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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 computationFri, 16 Aug 2013 05:20:51 -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/2013/Aug/16/t1376644879i3857bncfgq51oy.htm/, Retrieved Sun, 28 Apr 2024 09:24:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=211111, Retrieved Sun, 28 Apr 2024 09:24:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsStefanie Gubbi
Estimated Impact176

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] [Tijdreeks 2 - Stap 7] [2013-08-16 09:20:51] [3958f9c0a64aeec6b83979b094ee8a96] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
660
770
792
693
726
814
770
737
792
693
770
847
627
704
792
693
770
770
737
836
957
737
891
891
671
660
803
693
825
847
726
869
979
748
880
946
737
671
759
748
814
836
737
825
979
803
825
1034
814
704
704
825
847
858
704
803
1067
858
792
1155
869
671
583
825
803
957
737
825
1199
913
814
1111
858
704
649
847
715
968
770
869
1254
946
693
1166
924
792
627
869
627
880
869
858
1232
935
660
1155
891
825
605
814
550
825
902
891
1199
902
693
1188

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' @ fisher.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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211111&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' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211111&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211111&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' @ fisher.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01568.04383475704828.284763654495
0.02591.50085837821624.1765713123281
0.03610.13836030269820.1773276785667
0.04623.62325121893117.494096968415
0.05634.00752974810116.8733745228436
0.06642.78740240378716.7561423312537
0.07650.58369364787416.0647248500921
0.08657.54700377145215.0451156815469
0.09663.76417211656414.2802216970049
0.1669.38217324932913.9009207940406
0.11674.54109256311413.6064870915918
0.12679.30451241812813.078650034429
0.13683.66746826569512.2360475917577
0.14687.61471751956611.2488478478026
0.15691.17411963760210.4100545114966
0.16694.4343984083569.98303646824813
0.17697.52851593000710.0898130667723
0.18700.60040317835610.6909597236401
0.19703.77274844781311.6394416729442
0.2707.12563304003812.7443027943558
0.21710.68832871463213.812194575432
0.22714.44282561530614.6808328420205
0.23718.33655892362615.2506926297126
0.24722.30109312763415.5076741211394
0.25726.27233203472115.5198717464379
0.26730.20698696404815.4225217232166
0.27734.09080120032915.3628775314952
0.28737.93669045542115.4506193909172
0.29741.77450871886815.7195089300789
0.3745.63695170716916.1270000004779
0.31749.54692673341916.5792582055682
0.32753.51036011409116.9769206027652
0.33757.51572572551317.2487630641332
0.34761.53888727273917.3640092677263
0.35765.55026326849717.3309919455379
0.36769.52127182490317.1784479303835
0.37773.42816654282716.9386282446819
0.38777.2529574284716.6331520896816
0.39780.98234056349516.2730711685558
0.4784.60600843263615.8590747907606
0.41788.11541523163415.3935966535741
0.42791.50339441192614.8831100703858
