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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, 03 Dec 2015 13:58:11 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Dec/03/t1449151264ef336mvuq77oxlr.htm/, Retrieved Thu, 16 May 2024 07:38:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284939, Retrieved Thu, 16 May 2024 07:38:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Notched Boxplots] [Boxplot max prijz...] [2015-10-10 12:54:28] [caeec4f3373338cbe0826e56549ed528]
- RMPD  [Harrell-Davis Quantiles] [Percentielen Mini...] [2015-10-10 13:55:13] [caeec4f3373338cbe0826e56549ed528]
- R  D      [Harrell-Davis Quantiles] [Percentielen werk...] [2015-12-03 13:58:11] [ad5e328aab07d5d247de986d4dfd18ff] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
467
475
470
442
433
427
410
406
429
425
431
408
454
459
441
420
416
400
401
398
442
458
476
447
511
514
513
511
498
490
495
486
530
539
555
548
615
634
645
634
630
635
642
637
675
679
676
660
716
730
717
694
670
641
626
604
630
634
635
619

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'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284939&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284939&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284939&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'George Udny Yule' @ yule.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01398.5658169622581.98856731428469
0.02399.5363621233522.34305332955961
0.03400.793902429323.0573703254053
0.04402.2625169424853.89343191042346
0.05403.9036129855084.6826836865702
0.06405.6903311856295.39077094954237
0.07407.5970023984336.04448075254022
0.08409.5990921840546.65698453484789
0.09411.6734561996737.20670130101726
0.1413.7965377097497.65337119936496
0.11415.9429637397657.96503611077268
0.12418.0865850258618.1383799248663
0.13420.2037334045558.19733212221444
0.14422.2770166838388.18770613566093
0.15424.2979491935328.16340842460674
0.16426.2675556055648.17236882216434
0.17428.1950375148948.24825017698924
0.18430.0952067514918.40683805569033
0.19431.9855617937688.6474118419435
0.2433.8837221195558.95930441563158
0.21435.8056175281019.32851071508883
0.22437.7645108600529.74115511210101
0.23439.77070790699810.1858224653827
0.24441.83170871655710.6529547981356
0.25443.95256277431711.1347234627105
0.26446.1362634465411.6235674871641
0.27448.38410681753712.1110190138223
0.28450.69601022220512.590072407547
0.29453.07081903898913.0550201911607
0.3455.50662812182313.5030143923395
0.31458.00112066204413.9327050869054
0.32460.55190044661814.3453075406289
0.33463.15677824247614.7444478507103
0.34465.81397657581115.1346335573296
0.35468.52223837266415.5183455439112
0.36471.28085647084615.8983057994041
0.37474.08967279339616.2768354563909
0.38476.94911836248516.6555483369687
0.39479.86037147243417.0354469351894
0.4482.82569819922117.4215941270374
0.41485.84900782992417.8231884116469
0.42488.93660985783718.2551589846658
0.43492.0981054561418.7397936547694
0.44495.34729290760619.3069638979258
0.45498.70292206577719.9935585692565
0.46502.18910600294620.8384102390391
