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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 computationSat, 04 Oct 2014 22:52:18 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Oct/04/t1412459598dk3juw83x65nx15.htm/, Retrieved Sun, 12 May 2024 21:57:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=238662, Retrieved Sun, 12 May 2024 21:57:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Harrell-Davis Quantiles] [Harrel Davis deci...] [2014-10-04 21:52:18] [2cf7618d5ff65529ef2e27cea5366de0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
332
369
384
373
378
426
423
397
422
409
430
412
470
491
504
484
474
508
492
452
457
457
471
451
493
514
522
490
484
506
501
462
465
454
464
427
460
473
465
422
415
413
420
363
376
380
384
346
389
407
393
346
348
353
364
305
307
312
312
286
324
336
327
302
299
311
315
264
278
278
287
279
324
354
354
360
363
385
412
370
389
395
417
404
456
478
468
437
432
441
449
386
396
394
403
373
409
430
415
392
401
400
447
392
427
444
448
427
480
490
482
490
485
498
544
483
508
529
547
543
608
638
661
650
654
678
725
644
670
662
641
642

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'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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=238662&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=238662&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=238662&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01271.4656681948627.57190644776478
0.02278.4852973060155.23996330335317
0.03283.7830345508127.6009802111362
0.04289.3424997930299.52374950561058
0.05295.149088789579.9055070112241
0.06300.573668780769.28265955482322
0.07305.3406326675648.62715325307657
0.08309.5867437867568.60634679783441
0.09313.6319580310369.32046577009945
0.1317.7655420370610.4822099971409
0.11322.14126246925511.7170639643664
0.12326.76780828380812.7220345280754
0.13331.54957224414713.3147987823278
0.14336.34192019097213.4370357070213
0.15341.0010185026813.1446015600335
0.16345.41876539972712.5796119305351
0.17349.53892273055811.9055472265035
0.18353.35512859706411.2640089978861
0.19356.89628999856710.7312075578892
0.2360.20768048571710.3245526775952
0.21363.33502486749310.0210345335357
0.22366.3150337192929.78387278132391
0.23369.172070092339.57524445663578
0.24371.9187976631759.36348268887265
0.25374.5587462407219.12664502720884
0.26377.0896113458088.84993441453458
0.27379.5067929681738.53630731681108
0.28381.806873161198.19624675867818
0.29383.990638643657.85459227695464
0.3386.0651764450517.54093224537794
0.31388.0446552337397.28682287232152
0.32389.9496280146087.11787465273635
0.33391.8049646662487.04936871183904
0.34393.6367812933617.08180197674735
0.35395.4689479514267.19837969184771
0.36397.319892728497.3708685944332
0.37399.2004186363737.56290109229261
0.38401.1130556080457.73942653094148
0.39403.0530914728017.87294802761298
0.4405.0109657886667.95238749683101
0.41406.9753368104517.9775767235721
0.42408.9359997210397.96190735674294
0.43410.8860034035047.92364549399172
0.44412.8227087738557.88381810567904
0.45414.7479713571997.85912458451127
