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Description of Statistical Computation

Author's title

harrel davis percentielen gemiddelde consumentenprijs vitro keramische plat...

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationTue, 10 Feb 2015 18:02:33 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Feb/10/t142359142298frxzzueeufe7l.htm/, Retrieved Sat, 18 May 2024 02:30:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=276980, Retrieved Sat, 18 May 2024 02:30:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsAVW
Estimated Impact142

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 perc...] [2015-02-10 18:02:33] [09743efd8c85782f9ae22fefb9801b71] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
551,91
551,46
550,12
549,95
548,01
548,92
548,92
549,06
547,07
546,5
544,95
544,23
544,23
541,6
541,37
540,43
540,47
540,52
540,52
539,7
540,89
540,51
537,43
538,14
538,14
537,74
540,33
540,02
539,21
539,84
539,84
537,3
536,27
536,75
536,21
536,99
536,99
536,57
536,91
536,97
540,45
542,42
542,42
542,98
540,19
537,16
537,35
537,03
537,03
536,27
534,71
537,12
537,07
537,33
537,33
538,79
539,24
537,17
536,46
532,3
532,3
532,89
533,47
532,54
533,8
534,15
534,15
534,15
534,28
535,63
534,21
533,78
533,78
534,55
536,93
536,09
533,91
533,99
533,99
533,76
532,5
529,5
528,62
528,7
521,27
521,19
519,43
516,81
516,78
515,45
516,22
517,01
518,19
516,79
516,87
514,1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=276980&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]1 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=276980&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=276980&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 time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01514.6994505954811.10738500024083
0.02515.4765456286740.850096928898229
0.03516.0888686754630.650289636139575
0.04516.5208240633070.570137593015719
0.05516.8789865898360.73279571176199
0.06517.2827564869381.16528838941549
0.07517.8333616998871.81259160844142
0.08518.599874332992.59586138390268
0.09519.6112629991743.41434530089435
0.1520.8549626316484.15123009418184
0.11522.2817313988814.69854489595502
0.12523.8160377112424.98043491188994
0.13525.3704502536374.97008088416115
0.14526.8611861832434.69292113673131
0.15528.2211979216584.21890910504142
0.16529.4078534252713.63514337335893
0.17530.4041869285053.02334445158229
0.18531.2148214734252.44954719325005
0.19531.8589745205871.95068370294903
0.2532.363092244761.54091257063927
0.21532.7549174654841.21781383783731
0.22533.0597561676060.968579402875462
0.23533.298840693490.7815446085658
0.24533.4892048585960.64216660735642
0.25533.6443721183850.541363694013892
0.26533.7752820596380.47624553992778
0.27533.8910964314140.443450375382342
0.28533.9997275278390.442617277436017
0.29534.1080698316520.469584151695956
0.3534.221988207230.519887110242442
0.31534.3461446311040.588524593272098
0.32534.4837542861840.666086100618624
0.33534.6363631951710.746272033317812
0.34534.8037330381320.819545948769208
0.35534.9838983492990.87765820469622
0.36535.1734242065920.914443839038617
0.37535.3678445508490.927583125487669
0.38535.5622155378850.916242560958718
