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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, 02 Aug 2012 06:03:34 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Aug/02/t134390186192li11ixxlnh992.htm/, Retrieved Thu, 02 May 2024 21:26:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=168964, Retrieved Thu, 02 May 2024 21:26:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact179

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] [] [2012-08-02 10:03:34] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
567
557
547
527
729
719
567
466
476
476
486
507
446
385
335
335
527
547
395
223
314
314
385
426
416
314
365
345
517
476
314
193
304
335
365
405
324
254
284
294
557
557
405
385
446
416
497
598
618
476
436
395
669
689
638
689
679
598
689
790
831
709
628
689
952
1033
1013
1053
1043
942
1114
1155
1215
1033
962
1043
1236
1408
1367
1367
1387
1317
1499
1499
1468
1296
1327
1347
1479
1651
1529
1590
1539
1509
1742
1691
1620
1519
1620
1671
1732
1813
1732
1782
1721
1711
1964
1985
1904
1762
1883
1934
1995
2086
1995
2066
2035
1924
2157
2157

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'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168964&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168964&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168964&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'Herman Ole Andreas Wold' @ wold.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01214.8229217586931.2883738653664
0.02245.21963692285932.2914258147367
0.03270.66209663965927.3871490117345
0.04288.76708779698220.5625896157039
0.05300.94116396656515.2507754040662
0.06309.34118783683712.4804446185204
0.07315.86744916507212.2831786883807
0.08321.87809711627613.9671230565248
0.09328.18232945365516.5581534194303
0.1335.13479757019819.3293877498858
0.11342.77038027164521.7963209826742
0.12350.92988024540223.6013096657827
0.13359.35743109567424.5421880413172
0.14367.78225486254324.660068463936
0.15375.99239856751324.2490601708591
0.16383.88672757946623.7491874613321
0.17391.48724841323623.570693773514
0.18398.91012297069423.9441710319471
0.19406.31226807817624.8788686522709
0.2413.83697700158326.2061644934635
0.21421.57629948233527.6762466105269
0.22429.55738450012929.0479731271279
0.23437.7509116211530.1547770563641
0.24446.09421235274430.9417170430935
0.25454.51933206033231.4624803143523
0.26462.97654426480931.8486047503908
0.27471.44654825388732.2502921494178
0.28479.9392774819232.7741003001604
0.29488.48249027131833.4474012169234
0.3497.10705887332934.2268656520104
0.31505.83651046377835.0398805063225
0.32514.68568353925435.8454385532797
0.33523.66867454623836.6699270665108
0.34532.81174993868637.6195484482003
0.35542.16455874783438.8425863506161
0.36551.80370365407740.484306433051
0.37561.82609097613842.6153924726082
0.38572.3340509733645.2101050855652
0.39583.41819599314248.145859630264
0.4595.14583511783651.2695350828301
0.41607.56169001351754.4625932668217
0.42620.70379047120257.7343130995383
0.43634.6318027765861.2630859396147
0.44649.45936364423665.4015540830779
0.45665.37823137573970.6068144439968