0.46416.6679059895427.8647382868231
0.47418.592669065127.91621791557037
0.48420.5363876689888.02889264805718
0.49422.5169419638848.22063003075568
0.5424.5550156429938.50432991807856
0.51426.6718776778328.87973271101832
0.52428.8857994659319.32673054278055
0.53431.2076906940439.80123877207671
0.54433.63714516611610.2447767655146
0.55436.16029950994510.5927554487301
0.56438.75054905820310.793269259255
0.57441.37231953542610.816878794696
0.58443.98708298558210.6678179100982
0.59446.56004977473310.3773683575421
0.6449.06577936371510.0001065536381
0.61451.4913896535979.59554205429004
0.62453.836890810389.21878196053118
0.63456.1130487251768.9068952799596
0.64458.3377498004568.6813112734371
0.65460.5319351784718.54247609924731
0.66462.7158809654028.47996688757798
0.67464.906171035078.47258337007134
0.68467.1134087467288.49242009759189
0.69469.3406837122138.50875553830018
0.7471.5829930487668.48708212364905
0.71473.8280051173218.40063368810877
0.72476.0585252334798.2336911727022
0.73478.2566907088117.99048187679544
0.74480.4093976713467.69770838470999
0.75482.5139770128637.40137488407079
0.76484.5828953938777.16351095161884
0.77486.6463529752217.04958498570657
0.78488.7521347006537.1178059295845
0.79490.9630592037817.4060425468274
0.8493.3539166982357.93111078177397
0.81496.011519381748.69867643004804
0.82499.042380918579.74560673949338
0.83502.5914285264711.173971759108
0.84506.87165926286713.1845698770847
0.85512.19900740360316.0603500931085
0.86519.01754118206820.1141942364816
0.87527.88410544797625.5528624837017
0.88539.36236276270732.2033622176823
0.89553.7814071686539.1276786238142
0.9570.89114368021644.4542071248046
0.91589.60055790287645.9038019429956
0.92608.09215148273942.1001268195996
0.93624.45556325818333.8456630492534
0.94637.54935744182324.0570834410803
0.95647.47832034521216.014445288175
0.96655.39219704474111.3275642038425
0.97663.2697984158459.85154758464824
0.98675.27354941651612.9179914477293
0.99698.71361832392627.0139699352043

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 271.465668194862 & 7.57190644776478 \tabularnewline
0.02 & 278.485297306015 & 5.23996330335317 \tabularnewline
0.03 & 283.783034550812 & 7.6009802111362 \tabularnewline
0.04 & 289.342499793029 & 9.52374950561058 \tabularnewline
0.05 & 295.14908878957 & 9.9055070112241 \tabularnewline
0.06 & 300.57366878076 & 9.28265955482322 \tabularnewline
0.07 & 305.340632667564 & 8.62715325307657 \tabularnewline
0.08 & 309.586743786756 & 8.60634679783441 \tabularnewline
0.09 & 313.631958031036 & 9.32046577009945 \tabularnewline
0.1 & 317.76554203706 & 10.4822099971409 \tabularnewline
0.11 & 322.141262469255 & 11.7170639643664 \tabularnewline
0.12 & 326.767808283808 & 12.7220345280754 \tabularnewline
0.13 & 331.549572244147 & 13.3147987823278 \tabularnewline
0.14 & 336.341920190972 & 13.4370357070213 \tabularnewline
0.15 & 341.00101850268 & 13.1446015600335 \tabularnewline
0.16 & 345.418765399727 & 12.5796119305351 \tabularnewline
0.17 & 349.538922730558 & 11.9055472265035 \tabularnewline
0.18 & 353.355128597064 & 11.2640089978861 \tabularnewline
