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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, 10 Mar 2009 06:47:54 -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/Mar/10/t123668938333bzbq6mrezuktx.htm/, Retrieved Fri, 19 Apr 2024 01:31:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=38875, Retrieved Fri, 19 Apr 2024 01:31:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138

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 gem ...] [2009-03-10 12:47:54] [46186faee359a0c92d914c5fc942bc84] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
666.27
664.45
660.76
660.40
660.69
660.69
662.23
661.41
659.02
655.43
652.59
652.59
648.20
645.84
644.67
642.71
640.14
640.14
639.64
630.28
614.57
614.70
615.08
615.08
614.43
604.55
598.98
594.05
593.05
593.05
593.34
584.72
580.70
577.08
569.92
569.92
568.86
559.38
548.22
545.61
545.33
530.30
527.76
521.41
1601.93
1577.49
1551.43
1551.43
1516.88
1485.95
1438.22
1385.06
1329.49
1329.49
1276.16
1242.34
1181.59
1160.21
1135.18
1135.18
1084.96
1077.35
1061.13
1029.98
1013.08
1013.08
996.04
975.02
951.89
944.40
932.47
932.47
920.44
900.18
886.90

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=38875&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=38875&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=38875&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'Gwilym Jenkins' @ 72.249.127.135






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01523.7255926656366.12602892442293
0.02527.546994476077.1262738981346
0.03532.0420208193588.78450127012958
0.04536.7574445550619.9949467885735
0.05541.47271624307710.6187258314043
0.06546.07100617989511.0362774012967
0.07550.50759836987111.4602336995979
0.08554.7774141272811.8029109726740
0.09558.87716149402511.9218815641327
0.1562.79120925157211.7991290247584
0.11566.5019412436811.5380831325723
0.12570.00493063163411.2717272533348
0.13573.31409110397511.0796784526818
0.14576.4557670595410.9710894474275
0.15579.45888491521110.9086282991722
0.16582.34807898516110.8558392550449
0.17585.14230754324610.8032801438670
0.18587.85744938983710.7715952940206
0.19590.50979389906510.7947946234973
0.2593.11798541881710.9025245759637
0.21595.70261628489211.1067868704743
0.22598.28410904930811.3937967520219
0.23600.8801801429311.7344188419088
0.24603.5040110754512.1015402024765
0.25606.16361044464912.4695284157877
0.26608.86216655490212.8276481199095
0.27611.59879086884213.1662972049679
0.28614.36905100871213.4766291583730
0.29617.1650009082513.7420164138956
0.3619.97482949358713.9379558782064
0.31622.78255560383314.0310561271463
0.32625.56826679141813.9944307697012
0.33628.309226483913.8087124304069
0.34630.98185584051513.4732705503716
0.35633.56428034028713.0050600280041
0.36636.03894705901212.4395449225730
0.37638.39483316582511.8213896851585
0.38640.62896655779611.2019984886988
0.39642.74728919082110.6331203955092
0.4644.7652060416810.1655399656573
0.41646.7083769859699.85201651664532
0.42648.6143554239549.7568284417602
0.43650.535527748799.97146951159552
0.44652.54347301872110.6251021403135
0.45654.73438715735511.8956883167636
