW]
[ROW][C]0.78[/C][C]171.101254074085[/C][C]1.02978277582586[/C][/ROW]
[ROW][C]0.79[/C][C]171.285560124584[/C][C]0.924110059731419[/C][/ROW]
[ROW][C]0.8[/C][C]171.450788720796[/C][C]0.8059910374732[/C][/ROW]
[ROW][C]0.81[/C][C]171.595893994357[/C][C]0.685133020414986[/C][/ROW]
[ROW][C]0.82[/C][C]171.721561773302[/C][C]0.571064458785723[/C][/ROW]
[ROW][C]0.83[/C][C]171.829959877251[/C][C]0.471530152417532[/C][/ROW]
[ROW][C]0.84[/C][C]171.924290383176[/C][C]0.392106969633768[/C][/ROW]
[ROW][C]0.85[/C][C]172.008224249952[/C][C]0.334932909021396[/C][/ROW]
[ROW][C]0.86[/C][C]172.085314072893[/C][C]0.298665014596598[/C][/ROW]
[ROW][C]0.87[/C][C]172.158477909896[/C][C]0.278286640144158[/C][/ROW]
[ROW][C]0.88[/C][C]172.229630434877[/C][C]0.267010374595119[/C][/ROW]
[ROW][C]0.89[/C][C]172.299515810338[/C][C]0.257907879396446[/C][/ROW]
[ROW][C]0.9[/C][C]172.367779725496[/C][C]0.245853181321814[/C][/ROW]
[ROW][C]0.91[/C][C]172.433313638386[/C][C]0.227539348529627[/C][/ROW]
[ROW][C]0.92[/C][C]172.494913065621[/C][C]0.202273166567988[/C][/ROW]
[ROW][C]0.93[/C][C]172.552298670955[/C][C]0.172105545647128[/C][/ROW]
[ROW][C]0.94[/C][C]172.607495985464[/C][C]0.142460469173558[/C][/ROW]
[ROW][C]0.95[/C][C]172.666298474746[/C][C]0.123902539756329[/C][/ROW]
[ROW][C]0.96[/C][C]172.738769200058[/C][C]0.133933507512159[/C][/ROW]
[ROW][C]0.97[/C][C]172.83638957635[/C][C]0.186104947988871[/C][/ROW]
[ROW][C]0.98[/C][C]172.962825555642[/C][C]0.276562627400497[/C][/ROW]
[ROW][C]0.99[/C][C]173.099456997557[/C][C]0.382596734863646[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=238626&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=238626&T=1

As an alternative you can also use a QR Code:  