0.19 & 356.896289998567 & 10.7312075578892 \tabularnewline
0.2 & 360.207680485717 & 10.3245526775952 \tabularnewline
0.21 & 363.335024867493 & 10.0210345335357 \tabularnewline
0.22 & 366.315033719292 & 9.78387278132391 \tabularnewline
0.23 & 369.17207009233 & 9.57524445663578 \tabularnewline
0.24 & 371.918797663175 & 9.36348268887265 \tabularnewline
0.25 & 374.558746240721 & 9.12664502720884 \tabularnewline
0.26 & 377.089611345808 & 8.84993441453458 \tabularnewline
0.27 & 379.506792968173 & 8.53630731681108 \tabularnewline
0.28 & 381.80687316119 & 8.19624675867818 \tabularnewline
0.29 & 383.99063864365 & 7.85459227695464 \tabularnewline
0.3 & 386.065176445051 & 7.54093224537794 \tabularnewline
0.31 & 388.044655233739 & 7.28682287232152 \tabularnewline
0.32 & 389.949628014608 & 7.11787465273635 \tabularnewline
0.33 & 391.804964666248 & 7.04936871183904 \tabularnewline
0.34 & 393.636781293361 & 7.08180197674735 \tabularnewline
0.35 & 395.468947951426 & 7.19837969184771 \tabularnewline
0.36 & 397.31989272849 & 7.3708685944332 \tabularnewline
0.37 & 399.200418636373 & 7.56290109229261 \tabularnewline
0.38 & 401.113055608045 & 7.73942653094148 \tabularnewline
0.39 & 403.053091472801 & 7.87294802761298 \tabularnewline
0.4 & 405.010965788666 & 7.95238749683101 \tabularnewline
0.41 & 406.975336810451 & 7.9775767235721 \tabularnewline
0.42 & 408.935999721039 & 7.96190735674294 \tabularnewline
0.43 & 410.886003403504 & 7.92364549399172 \tabularnewline
0.44 & 412.822708773855 & 7.88381810567904 \tabularnewline
0.45 & 414.747971357199 & 7.85912458451127 \tabularnewline
0.46 & 416.667905989542 & 7.8647382868231 \tabularnewline
0.47 & 418.59266906512 & 7.91621791557037 \tabularnewline
0.48 & 420.536387668988 & 8.02889264805718 \tabularnewline
0.49 & 422.516941963884 & 8.22063003075568 \tabularnewline
0.5 & 424.555015642993 & 8.50432991807856 \tabularnewline
0.51 & 426.671877677832 & 8.87973271101832 \tabularnewline
0.52 & 428.885799465931 & 9.32673054278055 \tabularnewline
0.53 & 431.207690694043 & 9.80123877207671 \tabularnewline
0.54 & 433.637145166116 & 10.2447767655146 \tabularnewline
0.55 & 436.160299509945 & 10.5927554487301 \tabularnewline
0.56 & 438.750549058203 & 10.793269259255 \tabularnewline
0.57 & 441.372319535426 & 10.816878794696 \tabularnewline
0.58 & 443.987082985582 & 10.6678179100982 \tabularnewline
0.59 & 446.560049774733 & 10.3773683575421 \tabularnewline
0.6 & 449.065779363715 & 10.0001065536381 \tabularnewline
0.61 & 451.491389653597 & 9.59554205429004 \tabularnewline
0.62 & 453.83689081038 & 9.21878196053118 \tabularnewline
0.63 & 456.113048725176 & 8.9068952799596 \tabularnewline
0.64 & 458.337749800456 & 8.6813112734371 \tabularnewline
0.65 & 460.531935178471 & 8.54247609924731 \tabularnewline
0.66 & 462.715880965402 & 8.47996688757798 \tabularnewline
0.67 & 464.90617103507 & 8.47258337007134 \tabularnewline
0.68 & 467.113408746728 & 8.49242009759189 \tabularnewline
0.69 & 469.340683712213 & 8.50875553830018 \tabularnewline
0.7 & 471.582993048766 & 8.48708212364905 \tabularnewline
0.71 & 473.828005117321 & 8.40063368810877 \tabularnewline
