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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationTue, 02 Jun 2009 10:58:24 -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/Jun/02/t1243961931yemudpomgd7g20h.htm/, Retrieved Thu, 09 May 2024 20:37:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=41324, Retrieved Thu, 09 May 2024 20:37:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Harrell-Davis Quantiles] [DECIELEN WERKLOZE...] [2009-06-02 16:58:24] [cec0b6ecf0cab4e1552eba4b21b592a6] [Current]
-         [Harrell-Davis Quantiles] [DECIELEN WERKLOZE...] [2009-06-02 17:05:36] [f4d91a94613ac4c8d4f7075ea31c5ee8]
- RMP     [Central Tendency] [CENTRUMMATEN WERK...] [2009-06-02 17:13:56] [f4d91a94613ac4c8d4f7075ea31c5ee8]
- RMP     [Mean versus Median] [MEAN VS MEDIAN - ...] [2009-06-02 17:18:28] [f4d91a94613ac4c8d4f7075ea31c5ee8]
- RMP     [Mean Plot] [MEAN PLOT WERKLOZ...] [2009-06-02 17:23:53] [f4d91a94613ac4c8d4f7075ea31c5ee8]
- RMP     [Univariate Data Series] [PLOT WERKLOZEN - ...] [2009-06-02 17:29:37] [f4d91a94613ac4c8d4f7075ea31c5ee8]
- RMP     [(Partial) Autocorrelation Function] [AUTOCORRELATIE WE...] [2009-06-02 17:33:47] [f4d91a94613ac4c8d4f7075ea31c5ee8]
- RMP     [Blocked Bootstrap Plot - Central Tendency] [50 SIMULATIES WER...] [2009-06-02 17:36:06] [f4d91a94613ac4c8d4f7075ea31c5ee8]
- RMP     [Blocked Bootstrap Plot - Central Tendency] [200 SIMULATIES WE...] [2009-06-02 17:54:27] [f4d91a94613ac4c8d4f7075ea31c5ee8]
- RMP     [Blocked Bootstrap Plot - Central Tendency] [750 SIMULATIES WE...] [2009-06-02 17:57:43] [f4d91a94613ac4c8d4f7075ea31c5ee8]
- RMP     [Variability] [SPREIDINGSMATEN W...] [2009-06-02 18:05:23] [f4d91a94613ac4c8d4f7075ea31c5ee8]
- RMP     [Standard Deviation Plot] [SPREIDINGSGRAFIEK...] [2009-06-02 18:09:07] [f4d91a94613ac4c8d4f7075ea31c5ee8]
- RMP     [Standard Deviation-Mean Plot] [MEAN PLOT WERKLOZ...] [2009-06-02 18:12:18] [f4d91a94613ac4c8d4f7075ea31c5ee8]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
509
501
507
569
580
578
565
547
555
562
561
555
544
537
543
594
611
613
611
594
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532
526
511
499
555
565
542
527
510
514
517
508
493
490
469
478
528
534
518
506
502
516
528
533
536

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' @ 72.249.76.132

\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' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41324&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' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41324&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41324&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' @ 72.249.76.132






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01472.3185177599129.21068506841421
0.02477.5342187085699.59308382242416
0.03483.0503511268869.30199864547606
0.04487.9579356148068.38531473057385
0.05492.0076298357637.3315464242666
0.06495.2724994699846.43091371334802
0.07497.918063067945.72645142681529
0.08500.1026148177725.18069057084887
0.09501.9496571396024.7612834644947
0.1503.5497190065364.44625827400893
0.11504.9699879947554.22696112686300
0.12506.2632678014974.10698961828869
0.13507.4740192101274.09903099914957
0.14508.6414459640864.21260975184434
0.15509.8002160517364.44387950673273