0.47505.8351957382221.8807537666656
0.48509.67495122386923.15079387455
0.49513.74490023906424.6659063926611
0.5518.08186409671926.4211213975795
0.51522.71973819254628.3886949851923
0.52527.68573495917730.5132983415855
0.53532.99641133705432.7122423125647
0.54538.65389447473134.8821759132617
0.55544.64276973199536.9013154341236
0.56550.92808860258838.6423709518819
0.57557.45488155682439.978153112299
0.58564.14942225597340.7976917525276
0.59570.9222971284141.0140460400911
0.6577.67311185682340.5759493304748
0.61584.29644710554839.4709650236392
0.62590.68849682807637.731390001046
0.63596.7537171610435.4301274444718
0.64602.41080439061732.6726478365059
0.65607.5974117812229.5903864961665
0.66612.27319282044326.3262669285649
0.67616.4209913034923.0232901993012
0.68620.04624494109219.8149147569105
0.69623.17488593561616.8141775836894
0.7625.85017434740814.1109624102066
0.71628.12896781877311.7706434205001
0.72630.0779111082999.83519325293203
0.73631.7699326750298.32983572290461
0.74633.2812849843687.26690393297802
0.75634.6891865482016.64909157957272
0.76636.0699443681776.46459204166475
0.77637.4972840121886.68052264033097
0.78639.0405233175177.24782914125465
0.79640.7622323432598.10287198638615
0.8642.7151656541989.17355079893205
0.81644.93855966357610.3748224045889
0.82647.45434708806511.6078577451397
0.83650.26437623291812.7600322158736
0.84653.35017123252813.7190875481439
0.85656.67688245460914.3894663290947
0.86660.20256478071414.721856376448
0.87663.89254991103314.7368038912403
0.88667.73641579707914.5456996008474
0.89671.76227471674414.3505433302869
0.9676.04080038066714.4002331465004
0.91680.6713572299114.8825518932012
0.92685.74706762151915.7749774559078
0.93691.30622779952516.7595671239688
0.94697.29203153870717.2899763444088
0.95703.5508090239416.8156987743008
0.96709.88116912053715.1340408386654
0.97716.08742093866712.7884418963609
0.98721.9234969010311.208797583514
0.99726.86839663784211.5407557582687

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 398.565816962258 & 1.98856731428469 \tabularnewline
0.02 & 399.536362123352 & 2.34305332955961 \tabularnewline
0.03 & 400.79390242932 & 3.0573703254053 \tabularnewline
0.04 & 402.262516942485 & 3.89343191042346 \tabularnewline
0.05 & 403.903612985508 & 4.6826836865702 \tabularnewline
0.06 & 405.690331185629 & 5.39077094954237 \tabularnewline
0.07 & 407.597002398433 & 6.04448075254022 \tabularnewline
0.08 & 409.599092184054 & 6.65698453484789 \tabularnewline
0.09 & 411.673456199673 & 7.20670130101726 \tabularnewline
0.1 & 413.796537709749 & 7.65337119936496 \tabularnewline
0.11 & 415.942963739765 & 7.96503611077268 \tabularnewline
0.12 & 418.086585025861 & 8.1383799248663 \tabularnewline
0.13 & 420.203733404555 & 8.19733212221444 \tabularnewline
0.14 & 422.277016683838 & 8.18770613566093 \tabularnewline
0.15 & 424.297949193532 & 8.16340842460674 \tabularnewline
0.16 & 426.267555605564 & 8.17236882216434 \tabularnewline
0.17 & 428.195037514894 & 8.24825017698924 \tabularnewline
0.18 & 430.095206751491 & 8.40683805569033 \tabularnewline
0.19 & 431.985561793768 & 8.6474118419435 \tabularnewline