0.72 & 476.058525233479 & 8.2336911727022 \tabularnewline
0.73 & 478.256690708811 & 7.99048187679544 \tabularnewline
0.74 & 480.409397671346 & 7.69770838470999 \tabularnewline
0.75 & 482.513977012863 & 7.40137488407079 \tabularnewline
0.76 & 484.582895393877 & 7.16351095161884 \tabularnewline
0.77 & 486.646352975221 & 7.04958498570657 \tabularnewline
0.78 & 488.752134700653 & 7.1178059295845 \tabularnewline
0.79 & 490.963059203781 & 7.4060425468274 \tabularnewline
0.8 & 493.353916698235 & 7.93111078177397 \tabularnewline
0.81 & 496.01151938174 & 8.69867643004804 \tabularnewline
0.82 & 499.04238091857 & 9.74560673949338 \tabularnewline
0.83 & 502.59142852647 & 11.173971759108 \tabularnewline
0.84 & 506.871659262867 & 13.1845698770847 \tabularnewline
0.85 & 512.199007403603 & 16.0603500931085 \tabularnewline
0.86 & 519.017541182068 & 20.1141942364816 \tabularnewline
0.87 & 527.884105447976 & 25.5528624837017 \tabularnewline
0.88 & 539.362362762707 & 32.2033622176823 \tabularnewline
0.89 & 553.78140716865 & 39.1276786238142 \tabularnewline
0.9 & 570.891143680216 & 44.4542071248046 \tabularnewline
0.91 & 589.600557902876 & 45.9038019429956 \tabularnewline
0.92 & 608.092151482739 & 42.1001268195996 \tabularnewline
0.93 & 624.455563258183 & 33.8456630492534 \tabularnewline
0.94 & 637.549357441823 & 24.0570834410803 \tabularnewline
0.95 & 647.478320345212 & 16.014445288175 \tabularnewline
0.96 & 655.392197044741 & 11.3275642038425 \tabularnewline
0.97 & 663.269798415845 & 9.85154758464824 \tabularnewline
0.98 & 675.273549416516 & 12.9179914477293 \tabularnewline
0.99 & 698.713618323926 & 27.0139699352043 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=238662&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]271.465668194862[/C][C]7.57190644776478[/C][/ROW]
[ROW][C]0.02[/C][C]278.485297306015[/C][C]5.23996330335317[/C][/ROW]
[ROW][C]0.03[/C][C]283.783034550812[/C][C]7.6009802111362[/C][/ROW]
[ROW][C]0.04[/C][C]289.342499793029[/C][C]9.52374950561058[/C][/ROW]
[ROW][C]0.05[/C][C]295.14908878957[/C][C]9.9055070112241[/C][/ROW]
[ROW][C]0.06[/C][C]300.57366878076[/C][C]9.28265955482322[/C][/ROW]
[ROW][C]0.07[/C][C]305.340632667564[/C][C]8.62715325307657[/C][/ROW]
[ROW][C]0.08[/C][C]309.586743786756[/C][C]8.60634679783441[/C][/ROW]
[ROW][C]0.09[/C][C]313.631958031036[/C][C]9.32046577009945[/C][/ROW]
[ROW][C]0.1[/C][C]317.76554203706[/C][C]10.4822099971409[/C][/ROW]
[ROW][C]0.11[/C][C]322.141262469255[/C][C]11.7170639643664[/C][/ROW]
[ROW][C]0.12[/C][C]326.767808283808[/C][C]12.7220345280754[/C][/ROW]
[ROW][C]0.13[/C][C]331.549572244147[/C][C]13.3147987823278[/C][/ROW]
[ROW][C]0.14[/C][C]336.341920190972[/C][C]13.4370357070213[/C][/ROW]
[ROW][C]0.15[/C][C]341.00101850268[/C][C]13.1446015600335[/C][/ROW]
[ROW][C]0.16[/C][C]345.418765399727[/C][C]12.5796119305351[/C][/ROW]
[ROW][C]0.17[/C][C]349.538922730558[/C][C]11.9055472265035[/C][/ROW]
[ROW][C]0.18[/C][C]353.355128597064[/C][C]11.2640089978861[/C][/ROW]
[ROW][C]0.19[/C][C]356.896289998567[/C][C]10.7312075578892[/C][/ROW]
[ROW][C]0.2[/C][C]360.207680485717[/C][C]10.3245526775952[/C][/ROW]