0.43794.76440654937514.3406660131696
0.44797.89491631923713.779691488572
0.45800.89349464756913.2133683260499
0.46803.76056148873512.6500911729774
0.47806.49800894652712.0932785676271
0.48809.10910957437511.5464308868346
0.49811.59906138436811.017930278826
0.5813.97628364608710.5223941329671
0.51816.25424441346810.0868626648698
0.52818.4532801757289.74966326783001
0.53820.6016684642629.55446171063149
0.54822.7352270964799.54153264989596
0.55824.8949859626789.73611136594666
0.56827.12297729605610.1346767502408
0.57829.45679053526610.6974797547305
0.58831.92403862513611.3562261793625
0.59834.53808331620412.027475813971
0.6837.29615698424812.6299656506591
0.61840.18044021342613.097482374735
0.62843.16189902096113.3916800170956
0.63846.20601423355213.5055368941447
0.64849.2791632755113.4609416463327
0.65852.35441915262313.3025059133352
0.66855.41583642085813.0907889082463
0.67858.46073515936512.885714653574
0.68861.49992411274112.7483672422729
0.69864.55616613133712.7247664841086
0.7867.66150489036112.8462563821599
0.71870.85435294381113.1277503715545
0.72874.1773905664913.5666839633713
0.73877.67713061371114.1656692289398
0.74881.40527770718214.9332748352423
0.75885.42081523266415.8966259985693
0.76889.79057628251917.0902805577549
0.77894.58572412644118.5275886794444
0.78899.87287000803320.1703538618693
0.79905.7016744448221.9135618492285
0.8912.09487566513823.6007079171372
0.81919.04994244360125.0922348873362
0.82926.56172038093426.3473332191244
0.83934.67074034621327.5297466615916
0.84943.53170386120629.0782791026203
0.85953.4821974768231.683034112535
0.86965.07641676573936.0885358390509
0.87979.03956961081942.7022162835094
0.88996.10679470452551.1785870189699
0.891016.7481286474760.2070030933256
0.91040.8508804662267.6487111843506
0.911067.5080357558271.1277432160834
0.921095.0845087770869.0122903778635
0.931121.6338015311261.3651892773917
0.941145.5301335151750.153084534177
0.951166.0418002278438.3618216002501
0.961183.6974580437828.7208054636116
0.971200.4495903410123.5831922385104
0.981219.0340434891723.683068594079
0.991239.6010390502523.6792840453542

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 568.043834757048 & 28.284763654495 \tabularnewline
0.02 & 591.500858378216 & 24.1765713123281 \tabularnewline
0.03 & 610.138360302698 & 20.1773276785667 \tabularnewline
0.04 & 623.623251218931 & 17.494096968415 \tabularnewline
0.05 & 634.007529748101 & 16.8733745228436 \tabularnewline
0.06 & 642.787402403787 & 16.7561423312537 \tabularnewline
0.07 & 650.583693647874 & 16.0647248500921 \tabularnewline
0.08 & 657.547003771452 & 15.0451156815469 \tabularnewline
0.09 & 663.764172116564 & 14.2802216970049 \tabularnewline
0.1 & 669.382173249329 & 13.9009207940406 \tabularnewline
0.11 & 674.541092563114 & 13.6064870915918 \tabularnewline
0.12 & 679.304512418128 & 13.078650034429 \tabularnewline
0.13 & 683.667468265695 & 12.2360475917577 \tabularnewline
0.14 & 687.614717519566 & 11.2488478478026 \tabularnewline
0.15 & 691.174119637602 & 10.4100545114966 \tabularnewline
0.16 & 694.434398408356 & 9.98303646824813 \tabularnewline
0.17 & 697.528515930007 & 10.0898130667723 \tabularnewline
