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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 computationThu, 12 Mar 2009 06:21:54 -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/Mar/12/t1236860556ftf8e3appeapmrx.htm/, Retrieved Thu, 02 May 2024 12:46:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=38980, Retrieved Thu, 02 May 2024 12:46:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact165

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] [Harrel-Davis deci...] [2009-03-12 11:58:27] [b92d8e33f38b56c8010fa2bf0795e6cd]
-   PD    [Harrell-Davis Quantiles] [Harrell-Davis per...] [2009-03-12 12:21:54] [8c726525c89fb87c09aaacaddee1db18] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
104.9
110.9
104.8
94.1
95.8
99.3
101.1
104.0
99.0
105.4
107.1
110.7
117.1
118.7
126.5
127.5
134.6
131.8
135.9
142.7
141.7
153.4
145.0
137.7
148.3
152.2
169.4
168.6
161.1
174.1
179.0
190.6
190.0
181.6
174.8
180.5
196.8
193.8
197.0
216.3
221.4
217.9
229.7
227.4
204.2
196.6
198.8
207.5
190.7
201.6
210.5
223.5
223.8
231.2
244.0
234.7
250.2
265.7
287.6
283.3
295.4
312.3
333.8
347.7
383.2
407.1
413.6
362.7
321.9
239.4
191.0
159.7
166.7

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=38980&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=38980&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=38980&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0194.82023249766211.94897534959023
0.0296.01743830253652.29965541509062
0.0397.37555196086442.47991908579631
0.0498.70366140292972.55580820929196
0.0599.94441891097182.64672187067251
0.06101.1047301429392.75466970979708
0.07102.2074637485332.85681633673199
0.08103.2773598264142.99112373204651
0.09104.3444845683663.24209720636071
0.1105.4483069980173.68034281398456
0.11106.6351038083544.32043191128926
0.12107.9499366373955.12427603015918
0.13109.4277297932686.0260424105968
0.14111.0870746403606.95123784965671
0.15112.9280881337877.82908464937439
0.16114.9338747277278.59940104250815
0.17117.0743953212729.2182237892858
0.18119.3115309350229.66112185999803
0.19121.6043895572449.92515129813151
0.2123.91416747803110.0270168886593
0.21126.2080731517469.99915600746624
0.22128.4619884646249.8852884688437
0.23130.6617206935359.73270957994096
0.24132.8028909152199.58640553721076
0.25134.8896803495529.48333348485796
0.26136.9327779381119.44946470726675
0.27138.9469198068369.49670604166977
0.28140.9483878174219.62468608078925
0.29142.9527619798499.8225681086672
0.3144.97312779753010.0709891597320
0.31147.01884750070710.3470477833848
0.32149.09492627390410.6257956220346
0.33151.20194392383210.8841082357747
0.34153.33647612848911.1024783609105
0.35155.49189362542811.2666099375409
0.36157.65940098370311.3688365916637
0.37159.82916087817811.4076858816658
0.38161.99134913318611.3878352856806
0.39164.13700401256411.3173639921522
0.4166.25857125448911.2075492678430
0.41168.35010069374611.0685640992989
0.42170.40711295475810.909277675891
0.43172.42621449726610.7343687561077
0.44174.40458451696410.545037192238
0.45176.33947839265310.3385931531772
0.46178.22788480213310.1105350953987