0.46682.66192369447877.3000142216222
0.47701.64080197008685.6815120925908
0.48722.64870680139895.5979203194567
0.49745.951128955741106.50483870224
0.5771.673261134456117.530664188478
0.51799.749744377204127.667557409684
0.52829.914327767199135.983526376876
0.53861.737166243047141.852201080858
0.54894.702950566829145.108283313641
0.55928.309325630134146.082898429949
0.56962.157225225902145.506143671198
0.57996.006211595077144.281388203981
0.581029.77876856749143.201340936916
0.591063.51428234171142.696293027946
0.61097.29021799313142.717932961514
0.611131.13857990535142.793125563645
0.621164.98615089265142.249398403808
0.631198.63714194519140.477339240323
0.641231.80070063143137.12621817702
0.651264.14969294507132.215692933826
0.661295.38762783379126.075145415034
0.671325.30102416268119.232951889537
0.681353.78399804074112.231443173156
0.691380.83540778641105.497747732209
0.71406.5398348026199.3027256449412
0.711431.0468449673493.8054837026454
0.721454.5574294221489.1364323551921
0.731477.3161449585285.4509568649423
0.741499.598933442482.8871950556435
0.751521.6856097460481.4554284459716
0.761543.8139181302480.916584716652
0.771566.1249101441580.7735504674231
0.781588.6201735763980.3760185521828
0.791611.1541115596479.1250351378335
0.81633.4771164188476.6841907652574
0.811655.3304368562273.1383217290843
0.821676.5749490536369.0525724755642
0.831697.3176617461865.426582667747
0.841717.9856660485563.4769467514614
0.851739.2948410831864.17583206955
0.861762.081506919567.6531041726099
0.871787.0174521378272.8202314753563
0.881814.3013424891477.6259543595578
0.891843.4720771580979.8397808461628
0.91873.4699992431778.0015625682755
0.911902.9667663164172.0586274085793
0.921930.858277469363.3842264668665
0.931956.7579212663654.2682422286436
0.941981.3379682497547.2962933117084
0.952006.3756703866844.49924291585
0.962034.4297187800345.8343053430379
0.972068.0054129688849.3793020369179
0.982106.7365366188650.4935849149142
0.992141.430523292133.2588166473821

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 214.82292175869 & 31.2883738653664 \tabularnewline
0.02 & 245.219636922859 & 32.2914258147367 \tabularnewline
0.03 & 270.662096639659 & 27.3871490117345 \tabularnewline
0.04 & 288.767087796982 & 20.5625896157039 \tabularnewline
0.05 & 300.941163966565 & 15.2507754040662 \tabularnewline
0.06 & 309.341187836837 & 12.4804446185204 \tabularnewline
0.07 & 315.867449165072 & 12.2831786883807 \tabularnewline
0.08 & 321.878097116276 & 13.9671230565248 \tabularnewline
0.09 & 328.182329453655 & 16.5581534194303 \tabularnewline
0.1 & 335.134797570198 & 19.3293877498858 \tabularnewline
0.11 & 342.770380271645 & 21.7963209826742 \tabularnewline
0.12 & 350.929880245402 & 23.6013096657827 \tabularnewline
0.13 & 359.357431095674 & 24.5421880413172 \tabularnewline
0.14 & 367.782254862543 & 24.660068463936 \tabularnewline
0.15 & 375.992398567513 & 24.2490601708591 \tabularnewline
0.16 & 383.886727579466 & 23.7491874613321 \tabularnewline
0.17 & 391.487248413236 & 23.570693773514 \tabularnewline
0.18 & 398.910122970694 & 23.9441710319471 \tabularnewline
