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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 computationTue, 28 Jul 2009 02:19:34 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Jul/28/t1248769242r8bgd85n5418niu.htm/, Retrieved Sat, 18 May 2024 17:55:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=42406, Retrieved Sat, 18 May 2024 17:55:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact207

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Harrell-Davis Quantiles] [Decielen Aantal O...] [2009-07-28 08:12:34] [3277f4fd1367f73c9bc433502ffbb1d3]
-   P     [Harrell-Davis Quantiles] [] [2009-07-28 08:19:34] [b5b38cb8cda4101c154c09cb859ab89a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6430
5124
4836
4629
4597
4490
4517
4560
4135
4559
4739
4886
5605
4616
4997
4607
4882
4555
4462
4476
4277
4369
4492
5183
6039
4923
4953
4892
4614
4363
4675
4556
4217
4664
4601
5428
5607
4869
5174
5031
4671
4491
4504
4615
4582
4800
4775
5791
5818
4714
4915
4598
4407
4383
4412
4274
4236
4637
4534
5271
5467
5204
5752
4724
4623
4451
4138
4140
4169
4603
4434
5185

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42406&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42406&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42406&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Harrell-Davis Quantiles
quantilesvaluestandard error
0.014137.140899533696.20581061547489
0.024142.5243409959915.1900753683906
0.034152.0328422645827.3844856271183
0.044165.8309959471739.4121963188005
0.054183.2687461027649.072986383226
0.064203.2215719805455.9104591260618
0.074224.5501622380460.5713200671163
0.084246.3743053620863.8072130541721
0.094268.1067032978765.9444632887688
0.14289.3571046977166.8896212698728
0.114309.830606576166.4669117402375
0.124329.2804626518964.6806293806098
0.134347.5126453599661.8213261398107
0.144364.4102679257158.3571188710928
0.154379.9483532462754.7733615394797
0.164394.1864789874851.4317059492449
0.174407.2431387309448.5176922265047
0.184419.2636980036446.0344305188984
0.194430.3933956733643.911938371902
0.24440.7616138078042.0534146478019
0.214450.4777217843240.3952521615131
0.224459.6348100911938.9305749633831
0.234468.3163220160137.6906616284068
0.244476.6014238186836.7333892006289
0.254484.5668687269736.0725948779191
0.264492.285120385835.7253169513485
0.274499.8199649005935.6258146706672
0.284507.2214986445935.6860347030577
0.294514.52227782535.7952868019603
0.34521.7357919951335.8464764713773
0.314528.8575909791135.7458462120354
0.324535.8686464030635.4404079063491
0.334542.7400660415534.9103252551978
0.344549.4381732526734.1575826475628
0.354555.9291622310833.1928063173789
0.364562.1829062393632.0550332650814
0.374568.1758702455130.7845842386588
0.384573.8933348504829.4293322576541
0.394579.3312173350528.0462697686282
0.44584.4976944658926.7024884683067
0.414589.4146594171725.4690736868954
0.424594.1188683906224.4489646844059
0.434598.6625219724723.7343163332739
0.444603.1130164180623.4274025609145
0.454607.5516858240523.6245977168507
0.464612.0715033752624.3861833852497
0.474616.7738721390625.7591956345592