0.47180.0664386328899.85594829762519
0.48181.8516366175429.57334480308896
0.49183.5803386983899.26417200266066
0.5185.2504784536118.93555948028845
0.51186.8618619274738.60002682752121
0.52188.4169132219518.2755251199683
0.53189.9212291507847.98284864985737
0.54191.3838309350047.74444022082646
0.55192.8170416822217.58142774175128
0.56194.2359664902517.51040604246408
0.57195.6576007367637.54099000678739
0.58197.0996369449897.6744237499671
0.59198.5790791080437.90136322687483
0.6200.1108040188838.20440892921583
0.61201.7062300614328.55758467877004
0.62203.3722619001558.93031891265969
0.63205.1106704868989.2910260266783
0.64206.91803832159.6090658497643
0.65208.7863492340739.85926687903099
0.66210.7042339375410.0253081077468
0.67212.65880615824410.1021418672663
0.68214.63795194070610.0972062513581
0.69216.63287982877710.03203335763
0.7218.6407111356829.9417118402201
0.71220.6668883654179.87200170511472
0.72222.7271968476699.8780141031298
0.73224.84921249731310.0203588808968
0.74227.07298890858910.3594530380757
0.75229.45077152069810.9501781535227
0.76232.04548946361911.8332398845100
0.77234.92777013470913.0287209599280
0.78238.17131332706214.5277088069074
0.79241.84671329439116.2871428665131
0.8246.01424462134918.2275048928961
0.81250.71665636391520.2371786997449
0.82255.97346611701222.1826556599358
0.83261.77836401729223.9291576427541
0.84268.1009265739225.3638483212584
0.85274.89289635372826.4181570490565
0.86282.09808836929327.0799289985247
0.87289.66404870745127.3905289746052
0.88297.553408654327.4280742092355
0.89305.75358120581627.2867596699853
0.9314.28456568732127.0605717541866
0.91323.20509314329326.8399567790036
0.92332.61571594456326.7097370472072
0.93342.65225181504226.7318430718795
0.94353.45379389816726.8902981949929
0.95365.08026697087926.974886448394
0.96377.35935598167226.4007058135568
0.97389.68476104077624.0983621538877
0.98400.87589420229918.9691661760214
0.99409.30996337512111.6232909783428

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 94.8202324976621 & 1.94897534959023 \tabularnewline
0.02 & 96.0174383025365 & 2.29965541509062 \tabularnewline
0.03 & 97.3755519608644 & 2.47991908579631 \tabularnewline
0.04 & 98.7036614029297 & 2.55580820929196 \tabularnewline
0.05 & 99.9444189109718 & 2.64672187067251 \tabularnewline
0.06 & 101.104730142939 & 2.75466970979708 \tabularnewline
0.07 & 102.207463748533 & 2.85681633673199 \tabularnewline
0.08 & 103.277359826414 & 2.99112373204651 \tabularnewline
0.09 & 104.344484568366 & 3.24209720636071 \tabularnewline
0.1 & 105.448306998017 & 3.68034281398456 \tabularnewline
0.11 & 106.635103808354 & 4.32043191128926 \tabularnewline
0.12 & 107.949936637395 & 5.12427603015918 \tabularnewline
0.13 & 109.427729793268 & 6.0260424105968 \tabularnewline
0.14 & 111.087074640360 & 6.95123784965671 \tabularnewline
0.15 & 112.928088133787 & 7.82908464937439 \tabularnewline
0.16 & 114.933874727727 & 8.59940104250815 \tabularnewline
0.17 & 117.074395321272 & 9.2182237892858 \tabularnewline
0.18 & 119.311530935022 & 9.66112185999803 \tabularnewline
0.19 & 121.604389557244 & 9.92515129813151 \tabularnewline