0.18 & 700.600403178356 & 10.6909597236401 \tabularnewline
0.19 & 703.772748447813 & 11.6394416729442 \tabularnewline
0.2 & 707.125633040038 & 12.7443027943558 \tabularnewline
0.21 & 710.688328714632 & 13.812194575432 \tabularnewline
0.22 & 714.442825615306 & 14.6808328420205 \tabularnewline
0.23 & 718.336558923626 & 15.2506926297126 \tabularnewline
0.24 & 722.301093127634 & 15.5076741211394 \tabularnewline
0.25 & 726.272332034721 & 15.5198717464379 \tabularnewline
0.26 & 730.206986964048 & 15.4225217232166 \tabularnewline
0.27 & 734.090801200329 & 15.3628775314952 \tabularnewline
0.28 & 737.936690455421 & 15.4506193909172 \tabularnewline
0.29 & 741.774508718868 & 15.7195089300789 \tabularnewline
0.3 & 745.636951707169 & 16.1270000004779 \tabularnewline
0.31 & 749.546926733419 & 16.5792582055682 \tabularnewline
0.32 & 753.510360114091 & 16.9769206027652 \tabularnewline
0.33 & 757.515725725513 & 17.2487630641332 \tabularnewline
0.34 & 761.538887272739 & 17.3640092677263 \tabularnewline
0.35 & 765.550263268497 & 17.3309919455379 \tabularnewline
0.36 & 769.521271824903 & 17.1784479303835 \tabularnewline
0.37 & 773.428166542827 & 16.9386282446819 \tabularnewline
0.38 & 777.25295742847 & 16.6331520896816 \tabularnewline
0.39 & 780.982340563495 & 16.2730711685558 \tabularnewline
0.4 & 784.606008432636 & 15.8590747907606 \tabularnewline
0.41 & 788.115415231634 & 15.3935966535741 \tabularnewline
0.42 & 791.503394411926 & 14.8831100703858 \tabularnewline
0.43 & 794.764406549375 & 14.3406660131696 \tabularnewline
0.44 & 797.894916319237 & 13.779691488572 \tabularnewline
0.45 & 800.893494647569 & 13.2133683260499 \tabularnewline
0.46 & 803.760561488735 & 12.6500911729774 \tabularnewline
0.47 & 806.498008946527 & 12.0932785676271 \tabularnewline
0.48 & 809.109109574375 & 11.5464308868346 \tabularnewline
0.49 & 811.599061384368 & 11.017930278826 \tabularnewline
0.5 & 813.976283646087 & 10.5223941329671 \tabularnewline
0.51 & 816.254244413468 & 10.0868626648698 \tabularnewline
0.52 & 818.453280175728 & 9.74966326783001 \tabularnewline
0.53 & 820.601668464262 & 9.55446171063149 \tabularnewline
0.54 & 822.735227096479 & 9.54153264989596 \tabularnewline
0.55 & 824.894985962678 & 9.73611136594666 \tabularnewline
0.56 & 827.122977296056 & 10.1346767502408 \tabularnewline
0.57 & 829.456790535266 & 10.6974797547305 \tabularnewline
0.58 & 831.924038625136 & 11.3562261793625 \tabularnewline
0.59 & 834.538083316204 & 12.027475813971 \tabularnewline
0.6 & 837.296156984248 & 12.6299656506591 \tabularnewline
0.61 & 840.180440213426 & 13.097482374735 \tabularnewline
0.62 & 843.161899020961 & 13.3916800170956 \tabularnewline
0.63 & 846.206014233552 & 13.5055368941447 \tabularnewline
0.64 & 849.27916327551 & 13.4609416463327 \tabularnewline
0.65 & 852.354419152623 & 13.3025059133352 \tabularnewline
0.66 & 855.415836420858 & 13.0907889082463 \tabularnewline
0.67 & 858.460735159365 & 12.885714653574 \tabularnewline
0.68 & 861.499924112741 & 12.7483672422729 \tabularnewline
0.69 & 864.556166131337 & 12.7247664841086 \tabularnewline
0.7 & 867.661504890361 & 12.8462563821599 \tabularnewline