0.46657.2346735915313.9939920276089
0.47660.20529122704217.1398073880115
0.48663.8430923163921.5365605749112
0.49668.37730947654527.3345121784273
0.5674.05968119946434.6030919535010
0.51681.14750384805143.29807178309
0.52689.88013308202653.2241152064222
0.53700.45096649691364.0261432688953
0.54712.97842819417675.189363967901
0.55727.48056461483886.0703704692979
0.56743.858173171995.9683446735606
0.57761.890667179906104.199834983103
0.58781.247109263351110.188423029902
0.59801.512284952202113.547836916308
0.6822.224861558703114.142769465271
0.61842.922247437578112.099556851721
0.62863.185353654272107.802081450724
0.63882.676452685075101.820721788548
0.64901.16475426589894.8407822306443
0.65918.53682182162687.5655880739745
0.66934.79189835933980.6289568366924
0.67950.02487442931574.5297002993487
0.68964.40141772419669.5873061051895
0.69978.13039368187765.9401264118212
0.7991.43819153083763.5672786456646
0.711004.5482716792962.3402021997407
0.721017.6676428167062.0796905355953
0.731030.9804875171462.5933127207504
0.741044.6480283095063.7192611616089
0.751058.8129891336165.3312345677687
0.761073.6065430501367.3564514296626
0.771089.1553315350769.761915856308
0.781105.5860236243272.5485438596139
0.791123.0251778292375.7155007293302
0.81141.5931839373579.2182814631269
0.811161.3929264538982.9409969231014
0.821182.4961736016886.6789357345314
0.831204.9325705032990.1596136044359
0.841228.6861214140993.106665545322
0.851253.7011209568295.319092660111
0.861279.8938742361696.7147267297264
0.871307.1604319905197.3226376146841
0.881335.3677533838497.1763538413132
0.891364.3198454874896.1700562669773
0.91393.7025947966293.9475780042173
0.911423.0282213954289.9370998648016
0.921451.6162308621983.5533425462448
0.931478.6546815126374.5115596616672
0.941503.3743501671363.139833304943
0.951525.3254715783250.5937733556514
0.961544.6540656603238.8370462000336
0.971562.1219441811430.0850823595124
0.981578.4607154182825.3875154485684
0.991592.8644725550123.9014063228503

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 523.725592665636 & 6.12602892442293 \tabularnewline
0.02 & 527.54699447607 & 7.1262738981346 \tabularnewline
0.03 & 532.042020819358 & 8.78450127012958 \tabularnewline
0.04 & 536.757444555061 & 9.9949467885735 \tabularnewline
0.05 & 541.472716243077 & 10.6187258314043 \tabularnewline
0.06 & 546.071006179895 & 11.0362774012967 \tabularnewline
0.07 & 550.507598369871 & 11.4602336995979 \tabularnewline
0.08 & 554.77741412728 & 11.8029109726740 \tabularnewline
0.09 & 558.877161494025 & 11.9218815641327 \tabularnewline
0.1 & 562.791209251572 & 11.7991290247584 \tabularnewline
0.11 & 566.50194124368 & 11.5380831325723 \tabularnewline
0.12 & 570.004930631634 & 11.2717272533348 \tabularnewline
0.13 & 573.314091103975 & 11.0796784526818 \tabularnewline
0.14 & 576.45576705954 & 10.9710894474275 \tabularnewline
0.15 & 579.458884915211 & 10.9086282991722 \tabularnewline
0.16 & 582.348078985161 & 10.8558392550449 \tabularnewline
0.17 & 585.142307543246 & 10.8032801438670 \tabularnewline
0.18 & 587.857449389837 & 10.7715952940206 \tabularnewline