0.2 & 123.914167478031 & 10.0270168886593 \tabularnewline
0.21 & 126.208073151746 & 9.99915600746624 \tabularnewline
0.22 & 128.461988464624 & 9.8852884688437 \tabularnewline
0.23 & 130.661720693535 & 9.73270957994096 \tabularnewline
0.24 & 132.802890915219 & 9.58640553721076 \tabularnewline
0.25 & 134.889680349552 & 9.48333348485796 \tabularnewline
0.26 & 136.932777938111 & 9.44946470726675 \tabularnewline
0.27 & 138.946919806836 & 9.49670604166977 \tabularnewline
0.28 & 140.948387817421 & 9.62468608078925 \tabularnewline
0.29 & 142.952761979849 & 9.8225681086672 \tabularnewline
0.3 & 144.973127797530 & 10.0709891597320 \tabularnewline
0.31 & 147.018847500707 & 10.3470477833848 \tabularnewline
0.32 & 149.094926273904 & 10.6257956220346 \tabularnewline
0.33 & 151.201943923832 & 10.8841082357747 \tabularnewline
0.34 & 153.336476128489 & 11.1024783609105 \tabularnewline
0.35 & 155.491893625428 & 11.2666099375409 \tabularnewline
0.36 & 157.659400983703 & 11.3688365916637 \tabularnewline
0.37 & 159.829160878178 & 11.4076858816658 \tabularnewline
0.38 & 161.991349133186 & 11.3878352856806 \tabularnewline
0.39 & 164.137004012564 & 11.3173639921522 \tabularnewline
0.4 & 166.258571254489 & 11.2075492678430 \tabularnewline
0.41 & 168.350100693746 & 11.0685640992989 \tabularnewline
0.42 & 170.407112954758 & 10.909277675891 \tabularnewline
0.43 & 172.426214497266 & 10.7343687561077 \tabularnewline
0.44 & 174.404584516964 & 10.545037192238 \tabularnewline
0.45 & 176.339478392653 & 10.3385931531772 \tabularnewline
0.46 & 178.227884802133 & 10.1105350953987 \tabularnewline
0.47 & 180.066438632889 & 9.85594829762519 \tabularnewline
0.48 & 181.851636617542 & 9.57334480308896 \tabularnewline
0.49 & 183.580338698389 & 9.26417200266066 \tabularnewline
0.5 & 185.250478453611 & 8.93555948028845 \tabularnewline
0.51 & 186.861861927473 & 8.60002682752121 \tabularnewline
0.52 & 188.416913221951 & 8.2755251199683 \tabularnewline
0.53 & 189.921229150784 & 7.98284864985737 \tabularnewline
0.54 & 191.383830935004 & 7.74444022082646 \tabularnewline
0.55 & 192.817041682221 & 7.58142774175128 \tabularnewline
0.56 & 194.235966490251 & 7.51040604246408 \tabularnewline
0.57 & 195.657600736763 & 7.54099000678739 \tabularnewline
0.58 & 197.099636944989 & 7.6744237499671 \tabularnewline
0.59 & 198.579079108043 & 7.90136322687483 \tabularnewline
0.6 & 200.110804018883 & 8.20440892921583 \tabularnewline
0.61 & 201.706230061432 & 8.55758467877004 \tabularnewline
0.62 & 203.372261900155 & 8.93031891265969 \tabularnewline
0.63 & 205.110670486898 & 9.2910260266783 \tabularnewline
0.64 & 206.9180383215 & 9.6090658497643 \tabularnewline
0.65 & 208.786349234073 & 9.85926687903099 \tabularnewline
0.66 & 210.70423393754 & 10.0253081077468 \tabularnewline
0.67 & 212.658806158244 & 10.1021418672663 \tabularnewline
0.68 & 214.637951940706 & 10.0972062513581 \tabularnewline
0.69 & 216.632879828777 & 10.03203335763 \tabularnewline
0.7 & 218.640711135682 & 9.9417118402201 \tabularnewline
0.71 & 220.666888365417 & 9.87200170511472 \tabularnewline