0.2 & 433.883722119555 & 8.95930441563158 \tabularnewline
0.21 & 435.805617528101 & 9.32851071508883 \tabularnewline
0.22 & 437.764510860052 & 9.74115511210101 \tabularnewline
0.23 & 439.770707906998 & 10.1858224653827 \tabularnewline
0.24 & 441.831708716557 & 10.6529547981356 \tabularnewline
0.25 & 443.952562774317 & 11.1347234627105 \tabularnewline
0.26 & 446.13626344654 & 11.6235674871641 \tabularnewline
0.27 & 448.384106817537 & 12.1110190138223 \tabularnewline
0.28 & 450.696010222205 & 12.590072407547 \tabularnewline
0.29 & 453.070819038989 & 13.0550201911607 \tabularnewline
0.3 & 455.506628121823 & 13.5030143923395 \tabularnewline
0.31 & 458.001120662044 & 13.9327050869054 \tabularnewline
0.32 & 460.551900446618 & 14.3453075406289 \tabularnewline
0.33 & 463.156778242476 & 14.7444478507103 \tabularnewline
0.34 & 465.813976575811 & 15.1346335573296 \tabularnewline
0.35 & 468.522238372664 & 15.5183455439112 \tabularnewline
0.36 & 471.280856470846 & 15.8983057994041 \tabularnewline
0.37 & 474.089672793396 & 16.2768354563909 \tabularnewline
0.38 & 476.949118362485 & 16.6555483369687 \tabularnewline
0.39 & 479.860371472434 & 17.0354469351894 \tabularnewline
0.4 & 482.825698199221 & 17.4215941270374 \tabularnewline
0.41 & 485.849007829924 & 17.8231884116469 \tabularnewline
0.42 & 488.936609857837 & 18.2551589846658 \tabularnewline
0.43 & 492.09810545614 & 18.7397936547694 \tabularnewline
0.44 & 495.347292907606 & 19.3069638979258 \tabularnewline
0.45 & 498.702922065777 & 19.9935585692565 \tabularnewline
0.46 & 502.189106002946 & 20.8384102390391 \tabularnewline
0.47 & 505.83519573822 & 21.8807537666656 \tabularnewline
0.48 & 509.674951223869 & 23.15079387455 \tabularnewline
0.49 & 513.744900239064 & 24.6659063926611 \tabularnewline
0.5 & 518.081864096719 & 26.4211213975795 \tabularnewline
0.51 & 522.719738192546 & 28.3886949851923 \tabularnewline
0.52 & 527.685734959177 & 30.5132983415855 \tabularnewline
0.53 & 532.996411337054 & 32.7122423125647 \tabularnewline
0.54 & 538.653894474731 & 34.8821759132617 \tabularnewline
0.55 & 544.642769731995 & 36.9013154341236 \tabularnewline
0.56 & 550.928088602588 & 38.6423709518819 \tabularnewline
0.57 & 557.454881556824 & 39.978153112299 \tabularnewline
0.58 & 564.149422255973 & 40.7976917525276 \tabularnewline
0.59 & 570.92229712841 & 41.0140460400911 \tabularnewline
0.6 & 577.673111856823 & 40.5759493304748 \tabularnewline
0.61 & 584.296447105548 & 39.4709650236392 \tabularnewline
0.62 & 590.688496828076 & 37.731390001046 \tabularnewline
0.63 & 596.75371716104 & 35.4301274444718 \tabularnewline
0.64 & 602.410804390617 & 32.6726478365059 \tabularnewline
0.65 & 607.59741178122 & 29.5903864961665 \tabularnewline
0.66 & 612.273192820443 & 26.3262669285649 \tabularnewline
0.67 & 616.42099130349 & 23.0232901993012 \tabularnewline
0.68 & 620.046244941092 & 19.8149147569105 \tabularnewline
0.69 & 623.174885935616 & 16.8141775836894 \tabularnewline
0.7 & 625.850174347408 & 14.1109624102066 \tabularnewline
0.71 & 628.128967818773 & 11.7706434205001 \tabularnewline