0.19 & 590.509793899065 & 10.7947946234973 \tabularnewline
0.2 & 593.117985418817 & 10.9025245759637 \tabularnewline
0.21 & 595.702616284892 & 11.1067868704743 \tabularnewline
0.22 & 598.284109049308 & 11.3937967520219 \tabularnewline
0.23 & 600.88018014293 & 11.7344188419088 \tabularnewline
0.24 & 603.50401107545 & 12.1015402024765 \tabularnewline
0.25 & 606.163610444649 & 12.4695284157877 \tabularnewline
0.26 & 608.862166554902 & 12.8276481199095 \tabularnewline
0.27 & 611.598790868842 & 13.1662972049679 \tabularnewline
0.28 & 614.369051008712 & 13.4766291583730 \tabularnewline
0.29 & 617.16500090825 & 13.7420164138956 \tabularnewline
0.3 & 619.974829493587 & 13.9379558782064 \tabularnewline
0.31 & 622.782555603833 & 14.0310561271463 \tabularnewline
0.32 & 625.568266791418 & 13.9944307697012 \tabularnewline
0.33 & 628.3092264839 & 13.8087124304069 \tabularnewline
0.34 & 630.981855840515 & 13.4732705503716 \tabularnewline
0.35 & 633.564280340287 & 13.0050600280041 \tabularnewline
0.36 & 636.038947059012 & 12.4395449225730 \tabularnewline
0.37 & 638.394833165825 & 11.8213896851585 \tabularnewline
0.38 & 640.628966557796 & 11.2019984886988 \tabularnewline
0.39 & 642.747289190821 & 10.6331203955092 \tabularnewline
0.4 & 644.76520604168 & 10.1655399656573 \tabularnewline
0.41 & 646.708376985969 & 9.85201651664532 \tabularnewline
0.42 & 648.614355423954 & 9.7568284417602 \tabularnewline
0.43 & 650.53552774879 & 9.97146951159552 \tabularnewline
0.44 & 652.543473018721 & 10.6251021403135 \tabularnewline
0.45 & 654.734387157355 & 11.8956883167636 \tabularnewline
0.46 & 657.23467359153 & 13.9939920276089 \tabularnewline
0.47 & 660.205291227042 & 17.1398073880115 \tabularnewline
0.48 & 663.84309231639 & 21.5365605749112 \tabularnewline
0.49 & 668.377309476545 & 27.3345121784273 \tabularnewline
0.5 & 674.059681199464 & 34.6030919535010 \tabularnewline
0.51 & 681.147503848051 & 43.29807178309 \tabularnewline
0.52 & 689.880133082026 & 53.2241152064222 \tabularnewline
0.53 & 700.450966496913 & 64.0261432688953 \tabularnewline
0.54 & 712.978428194176 & 75.189363967901 \tabularnewline
0.55 & 727.480564614838 & 86.0703704692979 \tabularnewline
0.56 & 743.8581731719 & 95.9683446735606 \tabularnewline
0.57 & 761.890667179906 & 104.199834983103 \tabularnewline
0.58 & 781.247109263351 & 110.188423029902 \tabularnewline
0.59 & 801.512284952202 & 113.547836916308 \tabularnewline
0.6 & 822.224861558703 & 114.142769465271 \tabularnewline
0.61 & 842.922247437578 & 112.099556851721 \tabularnewline
0.62 & 863.185353654272 & 107.802081450724 \tabularnewline
0.63 & 882.676452685075 & 101.820721788548 \tabularnewline
0.64 & 901.164754265898 & 94.8407822306443 \tabularnewline
0.65 & 918.536821821626 & 87.5655880739745 \tabularnewline
0.66 & 934.791898359339 & 80.6289568366924 \tabularnewline
0.67 & 950.024874429315 & 74.5297002993487 \tabularnewline
0.68 & 964.401417724196 & 69.5873061051895 \tabularnewline
0.69 & 978.130393681877 & 65.9401264118212 \tabularnewline
0.7 & 991.438191530837 & 63.5672786456646 \tabularnewline
0.71 & 1004.54827167929 & 62.3402021997407 \tabularnewline
