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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationFri, 09 Oct 2015 14:52:24 +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/2015/Oct/09/t1444398856kck6fw9n7rujzgf.htm/, Retrieved Tue, 14 May 2024 16:39:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=281904, Retrieved Tue, 14 May 2024 16:39:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact52

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] [] [2015-10-09 13:52:24] [bfd47bf74fe11b18de27163a0fd6b465] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
83.36
83.61
83.41
83.64
84.06
83.93
84.1
84.37
84.18
84.11
84.56
84.2
84.45
84.28
84.28
84.7
85.04
85.31
85.18
85.02
86.31
86.56
86.4
86.84
87.42
87.28
87.27
87.73
87.32
87.15
87.5
87.43
88.81
89.38
88.83
88.91
89.34
89.56
89.32
89.31
89.45
88.92
89.35
88.89
90.1
90.49
89.96
89.93
90.32
90.24
90.61
91.06
90.81
91.09
91.17
90.87
91.92
92.67
92.03
92.09
92.61
92.19
92.68
92.66
92.77
92.21
92.58
91.9
93.81
94.05
94.51
94.49
94.36
94.72
95.57
95.87
95.93
96.09
95.82
96.06
97.09
97.67
98.53
98.12
98.84
98.98
100.04
99.47
99.84
99.52
99.81
99.55
100.21
101.44
101
101.32
101.84
101.81
101.83
102.18
101.97
101.8
101.69
101.91
102.27
102.73
102.61
102.89

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=281904&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=281904&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281904&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
0.0183.41963319280680.114950260653807
0.0283.53613477365850.182612049220676
0.0383.67560099138160.217288836648873
0.0483.81281086388430.220243909742539
0.0583.93342555654320.196469024413591
0.0684.03218639051760.165881797084564
0.0784.11224577472840.149272661502234
0.0884.18205782622050.155929371630939
0.0984.25129684704670.185108925880167
0.184.32842552640430.233657912166159
0.1184.42012674953850.299313705332873
0.1284.53150577336910.379518265130788
0.1384.66625332234830.471249479804184
0.1484.82654655956880.570161169061951
0.1585.01275785784740.669322821465253
0.1685.22313043140350.760693686794421
0.1785.45362546077780.834776309947532
0.1885.69815197065540.883913859170449
0.1985.94929763969520.903870779472623
0.286.19948721533330.895892279190724
0.2186.44229347003460.866334644646699
0.2286.67352314490880.826179317441675
0.2386.89175139209440.786479386440045
0.2487.098155817360.757921119155301
0.2587.29572507256320.745691459379977
0.2687.48810129700150.749364447216998
0.2787.67840369891430.763026736002218
0.2887.868355668150.777945298792063
0.2988.05791974370910.785497449578924
0.388.24547858263640.780090548135774
0.3188.42844127612350.759237850588095
0.3288.60405116746650.725111605642573
0.3388.77014886999940.682293522532522
0.3488.92569741672870.63741965436791
0.3589.07097567499440.596771180294985
0.3689.2074518764150.565984330676843
0.3789.3374284507940.547584001686926
0.3889.4635859401840.54203498290202
0.3989.5885485848440.547668838764447
0.489.71455972062450.561972393072286
0.4189.84330778862670.581505533256405
0.4289.97589808672730.60364190191886
0.4390.11293149152130.626622694342686
0.4490.25463448648610.64930667543319
0.4590.40098578906950.671469750293694
0.4690.5518007557770.692257020284956
0.4790.70675968590660.711441662858544
0.4890.86539253634540.728143988050216
0.4991.0270527430710.741418573345679
0.591.19092095041860.750160580606917
0.5191.35607293095790.753515200163779
0.5291.52162637541420.752267916219485
0.5391.68695387126640.747707923933819
0.5491.85192205475680.742809487572869
0.5592.01709783155280.74130223734212
0.5692.18385821392370.747731427949398
0.5792.35435375256950.766016772445319
0.5892.53130532384680.798533125169052
0.5992.71765416774660.845331696715724
0.692.91612586996260.903688917989196
0.6193.1287990990370.969084357696842
0.6293.35677943563221.03550424681753
0.6393.6000624844061.09765573657017
0.6493.85763066937311.15091136424627
0.6594.12777360299451.19299480562409
0.6694.40856560001161.22422030231628
0.6794.69838865372171.24728208907771
0.6894.99636506658561.26658727545034
0.6995.30256785052221.28724261667325
0.795.61791350569271.3132425289614
0.7195.94371177145981.34594713663343
0.7296.28094312822371.38258824990766
0.7396.62943646615331.4166484735601
0.7496.98719254913381.43849508425737
0.7597.35010719278091.43906575770388
0.7697.71227048072031.41116496096201
0.7798.06686489423011.35300517432196
0.7898.40749821186191.26886515164501
0.7998.72964504300561.16863015548179
0.899.03178535804831.06619280626799
0.8199.31584835332030.976418649280295
0.8299.58670218597330.910711362569965
0.8399.85066568662670.873461619875012
0.84100.1133278586030.858504411779439
0.85100.377274281930.850834025470908
0.86100.6405122239220.831517812840143
0.87100.8963156212970.784688550785962
0.88101.1348082118370.703683703958416
0.89101.3459658908870.593111310539217
0.9101.5231127963530.46826204943805
0.91101.6657093281530.349676240545672
0.92101.7804372167570.257629538899896
0.93101.8801944537090.207242478459176
0.94101.9813278328490.201758602025563
0.95102.0997638809110.227853822536926
0.96102.2462529259660.262814364456816
0.97102.4208645561590.278216965225492
0.98102.6096225274550.245188077080856
0.99102.7839699989520.179771804231946