0.16510.9796688809764.77166764390566
0.17512.2024464433035.16735501353202
0.18513.4833420279775.5953323045982
0.19514.8288476860936.0211741685536
0.2516.2375563612206.41149391535598
0.21517.7013466240486.74032207852783
0.22519.2071626601846.99023300243771
0.23520.7391566445057.15238430603823
0.24522.2809406491097.22953173766101
0.25523.817685890557.23517745070663
0.26525.3378197491527.1900915465764
0.27526.8341222174827.11990441914961
0.28528.304116124567.05283486428736
0.29529.7497626841797.0100816774822
0.3531.1765860675517.00853987282262
0.31532.5924291838487.05575204651389
0.32534.0060715643187.15028118400728
0.33535.4259200138317.28491024886868
0.34536.8589280832337.44763535853067
0.35538.309832042447.6230255606624
0.36539.7807275767817.7959709466583
0.37541.2709644601257.95164081838985
0.38542.7773091673568.07667734495173
0.39544.2943144835528.16018158500993
0.4545.8148343257618.19513078303913
0.41547.3306252162158.17674152403731
0.42548.8329795926148.104572613935
0.43550.3133398410477.98097396263406
0.44551.7638471040357.81189593829093
0.45553.1777875170187.60504165794204
0.46554.5499114138197.36911951270907
0.47555.8766171238827.11592835410061
0.48557.1560074407766.85455824776875
0.49558.3878402181836.59348580295915
0.5559.5734021810946.3414851777135
0.51560.7153361262346.10508858769474
0.52561.8174475164255.89012651551586
0.53562.8845097174735.70165290631052
0.54563.9220805317895.54346557227246
0.55564.9363378210845.42005784691521
0.56565.9339386582285.33090753796361
0.57566.9219029209715.2786810580079
0.58567.9075165312135.26516687201663
0.59568.8982407557895.28908850732423
0.6569.9016033722985.35098230378536
0.61570.9250385876865.44934989936779
0.62571.9756401894015.58297156040177
0.63573.0598008336855.74635851402043
0.64574.1827315350865.93438748156283
0.65575.3478874503516.13463039540003
0.66576.5563631326786.33381558737226
0.67577.8063539718436.51407014146542
0.68579.0928014131246.657321765794
0.69580.4073408253046.74605440622566
0.7581.738650080766.76347575128391
0.71583.0732569216736.70110685300422
0.72584.3968112224576.55604761188336
0.73585.6957726111766.33441989943364
0.74586.9594094665266.05223828544466
0.75588.1819498808195.73641202307594
0.76589.364659785415.42244965910815
0.77590.517539259795.15559136189113
0.78591.6602303708144.9863643579069
0.79592.8216539788084.96564624922504
0.8594.0379107201265.13120315543199
0.81595.3481845338635.49049164544569
0.82596.7888380702446.01227102627317
0.83598.3865497225746.6259756193259
0.84600.1520160352547.23398785805528
0.85602.0760942462887.73135573851017
0.86604.129947234258.0287557760606
0.87606.2696711059348.07419628223135
0.88608.4443738330577.86645310935283
0.89610.6054877810557.45143781345226
0.9612.7149831090586.90131503783966
0.91614.751132779336.29097675729794
0.92616.7114706213445.68290140046013
0.93618.6120260683685.13277581917094
0.94620.4797159424814.68819362664879
0.95622.3340265962014.34400250984649
0.96624.1595580415423.97766473881327
0.97625.8822434209963.38760583601329
0.98627.3677909437932.48421051496160
0.99628.4509023406451.50799181529399

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 472.318517759912 & 9.21068506841421 \tabularnewline
0.02 & 477.534218708569 & 9.59308382242416 \tabularnewline
0.03 & 483.050351126886 & 9.30199864547606 \tabularnewline