0.484621.7647702771527.7415202478057
0.494627.1505925120330.3097304254556
0.54633.0340365280433.4117114532716
0.514639.510322764636.9850192191178
0.524646.663924702240.9451163762109
0.534654.5658501682545.2079272085711
0.544663.2713854458749.6912208523154
0.554672.8181292801454.2758719288066
0.564683.2241363413158.8794959235409
0.574694.4860805455563.3622017893964
0.584706.5775375841867.6136864674015
0.594719.4477439404271.4931663590656
0.64733.0214570706274.8602588690059
0.614747.200735574677.590252239613
0.624761.8694896288779.5888772827736
0.634776.9014479929180.7834549493395
0.644792.1717176444181.2001947114707
0.654807.5714061651880.9266506212652
0.664823.0239349014680.1632524506108
0.674838.5008523838379.1945032887463
0.684854.0343582985578.3950789100073
0.694869.7235659325378.1654405449567
0.74885.7319272733878.8891291833031
0.714902.2743110870780.8561484198411
0.724919.5939492171284.1721973503675
0.734937.9317043667188.7244193068077
0.744957.4925492405894.1749282237735
0.754978.41627285367100.030093052579
0.765000.76055315635105.731170034215
0.775024.50387807253110.751221591915
0.785049.57271893048114.759806447627
0.795075.89170577613117.723364658762
0.85103.44804124129119.990121542888
0.815132.35385158615122.286949863258
0.825162.88540632758125.560892576431
0.835195.47915725043130.690751363579
0.845230.67326980027138.098864680913
0.855268.9990444815147.458384682295
0.865310.8451006293157.680889596164
0.875356.33127169172167.164691276969
0.885405.23181859179174.226993453698
0.895456.97703661656177.533257331226
0.95510.74699564216176.384961462492
0.915565.66931664998170.828267498995
0.925621.16177189899161.676137271184
0.935677.51402695583150.733314982106
0.945736.82676295921141.723808656548
0.955804.28734951953141.617646034818
0.965889.15394341146159.473748227126
0.976003.17549092469200.320076642061
0.986151.62198994349261.689169612746
0.996313.83282413582332.54126582796

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 4137.14089953369 & 6.20581061547489 \tabularnewline
0.02 & 4142.52434099599 & 15.1900753683906 \tabularnewline
0.03 & 4152.03284226458 & 27.3844856271183 \tabularnewline
0.04 & 4165.83099594717 & 39.4121963188005 \tabularnewline
0.05 & 4183.26874610276 & 49.072986383226 \tabularnewline
0.06 & 4203.22157198054 & 55.9104591260618 \tabularnewline
0.07 & 4224.55016223804 & 60.5713200671163 \tabularnewline
0.08 & 4246.37430536208 & 63.8072130541721 \tabularnewline
0.09 & 4268.10670329787 & 65.9444632887688 \tabularnewline
0.1 & 4289.35710469771 & 66.8896212698728 \tabularnewline
0.11 & 4309.8306065761 & 66.4669117402375 \tabularnewline
0.12 & 4329.28046265189 & 64.6806293806098 \tabularnewline
0.13 & 4347.51264535996 & 61.8213261398107 \tabularnewline
0.14 & 4364.41026792571 & 58.3571188710928 \tabularnewline
0.15 & 4379.94835324627 & 54.7733615394797 \tabularnewline
0.16 & 4394.18647898748 & 51.4317059492449 \tabularnewline
0.17 & 4407.24313873094 & 48.5176922265047 \tabularnewline
0.18 & 4419.26369800364 & 46.0344305188984 \tabularnewline
0.19 & 4430.39339567336 & 43.911938371902 \tabularnewline