0.72 & 630.077911108299 & 9.83519325293203 \tabularnewline
0.73 & 631.769932675029 & 8.32983572290461 \tabularnewline
0.74 & 633.281284984368 & 7.26690393297802 \tabularnewline
0.75 & 634.689186548201 & 6.64909157957272 \tabularnewline
0.76 & 636.069944368177 & 6.46459204166475 \tabularnewline
0.77 & 637.497284012188 & 6.68052264033097 \tabularnewline
0.78 & 639.040523317517 & 7.24782914125465 \tabularnewline
0.79 & 640.762232343259 & 8.10287198638615 \tabularnewline
0.8 & 642.715165654198 & 9.17355079893205 \tabularnewline
0.81 & 644.938559663576 & 10.3748224045889 \tabularnewline
0.82 & 647.454347088065 & 11.6078577451397 \tabularnewline
0.83 & 650.264376232918 & 12.7600322158736 \tabularnewline
0.84 & 653.350171232528 & 13.7190875481439 \tabularnewline
0.85 & 656.676882454609 & 14.3894663290947 \tabularnewline
0.86 & 660.202564780714 & 14.721856376448 \tabularnewline
0.87 & 663.892549911033 & 14.7368038912403 \tabularnewline
0.88 & 667.736415797079 & 14.5456996008474 \tabularnewline
0.89 & 671.762274716744 & 14.3505433302869 \tabularnewline
0.9 & 676.040800380667 & 14.4002331465004 \tabularnewline
0.91 & 680.67135722991 & 14.8825518932012 \tabularnewline
0.92 & 685.747067621519 & 15.7749774559078 \tabularnewline
0.93 & 691.306227799525 & 16.7595671239688 \tabularnewline
0.94 & 697.292031538707 & 17.2899763444088 \tabularnewline
0.95 & 703.55080902394 & 16.8156987743008 \tabularnewline
0.96 & 709.881169120537 & 15.1340408386654 \tabularnewline
0.97 & 716.087420938667 & 12.7884418963609 \tabularnewline
0.98 & 721.92349690103 & 11.208797583514 \tabularnewline
0.99 & 726.868396637842 & 11.5407557582687 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284939&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]398.565816962258[/C][C]1.98856731428469[/C][/ROW]
[ROW][C]0.02[/C][C]399.536362123352[/C][C]2.34305332955961[/C][/ROW]
[ROW][C]0.03[/C][C]400.79390242932[/C][C]3.0573703254053[/C][/ROW]
[ROW][C]0.04[/C][C]402.262516942485[/C][C]3.89343191042346[/C][/ROW]
[ROW][C]0.05[/C][C]403.903612985508[/C][C]4.6826836865702[/C][/ROW]
[ROW][C]0.06[/C][C]405.690331185629[/C][C]5.39077094954237[/C][/ROW]
[ROW][C]0.07[/C][C]407.597002398433[/C][C]6.04448075254022[/C][/ROW]
[ROW][C]0.08[/C][C]409.599092184054[/C][C]6.65698453484789[/C][/ROW]
[ROW][C]0.09[/C][C]411.673456199673[/C][C]7.20670130101726[/C][/ROW]
[ROW][C]0.1[/C][C]413.796537709749[/C][C]7.65337119936496[/C][/ROW]
[ROW][C]0.11[/C][C]415.942963739765[/C][C]7.96503611077268[/C][/ROW]
[ROW][C]0.12[/C][C]418.086585025861[/C][C]8.1383799248663[/C][/ROW]
[ROW][C]0.13[/C][C]420.203733404555[/C][C]8.19733212221444[/C][/ROW]
[ROW][C]0.14[/C][C]422.277016683838[/C][C]8.18770613566093[/C][/ROW]
[ROW][C]0.15[/C][C]424.297949193532[/C][C]8.16340842460674[/C][/ROW]
[ROW][C]0.16[/C][C]426.267555605564[/C][C]8.17236882216434[/C][/ROW]
[ROW][C]0.17[/C][C]428.195037514894[/C][C]8.24825017698924[/C][/ROW]
[ROW][C]0.18[/C][C]430.095206751491[/C][C]8.40683805569033[/C][/ROW]
[ROW][C]0.19[/C][C]431.985561793768[/C][C]8.6474118419435[/C][/ROW]
[ROW][C]0.2[/C][C]433.883722119555[/C][C]8.95930441563158[/C][/ROW]