0.39535.7516895735980.881717659640053
0.4535.9320133569810.829227703726771
0.41536.099877232340.762921026240451
0.42536.2530840052950.689803511418362
0.43536.390548711040.613732946303712
0.44536.5121732844550.538770239641983
0.45536.618654200230.469430012613631
0.46536.7112770799910.408404819010575
0.47536.7917361692080.353769487621542
0.48536.8619969770060.309251578326063
0.49536.9242043018430.275740205474076
0.5536.9806286328840.251989288408508
0.51537.0336408711760.240709686469929
0.52537.0857053783910.24155243485207
0.53537.1393812296970.255115616852394
0.54537.1973195059850.281794253359092
0.55537.2622411310690.322456551799629
0.56537.3368776512220.375147605050488
0.57537.4238595489180.439475104849659
0.58537.5255452377830.515171438595959
0.59537.6437985790640.596561552699491
0.6537.7797406501080.680811926394504
0.61537.9335175141820.764205766857896
0.62538.1041342073420.837578950352508
0.63538.2894017730650.898191054321583
0.64538.4860278412290.940041353870027
0.65538.6898550049120.958706463776717
0.66538.8962218333640.955023083387451
0.67539.1003973108210.928864709856074
0.68539.2980282646520.883535055930868
0.69539.4855443879430.823523414162041
0.7539.6604843981660.754545167459309
0.71539.8217317981510.68279483824136
0.72539.9696688725780.614950750455858
0.73540.1062638358560.556942793137269
0.74540.235095546240.517003006528049
0.75540.3612988648880.501414615085184
0.76540.4913951697810.51503060680803
0.77540.6329724741480.562416937287202
0.78540.7942076681080.642774300357715
0.79540.983275729130.750638203801843
0.8541.2077478552750.881122532452494
0.81541.4741131008381.0263684416102
0.82541.7875395181611.17947965966972
0.83542.1519101138411.33424465037587
0.84542.570038882931.48643142484723
0.85543.0438298639311.63352358214751
0.86543.5740458808751.77053857323079
0.87544.1593789211421.89208429570147
0.88544.7947412324041.98526448621206
0.89545.4691715260372.03096826889151
0.9546.1644057538922.0075522852265
0.91546.8557042684731.8990725105178
0.92547.5163999795091.70607909103761
0.93548.1262825586821.45581650839362
0.94548.6815453701021.20164239749913
0.95549.2019274722411.00833435603792
0.96549.729576954590.922550925525593
0.97550.3115642457510.935660440368863
0.98550.9547687507090.928353742307972
0.99551.5590717308460.714229468271526

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 514.699450595481 & 1.10738500024083 \tabularnewline
0.02 & 515.476545628674 & 0.850096928898229 \tabularnewline
0.03 & 516.088868675463 & 0.650289636139575 \tabularnewline
0.04 & 516.520824063307 & 0.570137593015719 \tabularnewline
0.05 & 516.878986589836 & 0.73279571176199 \tabularnewline
0.06 & 517.282756486938 & 1.16528838941549 \tabularnewline
0.07 & 517.833361699887 & 1.81259160844142 \tabularnewline
0.08 & 518.59987433299 & 2.59586138390268 \tabularnewline
0.09 & 519.611262999174 & 3.41434530089435 \tabularnewline
0.1 & 520.854962631648 & 4.15123009418184 \tabularnewline
0.11 & 522.281731398881 & 4.69854489595502 \tabularnewline
0.12 & 523.816037711242 & 4.98043491188994 \tabularnewline
0.13 & 525.370450253637 & 4.97008088416115 \tabularnewline
0.14 & 526.861186183243 & 4.69292113673131 \tabularnewline
