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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationSun, 17 Aug 2014 21:49:25 +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/Aug/17/t1408309064ef05lhhaow3hk8w.htm/, Retrieved Sat, 07 Feb 2026 03:45:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=235641, Retrieved Sat, 07 Feb 2026 03:45:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsStefaan Segers
Estimated Impact400

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Tijdreeks A - Sta...] [2014-08-17 17:13:10] [40556739fb744d7815ea48083fb3e63a]
- R P   [(Partial) Autocorrelation Function] [Tijdreeks A - Sta...] [2014-08-17 17:15:53] [40556739fb744d7815ea48083fb3e63a]
- R P     [(Partial) Autocorrelation Function] [Tijdreeks A - Sta...] [2014-08-17 17:34:53] [40556739fb744d7815ea48083fb3e63a]
- RMPD      [Univariate Data Series] [Tijdreeks B - Sta...] [2014-08-17 20:10:51] [f85cc8f00ef4b762f0a6fdfddc793773]
- RM            [Harrell-Davis Quantiles] [Tijdreeks B - Stap 7] [2014-08-17 20:49:25] [92f35a2db74bf110e350beffc19b3da6] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=235641&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]2 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=235641&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235641&T=0

As an alternative you can also use a QR Code:  
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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01485.7963774067059.21646023823546
0.02493.5672255503538.32934920996385
0.03500.0754502858837.63195916390023
0.04505.24948357537.5809562589117
0.05509.7459107626078.08377488319814
0.06514.0405697277019.01137284365043
0.07518.40192309940410.1925129122741
0.08522.9832019352411.579285136322
0.09527.89935639028413.3313971619058
0.1533.26665109032215.5689054548449
0.11539.18159411916218.1135961603128
0.12545.65815022771920.4919795646039
0.13552.57806420363322.1523386785361
0.14559.69765363070922.7219566714939
0.15566.71322512111322.159116999093
0.16573.35195343970320.7537107902267
0.17579.4457214071118.9956778672696
0.18584.9603100039617.3983507447331
0.19589.97695051160216.3266977180128
0.2594.64274499056815.9036146482224
0.21599.11361833426916.0135357044834
0.22603.50951574148216.4015848514862
0.23607.89207732217616.7937284401154
0.24612.26538667536716.9897499190347
0.25616.59361833720216.8969424270256
0.26620.82630636339516.5383506111965
0.27624.92211858656116.0239077835895
0.28628.86454353345615.5056935936956
0.29632.66663427241715.1275298493545
0.3636.36567544261714.9786514694546
0.31640.01130755822815.0753508139794
0.32643.65171070956415.3653085930234
0.33647.3219815773815.7511801317376
0.34651.03735783210416.1263800614164
0.35654.79213643737916.3971783202328
0.36658.563566214816.5039527263759
0.37662.3189900368616.4245584614832
0.38666.02414267018216.1776122853333
0.39669.65068137663915.8116357804774
0.4673.18155671466315.391796823365
0.41676.61351799495714.9885644891751
0.42679.95671303773814.6641008350463
0.43683.23186160159114.4603631660006
0.44686.4658009975114.3936834323223
0.45689.68632672895514.4556030850899
0.46692.91722141295914.6122336449127