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

Harrell-Davis Quantiles
quantilesvaluestandard error
0.01161.7702293255910.284805339411884
0.02161.8974787714810.281265627174338
0.03162.0489230806680.32593845633287
0.04162.2158890969420.418379943798544
0.05162.4000642337760.534163069260603
0.06162.6041821117330.646342661178127
0.07162.8266842185950.734626774696923
0.08163.0611626238420.78680145367277
0.09163.2983076457110.799388500607141
0.1163.5283469341450.775043922061135
0.11163.7429600390930.721422404667687
0.12163.9363759970330.648390457976331
0.13164.1057153281650.567214966845741
0.14164.2507658608340.487276898175343
0.15164.3734079552040.41650359242982
0.16164.4768896927820.359743874865342
0.17164.5651158853820.3189253748248
0.18164.6420627610380.293901021241618
0.19164.7113716351360.282515312804278
0.2164.7761221804260.281955374873924
0.21164.8387497967190.289342168168908
0.22164.9010564333260.302111876579383
0.23164.9642673595350.318215141765348
0.24165.0291006334810.335584411765123
0.25165.095833298150.352460423715975
0.26165.1643624132050.36701003665195
0.27165.2342667964210.37770023981187
0.28165.3048766405970.383159234810066
0.29165.3753548274750.382970014003268
0.3165.4447884187230.376763140990785
0.31165.5122839033030.365320934834554
0.32165.5770569446070.349242876776731
0.33165.6385072136760.329805280349866
0.34165.69627114710.308767582073267
0.35165.7502492828840.287782257917667
0.36165.8006091278950.268398885432509
0.37165.8477682805750.251842488599379
0.38165.8923650081570.240026023717039
0.39165.9352242356540.233420487625962
0.4165.9773258780120.233323538010638
0.41166.0197798964450.240358293918044
0.42166.06380891410.254979339671662
0.43166.110735406970.278049324808312
0.44166.1619672100110.309979783294614
0.45166.2189731325820.35124690895555
0.46166.2832404764430.401991628588602
0.47166.3562084927590.461910066395118
0.48166.4391761737470.529458965812121
0.49166.5331886463560.602733750748332
0.5166.6389127897690.678886587720355
0.51166.7565182339170.754274729261876
0.52166.8855832884590.825008270621458
0.53167.0250455521470.886625265905572
0.54167.173213467150.935047652427909
0.55167.3278481549250.967406039692325
0.56167.4863154987190.981306320620937
0.57167.645798207110.976205826926099
0.58167.8035483330240.95301673487051
0.59167.9571540826150.914371216303477
0.6168.1047917996590.864561191488325
0.61168.2454350027420.808821072788947
0.62168.378996705160.753260229936858
0.63168.5063878013910.704924514093631
0.64168.6294817494960.670010378729465
0.65168.7509831229510.654808364494461
0.66168.8742044999980.663439587078833
0.67169.0027629389810.696782595912527
0.68169.1402146699160.752985709406211
0.69169.2896551371590.827194263433464
0.7169.4533208439770.911921659215507
0.71169.6322380075540.998953360658322
0.72169.8259680537241.07887112650195
0.73170.0324981267291.1427283285383
0.74170.2483133183691.1824962145532
0.75170.4686654104361.19244692303834
0.76170.6880226677391.16934252641889
0.77170.9006518062141.11383831633459
0.78171.1012540740851.02978277582586
0.79171.2855601245840.924110059731419
0.8171.4507887207960.8059910374732
0.81171.5958939943570.685133020414986
0.82171.7215617733020.571064458785723
0.83171.8299598772510.471530152417532
0.84171.9242903831760.392106969633768
0.85172.0082242499520.334932909021396
0.86172.0853140728930.298665014596598
0.87172.1584779098960.278286640144158
0.88172.2296304348770.267010374595119
0.89172.2995158103380.257907879396446
0.9172.3677797254960.245853181321814
0.91172.4333136383860.227539348529627
0.92172.4949130656210.202273166567988
0.93172.5522986709550.172105545647128
0.94172.6074959854640.142460469173558
0.95172.6662984747460.123902539756329
0.96172.7387692000580.133933507512159
0.97172.836389576350.186104947988871
0.98172.9628255556420.276562627400497
0.99173.0994569975570.382596734863646



Parameters (Session):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
Parameters (R input):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
R code (references can be found in the software module):
par1 <- as(par1,'numeric')
par2 <- as(par2,'numeric')
par3 <- as(par3,'numeric')
library(Hmisc)
myseq <- seq(par1, par2, par3)
hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE)
bitmap(file='test1.png')
plot(myseq,hd,col=2,main=main,xlab=xlab,ylab=ylab)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Harrell-Davis Quantiles',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'quantiles',header=TRUE)
a<-table.element(a,'value',header=TRUE)
a<-table.element(a,'standard error',header=TRUE)
a<-table.row.end(a)
length(hd)
for (i in 1:length(hd))
{
a<-table.row.start(a)
a<-table.element(a,as(labels(hd)[i],'numeric'),header=TRUE)
a<-table.element(a,as.matrix(hd[i])[1,1])
a<-table.element(a,as.matrix(attr(hd,'se')[i])[1,1])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')