0.19 & 406.312268078176 & 24.8788686522709 \tabularnewline
0.2 & 413.836977001583 & 26.2061644934635 \tabularnewline
0.21 & 421.576299482335 & 27.6762466105269 \tabularnewline
0.22 & 429.557384500129 & 29.0479731271279 \tabularnewline
0.23 & 437.75091162115 & 30.1547770563641 \tabularnewline
0.24 & 446.094212352744 & 30.9417170430935 \tabularnewline
0.25 & 454.519332060332 & 31.4624803143523 \tabularnewline
0.26 & 462.976544264809 & 31.8486047503908 \tabularnewline
0.27 & 471.446548253887 & 32.2502921494178 \tabularnewline
0.28 & 479.93927748192 & 32.7741003001604 \tabularnewline
0.29 & 488.482490271318 & 33.4474012169234 \tabularnewline
0.3 & 497.107058873329 & 34.2268656520104 \tabularnewline
0.31 & 505.836510463778 & 35.0398805063225 \tabularnewline
0.32 & 514.685683539254 & 35.8454385532797 \tabularnewline
0.33 & 523.668674546238 & 36.6699270665108 \tabularnewline
0.34 & 532.811749938686 & 37.6195484482003 \tabularnewline
0.35 & 542.164558747834 & 38.8425863506161 \tabularnewline
0.36 & 551.803703654077 & 40.484306433051 \tabularnewline
0.37 & 561.826090976138 & 42.6153924726082 \tabularnewline
0.38 & 572.33405097336 & 45.2101050855652 \tabularnewline
0.39 & 583.418195993142 & 48.145859630264 \tabularnewline
0.4 & 595.145835117836 & 51.2695350828301 \tabularnewline
0.41 & 607.561690013517 & 54.4625932668217 \tabularnewline
0.42 & 620.703790471202 & 57.7343130995383 \tabularnewline
0.43 & 634.63180277658 & 61.2630859396147 \tabularnewline
0.44 & 649.459363644236 & 65.4015540830779 \tabularnewline
0.45 & 665.378231375739 & 70.6068144439968 \tabularnewline
0.46 & 682.661923694478 & 77.3000142216222 \tabularnewline
0.47 & 701.640801970086 & 85.6815120925908 \tabularnewline
0.48 & 722.648706801398 & 95.5979203194567 \tabularnewline
0.49 & 745.951128955741 & 106.50483870224 \tabularnewline
0.5 & 771.673261134456 & 117.530664188478 \tabularnewline
0.51 & 799.749744377204 & 127.667557409684 \tabularnewline
0.52 & 829.914327767199 & 135.983526376876 \tabularnewline
0.53 & 861.737166243047 & 141.852201080858 \tabularnewline
0.54 & 894.702950566829 & 145.108283313641 \tabularnewline
0.55 & 928.309325630134 & 146.082898429949 \tabularnewline
0.56 & 962.157225225902 & 145.506143671198 \tabularnewline
0.57 & 996.006211595077 & 144.281388203981 \tabularnewline
0.58 & 1029.77876856749 & 143.201340936916 \tabularnewline
0.59 & 1063.51428234171 & 142.696293027946 \tabularnewline
0.6 & 1097.29021799313 & 142.717932961514 \tabularnewline
0.61 & 1131.13857990535 & 142.793125563645 \tabularnewline
0.62 & 1164.98615089265 & 142.249398403808 \tabularnewline
0.63 & 1198.63714194519 & 140.477339240323 \tabularnewline
0.64 & 1231.80070063143 & 137.12621817702 \tabularnewline
0.65 & 1264.14969294507 & 132.215692933826 \tabularnewline
0.66 & 1295.38762783379 & 126.075145415034 \tabularnewline
0.67 & 1325.30102416268 & 119.232951889537 \tabularnewline
0.68 & 1353.78399804074 & 112.231443173156 \tabularnewline
0.69 & 1380.83540778641 & 105.497747732209 \tabularnewline
0.7 & 1406.53983480261 & 99.3027256449412 \tabularnewline
0.71 & 1431.04684496734 & 93.8054837026454 \tabularnewline