0.71 & 870.854352943811 & 13.1277503715545 \tabularnewline
0.72 & 874.17739056649 & 13.5666839633713 \tabularnewline
0.73 & 877.677130613711 & 14.1656692289398 \tabularnewline
0.74 & 881.405277707182 & 14.9332748352423 \tabularnewline
0.75 & 885.420815232664 & 15.8966259985693 \tabularnewline
0.76 & 889.790576282519 & 17.0902805577549 \tabularnewline
0.77 & 894.585724126441 & 18.5275886794444 \tabularnewline
0.78 & 899.872870008033 & 20.1703538618693 \tabularnewline
0.79 & 905.70167444482 & 21.9135618492285 \tabularnewline
0.8 & 912.094875665138 & 23.6007079171372 \tabularnewline
0.81 & 919.049942443601 & 25.0922348873362 \tabularnewline
0.82 & 926.561720380934 & 26.3473332191244 \tabularnewline
0.83 & 934.670740346213 & 27.5297466615916 \tabularnewline
0.84 & 943.531703861206 & 29.0782791026203 \tabularnewline
0.85 & 953.48219747682 & 31.683034112535 \tabularnewline
0.86 & 965.076416765739 & 36.0885358390509 \tabularnewline
0.87 & 979.039569610819 & 42.7022162835094 \tabularnewline
0.88 & 996.106794704525 & 51.1785870189699 \tabularnewline
0.89 & 1016.74812864747 & 60.2070030933256 \tabularnewline
0.9 & 1040.85088046622 & 67.6487111843506 \tabularnewline
0.91 & 1067.50803575582 & 71.1277432160834 \tabularnewline
0.92 & 1095.08450877708 & 69.0122903778635 \tabularnewline
0.93 & 1121.63380153112 & 61.3651892773917 \tabularnewline
0.94 & 1145.53013351517 & 50.153084534177 \tabularnewline
0.95 & 1166.04180022784 & 38.3618216002501 \tabularnewline
0.96 & 1183.69745804378 & 28.7208054636116 \tabularnewline
0.97 & 1200.44959034101 & 23.5831922385104 \tabularnewline
0.98 & 1219.03404348917 & 23.683068594079 \tabularnewline
0.99 & 1239.60103905025 & 23.6792840453542 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211111&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]568.043834757048[/C][C]28.284763654495[/C][/ROW]
[ROW][C]0.02[/C][C]591.500858378216[/C][C]24.1765713123281[/C][/ROW]
[ROW][C]0.03[/C][C]610.138360302698[/C][C]20.1773276785667[/C][/ROW]
[ROW][C]0.04[/C][C]623.623251218931[/C][C]17.494096968415[/C][/ROW]
[ROW][C]0.05[/C][C]634.007529748101[/C][C]16.8733745228436[/C][/ROW]
[ROW][C]0.06[/C][C]642.787402403787[/C][C]16.7561423312537[/C][/ROW]
[ROW][C]0.07[/C][C]650.583693647874[/C][C]16.0647248500921[/C][/ROW]
[ROW][C]0.08[/C][C]657.547003771452[/C][C]15.0451156815469[/C][/ROW]
[ROW][C]0.09[/C][C]663.764172116564[/C][C]14.2802216970049[/C][/ROW]
[ROW][C]0.1[/C][C]669.382173249329[/C][C]13.9009207940406[/C][/ROW]
[ROW][C]0.11[/C][C]674.541092563114[/C][C]13.6064870915918[/C][/ROW]
[ROW][C]0.12[/C][C]679.304512418128[/C][C]13.078650034429[/C][/ROW]
[ROW][C]0.13[/C][C]683.667468265695[/C][C]12.2360475917577[/C][/ROW]
[ROW][C]0.14[/C][C]687.614717519566[/C][C]11.2488478478026[/C][/ROW]
[ROW][C]0.15[/C][C]691.174119637602[/C][C]10.4100545114966[/C][/ROW]
[ROW][C]0.16[/C][C]694.434398408356[/C][C]9.98303646824813[/C][/ROW]
[ROW][C]0.17[/C][C]697.528515930007[/C][C]10.0898130667723[/C][/ROW]
[ROW][C]0.18[/C][C]700.600403178356[/C][C]10.6909597236401[/C][/ROW]
[ROW][C]0.19[/C][C]703.772748447813[/C][C]11.6394416729442[/C][/ROW]