[ROW][C]0.21[/C][C]435.805617528101[/C][C]9.32851071508883[/C][/ROW]
[ROW][C]0.22[/C][C]437.764510860052[/C][C]9.74115511210101[/C][/ROW]
[ROW][C]0.23[/C][C]439.770707906998[/C][C]10.1858224653827[/C][/ROW]
[ROW][C]0.24[/C][C]441.831708716557[/C][C]10.6529547981356[/C][/ROW]
[ROW][C]0.25[/C][C]443.952562774317[/C][C]11.1347234627105[/C][/ROW]
[ROW][C]0.26[/C][C]446.13626344654[/C][C]11.6235674871641[/C][/ROW]
[ROW][C]0.27[/C][C]448.384106817537[/C][C]12.1110190138223[/C][/ROW]
[ROW][C]0.28[/C][C]450.696010222205[/C][C]12.590072407547[/C][/ROW]
[ROW][C]0.29[/C][C]453.070819038989[/C][C]13.0550201911607[/C][/ROW]
[ROW][C]0.3[/C][C]455.506628121823[/C][C]13.5030143923395[/C][/ROW]
[ROW][C]0.31[/C][C]458.001120662044[/C][C]13.9327050869054[/C][/ROW]
[ROW][C]0.32[/C][C]460.551900446618[/C][C]14.3453075406289[/C][/ROW]
[ROW][C]0.33[/C][C]463.156778242476[/C][C]14.7444478507103[/C][/ROW]
[ROW][C]0.34[/C][C]465.813976575811[/C][C]15.1346335573296[/C][/ROW]
[ROW][C]0.35[/C][C]468.522238372664[/C][C]15.5183455439112[/C][/ROW]
[ROW][C]0.36[/C][C]471.280856470846[/C][C]15.8983057994041[/C][/ROW]
[ROW][C]0.37[/C][C]474.089672793396[/C][C]16.2768354563909[/C][/ROW]
[ROW][C]0.38[/C][C]476.949118362485[/C][C]16.6555483369687[/C][/ROW]
[ROW][C]0.39[/C][C]479.860371472434[/C][C]17.0354469351894[/C][/ROW]
[ROW][C]0.4[/C][C]482.825698199221[/C][C]17.4215941270374[/C][/ROW]
[ROW][C]0.41[/C][C]485.849007829924[/C][C]17.8231884116469[/C][/ROW]
[ROW][C]0.42[/C][C]488.936609857837[/C][C]18.2551589846658[/C][/ROW]
[ROW][C]0.43[/C][C]492.09810545614[/C][C]18.7397936547694[/C][/ROW]
[ROW][C]0.44[/C][C]495.347292907606[/C][C]19.3069638979258[/C][/ROW]
[ROW][C]0.45[/C][C]498.702922065777[/C][C]19.9935585692565[/C][/ROW]
[ROW][C]0.46[/C][C]502.189106002946[/C][C]20.8384102390391[/C][/ROW]
[ROW][C]0.47[/C][C]505.83519573822[/C][C]21.8807537666656[/C][/ROW]
[ROW][C]0.48[/C][C]509.674951223869[/C][C]23.15079387455[/C][/ROW]
[ROW][C]0.49[/C][C]513.744900239064[/C][C]24.6659063926611[/C][/ROW]
[ROW][C]0.5[/C][C]518.081864096719[/C][C]26.4211213975795[/C][/ROW]
[ROW][C]0.51[/C][C]522.719738192546[/C][C]28.3886949851923[/C][/ROW]
[ROW][C]0.52[/C][C]527.685734959177[/C][C]30.5132983415855[/C][/ROW]
[ROW][C]0.53[/C][C]532.996411337054[/C][C]32.7122423125647[/C][/ROW]
[ROW][C]0.54[/C][C]538.653894474731[/C][C]34.8821759132617[/C][/ROW]
[ROW][C]0.55[/C][C]544.642769731995[/C][C]36.9013154341236[/C][/ROW]
[ROW][C]0.56[/C][C]550.928088602588[/C][C]38.6423709518819[/C][/ROW]
[ROW][C]0.57[/C][C]557.454881556824[/C][C]39.978153112299[/C][/ROW]
[ROW][C]0.58[/C][C]564.149422255973[/C][C]40.7976917525276[/C][/ROW]
[ROW][C]0.59[/C][C]570.92229712841[/C][C]41.0140460400911[/C][/ROW]
[ROW][C]0.6[/C][C]577.673111856823[/C][C]40.5759493304748[/C][/ROW]
[ROW][C]0.61[/C][C]584.296447105548[/C][C]39.4709650236392[/C][/ROW]
[ROW][C]0.62[/C][C]590.688496828076[/C][C]37.731390001046[/C][/ROW]
[ROW][C]0.63[/C][C]596.75371716104[/C][C]35.4301274444718[/C][/ROW]
[ROW][C]0.64[/C][C]602.410804390617[/C][C]32.6726478365059[/C][/ROW]
[ROW][C]0.65[/C][C]607.59741178122[/C][C]29.5903864961665[/C][/ROW]