0.72 & 1454.55742942214 & 89.1364323551921 \tabularnewline
0.73 & 1477.31614495852 & 85.4509568649423 \tabularnewline
0.74 & 1499.5989334424 & 82.8871950556435 \tabularnewline
0.75 & 1521.68560974604 & 81.4554284459716 \tabularnewline
0.76 & 1543.81391813024 & 80.916584716652 \tabularnewline
0.77 & 1566.12491014415 & 80.7735504674231 \tabularnewline
0.78 & 1588.62017357639 & 80.3760185521828 \tabularnewline
0.79 & 1611.15411155964 & 79.1250351378335 \tabularnewline
0.8 & 1633.47711641884 & 76.6841907652574 \tabularnewline
0.81 & 1655.33043685622 & 73.1383217290843 \tabularnewline
0.82 & 1676.57494905363 & 69.0525724755642 \tabularnewline
0.83 & 1697.31766174618 & 65.426582667747 \tabularnewline
0.84 & 1717.98566604855 & 63.4769467514614 \tabularnewline
0.85 & 1739.29484108318 & 64.17583206955 \tabularnewline
0.86 & 1762.0815069195 & 67.6531041726099 \tabularnewline
0.87 & 1787.01745213782 & 72.8202314753563 \tabularnewline
0.88 & 1814.30134248914 & 77.6259543595578 \tabularnewline
0.89 & 1843.47207715809 & 79.8397808461628 \tabularnewline
0.9 & 1873.46999924317 & 78.0015625682755 \tabularnewline
0.91 & 1902.96676631641 & 72.0586274085793 \tabularnewline
0.92 & 1930.8582774693 & 63.3842264668665 \tabularnewline
0.93 & 1956.75792126636 & 54.2682422286436 \tabularnewline
0.94 & 1981.33796824975 & 47.2962933117084 \tabularnewline
0.95 & 2006.37567038668 & 44.49924291585 \tabularnewline
0.96 & 2034.42971878003 & 45.8343053430379 \tabularnewline
0.97 & 2068.00541296888 & 49.3793020369179 \tabularnewline
0.98 & 2106.73653661886 & 50.4935849149142 \tabularnewline
0.99 & 2141.4305232921 & 33.2588166473821 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168964&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]214.82292175869[/C][C]31.2883738653664[/C][/ROW]
[ROW][C]0.02[/C][C]245.219636922859[/C][C]32.2914258147367[/C][/ROW]
[ROW][C]0.03[/C][C]270.662096639659[/C][C]27.3871490117345[/C][/ROW]
[ROW][C]0.04[/C][C]288.767087796982[/C][C]20.5625896157039[/C][/ROW]
[ROW][C]0.05[/C][C]300.941163966565[/C][C]15.2507754040662[/C][/ROW]
[ROW][C]0.06[/C][C]309.341187836837[/C][C]12.4804446185204[/C][/ROW]
[ROW][C]0.07[/C][C]315.867449165072[/C][C]12.2831786883807[/C][/ROW]
[ROW][C]0.08[/C][C]321.878097116276[/C][C]13.9671230565248[/C][/ROW]
[ROW][C]0.09[/C][C]328.182329453655[/C][C]16.5581534194303[/C][/ROW]
[ROW][C]0.1[/C][C]335.134797570198[/C][C]19.3293877498858[/C][/ROW]
[ROW][C]0.11[/C][C]342.770380271645[/C][C]21.7963209826742[/C][/ROW]
[ROW][C]0.12[/C][C]350.929880245402[/C][C]23.6013096657827[/C][/ROW]
[ROW][C]0.13[/C][C]359.357431095674[/C][C]24.5421880413172[/C][/ROW]
[ROW][C]0.14[/C][C]367.782254862543[/C][C]24.660068463936[/C][/ROW]
[ROW][C]0.15[/C][C]375.992398567513[/C][C]24.2490601708591[/C][/ROW]
[ROW][C]0.16[/C][C]383.886727579466[/C][C]23.7491874613321[/C][/ROW]
[ROW][C]0.17[/C][C]391.487248413236[/C][C]23.570693773514[/C][/ROW]
[ROW][C]0.18[/C][C]398.910122970694[/C][C]23.9441710319471[/C][/ROW]
[ROW][C]0.19[/C][C]406.312268078176[/C][C]24.8788686522709[/C][/ROW]
[ROW][C]0.2[/C][C]413.836977001583[/C][C]26.2061644934635[/C][/ROW]