0.15 & 528.221197921658 & 4.21890910504142 \tabularnewline
0.16 & 529.407853425271 & 3.63514337335893 \tabularnewline
0.17 & 530.404186928505 & 3.02334445158229 \tabularnewline
0.18 & 531.214821473425 & 2.44954719325005 \tabularnewline
0.19 & 531.858974520587 & 1.95068370294903 \tabularnewline
0.2 & 532.36309224476 & 1.54091257063927 \tabularnewline
0.21 & 532.754917465484 & 1.21781383783731 \tabularnewline
0.22 & 533.059756167606 & 0.968579402875462 \tabularnewline
0.23 & 533.29884069349 & 0.7815446085658 \tabularnewline
0.24 & 533.489204858596 & 0.64216660735642 \tabularnewline
0.25 & 533.644372118385 & 0.541363694013892 \tabularnewline
0.26 & 533.775282059638 & 0.47624553992778 \tabularnewline
0.27 & 533.891096431414 & 0.443450375382342 \tabularnewline
0.28 & 533.999727527839 & 0.442617277436017 \tabularnewline
0.29 & 534.108069831652 & 0.469584151695956 \tabularnewline
0.3 & 534.22198820723 & 0.519887110242442 \tabularnewline
0.31 & 534.346144631104 & 0.588524593272098 \tabularnewline
0.32 & 534.483754286184 & 0.666086100618624 \tabularnewline
0.33 & 534.636363195171 & 0.746272033317812 \tabularnewline
0.34 & 534.803733038132 & 0.819545948769208 \tabularnewline
0.35 & 534.983898349299 & 0.87765820469622 \tabularnewline
0.36 & 535.173424206592 & 0.914443839038617 \tabularnewline
0.37 & 535.367844550849 & 0.927583125487669 \tabularnewline
0.38 & 535.562215537885 & 0.916242560958718 \tabularnewline
0.39 & 535.751689573598 & 0.881717659640053 \tabularnewline
0.4 & 535.932013356981 & 0.829227703726771 \tabularnewline
0.41 & 536.09987723234 & 0.762921026240451 \tabularnewline
0.42 & 536.253084005295 & 0.689803511418362 \tabularnewline
0.43 & 536.39054871104 & 0.613732946303712 \tabularnewline
0.44 & 536.512173284455 & 0.538770239641983 \tabularnewline
0.45 & 536.61865420023 & 0.469430012613631 \tabularnewline
0.46 & 536.711277079991 & 0.408404819010575 \tabularnewline
0.47 & 536.791736169208 & 0.353769487621542 \tabularnewline
0.48 & 536.861996977006 & 0.309251578326063 \tabularnewline
0.49 & 536.924204301843 & 0.275740205474076 \tabularnewline
0.5 & 536.980628632884 & 0.251989288408508 \tabularnewline
0.51 & 537.033640871176 & 0.240709686469929 \tabularnewline
0.52 & 537.085705378391 & 0.24155243485207 \tabularnewline
0.53 & 537.139381229697 & 0.255115616852394 \tabularnewline
0.54 & 537.197319505985 & 0.281794253359092 \tabularnewline
0.55 & 537.262241131069 & 0.322456551799629 \tabularnewline
0.56 & 537.336877651222 & 0.375147605050488 \tabularnewline
0.57 & 537.423859548918 & 0.439475104849659 \tabularnewline
0.58 & 537.525545237783 & 0.515171438595959 \tabularnewline
0.59 & 537.643798579064 & 0.596561552699491 \tabularnewline
0.6 & 537.779740650108 & 0.680811926394504 \tabularnewline
0.61 & 537.933517514182 & 0.764205766857896 \tabularnewline
0.62 & 538.104134207342 & 0.837578950352508 \tabularnewline
0.63 & 538.289401773065 & 0.898191054321583 \tabularnewline
0.64 & 538.486027841229 & 0.940041353870027 \tabularnewline
0.65 & 538.689855004912 & 0.958706463776717 \tabularnewline
0.66 & 538.896221833364 & 0.955023083387451 \tabularnewline
0.67 & 539.100397310821 & 0.928864709856074 \tabularnewline
0.68 & 539.298028264652 & 0.883535055930868 \tabularnewline