0.72 & 1017.66764281670 & 62.0796905355953 \tabularnewline
0.73 & 1030.98048751714 & 62.5933127207504 \tabularnewline
0.74 & 1044.64802830950 & 63.7192611616089 \tabularnewline
0.75 & 1058.81298913361 & 65.3312345677687 \tabularnewline
0.76 & 1073.60654305013 & 67.3564514296626 \tabularnewline
0.77 & 1089.15533153507 & 69.761915856308 \tabularnewline
0.78 & 1105.58602362432 & 72.5485438596139 \tabularnewline
0.79 & 1123.02517782923 & 75.7155007293302 \tabularnewline
0.8 & 1141.59318393735 & 79.2182814631269 \tabularnewline
0.81 & 1161.39292645389 & 82.9409969231014 \tabularnewline
0.82 & 1182.49617360168 & 86.6789357345314 \tabularnewline
0.83 & 1204.93257050329 & 90.1596136044359 \tabularnewline
0.84 & 1228.68612141409 & 93.106665545322 \tabularnewline
0.85 & 1253.70112095682 & 95.319092660111 \tabularnewline
0.86 & 1279.89387423616 & 96.7147267297264 \tabularnewline
0.87 & 1307.16043199051 & 97.3226376146841 \tabularnewline
0.88 & 1335.36775338384 & 97.1763538413132 \tabularnewline
0.89 & 1364.31984548748 & 96.1700562669773 \tabularnewline
0.9 & 1393.70259479662 & 93.9475780042173 \tabularnewline
0.91 & 1423.02822139542 & 89.9370998648016 \tabularnewline
0.92 & 1451.61623086219 & 83.5533425462448 \tabularnewline
0.93 & 1478.65468151263 & 74.5115596616672 \tabularnewline
0.94 & 1503.37435016713 & 63.139833304943 \tabularnewline
0.95 & 1525.32547157832 & 50.5937733556514 \tabularnewline
0.96 & 1544.65406566032 & 38.8370462000336 \tabularnewline
0.97 & 1562.12194418114 & 30.0850823595124 \tabularnewline
0.98 & 1578.46071541828 & 25.3875154485684 \tabularnewline
0.99 & 1592.86447255501 & 23.9014063228503 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=38875&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]523.725592665636[/C][C]6.12602892442293[/C][/ROW]
[ROW][C]0.02[/C][C]527.54699447607[/C][C]7.1262738981346[/C][/ROW]
[ROW][C]0.03[/C][C]532.042020819358[/C][C]8.78450127012958[/C][/ROW]
[ROW][C]0.04[/C][C]536.757444555061[/C][C]9.9949467885735[/C][/ROW]
[ROW][C]0.05[/C][C]541.472716243077[/C][C]10.6187258314043[/C][/ROW]
[ROW][C]0.06[/C][C]546.071006179895[/C][C]11.0362774012967[/C][/ROW]
[ROW][C]0.07[/C][C]550.507598369871[/C][C]11.4602336995979[/C][/ROW]
[ROW][C]0.08[/C][C]554.77741412728[/C][C]11.8029109726740[/C][/ROW]
[ROW][C]0.09[/C][C]558.877161494025[/C][C]11.9218815641327[/C][/ROW]
[ROW][C]0.1[/C][C]562.791209251572[/C][C]11.7991290247584[/C][/ROW]
[ROW][C]0.11[/C][C]566.50194124368[/C][C]11.5380831325723[/C][/ROW]
[ROW][C]0.12[/C][C]570.004930631634[/C][C]11.2717272533348[/C][/ROW]
[ROW][C]0.13[/C][C]573.314091103975[/C][C]11.0796784526818[/C][/ROW]
[ROW][C]0.14[/C][C]576.45576705954[/C][C]10.9710894474275[/C][/ROW]
[ROW][C]0.15[/C][C]579.458884915211[/C][C]10.9086282991722[/C][/ROW]
[ROW][C]0.16[/C][C]582.348078985161[/C][C]10.8558392550449[/C][/ROW]
[ROW][C]0.17[/C][C]585.142307543246[/C][C]10.8032801438670[/C][/ROW]
[ROW][C]0.18[/C][C]587.857449389837[/C][C]10.7715952940206[/C][/ROW]
[ROW][C]0.19[/C][C]590.509793899065[/C][C]10.7947946234973[/C][/ROW]
[ROW][C]0.2[/C][C]593.117985418817[/C][C]10.9025245759637[/C][/ROW]