0.47696.17422732115714.8155096408568
0.48699.46250302569415.008062452201
0.49702.77583153604615.1331623095612
0.5706.09753910191415.1463294473091
0.51709.40278548575315.0172471624191
0.52712.66166601911714.7315470491254
0.53715.84249285395714.2926862525976
0.54718.91473304711213.7152802711517
0.55721.85134525271213.022215548055
0.56724.63057586333712.2421948849281
0.57727.23751078340311.4064737579454
0.58729.66570951009710.552343849134
0.59731.9190312392839.7265462546886
0.6734.0133700797838.98477280771382
0.61735.977623219338.38914139155831
0.62737.8530385235338.00525358677288
0.63739.6902901699597.87797503470102
0.64741.5442333549398.01884239404273
0.65743.4671275264268.39493257009554
0.66745.501878935038.93266180233544
0.67747.6771921952819.54398288284904
0.68750.00621668521110.145967961373
0.69752.48935864288210.6863227710246
0.7755.12070991057911.1515649536144
0.71757.89648379142111.5707807666415
0.72760.82335259561312.0083817304593
0.73763.92478455161712.5459688316259
0.74767.24416413739213.2652992428342
0.75770.84420721573214.2353267481823
0.76774.80256504551415.4958327973447
0.77779.20351075022317.0480292647393
0.78784.12563155895618.8403111459184
0.79789.62616774516220.7570713910324
0.8795.72445583065422.6220703826262
0.81802.38947186545724.2161139138754
0.82809.53837312609925.3347500113782
0.83817.05242733929825.852997109815
0.84824.81295926406225.8024413114751
0.85832.75445680578825.4128222454369
0.86840.92858953061925.1143657397723
0.87849.57470556078225.5102947436561
0.88859.19618188234127.3524228638945
0.89870.63454070115331.5144176007572
0.9885.09781565935638.822496795245
0.91904.03996393739949.5094424625889
0.92928.75865569433162.3661783231952
0.93959.67813413840574.1601213614192
0.94995.56235479026380.1936958024722
0.951033.2457021747376.4570803370019
0.961068.701880216362.5458742503605
0.971100.4462463114844.0643049290632
0.981135.0064831143937.9057548078551
0.991183.8191375065868.0829013248553

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 485.796377406705 & 9.21646023823546 \tabularnewline
0.02 & 493.567225550353 & 8.32934920996385 \tabularnewline
0.03 & 500.075450285883 & 7.63195916390023 \tabularnewline
0.04 & 505.2494835753 & 7.5809562589117 \tabularnewline
0.05 & 509.745910762607 & 8.08377488319814 \tabularnewline
0.06 & 514.040569727701 & 9.01137284365043 \tabularnewline
0.07 & 518.401923099404 & 10.1925129122741 \tabularnewline
0.08 & 522.98320193524 & 11.579285136322 \tabularnewline
0.09 & 527.899356390284 & 13.3313971619058 \tabularnewline
0.1 & 533.266651090322 & 15.5689054548449 \tabularnewline
0.11 & 539.181594119162 & 18.1135961603128 \tabularnewline
0.12 & 545.658150227719 & 20.4919795646039 \tabularnewline
0.13 & 552.578064203633 & 22.1523386785361 \tabularnewline
0.14 & 559.697653630709 & 22.7219566714939 \tabularnewline
0.15 & 566.713225121113 & 22.159116999093 \tabularnewline
0.16 & 573.351953439703 & 20.7537107902267 \tabularnewline
0.17 & 579.44572140711 & 18.9956778672696 \tabularnewline
0.18 & 584.96031000396 & 17.3983507447331 \tabularnewline
0.19 & 589.976950511602 & 16.3266977180128 \tabularnewline
0.2 & 594.642744990568 & 15.9036146482224 \tabularnewline