0.72 & 222.727196847669 & 9.8780141031298 \tabularnewline
0.73 & 224.849212497313 & 10.0203588808968 \tabularnewline
0.74 & 227.072988908589 & 10.3594530380757 \tabularnewline
0.75 & 229.450771520698 & 10.9501781535227 \tabularnewline
0.76 & 232.045489463619 & 11.8332398845100 \tabularnewline
0.77 & 234.927770134709 & 13.0287209599280 \tabularnewline
0.78 & 238.171313327062 & 14.5277088069074 \tabularnewline
0.79 & 241.846713294391 & 16.2871428665131 \tabularnewline
0.8 & 246.014244621349 & 18.2275048928961 \tabularnewline
0.81 & 250.716656363915 & 20.2371786997449 \tabularnewline
0.82 & 255.973466117012 & 22.1826556599358 \tabularnewline
0.83 & 261.778364017292 & 23.9291576427541 \tabularnewline
0.84 & 268.10092657392 & 25.3638483212584 \tabularnewline
0.85 & 274.892896353728 & 26.4181570490565 \tabularnewline
0.86 & 282.098088369293 & 27.0799289985247 \tabularnewline
0.87 & 289.664048707451 & 27.3905289746052 \tabularnewline
0.88 & 297.5534086543 & 27.4280742092355 \tabularnewline
0.89 & 305.753581205816 & 27.2867596699853 \tabularnewline
0.9 & 314.284565687321 & 27.0605717541866 \tabularnewline
0.91 & 323.205093143293 & 26.8399567790036 \tabularnewline
0.92 & 332.615715944563 & 26.7097370472072 \tabularnewline
0.93 & 342.652251815042 & 26.7318430718795 \tabularnewline
0.94 & 353.453793898167 & 26.8902981949929 \tabularnewline
0.95 & 365.080266970879 & 26.974886448394 \tabularnewline
0.96 & 377.359355981672 & 26.4007058135568 \tabularnewline
0.97 & 389.684761040776 & 24.0983621538877 \tabularnewline
0.98 & 400.875894202299 & 18.9691661760214 \tabularnewline
0.99 & 409.309963375121 & 11.6232909783428 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=38980&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]94.8202324976621[/C][C]1.94897534959023[/C][/ROW]
[ROW][C]0.02[/C][C]96.0174383025365[/C][C]2.29965541509062[/C][/ROW]
[ROW][C]0.03[/C][C]97.3755519608644[/C][C]2.47991908579631[/C][/ROW]
[ROW][C]0.04[/C][C]98.7036614029297[/C][C]2.55580820929196[/C][/ROW]
[ROW][C]0.05[/C][C]99.9444189109718[/C][C]2.64672187067251[/C][/ROW]
[ROW][C]0.06[/C][C]101.104730142939[/C][C]2.75466970979708[/C][/ROW]
[ROW][C]0.07[/C][C]102.207463748533[/C][C]2.85681633673199[/C][/ROW]
[ROW][C]0.08[/C][C]103.277359826414[/C][C]2.99112373204651[/C][/ROW]
[ROW][C]0.09[/C][C]104.344484568366[/C][C]3.24209720636071[/C][/ROW]
[ROW][C]0.1[/C][C]105.448306998017[/C][C]3.68034281398456[/C][/ROW]
[ROW][C]0.11[/C][C]106.635103808354[/C][C]4.32043191128926[/C][/ROW]
[ROW][C]0.12[/C][C]107.949936637395[/C][C]5.12427603015918[/C][/ROW]
[ROW][C]0.13[/C][C]109.427729793268[/C][C]6.0260424105968[/C][/ROW]
[ROW][C]0.14[/C][C]111.087074640360[/C][C]6.95123784965671[/C][/ROW]
[ROW][C]0.15[/C][C]112.928088133787[/C][C]7.82908464937439[/C][/ROW]
[ROW][C]0.16[/C][C]114.933874727727[/C][C]8.59940104250815[/C][/ROW]
[ROW][C]0.17[/C][C]117.074395321272[/C][C]9.2182237892858[/C][/ROW]
[ROW][C]0.18[/C][C]119.311530935022[/C][C]9.66112185999803[/C][/ROW]
[ROW][C]0.19[/C][C]121.604389557244[/C][C]9.92515129813151[/C][/ROW]
[ROW][C]0.2[/C][C]123.914167478031[/C][C]10.0270168886593[/C][/ROW]