[ROW][C]0.21[/C][C]363.335024867493[/C][C]10.0210345335357[/C][/ROW]
[ROW][C]0.22[/C][C]366.315033719292[/C][C]9.78387278132391[/C][/ROW]
[ROW][C]0.23[/C][C]369.17207009233[/C][C]9.57524445663578[/C][/ROW]
[ROW][C]0.24[/C][C]371.918797663175[/C][C]9.36348268887265[/C][/ROW]
[ROW][C]0.25[/C][C]374.558746240721[/C][C]9.12664502720884[/C][/ROW]
[ROW][C]0.26[/C][C]377.089611345808[/C][C]8.84993441453458[/C][/ROW]
[ROW][C]0.27[/C][C]379.506792968173[/C][C]8.53630731681108[/C][/ROW]
[ROW][C]0.28[/C][C]381.80687316119[/C][C]8.19624675867818[/C][/ROW]
[ROW][C]0.29[/C][C]383.99063864365[/C][C]7.85459227695464[/C][/ROW]
[ROW][C]0.3[/C][C]386.065176445051[/C][C]7.54093224537794[/C][/ROW]
[ROW][C]0.31[/C][C]388.044655233739[/C][C]7.28682287232152[/C][/ROW]
[ROW][C]0.32[/C][C]389.949628014608[/C][C]7.11787465273635[/C][/ROW]
[ROW][C]0.33[/C][C]391.804964666248[/C][C]7.04936871183904[/C][/ROW]
[ROW][C]0.34[/C][C]393.636781293361[/C][C]7.08180197674735[/C][/ROW]
[ROW][C]0.35[/C][C]395.468947951426[/C][C]7.19837969184771[/C][/ROW]
[ROW][C]0.36[/C][C]397.31989272849[/C][C]7.3708685944332[/C][/ROW]
[ROW][C]0.37[/C][C]399.200418636373[/C][C]7.56290109229261[/C][/ROW]
[ROW][C]0.38[/C][C]401.113055608045[/C][C]7.73942653094148[/C][/ROW]
[ROW][C]0.39[/C][C]403.053091472801[/C][C]7.87294802761298[/C][/ROW]
[ROW][C]0.4[/C][C]405.010965788666[/C][C]7.95238749683101[/C][/ROW]
[ROW][C]0.41[/C][C]406.975336810451[/C][C]7.9775767235721[/C][/ROW]
[ROW][C]0.42[/C][C]408.935999721039[/C][C]7.96190735674294[/C][/ROW]
[ROW][C]0.43[/C][C]410.886003403504[/C][C]7.92364549399172[/C][/ROW]
[ROW][C]0.44[/C][C]412.822708773855[/C][C]7.88381810567904[/C][/ROW]
[ROW][C]0.45[/C][C]414.747971357199[/C][C]7.85912458451127[/C][/ROW]
[ROW][C]0.46[/C][C]416.667905989542[/C][C]7.8647382868231[/C][/ROW]
[ROW][C]0.47[/C][C]418.59266906512[/C][C]7.91621791557037[/C][/ROW]
[ROW][C]0.48[/C][C]420.536387668988[/C][C]8.02889264805718[/C][/ROW]
[ROW][C]0.49[/C][C]422.516941963884[/C][C]8.22063003075568[/C][/ROW]
[ROW][C]0.5[/C][C]424.555015642993[/C][C]8.50432991807856[/C][/ROW]
[ROW][C]0.51[/C][C]426.671877677832[/C][C]8.87973271101832[/C][/ROW]
[ROW][C]0.52[/C][C]428.885799465931[/C][C]9.32673054278055[/C][/ROW]
[ROW][C]0.53[/C][C]431.207690694043[/C][C]9.80123877207671[/C][/ROW]
[ROW][C]0.54[/C][C]433.637145166116[/C][C]10.2447767655146[/C][/ROW]
[ROW][C]0.55[/C][C]436.160299509945[/C][C]10.5927554487301[/C][/ROW]
[ROW][C]0.56[/C][C]438.750549058203[/C][C]10.793269259255[/C][/ROW]
[ROW][C]0.57[/C][C]441.372319535426[/C][C]10.816878794696[/C][/ROW]
[ROW][C]0.58[/C][C]443.987082985582[/C][C]10.6678179100982[/C][/ROW]
[ROW][C]0.59[/C][C]446.560049774733[/C][C]10.3773683575421[/C][/ROW]
[ROW][C]0.6[/C][C]449.065779363715[/C][C]10.0001065536381[/C][/ROW]
[ROW][C]0.61[/C][C]451.491389653597[/C][C]9.59554205429004[/C][/ROW]
[ROW][C]0.62[/C][C]453.83689081038[/C][C]9.21878196053118[/C][/ROW]
[ROW][C]0.63[/C][C]456.113048725176[/C][C]8.9068952799596[/C][/ROW]
[ROW][C]0.64[/C][C]458.337749800456[/C][C]8.6813112734371[/C][/ROW]
[ROW][C]0.65[/C][C]460.531935178471[/C][C]8.54247609924731[/C][/ROW]