0.21 & 599.113618334269 & 16.0135357044834 \tabularnewline
0.22 & 603.509515741482 & 16.4015848514862 \tabularnewline
0.23 & 607.892077322176 & 16.7937284401154 \tabularnewline
0.24 & 612.265386675367 & 16.9897499190347 \tabularnewline
0.25 & 616.593618337202 & 16.8969424270256 \tabularnewline
0.26 & 620.826306363395 & 16.5383506111965 \tabularnewline
0.27 & 624.922118586561 & 16.0239077835895 \tabularnewline
0.28 & 628.864543533456 & 15.5056935936956 \tabularnewline
0.29 & 632.666634272417 & 15.1275298493545 \tabularnewline
0.3 & 636.365675442617 & 14.9786514694546 \tabularnewline
0.31 & 640.011307558228 & 15.0753508139794 \tabularnewline
0.32 & 643.651710709564 & 15.3653085930234 \tabularnewline
0.33 & 647.32198157738 & 15.7511801317376 \tabularnewline
0.34 & 651.037357832104 & 16.1263800614164 \tabularnewline
0.35 & 654.792136437379 & 16.3971783202328 \tabularnewline
0.36 & 658.5635662148 & 16.5039527263759 \tabularnewline
0.37 & 662.31899003686 & 16.4245584614832 \tabularnewline
0.38 & 666.024142670182 & 16.1776122853333 \tabularnewline
0.39 & 669.650681376639 & 15.8116357804774 \tabularnewline
0.4 & 673.181556714663 & 15.391796823365 \tabularnewline
0.41 & 676.613517994957 & 14.9885644891751 \tabularnewline
0.42 & 679.956713037738 & 14.6641008350463 \tabularnewline
0.43 & 683.231861601591 & 14.4603631660006 \tabularnewline
0.44 & 686.46580099751 & 14.3936834323223 \tabularnewline
0.45 & 689.686326728955 & 14.4556030850899 \tabularnewline
0.46 & 692.917221412959 & 14.6122336449127 \tabularnewline
0.47 & 696.174227321157 & 14.8155096408568 \tabularnewline
0.48 & 699.462503025694 & 15.008062452201 \tabularnewline
0.49 & 702.775831536046 & 15.1331623095612 \tabularnewline
0.5 & 706.097539101914 & 15.1463294473091 \tabularnewline
0.51 & 709.402785485753 & 15.0172471624191 \tabularnewline
0.52 & 712.661666019117 & 14.7315470491254 \tabularnewline
0.53 & 715.842492853957 & 14.2926862525976 \tabularnewline
0.54 & 718.914733047112 & 13.7152802711517 \tabularnewline
0.55 & 721.851345252712 & 13.022215548055 \tabularnewline
0.56 & 724.630575863337 & 12.2421948849281 \tabularnewline
0.57 & 727.237510783403 & 11.4064737579454 \tabularnewline
0.58 & 729.665709510097 & 10.552343849134 \tabularnewline
0.59 & 731.919031239283 & 9.7265462546886 \tabularnewline
0.6 & 734.013370079783 & 8.98477280771382 \tabularnewline
0.61 & 735.97762321933 & 8.38914139155831 \tabularnewline
0.62 & 737.853038523533 & 8.00525358677288 \tabularnewline
0.63 & 739.690290169959 & 7.87797503470102 \tabularnewline
0.64 & 741.544233354939 & 8.01884239404273 \tabularnewline
0.65 & 743.467127526426 & 8.39493257009554 \tabularnewline
0.66 & 745.50187893503 & 8.93266180233544 \tabularnewline
0.67 & 747.677192195281 & 9.54398288284904 \tabularnewline
0.68 & 750.006216685211 & 10.145967961373 \tabularnewline
0.69 & 752.489358642882 & 10.6863227710246 \tabularnewline
0.7 & 755.120709910579 & 11.1515649536144 \tabularnewline
0.71 & 757.896483791421 & 11.5707807666415 \tabularnewline
0.72 & 760.823352595613 & 12.0083817304593 \tabularnewline
0.73 & 763.924784551617 & 12.5459688316259 \tabularnewline