[ROW][C]0.21[/C][C]421.576299482335[/C][C]27.6762466105269[/C][/ROW]
[ROW][C]0.22[/C][C]429.557384500129[/C][C]29.0479731271279[/C][/ROW]
[ROW][C]0.23[/C][C]437.75091162115[/C][C]30.1547770563641[/C][/ROW]
[ROW][C]0.24[/C][C]446.094212352744[/C][C]30.9417170430935[/C][/ROW]
[ROW][C]0.25[/C][C]454.519332060332[/C][C]31.4624803143523[/C][/ROW]
[ROW][C]0.26[/C][C]462.976544264809[/C][C]31.8486047503908[/C][/ROW]
[ROW][C]0.27[/C][C]471.446548253887[/C][C]32.2502921494178[/C][/ROW]
[ROW][C]0.28[/C][C]479.93927748192[/C][C]32.7741003001604[/C][/ROW]
[ROW][C]0.29[/C][C]488.482490271318[/C][C]33.4474012169234[/C][/ROW]
[ROW][C]0.3[/C][C]497.107058873329[/C][C]34.2268656520104[/C][/ROW]
[ROW][C]0.31[/C][C]505.836510463778[/C][C]35.0398805063225[/C][/ROW]
[ROW][C]0.32[/C][C]514.685683539254[/C][C]35.8454385532797[/C][/ROW]
[ROW][C]0.33[/C][C]523.668674546238[/C][C]36.6699270665108[/C][/ROW]
[ROW][C]0.34[/C][C]532.811749938686[/C][C]37.6195484482003[/C][/ROW]
[ROW][C]0.35[/C][C]542.164558747834[/C][C]38.8425863506161[/C][/ROW]
[ROW][C]0.36[/C][C]551.803703654077[/C][C]40.484306433051[/C][/ROW]
[ROW][C]0.37[/C][C]561.826090976138[/C][C]42.6153924726082[/C][/ROW]
[ROW][C]0.38[/C][C]572.33405097336[/C][C]45.2101050855652[/C][/ROW]
[ROW][C]0.39[/C][C]583.418195993142[/C][C]48.145859630264[/C][/ROW]
[ROW][C]0.4[/C][C]595.145835117836[/C][C]51.2695350828301[/C][/ROW]
[ROW][C]0.41[/C][C]607.561690013517[/C][C]54.4625932668217[/C][/ROW]
[ROW][C]0.42[/C][C]620.703790471202[/C][C]57.7343130995383[/C][/ROW]
[ROW][C]0.43[/C][C]634.63180277658[/C][C]61.2630859396147[/C][/ROW]
[ROW][C]0.44[/C][C]649.459363644236[/C][C]65.4015540830779[/C][/ROW]
[ROW][C]0.45[/C][C]665.378231375739[/C][C]70.6068144439968[/C][/ROW]
[ROW][C]0.46[/C][C]682.661923694478[/C][C]77.3000142216222[/C][/ROW]
[ROW][C]0.47[/C][C]701.640801970086[/C][C]85.6815120925908[/C][/ROW]
[ROW][C]0.48[/C][C]722.648706801398[/C][C]95.5979203194567[/C][/ROW]
[ROW][C]0.49[/C][C]745.951128955741[/C][C]106.50483870224[/C][/ROW]
[ROW][C]0.5[/C][C]771.673261134456[/C][C]117.530664188478[/C][/ROW]
[ROW][C]0.51[/C][C]799.749744377204[/C][C]127.667557409684[/C][/ROW]
[ROW][C]0.52[/C][C]829.914327767199[/C][C]135.983526376876[/C][/ROW]
[ROW][C]0.53[/C][C]861.737166243047[/C][C]141.852201080858[/C][/ROW]
[ROW][C]0.54[/C][C]894.702950566829[/C][C]145.108283313641[/C][/ROW]
[ROW][C]0.55[/C][C]928.309325630134[/C][C]146.082898429949[/C][/ROW]
[ROW][C]0.56[/C][C]962.157225225902[/C][C]145.506143671198[/C][/ROW]
[ROW][C]0.57[/C][C]996.006211595077[/C][C]144.281388203981[/C][/ROW]
[ROW][C]0.58[/C][C]1029.77876856749[/C][C]143.201340936916[/C][/ROW]
[ROW][C]0.59[/C][C]1063.51428234171[/C][C]142.696293027946[/C][/ROW]
[ROW][C]0.6[/C][C]1097.29021799313[/C][C]142.717932961514[/C][/ROW]
[ROW][C]0.61[/C][C]1131.13857990535[/C][C]142.793125563645[/C][/ROW]
[ROW][C]0.62[/C][C]1164.98615089265[/C][C]142.249398403808[/C][/ROW]
[ROW][C]0.63[/C][C]1198.63714194519[/C][C]140.477339240323[/C][/ROW]
[ROW][C]0.64[/C][C]1231.80070063143[/C][C]137.12621817702[/C][/ROW]
[ROW][C]0.65[/C][C]1264.14969294507[/C][C]132.215692933826[/C][/ROW]