[ROW][C]0.66[/C][C]462.715880965402[/C][C]8.47996688757798[/C][/ROW]
[ROW][C]0.67[/C][C]464.90617103507[/C][C]8.47258337007134[/C][/ROW]
[ROW][C]0.68[/C][C]467.113408746728[/C][C]8.49242009759189[/C][/ROW]
[ROW][C]0.69[/C][C]469.340683712213[/C][C]8.50875553830018[/C][/ROW]
[ROW][C]0.7[/C][C]471.582993048766[/C][C]8.48708212364905[/C][/ROW]
[ROW][C]0.71[/C][C]473.828005117321[/C][C]8.40063368810877[/C][/ROW]
[ROW][C]0.72[/C][C]476.058525233479[/C][C]8.2336911727022[/C][/ROW]
[ROW][C]0.73[/C][C]478.256690708811[/C][C]7.99048187679544[/C][/ROW]
[ROW][C]0.74[/C][C]480.409397671346[/C][C]7.69770838470999[/C][/ROW]
[ROW][C]0.75[/C][C]482.513977012863[/C][C]7.40137488407079[/C][/ROW]
[ROW][C]0.76[/C][C]484.582895393877[/C][C]7.16351095161884[/C][/ROW]
[ROW][C]0.77[/C][C]486.646352975221[/C][C]7.04958498570657[/C][/ROW]
[ROW][C]0.78[/C][C]488.752134700653[/C][C]7.1178059295845[/C][/ROW]
[ROW][C]0.79[/C][C]490.963059203781[/C][C]7.4060425468274[/C][/ROW]
[ROW][C]0.8[/C][C]493.353916698235[/C][C]7.93111078177397[/C][/ROW]
[ROW][C]0.81[/C][C]496.01151938174[/C][C]8.69867643004804[/C][/ROW]
[ROW][C]0.82[/C][C]499.04238091857[/C][C]9.74560673949338[/C][/ROW]
[ROW][C]0.83[/C][C]502.59142852647[/C][C]11.173971759108[/C][/ROW]
[ROW][C]0.84[/C][C]506.871659262867[/C][C]13.1845698770847[/C][/ROW]
[ROW][C]0.85[/C][C]512.199007403603[/C][C]16.0603500931085[/C][/ROW]
[ROW][C]0.86[/C][C]519.017541182068[/C][C]20.1141942364816[/C][/ROW]
[ROW][C]0.87[/C][C]527.884105447976[/C][C]25.5528624837017[/C][/ROW]
[ROW][C]0.88[/C][C]539.362362762707[/C][C]32.2033622176823[/C][/ROW]
[ROW][C]0.89[/C][C]553.78140716865[/C][C]39.1276786238142[/C][/ROW]
[ROW][C]0.9[/C][C]570.891143680216[/C][C]44.4542071248046[/C][/ROW]
[ROW][C]0.91[/C][C]589.600557902876[/C][C]45.9038019429956[/C][/ROW]
[ROW][C]0.92[/C][C]608.092151482739[/C][C]42.1001268195996[/C][/ROW]
[ROW][C]0.93[/C][C]624.455563258183[/C][C]33.8456630492534[/C][/ROW]
[ROW][C]0.94[/C][C]637.549357441823[/C][C]24.0570834410803[/C][/ROW]
[ROW][C]0.95[/C][C]647.478320345212[/C][C]16.014445288175[/C][/ROW]
[ROW][C]0.96[/C][C]655.392197044741[/C][C]11.3275642038425[/C][/ROW]
[ROW][C]0.97[/C][C]663.269798415845[/C][C]9.85154758464824[/C][/ROW]
[ROW][C]0.98[/C][C]675.273549416516[/C][C]12.9179914477293[/C][/ROW]
[ROW][C]0.99[/C][C]698.713618323926[/C][C]27.0139699352043[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=238662&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=238662&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
0.01271.4656681948627.57190644776478
0.02278.4852973060155.23996330335317
0.03283.7830345508127.6009802111362
0.04289.3424997930299.52374950561058
0.05295.149088789579.9055070112241
0.06300.573668780769.28265955482322
0.07305.3406326675648.62715325307657
0.08309.5867437867568.60634679783441
0.09313.6319580310369.32046577009945
0.1317.7655420370610.4822099971409
0.11322.14126246925511.7170639643664
0.12326.76780828380812.7220345280754
0.13331.54957224414713.3147987823278
0.14336.34192019097213.4370357070213
0.15341.0010185026813.1446015600335
0.16345.41876539972712.5796119305351