0.04 & 487.957935614806 & 8.38531473057385 \tabularnewline
0.05 & 492.007629835763 & 7.3315464242666 \tabularnewline
0.06 & 495.272499469984 & 6.43091371334802 \tabularnewline
0.07 & 497.91806306794 & 5.72645142681529 \tabularnewline
0.08 & 500.102614817772 & 5.18069057084887 \tabularnewline
0.09 & 501.949657139602 & 4.7612834644947 \tabularnewline
0.1 & 503.549719006536 & 4.44625827400893 \tabularnewline
0.11 & 504.969987994755 & 4.22696112686300 \tabularnewline
0.12 & 506.263267801497 & 4.10698961828869 \tabularnewline
0.13 & 507.474019210127 & 4.09903099914957 \tabularnewline
0.14 & 508.641445964086 & 4.21260975184434 \tabularnewline
0.15 & 509.800216051736 & 4.44387950673273 \tabularnewline
0.16 & 510.979668880976 & 4.77166764390566 \tabularnewline
0.17 & 512.202446443303 & 5.16735501353202 \tabularnewline
0.18 & 513.483342027977 & 5.5953323045982 \tabularnewline
0.19 & 514.828847686093 & 6.0211741685536 \tabularnewline
0.2 & 516.237556361220 & 6.41149391535598 \tabularnewline
0.21 & 517.701346624048 & 6.74032207852783 \tabularnewline
0.22 & 519.207162660184 & 6.99023300243771 \tabularnewline
0.23 & 520.739156644505 & 7.15238430603823 \tabularnewline
0.24 & 522.280940649109 & 7.22953173766101 \tabularnewline
0.25 & 523.81768589055 & 7.23517745070663 \tabularnewline
0.26 & 525.337819749152 & 7.1900915465764 \tabularnewline
0.27 & 526.834122217482 & 7.11990441914961 \tabularnewline
0.28 & 528.30411612456 & 7.05283486428736 \tabularnewline
0.29 & 529.749762684179 & 7.0100816774822 \tabularnewline
0.3 & 531.176586067551 & 7.00853987282262 \tabularnewline
0.31 & 532.592429183848 & 7.05575204651389 \tabularnewline
0.32 & 534.006071564318 & 7.15028118400728 \tabularnewline
0.33 & 535.425920013831 & 7.28491024886868 \tabularnewline
0.34 & 536.858928083233 & 7.44763535853067 \tabularnewline
0.35 & 538.30983204244 & 7.6230255606624 \tabularnewline
0.36 & 539.780727576781 & 7.7959709466583 \tabularnewline
0.37 & 541.270964460125 & 7.95164081838985 \tabularnewline
0.38 & 542.777309167356 & 8.07667734495173 \tabularnewline
0.39 & 544.294314483552 & 8.16018158500993 \tabularnewline
0.4 & 545.814834325761 & 8.19513078303913 \tabularnewline
0.41 & 547.330625216215 & 8.17674152403731 \tabularnewline
0.42 & 548.832979592614 & 8.104572613935 \tabularnewline
0.43 & 550.313339841047 & 7.98097396263406 \tabularnewline
0.44 & 551.763847104035 & 7.81189593829093 \tabularnewline
0.45 & 553.177787517018 & 7.60504165794204 \tabularnewline
0.46 & 554.549911413819 & 7.36911951270907 \tabularnewline
0.47 & 555.876617123882 & 7.11592835410061 \tabularnewline
0.48 & 557.156007440776 & 6.85455824776875 \tabularnewline
0.49 & 558.387840218183 & 6.59348580295915 \tabularnewline
0.5 & 559.573402181094 & 6.3414851777135 \tabularnewline
0.51 & 560.715336126234 & 6.10508858769474 \tabularnewline
0.52 & 561.817447516425 & 5.89012651551586 \tabularnewline
0.53 & 562.884509717473 & 5.70165290631052 \tabularnewline
0.54 & 563.922080531789 & 5.54346557227246 \tabularnewline
0.55 & 564.936337821084 & 5.42005784691521 \tabularnewline
0.56 & 565.933938658228 & 5.33090753796361 \tabularnewline
0.57 & 566.921902920971 & 5.2786810580079 \tabularnewline
0.58 & 567.907516531213 & 5.26516687201663 \tabularnewline