[ROW][C]0.2[/C][C]707.125633040038[/C][C]12.7443027943558[/C][/ROW]
[ROW][C]0.21[/C][C]710.688328714632[/C][C]13.812194575432[/C][/ROW]
[ROW][C]0.22[/C][C]714.442825615306[/C][C]14.6808328420205[/C][/ROW]
[ROW][C]0.23[/C][C]718.336558923626[/C][C]15.2506926297126[/C][/ROW]
[ROW][C]0.24[/C][C]722.301093127634[/C][C]15.5076741211394[/C][/ROW]
[ROW][C]0.25[/C][C]726.272332034721[/C][C]15.5198717464379[/C][/ROW]
[ROW][C]0.26[/C][C]730.206986964048[/C][C]15.4225217232166[/C][/ROW]
[ROW][C]0.27[/C][C]734.090801200329[/C][C]15.3628775314952[/C][/ROW]
[ROW][C]0.28[/C][C]737.936690455421[/C][C]15.4506193909172[/C][/ROW]
[ROW][C]0.29[/C][C]741.774508718868[/C][C]15.7195089300789[/C][/ROW]
[ROW][C]0.3[/C][C]745.636951707169[/C][C]16.1270000004779[/C][/ROW]
[ROW][C]0.31[/C][C]749.546926733419[/C][C]16.5792582055682[/C][/ROW]
[ROW][C]0.32[/C][C]753.510360114091[/C][C]16.9769206027652[/C][/ROW]
[ROW][C]0.33[/C][C]757.515725725513[/C][C]17.2487630641332[/C][/ROW]
[ROW][C]0.34[/C][C]761.538887272739[/C][C]17.3640092677263[/C][/ROW]
[ROW][C]0.35[/C][C]765.550263268497[/C][C]17.3309919455379[/C][/ROW]
[ROW][C]0.36[/C][C]769.521271824903[/C][C]17.1784479303835[/C][/ROW]
[ROW][C]0.37[/C][C]773.428166542827[/C][C]16.9386282446819[/C][/ROW]
[ROW][C]0.38[/C][C]777.25295742847[/C][C]16.6331520896816[/C][/ROW]
[ROW][C]0.39[/C][C]780.982340563495[/C][C]16.2730711685558[/C][/ROW]
[ROW][C]0.4[/C][C]784.606008432636[/C][C]15.8590747907606[/C][/ROW]
[ROW][C]0.41[/C][C]788.115415231634[/C][C]15.3935966535741[/C][/ROW]
[ROW][C]0.42[/C][C]791.503394411926[/C][C]14.8831100703858[/C][/ROW]
[ROW][C]0.43[/C][C]794.764406549375[/C][C]14.3406660131696[/C][/ROW]
[ROW][C]0.44[/C][C]797.894916319237[/C][C]13.779691488572[/C][/ROW]
[ROW][C]0.45[/C][C]800.893494647569[/C][C]13.2133683260499[/C][/ROW]
[ROW][C]0.46[/C][C]803.760561488735[/C][C]12.6500911729774[/C][/ROW]
[ROW][C]0.47[/C][C]806.498008946527[/C][C]12.0932785676271[/C][/ROW]
[ROW][C]0.48[/C][C]809.109109574375[/C][C]11.5464308868346[/C][/ROW]
[ROW][C]0.49[/C][C]811.599061384368[/C][C]11.017930278826[/C][/ROW]
[ROW][C]0.5[/C][C]813.976283646087[/C][C]10.5223941329671[/C][/ROW]
[ROW][C]0.51[/C][C]816.254244413468[/C][C]10.0868626648698[/C][/ROW]
[ROW][C]0.52[/C][C]818.453280175728[/C][C]9.74966326783001[/C][/ROW]
[ROW][C]0.53[/C][C]820.601668464262[/C][C]9.55446171063149[/C][/ROW]
[ROW][C]0.54[/C][C]822.735227096479[/C][C]9.54153264989596[/C][/ROW]
[ROW][C]0.55[/C][C]824.894985962678[/C][C]9.73611136594666[/C][/ROW]
[ROW][C]0.56[/C][C]827.122977296056[/C][C]10.1346767502408[/C][/ROW]
[ROW][C]0.57[/C][C]829.456790535266[/C][C]10.6974797547305[/C][/ROW]
[ROW][C]0.58[/C][C]831.924038625136[/C][C]11.3562261793625[/C][/ROW]
[ROW][C]0.59[/C][C]834.538083316204[/C][C]12.027475813971[/C][/ROW]
[ROW][C]0.6[/C][C]837.296156984248[/C][C]12.6299656506591[/C][/ROW]
[ROW][C]0.61[/C][C]840.180440213426[/C][C]13.097482374735[/C][/ROW]
[ROW][C]0.62[/C][C]843.161899020961[/C][C]13.3916800170956[/C][/ROW]
[ROW][C]0.63[/C][C]846.206014233552[/C][C]13.5055368941447[/C][/ROW]
[ROW][C]0.64[/C][C]849.27916327551[/C][C]13.4609416463327[/C][/ROW]