0.17349.53892273055811.9055472265035
0.18353.35512859706411.2640089978861
0.19356.89628999856710.7312075578892
0.2360.20768048571710.3245526775952
0.21363.33502486749310.0210345335357
0.22366.3150337192929.78387278132391
0.23369.172070092339.57524445663578
0.24371.9187976631759.36348268887265
0.25374.5587462407219.12664502720884
0.26377.0896113458088.84993441453458
0.27379.5067929681738.53630731681108
0.28381.806873161198.19624675867818
0.29383.990638643657.85459227695464
0.3386.0651764450517.54093224537794
0.31388.0446552337397.28682287232152
0.32389.9496280146087.11787465273635
0.33391.8049646662487.04936871183904
0.34393.6367812933617.08180197674735
0.35395.4689479514267.19837969184771
0.36397.319892728497.3708685944332
0.37399.2004186363737.56290109229261
0.38401.1130556080457.73942653094148
0.39403.0530914728017.87294802761298
0.4405.0109657886667.95238749683101
0.41406.9753368104517.9775767235721
0.42408.9359997210397.96190735674294
0.43410.8860034035047.92364549399172
0.44412.8227087738557.88381810567904
0.45414.7479713571997.85912458451127
0.46416.6679059895427.8647382868231
0.47418.592669065127.91621791557037
0.48420.5363876689888.02889264805718
0.49422.5169419638848.22063003075568
0.5424.5550156429938.50432991807856
0.51426.6718776778328.87973271101832
0.52428.8857994659319.32673054278055
0.53431.2076906940439.80123877207671
0.54433.63714516611610.2447767655146
0.55436.16029950994510.5927554487301
0.56438.75054905820310.793269259255
0.57441.37231953542610.816878794696
0.58443.98708298558210.6678179100982
0.59446.56004977473310.3773683575421
0.6449.06577936371510.0001065536381
0.61451.4913896535979.59554205429004
0.62453.836890810389.21878196053118
0.63456.1130487251768.9068952799596
0.64458.3377498004568.6813112734371
0.65460.5319351784718.54247609924731
0.66462.7158809654028.47996688757798
0.67464.906171035078.47258337007134
0.68467.1134087467288.49242009759189
0.69469.3406837122138.50875553830018
0.7471.5829930487668.48708212364905
0.71473.8280051173218.40063368810877
0.72476.0585252334798.2336911727022
0.73478.2566907088117.99048187679544
0.74480.4093976713467.69770838470999
0.75482.5139770128637.40137488407079
0.76484.5828953938777.16351095161884
0.77486.6463529752217.04958498570657
0.78488.7521347006537.1178059295845
0.79490.9630592037817.4060425468274
0.8493.3539166982357.93111078177397
0.81496.011519381748.69867643004804
0.82499.042380918579.74560673949338
0.83502.5914285264711.173971759108
0.84506.87165926286713.1845698770847
0.85512.19900740360316.0603500931085
0.86519.01754118206820.1141942364816
0.87527.88410544797625.5528624837017
0.88539.36236276270732.2033622176823
0.89553.7814071686539.1276786238142
0.9570.89114368021644.4542071248046
0.91589.60055790287645.9038019429956
0.92608.09215148273942.1001268195996
0.93624.45556325818333.8456630492534
0.94637.54935744182324.0570834410803
0.95647.47832034521216.014445288175
0.96655.39219704474111.3275642038425
0.97663.2697984158459.85154758464824
0.98675.27354941651612.9179914477293
0.99698.71361832392627.0139699352043


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')