0.59 & 568.898240755789 & 5.28908850732423 \tabularnewline
0.6 & 569.901603372298 & 5.35098230378536 \tabularnewline
0.61 & 570.925038587686 & 5.44934989936779 \tabularnewline
0.62 & 571.975640189401 & 5.58297156040177 \tabularnewline
0.63 & 573.059800833685 & 5.74635851402043 \tabularnewline
0.64 & 574.182731535086 & 5.93438748156283 \tabularnewline
0.65 & 575.347887450351 & 6.13463039540003 \tabularnewline
0.66 & 576.556363132678 & 6.33381558737226 \tabularnewline
0.67 & 577.806353971843 & 6.51407014146542 \tabularnewline
0.68 & 579.092801413124 & 6.657321765794 \tabularnewline
0.69 & 580.407340825304 & 6.74605440622566 \tabularnewline
0.7 & 581.73865008076 & 6.76347575128391 \tabularnewline
0.71 & 583.073256921673 & 6.70110685300422 \tabularnewline
0.72 & 584.396811222457 & 6.55604761188336 \tabularnewline
0.73 & 585.695772611176 & 6.33441989943364 \tabularnewline
0.74 & 586.959409466526 & 6.05223828544466 \tabularnewline
0.75 & 588.181949880819 & 5.73641202307594 \tabularnewline
0.76 & 589.36465978541 & 5.42244965910815 \tabularnewline
0.77 & 590.51753925979 & 5.15559136189113 \tabularnewline
0.78 & 591.660230370814 & 4.9863643579069 \tabularnewline
0.79 & 592.821653978808 & 4.96564624922504 \tabularnewline
0.8 & 594.037910720126 & 5.13120315543199 \tabularnewline
0.81 & 595.348184533863 & 5.49049164544569 \tabularnewline
0.82 & 596.788838070244 & 6.01227102627317 \tabularnewline
0.83 & 598.386549722574 & 6.6259756193259 \tabularnewline
0.84 & 600.152016035254 & 7.23398785805528 \tabularnewline
0.85 & 602.076094246288 & 7.73135573851017 \tabularnewline
0.86 & 604.12994723425 & 8.0287557760606 \tabularnewline
0.87 & 606.269671105934 & 8.07419628223135 \tabularnewline
0.88 & 608.444373833057 & 7.86645310935283 \tabularnewline
0.89 & 610.605487781055 & 7.45143781345226 \tabularnewline
0.9 & 612.714983109058 & 6.90131503783966 \tabularnewline
0.91 & 614.75113277933 & 6.29097675729794 \tabularnewline
0.92 & 616.711470621344 & 5.68290140046013 \tabularnewline
0.93 & 618.612026068368 & 5.13277581917094 \tabularnewline
0.94 & 620.479715942481 & 4.68819362664879 \tabularnewline
0.95 & 622.334026596201 & 4.34400250984649 \tabularnewline
0.96 & 624.159558041542 & 3.97766473881327 \tabularnewline
0.97 & 625.882243420996 & 3.38760583601329 \tabularnewline
0.98 & 627.367790943793 & 2.48421051496160 \tabularnewline
0.99 & 628.450902340645 & 1.50799181529399 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41324&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]472.318517759912[/C][C]9.21068506841421[/C][/ROW]
[ROW][C]0.02[/C][C]477.534218708569[/C][C]9.59308382242416[/C][/ROW]
[ROW][C]0.03[/C][C]483.050351126886[/C][C]9.30199864547606[/C][/ROW]
[ROW][C]0.04[/C][C]487.957935614806[/C][C]8.38531473057385[/C][/ROW]
[ROW][C]0.05[/C][C]492.007629835763[/C][C]7.3315464242666[/C][/ROW]
[ROW][C]0.06[/C][C]495.272499469984[/C][C]6.43091371334802[/C][/ROW]
[ROW][C]0.07[/C][C]497.91806306794[/C][C]5.72645142681529[/C][/ROW]
[ROW][C]0.08[/C][C]500.102614817772[/C][C]5.18069057084887[/C][/ROW]
[ROW][C]0.09[/C][C]501.949657139602[/C][C]4.7612834644947[/C][/ROW]
[ROW][C]0.1[/C][C]503.549719006536[/C][C]4.44625827400893[/C][/ROW]
[ROW][C]0.11[/C][C]504.969987994755[/C][C]4.22696112686300[/C][/ROW]
[ROW][C]0.12[/C][C]506.263267801497[/C][C]4.10698961828869[/C][/ROW]