0.2 & 4440.76161380780 & 42.0534146478019 \tabularnewline
0.21 & 4450.47772178432 & 40.3952521615131 \tabularnewline
0.22 & 4459.63481009119 & 38.9305749633831 \tabularnewline
0.23 & 4468.31632201601 & 37.6906616284068 \tabularnewline
0.24 & 4476.60142381868 & 36.7333892006289 \tabularnewline
0.25 & 4484.56686872697 & 36.0725948779191 \tabularnewline
0.26 & 4492.2851203858 & 35.7253169513485 \tabularnewline
0.27 & 4499.81996490059 & 35.6258146706672 \tabularnewline
0.28 & 4507.22149864459 & 35.6860347030577 \tabularnewline
0.29 & 4514.522277825 & 35.7952868019603 \tabularnewline
0.3 & 4521.73579199513 & 35.8464764713773 \tabularnewline
0.31 & 4528.85759097911 & 35.7458462120354 \tabularnewline
0.32 & 4535.86864640306 & 35.4404079063491 \tabularnewline
0.33 & 4542.74006604155 & 34.9103252551978 \tabularnewline
0.34 & 4549.43817325267 & 34.1575826475628 \tabularnewline
0.35 & 4555.92916223108 & 33.1928063173789 \tabularnewline
0.36 & 4562.18290623936 & 32.0550332650814 \tabularnewline
0.37 & 4568.17587024551 & 30.7845842386588 \tabularnewline
0.38 & 4573.89333485048 & 29.4293322576541 \tabularnewline
0.39 & 4579.33121733505 & 28.0462697686282 \tabularnewline
0.4 & 4584.49769446589 & 26.7024884683067 \tabularnewline
0.41 & 4589.41465941717 & 25.4690736868954 \tabularnewline
0.42 & 4594.11886839062 & 24.4489646844059 \tabularnewline
0.43 & 4598.66252197247 & 23.7343163332739 \tabularnewline
0.44 & 4603.11301641806 & 23.4274025609145 \tabularnewline
0.45 & 4607.55168582405 & 23.6245977168507 \tabularnewline
0.46 & 4612.07150337526 & 24.3861833852497 \tabularnewline
0.47 & 4616.77387213906 & 25.7591956345592 \tabularnewline
0.48 & 4621.76477027715 & 27.7415202478057 \tabularnewline
0.49 & 4627.15059251203 & 30.3097304254556 \tabularnewline
0.5 & 4633.03403652804 & 33.4117114532716 \tabularnewline
0.51 & 4639.5103227646 & 36.9850192191178 \tabularnewline
0.52 & 4646.6639247022 & 40.9451163762109 \tabularnewline
0.53 & 4654.56585016825 & 45.2079272085711 \tabularnewline
0.54 & 4663.27138544587 & 49.6912208523154 \tabularnewline
0.55 & 4672.81812928014 & 54.2758719288066 \tabularnewline
0.56 & 4683.22413634131 & 58.8794959235409 \tabularnewline
0.57 & 4694.48608054555 & 63.3622017893964 \tabularnewline
0.58 & 4706.57753758418 & 67.6136864674015 \tabularnewline
0.59 & 4719.44774394042 & 71.4931663590656 \tabularnewline
0.6 & 4733.02145707062 & 74.8602588690059 \tabularnewline
0.61 & 4747.2007355746 & 77.590252239613 \tabularnewline
0.62 & 4761.86948962887 & 79.5888772827736 \tabularnewline
0.63 & 4776.90144799291 & 80.7834549493395 \tabularnewline
0.64 & 4792.17171764441 & 81.2001947114707 \tabularnewline
0.65 & 4807.57140616518 & 80.9266506212652 \tabularnewline
0.66 & 4823.02393490146 & 80.1632524506108 \tabularnewline
0.67 & 4838.50085238383 & 79.1945032887463 \tabularnewline
0.68 & 4854.03435829855 & 78.3950789100073 \tabularnewline
0.69 & 4869.72356593253 & 78.1654405449567 \tabularnewline
0.7 & 4885.73192727338 & 78.8891291833031 \tabularnewline
0.71 & 4902.27431108707 & 80.8561484198411 \tabularnewline
0.72 & 4919.59394921712 & 84.1721973503675 \tabularnewline