[ROW][C]0.21[/C][C]126.208073151746[/C][C]9.99915600746624[/C][/ROW]
[ROW][C]0.22[/C][C]128.461988464624[/C][C]9.8852884688437[/C][/ROW]
[ROW][C]0.23[/C][C]130.661720693535[/C][C]9.73270957994096[/C][/ROW]
[ROW][C]0.24[/C][C]132.802890915219[/C][C]9.58640553721076[/C][/ROW]
[ROW][C]0.25[/C][C]134.889680349552[/C][C]9.48333348485796[/C][/ROW]
[ROW][C]0.26[/C][C]136.932777938111[/C][C]9.44946470726675[/C][/ROW]
[ROW][C]0.27[/C][C]138.946919806836[/C][C]9.49670604166977[/C][/ROW]
[ROW][C]0.28[/C][C]140.948387817421[/C][C]9.62468608078925[/C][/ROW]
[ROW][C]0.29[/C][C]142.952761979849[/C][C]9.8225681086672[/C][/ROW]
[ROW][C]0.3[/C][C]144.973127797530[/C][C]10.0709891597320[/C][/ROW]
[ROW][C]0.31[/C][C]147.018847500707[/C][C]10.3470477833848[/C][/ROW]
[ROW][C]0.32[/C][C]149.094926273904[/C][C]10.6257956220346[/C][/ROW]
[ROW][C]0.33[/C][C]151.201943923832[/C][C]10.8841082357747[/C][/ROW]
[ROW][C]0.34[/C][C]153.336476128489[/C][C]11.1024783609105[/C][/ROW]
[ROW][C]0.35[/C][C]155.491893625428[/C][C]11.2666099375409[/C][/ROW]
[ROW][C]0.36[/C][C]157.659400983703[/C][C]11.3688365916637[/C][/ROW]
[ROW][C]0.37[/C][C]159.829160878178[/C][C]11.4076858816658[/C][/ROW]
[ROW][C]0.38[/C][C]161.991349133186[/C][C]11.3878352856806[/C][/ROW]
[ROW][C]0.39[/C][C]164.137004012564[/C][C]11.3173639921522[/C][/ROW]
[ROW][C]0.4[/C][C]166.258571254489[/C][C]11.2075492678430[/C][/ROW]
[ROW][C]0.41[/C][C]168.350100693746[/C][C]11.0685640992989[/C][/ROW]
[ROW][C]0.42[/C][C]170.407112954758[/C][C]10.909277675891[/C][/ROW]
[ROW][C]0.43[/C][C]172.426214497266[/C][C]10.7343687561077[/C][/ROW]
[ROW][C]0.44[/C][C]174.404584516964[/C][C]10.545037192238[/C][/ROW]
[ROW][C]0.45[/C][C]176.339478392653[/C][C]10.3385931531772[/C][/ROW]
[ROW][C]0.46[/C][C]178.227884802133[/C][C]10.1105350953987[/C][/ROW]
[ROW][C]0.47[/C][C]180.066438632889[/C][C]9.85594829762519[/C][/ROW]
[ROW][C]0.48[/C][C]181.851636617542[/C][C]9.57334480308896[/C][/ROW]
[ROW][C]0.49[/C][C]183.580338698389[/C][C]9.26417200266066[/C][/ROW]
[ROW][C]0.5[/C][C]185.250478453611[/C][C]8.93555948028845[/C][/ROW]
[ROW][C]0.51[/C][C]186.861861927473[/C][C]8.60002682752121[/C][/ROW]
[ROW][C]0.52[/C][C]188.416913221951[/C][C]8.2755251199683[/C][/ROW]
[ROW][C]0.53[/C][C]189.921229150784[/C][C]7.98284864985737[/C][/ROW]
[ROW][C]0.54[/C][C]191.383830935004[/C][C]7.74444022082646[/C][/ROW]
[ROW][C]0.55[/C][C]192.817041682221[/C][C]7.58142774175128[/C][/ROW]
[ROW][C]0.56[/C][C]194.235966490251[/C][C]7.51040604246408[/C][/ROW]
[ROW][C]0.57[/C][C]195.657600736763[/C][C]7.54099000678739[/C][/ROW]
[ROW][C]0.58[/C][C]197.099636944989[/C][C]7.6744237499671[/C][/ROW]
[ROW][C]0.59[/C][C]198.579079108043[/C][C]7.90136322687483[/C][/ROW]
[ROW][C]0.6[/C][C]200.110804018883[/C][C]8.20440892921583[/C][/ROW]
[ROW][C]0.61[/C][C]201.706230061432[/C][C]8.55758467877004[/C][/ROW]
[ROW][C]0.62[/C][C]203.372261900155[/C][C]8.93031891265969[/C][/ROW]
[ROW][C]0.63[/C][C]205.110670486898[/C][C]9.2910260266783[/C][/ROW]
[ROW][C]0.64[/C][C]206.9180383215[/C][C]9.6090658497643[/C][/ROW]
[ROW][C]0.65[/C][C]208.786349234073[/C][C]9.85926687903099[/C][/ROW]