[ROW][C]0.13[/C][C]507.474019210127[/C][C]4.09903099914957[/C][/ROW]
[ROW][C]0.14[/C][C]508.641445964086[/C][C]4.21260975184434[/C][/ROW]
[ROW][C]0.15[/C][C]509.800216051736[/C][C]4.44387950673273[/C][/ROW]
[ROW][C]0.16[/C][C]510.979668880976[/C][C]4.77166764390566[/C][/ROW]
[ROW][C]0.17[/C][C]512.202446443303[/C][C]5.16735501353202[/C][/ROW]
[ROW][C]0.18[/C][C]513.483342027977[/C][C]5.5953323045982[/C][/ROW]
[ROW][C]0.19[/C][C]514.828847686093[/C][C]6.0211741685536[/C][/ROW]
[ROW][C]0.2[/C][C]516.237556361220[/C][C]6.41149391535598[/C][/ROW]
[ROW][C]0.21[/C][C]517.701346624048[/C][C]6.74032207852783[/C][/ROW]
[ROW][C]0.22[/C][C]519.207162660184[/C][C]6.99023300243771[/C][/ROW]
[ROW][C]0.23[/C][C]520.739156644505[/C][C]7.15238430603823[/C][/ROW]
[ROW][C]0.24[/C][C]522.280940649109[/C][C]7.22953173766101[/C][/ROW]
[ROW][C]0.25[/C][C]523.81768589055[/C][C]7.23517745070663[/C][/ROW]
[ROW][C]0.26[/C][C]525.337819749152[/C][C]7.1900915465764[/C][/ROW]
[ROW][C]0.27[/C][C]526.834122217482[/C][C]7.11990441914961[/C][/ROW]
[ROW][C]0.28[/C][C]528.30411612456[/C][C]7.05283486428736[/C][/ROW]
[ROW][C]0.29[/C][C]529.749762684179[/C][C]7.0100816774822[/C][/ROW]
[ROW][C]0.3[/C][C]531.176586067551[/C][C]7.00853987282262[/C][/ROW]
[ROW][C]0.31[/C][C]532.592429183848[/C][C]7.05575204651389[/C][/ROW]
[ROW][C]0.32[/C][C]534.006071564318[/C][C]7.15028118400728[/C][/ROW]
[ROW][C]0.33[/C][C]535.425920013831[/C][C]7.28491024886868[/C][/ROW]
[ROW][C]0.34[/C][C]536.858928083233[/C][C]7.44763535853067[/C][/ROW]
[ROW][C]0.35[/C][C]538.30983204244[/C][C]7.6230255606624[/C][/ROW]
[ROW][C]0.36[/C][C]539.780727576781[/C][C]7.7959709466583[/C][/ROW]
[ROW][C]0.37[/C][C]541.270964460125[/C][C]7.95164081838985[/C][/ROW]
[ROW][C]0.38[/C][C]542.777309167356[/C][C]8.07667734495173[/C][/ROW]
[ROW][C]0.39[/C][C]544.294314483552[/C][C]8.16018158500993[/C][/ROW]
[ROW][C]0.4[/C][C]545.814834325761[/C][C]8.19513078303913[/C][/ROW]
[ROW][C]0.41[/C][C]547.330625216215[/C][C]8.17674152403731[/C][/ROW]
[ROW][C]0.42[/C][C]548.832979592614[/C][C]8.104572613935[/C][/ROW]
[ROW][C]0.43[/C][C]550.313339841047[/C][C]7.98097396263406[/C][/ROW]
[ROW][C]0.44[/C][C]551.763847104035[/C][C]7.81189593829093[/C][/ROW]
[ROW][C]0.45[/C][C]553.177787517018[/C][C]7.60504165794204[/C][/ROW]
[ROW][C]0.46[/C][C]554.549911413819[/C][C]7.36911951270907[/C][/ROW]
[ROW][C]0.47[/C][C]555.876617123882[/C][C]7.11592835410061[/C][/ROW]
[ROW][C]0.48[/C][C]557.156007440776[/C][C]6.85455824776875[/C][/ROW]
[ROW][C]0.49[/C][C]558.387840218183[/C][C]6.59348580295915[/C][/ROW]
[ROW][C]0.5[/C][C]559.573402181094[/C][C]6.3414851777135[/C][/ROW]
[ROW][C]0.51[/C][C]560.715336126234[/C][C]6.10508858769474[/C][/ROW]
[ROW][C]0.52[/C][C]561.817447516425[/C][C]5.89012651551586[/C][/ROW]
[ROW][C]0.53[/C][C]562.884509717473[/C][C]5.70165290631052[/C][/ROW]
[ROW][C]0.54[/C][C]563.922080531789[/C][C]5.54346557227246[/C][/ROW]
[ROW][C]0.55[/C][C]564.936337821084[/C][C]5.42005784691521[/C][/ROW]
[ROW][C]0.56[/C][C]565.933938658228[/C][C]5.33090753796361[/C][/ROW]
[ROW][C]0.57[/C][C]566.921902920971[/C][C]5.2786810580079[/C][/ROW]
[ROW][C]0.58[/C][C]567.907516531213[/C][C]5.26516687201663[/C][/ROW]
[ROW][C]0.59[/C][C]568.898240755789[/C][C]5.28908850732423[/C][/ROW]
[ROW][C]0.6[/C][C]569.901603372298[/C][C]5.35098230378536[/C][/ROW]