[ROW][C]0.21[/C][C]595.702616284892[/C][C]11.1067868704743[/C][/ROW]
[ROW][C]0.22[/C][C]598.284109049308[/C][C]11.3937967520219[/C][/ROW]
[ROW][C]0.23[/C][C]600.88018014293[/C][C]11.7344188419088[/C][/ROW]
[ROW][C]0.24[/C][C]603.50401107545[/C][C]12.1015402024765[/C][/ROW]
[ROW][C]0.25[/C][C]606.163610444649[/C][C]12.4695284157877[/C][/ROW]
[ROW][C]0.26[/C][C]608.862166554902[/C][C]12.8276481199095[/C][/ROW]
[ROW][C]0.27[/C][C]611.598790868842[/C][C]13.1662972049679[/C][/ROW]
[ROW][C]0.28[/C][C]614.369051008712[/C][C]13.4766291583730[/C][/ROW]
[ROW][C]0.29[/C][C]617.16500090825[/C][C]13.7420164138956[/C][/ROW]
[ROW][C]0.3[/C][C]619.974829493587[/C][C]13.9379558782064[/C][/ROW]
[ROW][C]0.31[/C][C]622.782555603833[/C][C]14.0310561271463[/C][/ROW]
[ROW][C]0.32[/C][C]625.568266791418[/C][C]13.9944307697012[/C][/ROW]
[ROW][C]0.33[/C][C]628.3092264839[/C][C]13.8087124304069[/C][/ROW]
[ROW][C]0.34[/C][C]630.981855840515[/C][C]13.4732705503716[/C][/ROW]
[ROW][C]0.35[/C][C]633.564280340287[/C][C]13.0050600280041[/C][/ROW]
[ROW][C]0.36[/C][C]636.038947059012[/C][C]12.4395449225730[/C][/ROW]
[ROW][C]0.37[/C][C]638.394833165825[/C][C]11.8213896851585[/C][/ROW]
[ROW][C]0.38[/C][C]640.628966557796[/C][C]11.2019984886988[/C][/ROW]
[ROW][C]0.39[/C][C]642.747289190821[/C][C]10.6331203955092[/C][/ROW]
[ROW][C]0.4[/C][C]644.76520604168[/C][C]10.1655399656573[/C][/ROW]
[ROW][C]0.41[/C][C]646.708376985969[/C][C]9.85201651664532[/C][/ROW]
[ROW][C]0.42[/C][C]648.614355423954[/C][C]9.7568284417602[/C][/ROW]
[ROW][C]0.43[/C][C]650.53552774879[/C][C]9.97146951159552[/C][/ROW]
[ROW][C]0.44[/C][C]652.543473018721[/C][C]10.6251021403135[/C][/ROW]
[ROW][C]0.45[/C][C]654.734387157355[/C][C]11.8956883167636[/C][/ROW]
[ROW][C]0.46[/C][C]657.23467359153[/C][C]13.9939920276089[/C][/ROW]
[ROW][C]0.47[/C][C]660.205291227042[/C][C]17.1398073880115[/C][/ROW]
[ROW][C]0.48[/C][C]663.84309231639[/C][C]21.5365605749112[/C][/ROW]
[ROW][C]0.49[/C][C]668.377309476545[/C][C]27.3345121784273[/C][/ROW]
[ROW][C]0.5[/C][C]674.059681199464[/C][C]34.6030919535010[/C][/ROW]
[ROW][C]0.51[/C][C]681.147503848051[/C][C]43.29807178309[/C][/ROW]
[ROW][C]0.52[/C][C]689.880133082026[/C][C]53.2241152064222[/C][/ROW]
[ROW][C]0.53[/C][C]700.450966496913[/C][C]64.0261432688953[/C][/ROW]
[ROW][C]0.54[/C][C]712.978428194176[/C][C]75.189363967901[/C][/ROW]
[ROW][C]0.55[/C][C]727.480564614838[/C][C]86.0703704692979[/C][/ROW]
[ROW][C]0.56[/C][C]743.8581731719[/C][C]95.9683446735606[/C][/ROW]
[ROW][C]0.57[/C][C]761.890667179906[/C][C]104.199834983103[/C][/ROW]
[ROW][C]0.58[/C][C]781.247109263351[/C][C]110.188423029902[/C][/ROW]
[ROW][C]0.59[/C][C]801.512284952202[/C][C]113.547836916308[/C][/ROW]
[ROW][C]0.6[/C][C]822.224861558703[/C][C]114.142769465271[/C][/ROW]
[ROW][C]0.61[/C][C]842.922247437578[/C][C]112.099556851721[/C][/ROW]
[ROW][C]0.62[/C][C]863.185353654272[/C][C]107.802081450724[/C][/ROW]
[ROW][C]0.63[/C][C]882.676452685075[/C][C]101.820721788548[/C][/ROW]
[ROW][C]0.64[/C][C]901.164754265898[/C][C]94.8407822306443[/C][/ROW]
[ROW][C]0.65[/C][C]918.536821821626[/C][C]87.5655880739745[/C][/ROW]