[ROW][C]0.66[/C][C]612.273192820443[/C][C]26.3262669285649[/C][/ROW]
[ROW][C]0.67[/C][C]616.42099130349[/C][C]23.0232901993012[/C][/ROW]
[ROW][C]0.68[/C][C]620.046244941092[/C][C]19.8149147569105[/C][/ROW]
[ROW][C]0.69[/C][C]623.174885935616[/C][C]16.8141775836894[/C][/ROW]
[ROW][C]0.7[/C][C]625.850174347408[/C][C]14.1109624102066[/C][/ROW]
[ROW][C]0.71[/C][C]628.128967818773[/C][C]11.7706434205001[/C][/ROW]
[ROW][C]0.72[/C][C]630.077911108299[/C][C]9.83519325293203[/C][/ROW]
[ROW][C]0.73[/C][C]631.769932675029[/C][C]8.32983572290461[/C][/ROW]
[ROW][C]0.74[/C][C]633.281284984368[/C][C]7.26690393297802[/C][/ROW]
[ROW][C]0.75[/C][C]634.689186548201[/C][C]6.64909157957272[/C][/ROW]
[ROW][C]0.76[/C][C]636.069944368177[/C][C]6.46459204166475[/C][/ROW]
[ROW][C]0.77[/C][C]637.497284012188[/C][C]6.68052264033097[/C][/ROW]
[ROW][C]0.78[/C][C]639.040523317517[/C][C]7.24782914125465[/C][/ROW]
[ROW][C]0.79[/C][C]640.762232343259[/C][C]8.10287198638615[/C][/ROW]
[ROW][C]0.8[/C][C]642.715165654198[/C][C]9.17355079893205[/C][/ROW]
[ROW][C]0.81[/C][C]644.938559663576[/C][C]10.3748224045889[/C][/ROW]
[ROW][C]0.82[/C][C]647.454347088065[/C][C]11.6078577451397[/C][/ROW]
[ROW][C]0.83[/C][C]650.264376232918[/C][C]12.7600322158736[/C][/ROW]
[ROW][C]0.84[/C][C]653.350171232528[/C][C]13.7190875481439[/C][/ROW]
[ROW][C]0.85[/C][C]656.676882454609[/C][C]14.3894663290947[/C][/ROW]
[ROW][C]0.86[/C][C]660.202564780714[/C][C]14.721856376448[/C][/ROW]
[ROW][C]0.87[/C][C]663.892549911033[/C][C]14.7368038912403[/C][/ROW]
[ROW][C]0.88[/C][C]667.736415797079[/C][C]14.5456996008474[/C][/ROW]
[ROW][C]0.89[/C][C]671.762274716744[/C][C]14.3505433302869[/C][/ROW]
[ROW][C]0.9[/C][C]676.040800380667[/C][C]14.4002331465004[/C][/ROW]
[ROW][C]0.91[/C][C]680.67135722991[/C][C]14.8825518932012[/C][/ROW]
[ROW][C]0.92[/C][C]685.747067621519[/C][C]15.7749774559078[/C][/ROW]
[ROW][C]0.93[/C][C]691.306227799525[/C][C]16.7595671239688[/C][/ROW]
[ROW][C]0.94[/C][C]697.292031538707[/C][C]17.2899763444088[/C][/ROW]
[ROW][C]0.95[/C][C]703.55080902394[/C][C]16.8156987743008[/C][/ROW]
[ROW][C]0.96[/C][C]709.881169120537[/C][C]15.1340408386654[/C][/ROW]
[ROW][C]0.97[/C][C]716.087420938667[/C][C]12.7884418963609[/C][/ROW]
[ROW][C]0.98[/C][C]721.92349690103[/C][C]11.208797583514[/C][/ROW]
[ROW][C]0.99[/C][C]726.868396637842[/C][C]11.5407557582687[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284939&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284939&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
0.01398.5658169622581.98856731428469
0.02399.5363621233522.34305332955961
0.03400.793902429323.0573703254053
0.04402.2625169424853.89343191042346
0.05403.9036129855084.6826836865702
0.06405.6903311856295.39077094954237
0.07407.5970023984336.04448075254022
0.08409.5990921840546.65698453484789
0.09411.6734561996737.20670130101726
0.1413.7965377097497.65337119936496
0.11415.9429637397657.96503611077268
0.12418.0865850258618.1383799248663
0.13420.2037334045558.19733212221444
0.14422.2770166838388.18770613566093
0.15424.2979491935328.16340842460674
0.16426.2675556055648.17236882216434