0.74 & 767.244164137392 & 13.2652992428342 \tabularnewline
0.75 & 770.844207215732 & 14.2353267481823 \tabularnewline
0.76 & 774.802565045514 & 15.4958327973447 \tabularnewline
0.77 & 779.203510750223 & 17.0480292647393 \tabularnewline
0.78 & 784.125631558956 & 18.8403111459184 \tabularnewline
0.79 & 789.626167745162 & 20.7570713910324 \tabularnewline
0.8 & 795.724455830654 & 22.6220703826262 \tabularnewline
0.81 & 802.389471865457 & 24.2161139138754 \tabularnewline
0.82 & 809.538373126099 & 25.3347500113782 \tabularnewline
0.83 & 817.052427339298 & 25.852997109815 \tabularnewline
0.84 & 824.812959264062 & 25.8024413114751 \tabularnewline
0.85 & 832.754456805788 & 25.4128222454369 \tabularnewline
0.86 & 840.928589530619 & 25.1143657397723 \tabularnewline
0.87 & 849.574705560782 & 25.5102947436561 \tabularnewline
0.88 & 859.196181882341 & 27.3524228638945 \tabularnewline
0.89 & 870.634540701153 & 31.5144176007572 \tabularnewline
0.9 & 885.097815659356 & 38.822496795245 \tabularnewline
0.91 & 904.039963937399 & 49.5094424625889 \tabularnewline
0.92 & 928.758655694331 & 62.3661783231952 \tabularnewline
0.93 & 959.678134138405 & 74.1601213614192 \tabularnewline
0.94 & 995.562354790263 & 80.1936958024722 \tabularnewline
0.95 & 1033.24570217473 & 76.4570803370019 \tabularnewline
0.96 & 1068.7018802163 & 62.5458742503605 \tabularnewline
0.97 & 1100.44624631148 & 44.0643049290632 \tabularnewline
0.98 & 1135.00648311439 & 37.9057548078551 \tabularnewline
0.99 & 1183.81913750658 & 68.0829013248553 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=235641&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]485.796377406705[/C][C]9.21646023823546[/C][/ROW]
[ROW][C]0.02[/C][C]493.567225550353[/C][C]8.32934920996385[/C][/ROW]
[ROW][C]0.03[/C][C]500.075450285883[/C][C]7.63195916390023[/C][/ROW]
[ROW][C]0.04[/C][C]505.2494835753[/C][C]7.5809562589117[/C][/ROW]
[ROW][C]0.05[/C][C]509.745910762607[/C][C]8.08377488319814[/C][/ROW]
[ROW][C]0.06[/C][C]514.040569727701[/C][C]9.01137284365043[/C][/ROW]
[ROW][C]0.07[/C][C]518.401923099404[/C][C]10.1925129122741[/C][/ROW]
[ROW][C]0.08[/C][C]522.98320193524[/C][C]11.579285136322[/C][/ROW]
[ROW][C]0.09[/C][C]527.899356390284[/C][C]13.3313971619058[/C][/ROW]
[ROW][C]0.1[/C][C]533.266651090322[/C][C]15.5689054548449[/C][/ROW]
[ROW][C]0.11[/C][C]539.181594119162[/C][C]18.1135961603128[/C][/ROW]
[ROW][C]0.12[/C][C]545.658150227719[/C][C]20.4919795646039[/C][/ROW]
[ROW][C]0.13[/C][C]552.578064203633[/C][C]22.1523386785361[/C][/ROW]
[ROW][C]0.14[/C][C]559.697653630709[/C][C]22.7219566714939[/C][/ROW]
[ROW][C]0.15[/C][C]566.713225121113[/C][C]22.159116999093[/C][/ROW]
[ROW][C]0.16[/C][C]573.351953439703[/C][C]20.7537107902267[/C][/ROW]
[ROW][C]0.17[/C][C]579.44572140711[/C][C]18.9956778672696[/C][/ROW]
[ROW][C]0.18[/C][C]584.96031000396[/C][C]17.3983507447331[/C][/ROW]
[ROW][C]0.19[/C][C]589.976950511602[/C][C]16.3266977180128[/C][/ROW]
[ROW][C]0.2[/C][C]594.642744990568[/C][C]15.9036146482224[/C][/ROW]
[ROW][C]0.21[/C][C]599.113618334269[/C][C]16.0135357044834[/C][/ROW]
[ROW][C]0.22[/C][C]603.509515741482[/C][C]16.4015848514862[/C][/ROW]
[ROW][C]0.23[/C][C]607.892077322176[/C][C]16.7937284401154[/C][/ROW]