[ROW][C]0.65[/C][C]852.354419152623[/C][C]13.3025059133352[/C][/ROW]
[ROW][C]0.66[/C][C]855.415836420858[/C][C]13.0907889082463[/C][/ROW]
[ROW][C]0.67[/C][C]858.460735159365[/C][C]12.885714653574[/C][/ROW]
[ROW][C]0.68[/C][C]861.499924112741[/C][C]12.7483672422729[/C][/ROW]
[ROW][C]0.69[/C][C]864.556166131337[/C][C]12.7247664841086[/C][/ROW]
[ROW][C]0.7[/C][C]867.661504890361[/C][C]12.8462563821599[/C][/ROW]
[ROW][C]0.71[/C][C]870.854352943811[/C][C]13.1277503715545[/C][/ROW]
[ROW][C]0.72[/C][C]874.17739056649[/C][C]13.5666839633713[/C][/ROW]
[ROW][C]0.73[/C][C]877.677130613711[/C][C]14.1656692289398[/C][/ROW]
[ROW][C]0.74[/C][C]881.405277707182[/C][C]14.9332748352423[/C][/ROW]
[ROW][C]0.75[/C][C]885.420815232664[/C][C]15.8966259985693[/C][/ROW]
[ROW][C]0.76[/C][C]889.790576282519[/C][C]17.0902805577549[/C][/ROW]
[ROW][C]0.77[/C][C]894.585724126441[/C][C]18.5275886794444[/C][/ROW]
[ROW][C]0.78[/C][C]899.872870008033[/C][C]20.1703538618693[/C][/ROW]
[ROW][C]0.79[/C][C]905.70167444482[/C][C]21.9135618492285[/C][/ROW]
[ROW][C]0.8[/C][C]912.094875665138[/C][C]23.6007079171372[/C][/ROW]
[ROW][C]0.81[/C][C]919.049942443601[/C][C]25.0922348873362[/C][/ROW]
[ROW][C]0.82[/C][C]926.561720380934[/C][C]26.3473332191244[/C][/ROW]
[ROW][C]0.83[/C][C]934.670740346213[/C][C]27.5297466615916[/C][/ROW]
[ROW][C]0.84[/C][C]943.531703861206[/C][C]29.0782791026203[/C][/ROW]
[ROW][C]0.85[/C][C]953.48219747682[/C][C]31.683034112535[/C][/ROW]
[ROW][C]0.86[/C][C]965.076416765739[/C][C]36.0885358390509[/C][/ROW]
[ROW][C]0.87[/C][C]979.039569610819[/C][C]42.7022162835094[/C][/ROW]
[ROW][C]0.88[/C][C]996.106794704525[/C][C]51.1785870189699[/C][/ROW]
[ROW][C]0.89[/C][C]1016.74812864747[/C][C]60.2070030933256[/C][/ROW]
[ROW][C]0.9[/C][C]1040.85088046622[/C][C]67.6487111843506[/C][/ROW]
[ROW][C]0.91[/C][C]1067.50803575582[/C][C]71.1277432160834[/C][/ROW]
[ROW][C]0.92[/C][C]1095.08450877708[/C][C]69.0122903778635[/C][/ROW]
[ROW][C]0.93[/C][C]1121.63380153112[/C][C]61.3651892773917[/C][/ROW]
[ROW][C]0.94[/C][C]1145.53013351517[/C][C]50.153084534177[/C][/ROW]
[ROW][C]0.95[/C][C]1166.04180022784[/C][C]38.3618216002501[/C][/ROW]
[ROW][C]0.96[/C][C]1183.69745804378[/C][C]28.7208054636116[/C][/ROW]
[ROW][C]0.97[/C][C]1200.44959034101[/C][C]23.5831922385104[/C][/ROW]
[ROW][C]0.98[/C][C]1219.03404348917[/C][C]23.683068594079[/C][/ROW]
[ROW][C]0.99[/C][C]1239.60103905025[/C][C]23.6792840453542[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211111&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211111&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
0.01568.04383475704828.284763654495
0.02591.50085837821624.1765713123281
0.03610.13836030269820.1773276785667
0.04623.62325121893117.494096968415
0.05634.00752974810116.8733745228436
0.06642.78740240378716.7561423312537
0.07650.58369364787416.0647248500921
0.08657.54700377145215.0451156815469
0.09663.76417211656414.2802216970049
0.1669.38217324932913.9009207940406
0.11674.54109256311413.6064870915918
0.12679.30451241812813.078650034429
0.13683.66746826569512.2360475917577
0.14687.61471751956611.2488478478026
0.15691.17411963760210.4100545114966
0.16694.4343984083569.98303646824813