0.73 & 4937.93170436671 & 88.7244193068077 \tabularnewline
0.74 & 4957.49254924058 & 94.1749282237735 \tabularnewline
0.75 & 4978.41627285367 & 100.030093052579 \tabularnewline
0.76 & 5000.76055315635 & 105.731170034215 \tabularnewline
0.77 & 5024.50387807253 & 110.751221591915 \tabularnewline
0.78 & 5049.57271893048 & 114.759806447627 \tabularnewline
0.79 & 5075.89170577613 & 117.723364658762 \tabularnewline
0.8 & 5103.44804124129 & 119.990121542888 \tabularnewline
0.81 & 5132.35385158615 & 122.286949863258 \tabularnewline
0.82 & 5162.88540632758 & 125.560892576431 \tabularnewline
0.83 & 5195.47915725043 & 130.690751363579 \tabularnewline
0.84 & 5230.67326980027 & 138.098864680913 \tabularnewline
0.85 & 5268.9990444815 & 147.458384682295 \tabularnewline
0.86 & 5310.8451006293 & 157.680889596164 \tabularnewline
0.87 & 5356.33127169172 & 167.164691276969 \tabularnewline
0.88 & 5405.23181859179 & 174.226993453698 \tabularnewline
0.89 & 5456.97703661656 & 177.533257331226 \tabularnewline
0.9 & 5510.74699564216 & 176.384961462492 \tabularnewline
0.91 & 5565.66931664998 & 170.828267498995 \tabularnewline
0.92 & 5621.16177189899 & 161.676137271184 \tabularnewline
0.93 & 5677.51402695583 & 150.733314982106 \tabularnewline
0.94 & 5736.82676295921 & 141.723808656548 \tabularnewline
0.95 & 5804.28734951953 & 141.617646034818 \tabularnewline
0.96 & 5889.15394341146 & 159.473748227126 \tabularnewline
0.97 & 6003.17549092469 & 200.320076642061 \tabularnewline
0.98 & 6151.62198994349 & 261.689169612746 \tabularnewline
0.99 & 6313.83282413582 & 332.54126582796 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42406&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]4137.14089953369[/C][C]6.20581061547489[/C][/ROW]
[ROW][C]0.02[/C][C]4142.52434099599[/C][C]15.1900753683906[/C][/ROW]
[ROW][C]0.03[/C][C]4152.03284226458[/C][C]27.3844856271183[/C][/ROW]
[ROW][C]0.04[/C][C]4165.83099594717[/C][C]39.4121963188005[/C][/ROW]
[ROW][C]0.05[/C][C]4183.26874610276[/C][C]49.072986383226[/C][/ROW]
[ROW][C]0.06[/C][C]4203.22157198054[/C][C]55.9104591260618[/C][/ROW]
[ROW][C]0.07[/C][C]4224.55016223804[/C][C]60.5713200671163[/C][/ROW]
[ROW][C]0.08[/C][C]4246.37430536208[/C][C]63.8072130541721[/C][/ROW]
[ROW][C]0.09[/C][C]4268.10670329787[/C][C]65.9444632887688[/C][/ROW]
[ROW][C]0.1[/C][C]4289.35710469771[/C][C]66.8896212698728[/C][/ROW]
[ROW][C]0.11[/C][C]4309.8306065761[/C][C]66.4669117402375[/C][/ROW]
[ROW][C]0.12[/C][C]4329.28046265189[/C][C]64.6806293806098[/C][/ROW]
[ROW][C]0.13[/C][C]4347.51264535996[/C][C]61.8213261398107[/C][/ROW]
[ROW][C]0.14[/C][C]4364.41026792571[/C][C]58.3571188710928[/C][/ROW]
[ROW][C]0.15[/C][C]4379.94835324627[/C][C]54.7733615394797[/C][/ROW]
[ROW][C]0.16[/C][C]4394.18647898748[/C][C]51.4317059492449[/C][/ROW]
[ROW][C]0.17[/C][C]4407.24313873094[/C][C]48.5176922265047[/C][/ROW]
[ROW][C]0.18[/C][C]4419.26369800364[/C][C]46.0344305188984[/C][/ROW]
[ROW][C]0.19[/C][C]4430.39339567336[/C][C]43.911938371902[/C][/ROW]
[ROW][C]0.2[/C][C]4440.76161380780[/C][C]42.0534146478019[/C][/ROW]
[ROW][C]0.21[/C][C]4450.47772178432[/C][C]40.3952521615131[/C][/ROW]