[ROW][C]0.66[/C][C]934.791898359339[/C][C]80.6289568366924[/C][/ROW]
[ROW][C]0.67[/C][C]950.024874429315[/C][C]74.5297002993487[/C][/ROW]
[ROW][C]0.68[/C][C]964.401417724196[/C][C]69.5873061051895[/C][/ROW]
[ROW][C]0.69[/C][C]978.130393681877[/C][C]65.9401264118212[/C][/ROW]
[ROW][C]0.7[/C][C]991.438191530837[/C][C]63.5672786456646[/C][/ROW]
[ROW][C]0.71[/C][C]1004.54827167929[/C][C]62.3402021997407[/C][/ROW]
[ROW][C]0.72[/C][C]1017.66764281670[/C][C]62.0796905355953[/C][/ROW]
[ROW][C]0.73[/C][C]1030.98048751714[/C][C]62.5933127207504[/C][/ROW]
[ROW][C]0.74[/C][C]1044.64802830950[/C][C]63.7192611616089[/C][/ROW]
[ROW][C]0.75[/C][C]1058.81298913361[/C][C]65.3312345677687[/C][/ROW]
[ROW][C]0.76[/C][C]1073.60654305013[/C][C]67.3564514296626[/C][/ROW]
[ROW][C]0.77[/C][C]1089.15533153507[/C][C]69.761915856308[/C][/ROW]
[ROW][C]0.78[/C][C]1105.58602362432[/C][C]72.5485438596139[/C][/ROW]
[ROW][C]0.79[/C][C]1123.02517782923[/C][C]75.7155007293302[/C][/ROW]
[ROW][C]0.8[/C][C]1141.59318393735[/C][C]79.2182814631269[/C][/ROW]
[ROW][C]0.81[/C][C]1161.39292645389[/C][C]82.9409969231014[/C][/ROW]
[ROW][C]0.82[/C][C]1182.49617360168[/C][C]86.6789357345314[/C][/ROW]
[ROW][C]0.83[/C][C]1204.93257050329[/C][C]90.1596136044359[/C][/ROW]
[ROW][C]0.84[/C][C]1228.68612141409[/C][C]93.106665545322[/C][/ROW]
[ROW][C]0.85[/C][C]1253.70112095682[/C][C]95.319092660111[/C][/ROW]
[ROW][C]0.86[/C][C]1279.89387423616[/C][C]96.7147267297264[/C][/ROW]
[ROW][C]0.87[/C][C]1307.16043199051[/C][C]97.3226376146841[/C][/ROW]
[ROW][C]0.88[/C][C]1335.36775338384[/C][C]97.1763538413132[/C][/ROW]
[ROW][C]0.89[/C][C]1364.31984548748[/C][C]96.1700562669773[/C][/ROW]
[ROW][C]0.9[/C][C]1393.70259479662[/C][C]93.9475780042173[/C][/ROW]
[ROW][C]0.91[/C][C]1423.02822139542[/C][C]89.9370998648016[/C][/ROW]
[ROW][C]0.92[/C][C]1451.61623086219[/C][C]83.5533425462448[/C][/ROW]
[ROW][C]0.93[/C][C]1478.65468151263[/C][C]74.5115596616672[/C][/ROW]
[ROW][C]0.94[/C][C]1503.37435016713[/C][C]63.139833304943[/C][/ROW]
[ROW][C]0.95[/C][C]1525.32547157832[/C][C]50.5937733556514[/C][/ROW]
[ROW][C]0.96[/C][C]1544.65406566032[/C][C]38.8370462000336[/C][/ROW]
[ROW][C]0.97[/C][C]1562.12194418114[/C][C]30.0850823595124[/C][/ROW]
[ROW][C]0.98[/C][C]1578.46071541828[/C][C]25.3875154485684[/C][/ROW]
[ROW][C]0.99[/C][C]1592.86447255501[/C][C]23.9014063228503[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=38875&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=38875&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
0.01523.7255926656366.12602892442293
0.02527.546994476077.1262738981346
0.03532.0420208193588.78450127012958
0.04536.7574445550619.9949467885735
0.05541.47271624307710.6187258314043
0.06546.07100617989511.0362774012967
0.07550.50759836987111.4602336995979
0.08554.7774141272811.8029109726740
0.09558.87716149402511.9218815641327
0.1562.79120925157211.7991290247584
0.11566.5019412436811.5380831325723
0.12570.00493063163411.2717272533348
0.13573.31409110397511.0796784526818
0.14576.4557670595410.9710894474275
0.15579.45888491521110.9086282991722
0.16582.34807898516110.8558392550449