0.17697.52851593000710.0898130667723
0.18700.60040317835610.6909597236401
0.19703.77274844781311.6394416729442
0.2707.12563304003812.7443027943558
0.21710.68832871463213.812194575432
0.22714.44282561530614.6808328420205
0.23718.33655892362615.2506926297126
0.24722.30109312763415.5076741211394
0.25726.27233203472115.5198717464379
0.26730.20698696404815.4225217232166
0.27734.09080120032915.3628775314952
0.28737.93669045542115.4506193909172
0.29741.77450871886815.7195089300789
0.3745.63695170716916.1270000004779
0.31749.54692673341916.5792582055682
0.32753.51036011409116.9769206027652
0.33757.51572572551317.2487630641332
0.34761.53888727273917.3640092677263
0.35765.55026326849717.3309919455379
0.36769.52127182490317.1784479303835
0.37773.42816654282716.9386282446819
0.38777.2529574284716.6331520896816
0.39780.98234056349516.2730711685558
0.4784.60600843263615.8590747907606
0.41788.11541523163415.3935966535741
0.42791.50339441192614.8831100703858
0.43794.76440654937514.3406660131696
0.44797.89491631923713.779691488572
0.45800.89349464756913.2133683260499
0.46803.76056148873512.6500911729774
0.47806.49800894652712.0932785676271
0.48809.10910957437511.5464308868346
0.49811.59906138436811.017930278826
0.5813.97628364608710.5223941329671
0.51816.25424441346810.0868626648698
0.52818.4532801757289.74966326783001
0.53820.6016684642629.55446171063149
0.54822.7352270964799.54153264989596
0.55824.8949859626789.73611136594666
0.56827.12297729605610.1346767502408
0.57829.45679053526610.6974797547305
0.58831.92403862513611.3562261793625
0.59834.53808331620412.027475813971
0.6837.29615698424812.6299656506591
0.61840.18044021342613.097482374735
0.62843.16189902096113.3916800170956
0.63846.20601423355213.5055368941447
0.64849.2791632755113.4609416463327
0.65852.35441915262313.3025059133352
0.66855.41583642085813.0907889082463
0.67858.46073515936512.885714653574
0.68861.49992411274112.7483672422729
0.69864.55616613133712.7247664841086
0.7867.66150489036112.8462563821599
0.71870.85435294381113.1277503715545
0.72874.1773905664913.5666839633713
0.73877.67713061371114.1656692289398
0.74881.40527770718214.9332748352423
0.75885.42081523266415.8966259985693
0.76889.79057628251917.0902805577549
0.77894.58572412644118.5275886794444
0.78899.87287000803320.1703538618693
0.79905.7016744448221.9135618492285
0.8912.09487566513823.6007079171372
0.81919.04994244360125.0922348873362
0.82926.56172038093426.3473332191244
0.83934.67074034621327.5297466615916
0.84943.53170386120629.0782791026203
0.85953.4821974768231.683034112535
0.86965.07641676573936.0885358390509
0.87979.03956961081942.7022162835094
0.88996.10679470452551.1785870189699
0.891016.7481286474760.2070030933256
0.91040.8508804662267.6487111843506
0.911067.5080357558271.1277432160834
0.921095.0845087770869.0122903778635
0.931121.6338015311261.3651892773917
0.941145.5301335151750.153084534177
0.951166.0418002278438.3618216002501
0.961183.6974580437828.7208054636116
0.971200.4495903410123.5831922385104
0.981219.0340434891723.683068594079
0.991239.6010390502523.6792840453542


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')