[ROW][C]0.22[/C][C]4459.63481009119[/C][C]38.9305749633831[/C][/ROW]
[ROW][C]0.23[/C][C]4468.31632201601[/C][C]37.6906616284068[/C][/ROW]
[ROW][C]0.24[/C][C]4476.60142381868[/C][C]36.7333892006289[/C][/ROW]
[ROW][C]0.25[/C][C]4484.56686872697[/C][C]36.0725948779191[/C][/ROW]
[ROW][C]0.26[/C][C]4492.2851203858[/C][C]35.7253169513485[/C][/ROW]
[ROW][C]0.27[/C][C]4499.81996490059[/C][C]35.6258146706672[/C][/ROW]
[ROW][C]0.28[/C][C]4507.22149864459[/C][C]35.6860347030577[/C][/ROW]
[ROW][C]0.29[/C][C]4514.522277825[/C][C]35.7952868019603[/C][/ROW]
[ROW][C]0.3[/C][C]4521.73579199513[/C][C]35.8464764713773[/C][/ROW]
[ROW][C]0.31[/C][C]4528.85759097911[/C][C]35.7458462120354[/C][/ROW]
[ROW][C]0.32[/C][C]4535.86864640306[/C][C]35.4404079063491[/C][/ROW]
[ROW][C]0.33[/C][C]4542.74006604155[/C][C]34.9103252551978[/C][/ROW]
[ROW][C]0.34[/C][C]4549.43817325267[/C][C]34.1575826475628[/C][/ROW]
[ROW][C]0.35[/C][C]4555.92916223108[/C][C]33.1928063173789[/C][/ROW]
[ROW][C]0.36[/C][C]4562.18290623936[/C][C]32.0550332650814[/C][/ROW]
[ROW][C]0.37[/C][C]4568.17587024551[/C][C]30.7845842386588[/C][/ROW]
[ROW][C]0.38[/C][C]4573.89333485048[/C][C]29.4293322576541[/C][/ROW]
[ROW][C]0.39[/C][C]4579.33121733505[/C][C]28.0462697686282[/C][/ROW]
[ROW][C]0.4[/C][C]4584.49769446589[/C][C]26.7024884683067[/C][/ROW]
[ROW][C]0.41[/C][C]4589.41465941717[/C][C]25.4690736868954[/C][/ROW]
[ROW][C]0.42[/C][C]4594.11886839062[/C][C]24.4489646844059[/C][/ROW]
[ROW][C]0.43[/C][C]4598.66252197247[/C][C]23.7343163332739[/C][/ROW]
[ROW][C]0.44[/C][C]4603.11301641806[/C][C]23.4274025609145[/C][/ROW]
[ROW][C]0.45[/C][C]4607.55168582405[/C][C]23.6245977168507[/C][/ROW]
[ROW][C]0.46[/C][C]4612.07150337526[/C][C]24.3861833852497[/C][/ROW]
[ROW][C]0.47[/C][C]4616.77387213906[/C][C]25.7591956345592[/C][/ROW]
[ROW][C]0.48[/C][C]4621.76477027715[/C][C]27.7415202478057[/C][/ROW]
[ROW][C]0.49[/C][C]4627.15059251203[/C][C]30.3097304254556[/C][/ROW]
[ROW][C]0.5[/C][C]4633.03403652804[/C][C]33.4117114532716[/C][/ROW]
[ROW][C]0.51[/C][C]4639.5103227646[/C][C]36.9850192191178[/C][/ROW]
[ROW][C]0.52[/C][C]4646.6639247022[/C][C]40.9451163762109[/C][/ROW]
[ROW][C]0.53[/C][C]4654.56585016825[/C][C]45.2079272085711[/C][/ROW]
[ROW][C]0.54[/C][C]4663.27138544587[/C][C]49.6912208523154[/C][/ROW]
[ROW][C]0.55[/C][C]4672.81812928014[/C][C]54.2758719288066[/C][/ROW]
[ROW][C]0.56[/C][C]4683.22413634131[/C][C]58.8794959235409[/C][/ROW]
[ROW][C]0.57[/C][C]4694.48608054555[/C][C]63.3622017893964[/C][/ROW]
[ROW][C]0.58[/C][C]4706.57753758418[/C][C]67.6136864674015[/C][/ROW]
[ROW][C]0.59[/C][C]4719.44774394042[/C][C]71.4931663590656[/C][/ROW]
[ROW][C]0.6[/C][C]4733.02145707062[/C][C]74.8602588690059[/C][/ROW]
[ROW][C]0.61[/C][C]4747.2007355746[/C][C]77.590252239613[/C][/ROW]
[ROW][C]0.62[/C][C]4761.86948962887[/C][C]79.5888772827736[/C][/ROW]
[ROW][C]0.63[/C][C]4776.90144799291[/C][C]80.7834549493395[/C][/ROW]
[ROW][C]0.64[/C][C]4792.17171764441[/C][C]81.2001947114707[/C][/ROW]
[ROW][C]0.65[/C][C]4807.57140616518[/C][C]80.9266506212652[/C][/ROW]
[ROW][C]0.66[/C][C]4823.02393490146[/C][C]80.1632524506108[/C][/ROW]