0.17585.14230754324610.8032801438670
0.18587.85744938983710.7715952940206
0.19590.50979389906510.7947946234973
0.2593.11798541881710.9025245759637
0.21595.70261628489211.1067868704743
0.22598.28410904930811.3937967520219
0.23600.8801801429311.7344188419088
0.24603.5040110754512.1015402024765
0.25606.16361044464912.4695284157877
0.26608.86216655490212.8276481199095
0.27611.59879086884213.1662972049679
0.28614.36905100871213.4766291583730
0.29617.1650009082513.7420164138956
0.3619.97482949358713.9379558782064
0.31622.78255560383314.0310561271463
0.32625.56826679141813.9944307697012
0.33628.309226483913.8087124304069
0.34630.98185584051513.4732705503716
0.35633.56428034028713.0050600280041
0.36636.03894705901212.4395449225730
0.37638.39483316582511.8213896851585
0.38640.62896655779611.2019984886988
0.39642.74728919082110.6331203955092
0.4644.7652060416810.1655399656573
0.41646.7083769859699.85201651664532
0.42648.6143554239549.7568284417602
0.43650.535527748799.97146951159552
0.44652.54347301872110.6251021403135
0.45654.73438715735511.8956883167636
0.46657.2346735915313.9939920276089
0.47660.20529122704217.1398073880115
0.48663.8430923163921.5365605749112
0.49668.37730947654527.3345121784273
0.5674.05968119946434.6030919535010
0.51681.14750384805143.29807178309
0.52689.88013308202653.2241152064222
0.53700.45096649691364.0261432688953
0.54712.97842819417675.189363967901
0.55727.48056461483886.0703704692979
0.56743.858173171995.9683446735606
0.57761.890667179906104.199834983103
0.58781.247109263351110.188423029902
0.59801.512284952202113.547836916308
0.6822.224861558703114.142769465271
0.61842.922247437578112.099556851721
0.62863.185353654272107.802081450724
0.63882.676452685075101.820721788548
0.64901.16475426589894.8407822306443
0.65918.53682182162687.5655880739745
0.66934.79189835933980.6289568366924
0.67950.02487442931574.5297002993487
0.68964.40141772419669.5873061051895
0.69978.13039368187765.9401264118212
0.7991.43819153083763.5672786456646
0.711004.5482716792962.3402021997407
0.721017.6676428167062.0796905355953
0.731030.9804875171462.5933127207504
0.741044.6480283095063.7192611616089
0.751058.8129891336165.3312345677687
0.761073.6065430501367.3564514296626
0.771089.1553315350769.761915856308
0.781105.5860236243272.5485438596139
0.791123.0251778292375.7155007293302
0.81141.5931839373579.2182814631269
0.811161.3929264538982.9409969231014
0.821182.4961736016886.6789357345314
0.831204.9325705032990.1596136044359
0.841228.6861214140993.106665545322
0.851253.7011209568295.319092660111
0.861279.8938742361696.7147267297264
0.871307.1604319905197.3226376146841
0.881335.3677533838497.1763538413132
0.891364.3198454874896.1700562669773
0.91393.7025947966293.9475780042173
0.911423.0282213954289.9370998648016
0.921451.6162308621983.5533425462448
0.931478.6546815126374.5115596616672
0.941503.3743501671363.139833304943
0.951525.3254715783250.5937733556514
0.961544.6540656603238.8370462000336
0.971562.1219441811430.0850823595124
0.981578.4607154182825.3875154485684
0.991592.8644725550123.9014063228503


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')