0.69 & 539.485544387943 & 0.823523414162041 \tabularnewline
0.7 & 539.660484398166 & 0.754545167459309 \tabularnewline
0.71 & 539.821731798151 & 0.68279483824136 \tabularnewline
0.72 & 539.969668872578 & 0.614950750455858 \tabularnewline
0.73 & 540.106263835856 & 0.556942793137269 \tabularnewline
0.74 & 540.23509554624 & 0.517003006528049 \tabularnewline
0.75 & 540.361298864888 & 0.501414615085184 \tabularnewline
0.76 & 540.491395169781 & 0.51503060680803 \tabularnewline
0.77 & 540.632972474148 & 0.562416937287202 \tabularnewline
0.78 & 540.794207668108 & 0.642774300357715 \tabularnewline
0.79 & 540.98327572913 & 0.750638203801843 \tabularnewline
0.8 & 541.207747855275 & 0.881122532452494 \tabularnewline
0.81 & 541.474113100838 & 1.0263684416102 \tabularnewline
0.82 & 541.787539518161 & 1.17947965966972 \tabularnewline
0.83 & 542.151910113841 & 1.33424465037587 \tabularnewline
0.84 & 542.57003888293 & 1.48643142484723 \tabularnewline
0.85 & 543.043829863931 & 1.63352358214751 \tabularnewline
0.86 & 543.574045880875 & 1.77053857323079 \tabularnewline
0.87 & 544.159378921142 & 1.89208429570147 \tabularnewline
0.88 & 544.794741232404 & 1.98526448621206 \tabularnewline
0.89 & 545.469171526037 & 2.03096826889151 \tabularnewline
0.9 & 546.164405753892 & 2.0075522852265 \tabularnewline
0.91 & 546.855704268473 & 1.8990725105178 \tabularnewline
0.92 & 547.516399979509 & 1.70607909103761 \tabularnewline
0.93 & 548.126282558682 & 1.45581650839362 \tabularnewline
0.94 & 548.681545370102 & 1.20164239749913 \tabularnewline
0.95 & 549.201927472241 & 1.00833435603792 \tabularnewline
0.96 & 549.72957695459 & 0.922550925525593 \tabularnewline
0.97 & 550.311564245751 & 0.935660440368863 \tabularnewline
0.98 & 550.954768750709 & 0.928353742307972 \tabularnewline
0.99 & 551.559071730846 & 0.714229468271526 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=276980&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]514.699450595481[/C][C]1.10738500024083[/C][/ROW]
[ROW][C]0.02[/C][C]515.476545628674[/C][C]0.850096928898229[/C][/ROW]
[ROW][C]0.03[/C][C]516.088868675463[/C][C]0.650289636139575[/C][/ROW]
[ROW][C]0.04[/C][C]516.520824063307[/C][C]0.570137593015719[/C][/ROW]
[ROW][C]0.05[/C][C]516.878986589836[/C][C]0.73279571176199[/C][/ROW]
[ROW][C]0.06[/C][C]517.282756486938[/C][C]1.16528838941549[/C][/ROW]
[ROW][C]0.07[/C][C]517.833361699887[/C][C]1.81259160844142[/C][/ROW]
[ROW][C]0.08[/C][C]518.59987433299[/C][C]2.59586138390268[/C][/ROW]
[ROW][C]0.09[/C][C]519.611262999174[/C][C]3.41434530089435[/C][/ROW]
[ROW][C]0.1[/C][C]520.854962631648[/C][C]4.15123009418184[/C][/ROW]
[ROW][C]0.11[/C][C]522.281731398881[/C][C]4.69854489595502[/C][/ROW]
[ROW][C]0.12[/C][C]523.816037711242[/C][C]4.98043491188994[/C][/ROW]
[ROW][C]0.13[/C][C]525.370450253637[/C][C]4.97008088416115[/C][/ROW]
[ROW][C]0.14[/C][C]526.861186183243[/C][C]4.69292113673131[/C][/ROW]
[ROW][C]0.15[/C][C]528.221197921658[/C][C]4.21890910504142[/C][/ROW]
[ROW][C]0.16[/C][C]529.407853425271[/C][C]3.63514337335893[/C][/ROW]
[ROW][C]0.17[/C][C]530.404186928505[/C][C]3.02334445158229[/C][/ROW]
[ROW][C]0.18[/C][C]531.214821473425[/C][C]2.44954719325005[/C][/ROW]