[ROW][C]0.24[/C][C]612.265386675367[/C][C]16.9897499190347[/C][/ROW]
[ROW][C]0.25[/C][C]616.593618337202[/C][C]16.8969424270256[/C][/ROW]
[ROW][C]0.26[/C][C]620.826306363395[/C][C]16.5383506111965[/C][/ROW]
[ROW][C]0.27[/C][C]624.922118586561[/C][C]16.0239077835895[/C][/ROW]
[ROW][C]0.28[/C][C]628.864543533456[/C][C]15.5056935936956[/C][/ROW]
[ROW][C]0.29[/C][C]632.666634272417[/C][C]15.1275298493545[/C][/ROW]
[ROW][C]0.3[/C][C]636.365675442617[/C][C]14.9786514694546[/C][/ROW]
[ROW][C]0.31[/C][C]640.011307558228[/C][C]15.0753508139794[/C][/ROW]
[ROW][C]0.32[/C][C]643.651710709564[/C][C]15.3653085930234[/C][/ROW]
[ROW][C]0.33[/C][C]647.32198157738[/C][C]15.7511801317376[/C][/ROW]
[ROW][C]0.34[/C][C]651.037357832104[/C][C]16.1263800614164[/C][/ROW]
[ROW][C]0.35[/C][C]654.792136437379[/C][C]16.3971783202328[/C][/ROW]
[ROW][C]0.36[/C][C]658.5635662148[/C][C]16.5039527263759[/C][/ROW]
[ROW][C]0.37[/C][C]662.31899003686[/C][C]16.4245584614832[/C][/ROW]
[ROW][C]0.38[/C][C]666.024142670182[/C][C]16.1776122853333[/C][/ROW]
[ROW][C]0.39[/C][C]669.650681376639[/C][C]15.8116357804774[/C][/ROW]
[ROW][C]0.4[/C][C]673.181556714663[/C][C]15.391796823365[/C][/ROW]
[ROW][C]0.41[/C][C]676.613517994957[/C][C]14.9885644891751[/C][/ROW]
[ROW][C]0.42[/C][C]679.956713037738[/C][C]14.6641008350463[/C][/ROW]
[ROW][C]0.43[/C][C]683.231861601591[/C][C]14.4603631660006[/C][/ROW]
[ROW][C]0.44[/C][C]686.46580099751[/C][C]14.3936834323223[/C][/ROW]
[ROW][C]0.45[/C][C]689.686326728955[/C][C]14.4556030850899[/C][/ROW]
[ROW][C]0.46[/C][C]692.917221412959[/C][C]14.6122336449127[/C][/ROW]
[ROW][C]0.47[/C][C]696.174227321157[/C][C]14.8155096408568[/C][/ROW]
[ROW][C]0.48[/C][C]699.462503025694[/C][C]15.008062452201[/C][/ROW]
[ROW][C]0.49[/C][C]702.775831536046[/C][C]15.1331623095612[/C][/ROW]
[ROW][C]0.5[/C][C]706.097539101914[/C][C]15.1463294473091[/C][/ROW]
[ROW][C]0.51[/C][C]709.402785485753[/C][C]15.0172471624191[/C][/ROW]
[ROW][C]0.52[/C][C]712.661666019117[/C][C]14.7315470491254[/C][/ROW]
[ROW][C]0.53[/C][C]715.842492853957[/C][C]14.2926862525976[/C][/ROW]
[ROW][C]0.54[/C][C]718.914733047112[/C][C]13.7152802711517[/C][/ROW]
[ROW][C]0.55[/C][C]721.851345252712[/C][C]13.022215548055[/C][/ROW]
[ROW][C]0.56[/C][C]724.630575863337[/C][C]12.2421948849281[/C][/ROW]
[ROW][C]0.57[/C][C]727.237510783403[/C][C]11.4064737579454[/C][/ROW]
[ROW][C]0.58[/C][C]729.665709510097[/C][C]10.552343849134[/C][/ROW]
[ROW][C]0.59[/C][C]731.919031239283[/C][C]9.7265462546886[/C][/ROW]
[ROW][C]0.6[/C][C]734.013370079783[/C][C]8.98477280771382[/C][/ROW]
[ROW][C]0.61[/C][C]735.97762321933[/C][C]8.38914139155831[/C][/ROW]
[ROW][C]0.62[/C][C]737.853038523533[/C][C]8.00525358677288[/C][/ROW]
[ROW][C]0.63[/C][C]739.690290169959[/C][C]7.87797503470102[/C][/ROW]
[ROW][C]0.64[/C][C]741.544233354939[/C][C]8.01884239404273[/C][/ROW]
[ROW][C]0.65[/C][C]743.467127526426[/C][C]8.39493257009554[/C][/ROW]
[ROW][C]0.66[/C][C]745.50187893503[/C][C]8.93266180233544[/C][/ROW]
[ROW][C]0.67[/C][C]747.677192195281[/C][C]9.54398288284904[/C][/ROW]
[ROW][C]0.68[/C][C]750.006216685211[/C][C]10.145967961373[/C][/ROW]
[ROW][C]0.69[/C][C]752.489358642882[/C][C]10.6863227710246[/C][/ROW]