[ROW][C]0.61[/C][C]570.925038587686[/C][C]5.44934989936779[/C][/ROW]
[ROW][C]0.62[/C][C]571.975640189401[/C][C]5.58297156040177[/C][/ROW]
[ROW][C]0.63[/C][C]573.059800833685[/C][C]5.74635851402043[/C][/ROW]
[ROW][C]0.64[/C][C]574.182731535086[/C][C]5.93438748156283[/C][/ROW]
[ROW][C]0.65[/C][C]575.347887450351[/C][C]6.13463039540003[/C][/ROW]
[ROW][C]0.66[/C][C]576.556363132678[/C][C]6.33381558737226[/C][/ROW]
[ROW][C]0.67[/C][C]577.806353971843[/C][C]6.51407014146542[/C][/ROW]
[ROW][C]0.68[/C][C]579.092801413124[/C][C]6.657321765794[/C][/ROW]
[ROW][C]0.69[/C][C]580.407340825304[/C][C]6.74605440622566[/C][/ROW]
[ROW][C]0.7[/C][C]581.73865008076[/C][C]6.76347575128391[/C][/ROW]
[ROW][C]0.71[/C][C]583.073256921673[/C][C]6.70110685300422[/C][/ROW]
[ROW][C]0.72[/C][C]584.396811222457[/C][C]6.55604761188336[/C][/ROW]
[ROW][C]0.73[/C][C]585.695772611176[/C][C]6.33441989943364[/C][/ROW]
[ROW][C]0.74[/C][C]586.959409466526[/C][C]6.05223828544466[/C][/ROW]
[ROW][C]0.75[/C][C]588.181949880819[/C][C]5.73641202307594[/C][/ROW]
[ROW][C]0.76[/C][C]589.36465978541[/C][C]5.42244965910815[/C][/ROW]
[ROW][C]0.77[/C][C]590.51753925979[/C][C]5.15559136189113[/C][/ROW]
[ROW][C]0.78[/C][C]591.660230370814[/C][C]4.9863643579069[/C][/ROW]
[ROW][C]0.79[/C][C]592.821653978808[/C][C]4.96564624922504[/C][/ROW]
[ROW][C]0.8[/C][C]594.037910720126[/C][C]5.13120315543199[/C][/ROW]
[ROW][C]0.81[/C][C]595.348184533863[/C][C]5.49049164544569[/C][/ROW]
[ROW][C]0.82[/C][C]596.788838070244[/C][C]6.01227102627317[/C][/ROW]
[ROW][C]0.83[/C][C]598.386549722574[/C][C]6.6259756193259[/C][/ROW]
[ROW][C]0.84[/C][C]600.152016035254[/C][C]7.23398785805528[/C][/ROW]
[ROW][C]0.85[/C][C]602.076094246288[/C][C]7.73135573851017[/C][/ROW]
[ROW][C]0.86[/C][C]604.12994723425[/C][C]8.0287557760606[/C][/ROW]
[ROW][C]0.87[/C][C]606.269671105934[/C][C]8.07419628223135[/C][/ROW]
[ROW][C]0.88[/C][C]608.444373833057[/C][C]7.86645310935283[/C][/ROW]
[ROW][C]0.89[/C][C]610.605487781055[/C][C]7.45143781345226[/C][/ROW]
[ROW][C]0.9[/C][C]612.714983109058[/C][C]6.90131503783966[/C][/ROW]
[ROW][C]0.91[/C][C]614.75113277933[/C][C]6.29097675729794[/C][/ROW]
[ROW][C]0.92[/C][C]616.711470621344[/C][C]5.68290140046013[/C][/ROW]
[ROW][C]0.93[/C][C]618.612026068368[/C][C]5.13277581917094[/C][/ROW]
[ROW][C]0.94[/C][C]620.479715942481[/C][C]4.68819362664879[/C][/ROW]
[ROW][C]0.95[/C][C]622.334026596201[/C][C]4.34400250984649[/C][/ROW]
[ROW][C]0.96[/C][C]624.159558041542[/C][C]3.97766473881327[/C][/ROW]
[ROW][C]0.97[/C][C]625.882243420996[/C][C]3.38760583601329[/C][/ROW]
[ROW][C]0.98[/C][C]627.367790943793[/C][C]2.48421051496160[/C][/ROW]
[ROW][C]0.99[/C][C]628.450902340645[/C][C]1.50799181529399[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41324&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41324&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
0.01472.3185177599129.21068506841421
0.02477.5342187085699.59308382242416
0.03483.0503511268869.30199864547606
0.04487.9579356148068.38531473057385
0.05492.0076298357637.3315464242666
0.06495.2724994699846.43091371334802
0.07497.918063067945.72645142681529
0.08500.1026148177725.18069057084887
0.09501.9496571396024.7612834644947
0.1503.5497190065364.44625827400893
0.11504.9699879947554.22696112686300