[ROW][C]0.19[/C][C]531.858974520587[/C][C]1.95068370294903[/C][/ROW]
[ROW][C]0.2[/C][C]532.36309224476[/C][C]1.54091257063927[/C][/ROW]
[ROW][C]0.21[/C][C]532.754917465484[/C][C]1.21781383783731[/C][/ROW]
[ROW][C]0.22[/C][C]533.059756167606[/C][C]0.968579402875462[/C][/ROW]
[ROW][C]0.23[/C][C]533.29884069349[/C][C]0.7815446085658[/C][/ROW]
[ROW][C]0.24[/C][C]533.489204858596[/C][C]0.64216660735642[/C][/ROW]
[ROW][C]0.25[/C][C]533.644372118385[/C][C]0.541363694013892[/C][/ROW]
[ROW][C]0.26[/C][C]533.775282059638[/C][C]0.47624553992778[/C][/ROW]
[ROW][C]0.27[/C][C]533.891096431414[/C][C]0.443450375382342[/C][/ROW]
[ROW][C]0.28[/C][C]533.999727527839[/C][C]0.442617277436017[/C][/ROW]
[ROW][C]0.29[/C][C]534.108069831652[/C][C]0.469584151695956[/C][/ROW]
[ROW][C]0.3[/C][C]534.22198820723[/C][C]0.519887110242442[/C][/ROW]
[ROW][C]0.31[/C][C]534.346144631104[/C][C]0.588524593272098[/C][/ROW]
[ROW][C]0.32[/C][C]534.483754286184[/C][C]0.666086100618624[/C][/ROW]
[ROW][C]0.33[/C][C]534.636363195171[/C][C]0.746272033317812[/C][/ROW]
[ROW][C]0.34[/C][C]534.803733038132[/C][C]0.819545948769208[/C][/ROW]
[ROW][C]0.35[/C][C]534.983898349299[/C][C]0.87765820469622[/C][/ROW]
[ROW][C]0.36[/C][C]535.173424206592[/C][C]0.914443839038617[/C][/ROW]
[ROW][C]0.37[/C][C]535.367844550849[/C][C]0.927583125487669[/C][/ROW]
[ROW][C]0.38[/C][C]535.562215537885[/C][C]0.916242560958718[/C][/ROW]
[ROW][C]0.39[/C][C]535.751689573598[/C][C]0.881717659640053[/C][/ROW]
[ROW][C]0.4[/C][C]535.932013356981[/C][C]0.829227703726771[/C][/ROW]
[ROW][C]0.41[/C][C]536.09987723234[/C][C]0.762921026240451[/C][/ROW]
[ROW][C]0.42[/C][C]536.253084005295[/C][C]0.689803511418362[/C][/ROW]
[ROW][C]0.43[/C][C]536.39054871104[/C][C]0.613732946303712[/C][/ROW]
[ROW][C]0.44[/C][C]536.512173284455[/C][C]0.538770239641983[/C][/ROW]
[ROW][C]0.45[/C][C]536.61865420023[/C][C]0.469430012613631[/C][/ROW]
[ROW][C]0.46[/C][C]536.711277079991[/C][C]0.408404819010575[/C][/ROW]
[ROW][C]0.47[/C][C]536.791736169208[/C][C]0.353769487621542[/C][/ROW]
[ROW][C]0.48[/C][C]536.861996977006[/C][C]0.309251578326063[/C][/ROW]
[ROW][C]0.49[/C][C]536.924204301843[/C][C]0.275740205474076[/C][/ROW]
[ROW][C]0.5[/C][C]536.980628632884[/C][C]0.251989288408508[/C][/ROW]
[ROW][C]0.51[/C][C]537.033640871176[/C][C]0.240709686469929[/C][/ROW]
[ROW][C]0.52[/C][C]537.085705378391[/C][C]0.24155243485207[/C][/ROW]
[ROW][C]0.53[/C][C]537.139381229697[/C][C]0.255115616852394[/C][/ROW]
[ROW][C]0.54[/C][C]537.197319505985[/C][C]0.281794253359092[/C][/ROW]
[ROW][C]0.55[/C][C]537.262241131069[/C][C]0.322456551799629[/C][/ROW]
[ROW][C]0.56[/C][C]537.336877651222[/C][C]0.375147605050488[/C][/ROW]
[ROW][C]0.57[/C][C]537.423859548918[/C][C]0.439475104849659[/C][/ROW]
[ROW][C]0.58[/C][C]537.525545237783[/C][C]0.515171438595959[/C][/ROW]
[ROW][C]0.59[/C][C]537.643798579064[/C][C]0.596561552699491[/C][/ROW]
[ROW][C]0.6[/C][C]537.779740650108[/C][C]0.680811926394504[/C][/ROW]
[ROW][C]0.61[/C][C]537.933517514182[/C][C]0.764205766857896[/C][/ROW]
[ROW][C]0.62[/C][C]538.104134207342[/C][C]0.837578950352508[/C][/ROW]
[ROW][C]0.63[/C][C]538.289401773065[/C][C]0.898191054321583[/C][/ROW]
[ROW][C]0.64[/C][C]538.486027841229[/C][C]0.940041353870027[/C][/ROW]