[ROW][C]0.66[/C][C]1295.38762783379[/C][C]126.075145415034[/C][/ROW]
[ROW][C]0.67[/C][C]1325.30102416268[/C][C]119.232951889537[/C][/ROW]
[ROW][C]0.68[/C][C]1353.78399804074[/C][C]112.231443173156[/C][/ROW]
[ROW][C]0.69[/C][C]1380.83540778641[/C][C]105.497747732209[/C][/ROW]
[ROW][C]0.7[/C][C]1406.53983480261[/C][C]99.3027256449412[/C][/ROW]
[ROW][C]0.71[/C][C]1431.04684496734[/C][C]93.8054837026454[/C][/ROW]
[ROW][C]0.72[/C][C]1454.55742942214[/C][C]89.1364323551921[/C][/ROW]
[ROW][C]0.73[/C][C]1477.31614495852[/C][C]85.4509568649423[/C][/ROW]
[ROW][C]0.74[/C][C]1499.5989334424[/C][C]82.8871950556435[/C][/ROW]
[ROW][C]0.75[/C][C]1521.68560974604[/C][C]81.4554284459716[/C][/ROW]
[ROW][C]0.76[/C][C]1543.81391813024[/C][C]80.916584716652[/C][/ROW]
[ROW][C]0.77[/C][C]1566.12491014415[/C][C]80.7735504674231[/C][/ROW]
[ROW][C]0.78[/C][C]1588.62017357639[/C][C]80.3760185521828[/C][/ROW]
[ROW][C]0.79[/C][C]1611.15411155964[/C][C]79.1250351378335[/C][/ROW]
[ROW][C]0.8[/C][C]1633.47711641884[/C][C]76.6841907652574[/C][/ROW]
[ROW][C]0.81[/C][C]1655.33043685622[/C][C]73.1383217290843[/C][/ROW]
[ROW][C]0.82[/C][C]1676.57494905363[/C][C]69.0525724755642[/C][/ROW]
[ROW][C]0.83[/C][C]1697.31766174618[/C][C]65.426582667747[/C][/ROW]
[ROW][C]0.84[/C][C]1717.98566604855[/C][C]63.4769467514614[/C][/ROW]
[ROW][C]0.85[/C][C]1739.29484108318[/C][C]64.17583206955[/C][/ROW]
[ROW][C]0.86[/C][C]1762.0815069195[/C][C]67.6531041726099[/C][/ROW]
[ROW][C]0.87[/C][C]1787.01745213782[/C][C]72.8202314753563[/C][/ROW]
[ROW][C]0.88[/C][C]1814.30134248914[/C][C]77.6259543595578[/C][/ROW]
[ROW][C]0.89[/C][C]1843.47207715809[/C][C]79.8397808461628[/C][/ROW]
[ROW][C]0.9[/C][C]1873.46999924317[/C][C]78.0015625682755[/C][/ROW]
[ROW][C]0.91[/C][C]1902.96676631641[/C][C]72.0586274085793[/C][/ROW]
[ROW][C]0.92[/C][C]1930.8582774693[/C][C]63.3842264668665[/C][/ROW]
[ROW][C]0.93[/C][C]1956.75792126636[/C][C]54.2682422286436[/C][/ROW]
[ROW][C]0.94[/C][C]1981.33796824975[/C][C]47.2962933117084[/C][/ROW]
[ROW][C]0.95[/C][C]2006.37567038668[/C][C]44.49924291585[/C][/ROW]
[ROW][C]0.96[/C][C]2034.42971878003[/C][C]45.8343053430379[/C][/ROW]
[ROW][C]0.97[/C][C]2068.00541296888[/C][C]49.3793020369179[/C][/ROW]
[ROW][C]0.98[/C][C]2106.73653661886[/C][C]50.4935849149142[/C][/ROW]
[ROW][C]0.99[/C][C]2141.4305232921[/C][C]33.2588166473821[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168964&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168964&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
0.01214.8229217586931.2883738653664
0.02245.21963692285932.2914258147367
0.03270.66209663965927.3871490117345
0.04288.76708779698220.5625896157039
0.05300.94116396656515.2507754040662
0.06309.34118783683712.4804446185204
0.07315.86744916507212.2831786883807
0.08321.87809711627613.9671230565248
0.09328.18232945365516.5581534194303
0.1335.13479757019819.3293877498858
0.11342.77038027164521.7963209826742
0.12350.92988024540223.6013096657827
0.13359.35743109567424.5421880413172
0.14367.78225486254324.660068463936
0.15375.99239856751324.2490601708591
0.16383.88672757946623.7491874613321