[ROW][C]0.66[/C][C]210.70423393754[/C][C]10.0253081077468[/C][/ROW]
[ROW][C]0.67[/C][C]212.658806158244[/C][C]10.1021418672663[/C][/ROW]
[ROW][C]0.68[/C][C]214.637951940706[/C][C]10.0972062513581[/C][/ROW]
[ROW][C]0.69[/C][C]216.632879828777[/C][C]10.03203335763[/C][/ROW]
[ROW][C]0.7[/C][C]218.640711135682[/C][C]9.9417118402201[/C][/ROW]
[ROW][C]0.71[/C][C]220.666888365417[/C][C]9.87200170511472[/C][/ROW]
[ROW][C]0.72[/C][C]222.727196847669[/C][C]9.8780141031298[/C][/ROW]
[ROW][C]0.73[/C][C]224.849212497313[/C][C]10.0203588808968[/C][/ROW]
[ROW][C]0.74[/C][C]227.072988908589[/C][C]10.3594530380757[/C][/ROW]
[ROW][C]0.75[/C][C]229.450771520698[/C][C]10.9501781535227[/C][/ROW]
[ROW][C]0.76[/C][C]232.045489463619[/C][C]11.8332398845100[/C][/ROW]
[ROW][C]0.77[/C][C]234.927770134709[/C][C]13.0287209599280[/C][/ROW]
[ROW][C]0.78[/C][C]238.171313327062[/C][C]14.5277088069074[/C][/ROW]
[ROW][C]0.79[/C][C]241.846713294391[/C][C]16.2871428665131[/C][/ROW]
[ROW][C]0.8[/C][C]246.014244621349[/C][C]18.2275048928961[/C][/ROW]
[ROW][C]0.81[/C][C]250.716656363915[/C][C]20.2371786997449[/C][/ROW]
[ROW][C]0.82[/C][C]255.973466117012[/C][C]22.1826556599358[/C][/ROW]
[ROW][C]0.83[/C][C]261.778364017292[/C][C]23.9291576427541[/C][/ROW]
[ROW][C]0.84[/C][C]268.10092657392[/C][C]25.3638483212584[/C][/ROW]
[ROW][C]0.85[/C][C]274.892896353728[/C][C]26.4181570490565[/C][/ROW]
[ROW][C]0.86[/C][C]282.098088369293[/C][C]27.0799289985247[/C][/ROW]
[ROW][C]0.87[/C][C]289.664048707451[/C][C]27.3905289746052[/C][/ROW]
[ROW][C]0.88[/C][C]297.5534086543[/C][C]27.4280742092355[/C][/ROW]
[ROW][C]0.89[/C][C]305.753581205816[/C][C]27.2867596699853[/C][/ROW]
[ROW][C]0.9[/C][C]314.284565687321[/C][C]27.0605717541866[/C][/ROW]
[ROW][C]0.91[/C][C]323.205093143293[/C][C]26.8399567790036[/C][/ROW]
[ROW][C]0.92[/C][C]332.615715944563[/C][C]26.7097370472072[/C][/ROW]
[ROW][C]0.93[/C][C]342.652251815042[/C][C]26.7318430718795[/C][/ROW]
[ROW][C]0.94[/C][C]353.453793898167[/C][C]26.8902981949929[/C][/ROW]
[ROW][C]0.95[/C][C]365.080266970879[/C][C]26.974886448394[/C][/ROW]
[ROW][C]0.96[/C][C]377.359355981672[/C][C]26.4007058135568[/C][/ROW]
[ROW][C]0.97[/C][C]389.684761040776[/C][C]24.0983621538877[/C][/ROW]
[ROW][C]0.98[/C][C]400.875894202299[/C][C]18.9691661760214[/C][/ROW]
[ROW][C]0.99[/C][C]409.309963375121[/C][C]11.6232909783428[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=38980&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=38980&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
0.0194.82023249766211.94897534959023
0.0296.01743830253652.29965541509062
0.0397.37555196086442.47991908579631
0.0498.70366140292972.55580820929196
0.0599.94441891097182.64672187067251
0.06101.1047301429392.75466970979708
0.07102.2074637485332.85681633673199
0.08103.2773598264142.99112373204651
0.09104.3444845683663.24209720636071
0.1105.4483069980173.68034281398456
0.11106.6351038083544.32043191128926
0.12107.9499366373955.12427603015918
0.13109.4277297932686.0260424105968
0.14111.0870746403606.95123784965671
0.15112.9280881337877.82908464937439
0.16114.9338747277278.59940104250815