[ROW][C]0.65[/C][C]538.689855004912[/C][C]0.958706463776717[/C][/ROW]
[ROW][C]0.66[/C][C]538.896221833364[/C][C]0.955023083387451[/C][/ROW]
[ROW][C]0.67[/C][C]539.100397310821[/C][C]0.928864709856074[/C][/ROW]
[ROW][C]0.68[/C][C]539.298028264652[/C][C]0.883535055930868[/C][/ROW]
[ROW][C]0.69[/C][C]539.485544387943[/C][C]0.823523414162041[/C][/ROW]
[ROW][C]0.7[/C][C]539.660484398166[/C][C]0.754545167459309[/C][/ROW]
[ROW][C]0.71[/C][C]539.821731798151[/C][C]0.68279483824136[/C][/ROW]
[ROW][C]0.72[/C][C]539.969668872578[/C][C]0.614950750455858[/C][/ROW]
[ROW][C]0.73[/C][C]540.106263835856[/C][C]0.556942793137269[/C][/ROW]
[ROW][C]0.74[/C][C]540.23509554624[/C][C]0.517003006528049[/C][/ROW]
[ROW][C]0.75[/C][C]540.361298864888[/C][C]0.501414615085184[/C][/ROW]
[ROW][C]0.76[/C][C]540.491395169781[/C][C]0.51503060680803[/C][/ROW]
[ROW][C]0.77[/C][C]540.632972474148[/C][C]0.562416937287202[/C][/ROW]
[ROW][C]0.78[/C][C]540.794207668108[/C][C]0.642774300357715[/C][/ROW]
[ROW][C]0.79[/C][C]540.98327572913[/C][C]0.750638203801843[/C][/ROW]
[ROW][C]0.8[/C][C]541.207747855275[/C][C]0.881122532452494[/C][/ROW]
[ROW][C]0.81[/C][C]541.474113100838[/C][C]1.0263684416102[/C][/ROW]
[ROW][C]0.82[/C][C]541.787539518161[/C][C]1.17947965966972[/C][/ROW]
[ROW][C]0.83[/C][C]542.151910113841[/C][C]1.33424465037587[/C][/ROW]
[ROW][C]0.84[/C][C]542.57003888293[/C][C]1.48643142484723[/C][/ROW]
[ROW][C]0.85[/C][C]543.043829863931[/C][C]1.63352358214751[/C][/ROW]
[ROW][C]0.86[/C][C]543.574045880875[/C][C]1.77053857323079[/C][/ROW]
[ROW][C]0.87[/C][C]544.159378921142[/C][C]1.89208429570147[/C][/ROW]
[ROW][C]0.88[/C][C]544.794741232404[/C][C]1.98526448621206[/C][/ROW]
[ROW][C]0.89[/C][C]545.469171526037[/C][C]2.03096826889151[/C][/ROW]
[ROW][C]0.9[/C][C]546.164405753892[/C][C]2.0075522852265[/C][/ROW]
[ROW][C]0.91[/C][C]546.855704268473[/C][C]1.8990725105178[/C][/ROW]
[ROW][C]0.92[/C][C]547.516399979509[/C][C]1.70607909103761[/C][/ROW]
[ROW][C]0.93[/C][C]548.126282558682[/C][C]1.45581650839362[/C][/ROW]
[ROW][C]0.94[/C][C]548.681545370102[/C][C]1.20164239749913[/C][/ROW]
[ROW][C]0.95[/C][C]549.201927472241[/C][C]1.00833435603792[/C][/ROW]
[ROW][C]0.96[/C][C]549.72957695459[/C][C]0.922550925525593[/C][/ROW]
[ROW][C]0.97[/C][C]550.311564245751[/C][C]0.935660440368863[/C][/ROW]
[ROW][C]0.98[/C][C]550.954768750709[/C][C]0.928353742307972[/C][/ROW]
[ROW][C]0.99[/C][C]551.559071730846[/C][C]0.714229468271526[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=276980&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=276980&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
0.01514.6994505954811.10738500024083
0.02515.4765456286740.850096928898229
0.03516.0888686754630.650289636139575
0.04516.5208240633070.570137593015719
0.05516.8789865898360.73279571176199
0.06517.2827564869381.16528838941549
0.07517.8333616998871.81259160844142
0.08518.599874332992.59586138390268
0.09519.6112629991743.41434530089435
0.1520.8549626316484.15123009418184
0.11522.2817313988814.69854489595502
0.12523.8160377112424.98043491188994
0.13525.3704502536374.97008088416115
0.14526.8611861832434.69292113673131
0.15528.2211979216584.21890910504142
0.16529.4078534252713.63514337335893