0.17428.1950375148948.24825017698924
0.18430.0952067514918.40683805569033
0.19431.9855617937688.6474118419435
0.2433.8837221195558.95930441563158
0.21435.8056175281019.32851071508883
0.22437.7645108600529.74115511210101
0.23439.77070790699810.1858224653827
0.24441.83170871655710.6529547981356
0.25443.95256277431711.1347234627105
0.26446.1362634465411.6235674871641
0.27448.38410681753712.1110190138223
0.28450.69601022220512.590072407547
0.29453.07081903898913.0550201911607
0.3455.50662812182313.5030143923395
0.31458.00112066204413.9327050869054
0.32460.55190044661814.3453075406289
0.33463.15677824247614.7444478507103
0.34465.81397657581115.1346335573296
0.35468.52223837266415.5183455439112
0.36471.28085647084615.8983057994041
0.37474.08967279339616.2768354563909
0.38476.94911836248516.6555483369687
0.39479.86037147243417.0354469351894
0.4482.82569819922117.4215941270374
0.41485.84900782992417.8231884116469
0.42488.93660985783718.2551589846658
0.43492.0981054561418.7397936547694
0.44495.34729290760619.3069638979258
0.45498.70292206577719.9935585692565
0.46502.18910600294620.8384102390391
0.47505.8351957382221.8807537666656
0.48509.67495122386923.15079387455
0.49513.74490023906424.6659063926611
0.5518.08186409671926.4211213975795
0.51522.71973819254628.3886949851923
0.52527.68573495917730.5132983415855
0.53532.99641133705432.7122423125647
0.54538.65389447473134.8821759132617
0.55544.64276973199536.9013154341236
0.56550.92808860258838.6423709518819
0.57557.45488155682439.978153112299
0.58564.14942225597340.7976917525276
0.59570.9222971284141.0140460400911
0.6577.67311185682340.5759493304748
0.61584.29644710554839.4709650236392
0.62590.68849682807637.731390001046
0.63596.7537171610435.4301274444718
0.64602.41080439061732.6726478365059
0.65607.5974117812229.5903864961665
0.66612.27319282044326.3262669285649
0.67616.4209913034923.0232901993012
0.68620.04624494109219.8149147569105
0.69623.17488593561616.8141775836894
0.7625.85017434740814.1109624102066
0.71628.12896781877311.7706434205001
0.72630.0779111082999.83519325293203
0.73631.7699326750298.32983572290461
0.74633.2812849843687.26690393297802
0.75634.6891865482016.64909157957272
0.76636.0699443681776.46459204166475
0.77637.4972840121886.68052264033097
0.78639.0405233175177.24782914125465
0.79640.7622323432598.10287198638615
0.8642.7151656541989.17355079893205
0.81644.93855966357610.3748224045889
0.82647.45434708806511.6078577451397
0.83650.26437623291812.7600322158736
0.84653.35017123252813.7190875481439
0.85656.67688245460914.3894663290947
0.86660.20256478071414.721856376448
0.87663.89254991103314.7368038912403
0.88667.73641579707914.5456996008474
0.89671.76227471674414.3505433302869
0.9676.04080038066714.4002331465004
0.91680.6713572299114.8825518932012
0.92685.74706762151915.7749774559078
0.93691.30622779952516.7595671239688
0.94697.29203153870717.2899763444088
0.95703.5508090239416.8156987743008
0.96709.88116912053715.1340408386654
0.97716.08742093866712.7884418963609
0.98721.9234969010311.208797583514
0.99726.86839663784211.5407557582687


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')