[ROW][C]0.67[/C][C]4838.50085238383[/C][C]79.1945032887463[/C][/ROW]
[ROW][C]0.68[/C][C]4854.03435829855[/C][C]78.3950789100073[/C][/ROW]
[ROW][C]0.69[/C][C]4869.72356593253[/C][C]78.1654405449567[/C][/ROW]
[ROW][C]0.7[/C][C]4885.73192727338[/C][C]78.8891291833031[/C][/ROW]
[ROW][C]0.71[/C][C]4902.27431108707[/C][C]80.8561484198411[/C][/ROW]
[ROW][C]0.72[/C][C]4919.59394921712[/C][C]84.1721973503675[/C][/ROW]
[ROW][C]0.73[/C][C]4937.93170436671[/C][C]88.7244193068077[/C][/ROW]
[ROW][C]0.74[/C][C]4957.49254924058[/C][C]94.1749282237735[/C][/ROW]
[ROW][C]0.75[/C][C]4978.41627285367[/C][C]100.030093052579[/C][/ROW]
[ROW][C]0.76[/C][C]5000.76055315635[/C][C]105.731170034215[/C][/ROW]
[ROW][C]0.77[/C][C]5024.50387807253[/C][C]110.751221591915[/C][/ROW]
[ROW][C]0.78[/C][C]5049.57271893048[/C][C]114.759806447627[/C][/ROW]
[ROW][C]0.79[/C][C]5075.89170577613[/C][C]117.723364658762[/C][/ROW]
[ROW][C]0.8[/C][C]5103.44804124129[/C][C]119.990121542888[/C][/ROW]
[ROW][C]0.81[/C][C]5132.35385158615[/C][C]122.286949863258[/C][/ROW]
[ROW][C]0.82[/C][C]5162.88540632758[/C][C]125.560892576431[/C][/ROW]
[ROW][C]0.83[/C][C]5195.47915725043[/C][C]130.690751363579[/C][/ROW]
[ROW][C]0.84[/C][C]5230.67326980027[/C][C]138.098864680913[/C][/ROW]
[ROW][C]0.85[/C][C]5268.9990444815[/C][C]147.458384682295[/C][/ROW]
[ROW][C]0.86[/C][C]5310.8451006293[/C][C]157.680889596164[/C][/ROW]
[ROW][C]0.87[/C][C]5356.33127169172[/C][C]167.164691276969[/C][/ROW]
[ROW][C]0.88[/C][C]5405.23181859179[/C][C]174.226993453698[/C][/ROW]
[ROW][C]0.89[/C][C]5456.97703661656[/C][C]177.533257331226[/C][/ROW]
[ROW][C]0.9[/C][C]5510.74699564216[/C][C]176.384961462492[/C][/ROW]
[ROW][C]0.91[/C][C]5565.66931664998[/C][C]170.828267498995[/C][/ROW]
[ROW][C]0.92[/C][C]5621.16177189899[/C][C]161.676137271184[/C][/ROW]
[ROW][C]0.93[/C][C]5677.51402695583[/C][C]150.733314982106[/C][/ROW]
[ROW][C]0.94[/C][C]5736.82676295921[/C][C]141.723808656548[/C][/ROW]
[ROW][C]0.95[/C][C]5804.28734951953[/C][C]141.617646034818[/C][/ROW]
[ROW][C]0.96[/C][C]5889.15394341146[/C][C]159.473748227126[/C][/ROW]
[ROW][C]0.97[/C][C]6003.17549092469[/C][C]200.320076642061[/C][/ROW]
[ROW][C]0.98[/C][C]6151.62198994349[/C][C]261.689169612746[/C][/ROW]
[ROW][C]0.99[/C][C]6313.83282413582[/C][C]332.54126582796[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42406&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42406&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
0.014137.140899533696.20581061547489
0.024142.5243409959915.1900753683906
0.034152.0328422645827.3844856271183
0.044165.8309959471739.4121963188005
0.054183.2687461027649.072986383226
0.064203.2215719805455.9104591260618
0.074224.5501622380460.5713200671163
0.084246.3743053620863.8072130541721
0.094268.1067032978765.9444632887688
0.14289.3571046977166.8896212698728
0.114309.830606576166.4669117402375
0.124329.2804626518964.6806293806098
0.134347.5126453599661.8213261398107
0.144364.4102679257158.3571188710928
0.154379.9483532462754.7733615394797
0.164394.1864789874851.4317059492449
0.174407.2431387309448.5176922265047
0.184419.2636980036446.0344305188984