[ROW][C]0.7[/C][C]755.120709910579[/C][C]11.1515649536144[/C][/ROW]
[ROW][C]0.71[/C][C]757.896483791421[/C][C]11.5707807666415[/C][/ROW]
[ROW][C]0.72[/C][C]760.823352595613[/C][C]12.0083817304593[/C][/ROW]
[ROW][C]0.73[/C][C]763.924784551617[/C][C]12.5459688316259[/C][/ROW]
[ROW][C]0.74[/C][C]767.244164137392[/C][C]13.2652992428342[/C][/ROW]
[ROW][C]0.75[/C][C]770.844207215732[/C][C]14.2353267481823[/C][/ROW]
[ROW][C]0.76[/C][C]774.802565045514[/C][C]15.4958327973447[/C][/ROW]
[ROW][C]0.77[/C][C]779.203510750223[/C][C]17.0480292647393[/C][/ROW]
[ROW][C]0.78[/C][C]784.125631558956[/C][C]18.8403111459184[/C][/ROW]
[ROW][C]0.79[/C][C]789.626167745162[/C][C]20.7570713910324[/C][/ROW]
[ROW][C]0.8[/C][C]795.724455830654[/C][C]22.6220703826262[/C][/ROW]
[ROW][C]0.81[/C][C]802.389471865457[/C][C]24.2161139138754[/C][/ROW]
[ROW][C]0.82[/C][C]809.538373126099[/C][C]25.3347500113782[/C][/ROW]
[ROW][C]0.83[/C][C]817.052427339298[/C][C]25.852997109815[/C][/ROW]
[ROW][C]0.84[/C][C]824.812959264062[/C][C]25.8024413114751[/C][/ROW]
[ROW][C]0.85[/C][C]832.754456805788[/C][C]25.4128222454369[/C][/ROW]
[ROW][C]0.86[/C][C]840.928589530619[/C][C]25.1143657397723[/C][/ROW]
[ROW][C]0.87[/C][C]849.574705560782[/C][C]25.5102947436561[/C][/ROW]
[ROW][C]0.88[/C][C]859.196181882341[/C][C]27.3524228638945[/C][/ROW]
[ROW][C]0.89[/C][C]870.634540701153[/C][C]31.5144176007572[/C][/ROW]
[ROW][C]0.9[/C][C]885.097815659356[/C][C]38.822496795245[/C][/ROW]
[ROW][C]0.91[/C][C]904.039963937399[/C][C]49.5094424625889[/C][/ROW]
[ROW][C]0.92[/C][C]928.758655694331[/C][C]62.3661783231952[/C][/ROW]
[ROW][C]0.93[/C][C]959.678134138405[/C][C]74.1601213614192[/C][/ROW]
[ROW][C]0.94[/C][C]995.562354790263[/C][C]80.1936958024722[/C][/ROW]
[ROW][C]0.95[/C][C]1033.24570217473[/C][C]76.4570803370019[/C][/ROW]
[ROW][C]0.96[/C][C]1068.7018802163[/C][C]62.5458742503605[/C][/ROW]
[ROW][C]0.97[/C][C]1100.44624631148[/C][C]44.0643049290632[/C][/ROW]
[ROW][C]0.98[/C][C]1135.00648311439[/C][C]37.9057548078551[/C][/ROW]
[ROW][C]0.99[/C][C]1183.81913750658[/C][C]68.0829013248553[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=235641&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235641&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Harrell-Davis Quantiles
quantilesvaluestandard error
0.01485.7963774067059.21646023823546
0.02493.5672255503538.32934920996385
0.03500.0754502858837.63195916390023
0.04505.24948357537.5809562589117
0.05509.7459107626078.08377488319814
0.06514.0405697277019.01137284365043
0.07518.40192309940410.1925129122741
0.08522.9832019352411.579285136322
0.09527.89935639028413.3313971619058
0.1533.26665109032215.5689054548449
0.11539.18159411916218.1135961603128
0.12545.65815022771920.4919795646039
0.13552.57806420363322.1523386785361
0.14559.69765363070922.7219566714939
0.15566.71322512111322.159116999093
0.16573.35195343970320.7537107902267
0.17579.4457214071118.9956778672696
0.18584.9603100039617.3983507447331
0.19589.97695051160216.3266977180128
0.2594.64274499056815.9036146482224
0.21599.11361833426916.0135357044834
0.22603.50951574148216.4015848514862
0.23607.89207732217616.7937284401154