0.17391.48724841323623.570693773514
0.18398.91012297069423.9441710319471
0.19406.31226807817624.8788686522709
0.2413.83697700158326.2061644934635
0.21421.57629948233527.6762466105269
0.22429.55738450012929.0479731271279
0.23437.7509116211530.1547770563641
0.24446.09421235274430.9417170430935
0.25454.51933206033231.4624803143523
0.26462.97654426480931.8486047503908
0.27471.44654825388732.2502921494178
0.28479.9392774819232.7741003001604
0.29488.48249027131833.4474012169234
0.3497.10705887332934.2268656520104
0.31505.83651046377835.0398805063225
0.32514.68568353925435.8454385532797
0.33523.66867454623836.6699270665108
0.34532.81174993868637.6195484482003
0.35542.16455874783438.8425863506161
0.36551.80370365407740.484306433051
0.37561.82609097613842.6153924726082
0.38572.3340509733645.2101050855652
0.39583.41819599314248.145859630264
0.4595.14583511783651.2695350828301
0.41607.56169001351754.4625932668217
0.42620.70379047120257.7343130995383
0.43634.6318027765861.2630859396147
0.44649.45936364423665.4015540830779
0.45665.37823137573970.6068144439968
0.46682.66192369447877.3000142216222
0.47701.64080197008685.6815120925908
0.48722.64870680139895.5979203194567
0.49745.951128955741106.50483870224
0.5771.673261134456117.530664188478
0.51799.749744377204127.667557409684
0.52829.914327767199135.983526376876
0.53861.737166243047141.852201080858
0.54894.702950566829145.108283313641
0.55928.309325630134146.082898429949
0.56962.157225225902145.506143671198
0.57996.006211595077144.281388203981
0.581029.77876856749143.201340936916
0.591063.51428234171142.696293027946
0.61097.29021799313142.717932961514
0.611131.13857990535142.793125563645
0.621164.98615089265142.249398403808
0.631198.63714194519140.477339240323
0.641231.80070063143137.12621817702
0.651264.14969294507132.215692933826
0.661295.38762783379126.075145415034
0.671325.30102416268119.232951889537
0.681353.78399804074112.231443173156
0.691380.83540778641105.497747732209
0.71406.5398348026199.3027256449412
0.711431.0468449673493.8054837026454
0.721454.5574294221489.1364323551921
0.731477.3161449585285.4509568649423
0.741499.598933442482.8871950556435
0.751521.6856097460481.4554284459716
0.761543.8139181302480.916584716652
0.771566.1249101441580.7735504674231
0.781588.6201735763980.3760185521828
0.791611.1541115596479.1250351378335
0.81633.4771164188476.6841907652574
0.811655.3304368562273.1383217290843
0.821676.5749490536369.0525724755642
0.831697.3176617461865.426582667747
0.841717.9856660485563.4769467514614
0.851739.2948410831864.17583206955
0.861762.081506919567.6531041726099
0.871787.0174521378272.8202314753563
0.881814.3013424891477.6259543595578
0.891843.4720771580979.8397808461628
0.91873.4699992431778.0015625682755
0.911902.9667663164172.0586274085793
0.921930.858277469363.3842264668665
0.931956.7579212663654.2682422286436
0.941981.3379682497547.2962933117084
0.952006.3756703866844.49924291585
0.962034.4297187800345.8343053430379
0.972068.0054129688849.3793020369179
0.982106.7365366188650.4935849149142
0.992141.430523292133.2588166473821


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')