0.194430.3933956733643.911938371902
0.24440.7616138078042.0534146478019
0.214450.4777217843240.3952521615131
0.224459.6348100911938.9305749633831
0.234468.3163220160137.6906616284068
0.244476.6014238186836.7333892006289
0.254484.5668687269736.0725948779191
0.264492.285120385835.7253169513485
0.274499.8199649005935.6258146706672
0.284507.2214986445935.6860347030577
0.294514.52227782535.7952868019603
0.34521.7357919951335.8464764713773
0.314528.8575909791135.7458462120354
0.324535.8686464030635.4404079063491
0.334542.7400660415534.9103252551978
0.344549.4381732526734.1575826475628
0.354555.9291622310833.1928063173789
0.364562.1829062393632.0550332650814
0.374568.1758702455130.7845842386588
0.384573.8933348504829.4293322576541
0.394579.3312173350528.0462697686282
0.44584.4976944658926.7024884683067
0.414589.4146594171725.4690736868954
0.424594.1188683906224.4489646844059
0.434598.6625219724723.7343163332739
0.444603.1130164180623.4274025609145
0.454607.5516858240523.6245977168507
0.464612.0715033752624.3861833852497
0.474616.7738721390625.7591956345592
0.484621.7647702771527.7415202478057
0.494627.1505925120330.3097304254556
0.54633.0340365280433.4117114532716
0.514639.510322764636.9850192191178
0.524646.663924702240.9451163762109
0.534654.5658501682545.2079272085711
0.544663.2713854458749.6912208523154
0.554672.8181292801454.2758719288066
0.564683.2241363413158.8794959235409
0.574694.4860805455563.3622017893964
0.584706.5775375841867.6136864674015
0.594719.4477439404271.4931663590656
0.64733.0214570706274.8602588690059
0.614747.200735574677.590252239613
0.624761.8694896288779.5888772827736
0.634776.9014479929180.7834549493395
0.644792.1717176444181.2001947114707
0.654807.5714061651880.9266506212652
0.664823.0239349014680.1632524506108
0.674838.5008523838379.1945032887463
0.684854.0343582985578.3950789100073
0.694869.7235659325378.1654405449567
0.74885.7319272733878.8891291833031
0.714902.2743110870780.8561484198411
0.724919.5939492171284.1721973503675
0.734937.9317043667188.7244193068077
0.744957.4925492405894.1749282237735
0.754978.41627285367100.030093052579
0.765000.76055315635105.731170034215
0.775024.50387807253110.751221591915
0.785049.57271893048114.759806447627
0.795075.89170577613117.723364658762
0.85103.44804124129119.990121542888
0.815132.35385158615122.286949863258
0.825162.88540632758125.560892576431
0.835195.47915725043130.690751363579
0.845230.67326980027138.098864680913
0.855268.9990444815147.458384682295
0.865310.8451006293157.680889596164
0.875356.33127169172167.164691276969
0.885405.23181859179174.226993453698
0.895456.97703661656177.533257331226
0.95510.74699564216176.384961462492
0.915565.66931664998170.828267498995
0.925621.16177189899161.676137271184
0.935677.51402695583150.733314982106
0.945736.82676295921141.723808656548
0.955804.28734951953141.617646034818
0.965889.15394341146159.473748227126
0.976003.17549092469200.320076642061
0.986151.62198994349261.689169612746
0.996313.83282413582332.54126582796


Figures (Output of Computation)

Input Parameters & R Code

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')