0.12506.2632678014974.10698961828869
0.13507.4740192101274.09903099914957
0.14508.6414459640864.21260975184434
0.15509.8002160517364.44387950673273
0.16510.9796688809764.77166764390566
0.17512.2024464433035.16735501353202
0.18513.4833420279775.5953323045982
0.19514.8288476860936.0211741685536
0.2516.2375563612206.41149391535598
0.21517.7013466240486.74032207852783
0.22519.2071626601846.99023300243771
0.23520.7391566445057.15238430603823
0.24522.2809406491097.22953173766101
0.25523.817685890557.23517745070663
0.26525.3378197491527.1900915465764
0.27526.8341222174827.11990441914961
0.28528.304116124567.05283486428736
0.29529.7497626841797.0100816774822
0.3531.1765860675517.00853987282262
0.31532.5924291838487.05575204651389
0.32534.0060715643187.15028118400728
0.33535.4259200138317.28491024886868
0.34536.8589280832337.44763535853067
0.35538.309832042447.6230255606624
0.36539.7807275767817.7959709466583
0.37541.2709644601257.95164081838985
0.38542.7773091673568.07667734495173
0.39544.2943144835528.16018158500993
0.4545.8148343257618.19513078303913
0.41547.3306252162158.17674152403731
0.42548.8329795926148.104572613935
0.43550.3133398410477.98097396263406
0.44551.7638471040357.81189593829093
0.45553.1777875170187.60504165794204
0.46554.5499114138197.36911951270907
0.47555.8766171238827.11592835410061
0.48557.1560074407766.85455824776875
0.49558.3878402181836.59348580295915
0.5559.5734021810946.3414851777135
0.51560.7153361262346.10508858769474
0.52561.8174475164255.89012651551586
0.53562.8845097174735.70165290631052
0.54563.9220805317895.54346557227246
0.55564.9363378210845.42005784691521
0.56565.9339386582285.33090753796361
0.57566.9219029209715.2786810580079
0.58567.9075165312135.26516687201663
0.59568.8982407557895.28908850732423
0.6569.9016033722985.35098230378536
0.61570.9250385876865.44934989936779
0.62571.9756401894015.58297156040177
0.63573.0598008336855.74635851402043
0.64574.1827315350865.93438748156283
0.65575.3478874503516.13463039540003
0.66576.5563631326786.33381558737226
0.67577.8063539718436.51407014146542
0.68579.0928014131246.657321765794
0.69580.4073408253046.74605440622566
0.7581.738650080766.76347575128391
0.71583.0732569216736.70110685300422
0.72584.3968112224576.55604761188336
0.73585.6957726111766.33441989943364
0.74586.9594094665266.05223828544466
0.75588.1819498808195.73641202307594
0.76589.364659785415.42244965910815
0.77590.517539259795.15559136189113
0.78591.6602303708144.9863643579069
0.79592.8216539788084.96564624922504
0.8594.0379107201265.13120315543199
0.81595.3481845338635.49049164544569
0.82596.7888380702446.01227102627317
0.83598.3865497225746.6259756193259
0.84600.1520160352547.23398785805528
0.85602.0760942462887.73135573851017
0.86604.129947234258.0287557760606
0.87606.2696711059348.07419628223135
0.88608.4443738330577.86645310935283
0.89610.6054877810557.45143781345226
0.9612.7149831090586.90131503783966
0.91614.751132779336.29097675729794
0.92616.7114706213445.68290140046013
0.93618.6120260683685.13277581917094
0.94620.4797159424814.68819362664879
0.95622.3340265962014.34400250984649
0.96624.1595580415423.97766473881327
0.97625.8822434209963.38760583601329
0.98627.3677909437932.48421051496160
0.99628.4509023406451.50799181529399


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')