0.24612.26538667536716.9897499190347
0.25616.59361833720216.8969424270256
0.26620.82630636339516.5383506111965
0.27624.92211858656116.0239077835895
0.28628.86454353345615.5056935936956
0.29632.66663427241715.1275298493545
0.3636.36567544261714.9786514694546
0.31640.01130755822815.0753508139794
0.32643.65171070956415.3653085930234
0.33647.3219815773815.7511801317376
0.34651.03735783210416.1263800614164
0.35654.79213643737916.3971783202328
0.36658.563566214816.5039527263759
0.37662.3189900368616.4245584614832
0.38666.02414267018216.1776122853333
0.39669.65068137663915.8116357804774
0.4673.18155671466315.391796823365
0.41676.61351799495714.9885644891751
0.42679.95671303773814.6641008350463
0.43683.23186160159114.4603631660006
0.44686.4658009975114.3936834323223
0.45689.68632672895514.4556030850899
0.46692.91722141295914.6122336449127
0.47696.17422732115714.8155096408568
0.48699.46250302569415.008062452201
0.49702.77583153604615.1331623095612
0.5706.09753910191415.1463294473091
0.51709.40278548575315.0172471624191
0.52712.66166601911714.7315470491254
0.53715.84249285395714.2926862525976
0.54718.91473304711213.7152802711517
0.55721.85134525271213.022215548055
0.56724.63057586333712.2421948849281
0.57727.23751078340311.4064737579454
0.58729.66570951009710.552343849134
0.59731.9190312392839.7265462546886
0.6734.0133700797838.98477280771382
0.61735.977623219338.38914139155831
0.62737.8530385235338.00525358677288
0.63739.6902901699597.87797503470102
0.64741.5442333549398.01884239404273
0.65743.4671275264268.39493257009554
0.66745.501878935038.93266180233544
0.67747.6771921952819.54398288284904
0.68750.00621668521110.145967961373
0.69752.48935864288210.6863227710246
0.7755.12070991057911.1515649536144
0.71757.89648379142111.5707807666415
0.72760.82335259561312.0083817304593
0.73763.92478455161712.5459688316259
0.74767.24416413739213.2652992428342
0.75770.84420721573214.2353267481823
0.76774.80256504551415.4958327973447
0.77779.20351075022317.0480292647393
0.78784.12563155895618.8403111459184
0.79789.62616774516220.7570713910324
0.8795.72445583065422.6220703826262
0.81802.38947186545724.2161139138754
0.82809.53837312609925.3347500113782
0.83817.05242733929825.852997109815
0.84824.81295926406225.8024413114751
0.85832.75445680578825.4128222454369
0.86840.92858953061925.1143657397723
0.87849.57470556078225.5102947436561
0.88859.19618188234127.3524228638945
0.89870.63454070115331.5144176007572
0.9885.09781565935638.822496795245
0.91904.03996393739949.5094424625889
0.92928.75865569433162.3661783231952
0.93959.67813413840574.1601213614192
0.94995.56235479026380.1936958024722
0.951033.2457021747376.4570803370019
0.961068.701880216362.5458742503605
0.971100.4462463114844.0643049290632
0.981135.0064831143937.9057548078551
0.991183.8191375065868.0829013248553


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Bezoeker in Ieper ; par3 = Aantal bezoekers stad Ieper ; par4 = 12 ;
Parameters (R input):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
R code (references can be found in the software module):
par3 <- '0.1'
par2 <- '0.99'
par1 <- '0.10'
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')