0.17117.0743953212729.2182237892858
0.18119.3115309350229.66112185999803
0.19121.6043895572449.92515129813151
0.2123.91416747803110.0270168886593
0.21126.2080731517469.99915600746624
0.22128.4619884646249.8852884688437
0.23130.6617206935359.73270957994096
0.24132.8028909152199.58640553721076
0.25134.8896803495529.48333348485796
0.26136.9327779381119.44946470726675
0.27138.9469198068369.49670604166977
0.28140.9483878174219.62468608078925
0.29142.9527619798499.8225681086672
0.3144.97312779753010.0709891597320
0.31147.01884750070710.3470477833848
0.32149.09492627390410.6257956220346
0.33151.20194392383210.8841082357747
0.34153.33647612848911.1024783609105
0.35155.49189362542811.2666099375409
0.36157.65940098370311.3688365916637
0.37159.82916087817811.4076858816658
0.38161.99134913318611.3878352856806
0.39164.13700401256411.3173639921522
0.4166.25857125448911.2075492678430
0.41168.35010069374611.0685640992989
0.42170.40711295475810.909277675891
0.43172.42621449726610.7343687561077
0.44174.40458451696410.545037192238
0.45176.33947839265310.3385931531772
0.46178.22788480213310.1105350953987
0.47180.0664386328899.85594829762519
0.48181.8516366175429.57334480308896
0.49183.5803386983899.26417200266066
0.5185.2504784536118.93555948028845
0.51186.8618619274738.60002682752121
0.52188.4169132219518.2755251199683
0.53189.9212291507847.98284864985737
0.54191.3838309350047.74444022082646
0.55192.8170416822217.58142774175128
0.56194.2359664902517.51040604246408
0.57195.6576007367637.54099000678739
0.58197.0996369449897.6744237499671
0.59198.5790791080437.90136322687483
0.6200.1108040188838.20440892921583
0.61201.7062300614328.55758467877004
0.62203.3722619001558.93031891265969
0.63205.1106704868989.2910260266783
0.64206.91803832159.6090658497643
0.65208.7863492340739.85926687903099
0.66210.7042339375410.0253081077468
0.67212.65880615824410.1021418672663
0.68214.63795194070610.0972062513581
0.69216.63287982877710.03203335763
0.7218.6407111356829.9417118402201
0.71220.6668883654179.87200170511472
0.72222.7271968476699.8780141031298
0.73224.84921249731310.0203588808968
0.74227.07298890858910.3594530380757
0.75229.45077152069810.9501781535227
0.76232.04548946361911.8332398845100
0.77234.92777013470913.0287209599280
0.78238.17131332706214.5277088069074
0.79241.84671329439116.2871428665131
0.8246.01424462134918.2275048928961
0.81250.71665636391520.2371786997449
0.82255.97346611701222.1826556599358
0.83261.77836401729223.9291576427541
0.84268.1009265739225.3638483212584
0.85274.89289635372826.4181570490565
0.86282.09808836929327.0799289985247
0.87289.66404870745127.3905289746052
0.88297.553408654327.4280742092355
0.89305.75358120581627.2867596699853
0.9314.28456568732127.0605717541866
0.91323.20509314329326.8399567790036
0.92332.61571594456326.7097370472072
0.93342.65225181504226.7318430718795
0.94353.45379389816726.8902981949929
0.95365.08026697087926.974886448394
0.96377.35935598167226.4007058135568
0.97389.68476104077624.0983621538877
0.98400.87589420229918.9691661760214
0.99409.30996337512111.6232909783428


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')