0.17530.4041869285053.02334445158229
0.18531.2148214734252.44954719325005
0.19531.8589745205871.95068370294903
0.2532.363092244761.54091257063927
0.21532.7549174654841.21781383783731
0.22533.0597561676060.968579402875462
0.23533.298840693490.7815446085658
0.24533.4892048585960.64216660735642
0.25533.6443721183850.541363694013892
0.26533.7752820596380.47624553992778
0.27533.8910964314140.443450375382342
0.28533.9997275278390.442617277436017
0.29534.1080698316520.469584151695956
0.3534.221988207230.519887110242442
0.31534.3461446311040.588524593272098
0.32534.4837542861840.666086100618624
0.33534.6363631951710.746272033317812
0.34534.8037330381320.819545948769208
0.35534.9838983492990.87765820469622
0.36535.1734242065920.914443839038617
0.37535.3678445508490.927583125487669
0.38535.5622155378850.916242560958718
0.39535.7516895735980.881717659640053
0.4535.9320133569810.829227703726771
0.41536.099877232340.762921026240451
0.42536.2530840052950.689803511418362
0.43536.390548711040.613732946303712
0.44536.5121732844550.538770239641983
0.45536.618654200230.469430012613631
0.46536.7112770799910.408404819010575
0.47536.7917361692080.353769487621542
0.48536.8619969770060.309251578326063
0.49536.9242043018430.275740205474076
0.5536.9806286328840.251989288408508
0.51537.0336408711760.240709686469929
0.52537.0857053783910.24155243485207
0.53537.1393812296970.255115616852394
0.54537.1973195059850.281794253359092
0.55537.2622411310690.322456551799629
0.56537.3368776512220.375147605050488
0.57537.4238595489180.439475104849659
0.58537.5255452377830.515171438595959
0.59537.6437985790640.596561552699491
0.6537.7797406501080.680811926394504
0.61537.9335175141820.764205766857896
0.62538.1041342073420.837578950352508
0.63538.2894017730650.898191054321583
0.64538.4860278412290.940041353870027
0.65538.6898550049120.958706463776717
0.66538.8962218333640.955023083387451
0.67539.1003973108210.928864709856074
0.68539.2980282646520.883535055930868
0.69539.4855443879430.823523414162041
0.7539.6604843981660.754545167459309
0.71539.8217317981510.68279483824136
0.72539.9696688725780.614950750455858
0.73540.1062638358560.556942793137269
0.74540.235095546240.517003006528049
0.75540.3612988648880.501414615085184
0.76540.4913951697810.51503060680803
0.77540.6329724741480.562416937287202
0.78540.7942076681080.642774300357715
0.79540.983275729130.750638203801843
0.8541.2077478552750.881122532452494
0.81541.4741131008381.0263684416102
0.82541.7875395181611.17947965966972
0.83542.1519101138411.33424465037587
0.84542.570038882931.48643142484723
0.85543.0438298639311.63352358214751
0.86543.5740458808751.77053857323079
0.87544.1593789211421.89208429570147
0.88544.7947412324041.98526448621206
0.89545.4691715260372.03096826889151
0.9546.1644057538922.0075522852265
0.91546.8557042684731.8990725105178
0.92547.5163999795091.70607909103761
0.93548.1262825586821.45581650839362
0.94548.6815453701021.20164239749913
0.95549.2019274722411.00833435603792
0.96549.729576954590.922550925525593
0.97550.3115642457510.935660440368863
0.98550.9547687507090.928353742307972
0.99551.5590717308460.714229468271526


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')