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 83.4196331928068 & 0.114950260653807 \tabularnewline
0.02 & 83.5361347736585 & 0.182612049220676 \tabularnewline
0.03 & 83.6756009913816 & 0.217288836648873 \tabularnewline
0.04 & 83.8128108638843 & 0.220243909742539 \tabularnewline
0.05 & 83.9334255565432 & 0.196469024413591 \tabularnewline
0.06 & 84.0321863905176 & 0.165881797084564 \tabularnewline
0.07 & 84.1122457747284 & 0.149272661502234 \tabularnewline
0.08 & 84.1820578262205 & 0.155929371630939 \tabularnewline
0.09 & 84.2512968470467 & 0.185108925880167 \tabularnewline
0.1 & 84.3284255264043 & 0.233657912166159 \tabularnewline
0.11 & 84.4201267495385 & 0.299313705332873 \tabularnewline
0.12 & 84.5315057733691 & 0.379518265130788 \tabularnewline
0.13 & 84.6662533223483 & 0.471249479804184 \tabularnewline
0.14 & 84.8265465595688 & 0.570161169061951 \tabularnewline
0.15 & 85.0127578578474 & 0.669322821465253 \tabularnewline
0.16 & 85.2231304314035 & 0.760693686794421 \tabularnewline
0.17 & 85.4536254607778 & 0.834776309947532 \tabularnewline
0.18 & 85.6981519706554 & 0.883913859170449 \tabularnewline
0.19 & 85.9492976396952 & 0.903870779472623 \tabularnewline
0.2 & 86.1994872153333 & 0.895892279190724 \tabularnewline
0.21 & 86.4422934700346 & 0.866334644646699 \tabularnewline
0.22 & 86.6735231449088 & 0.826179317441675 \tabularnewline
0.23 & 86.8917513920944 & 0.786479386440045 \tabularnewline
0.24 & 87.09815581736 & 0.757921119155301 \tabularnewline
0.25 & 87.2957250725632 & 0.745691459379977 \tabularnewline
0.26 & 87.4881012970015 & 0.749364447216998 \tabularnewline
0.27 & 87.6784036989143 & 0.763026736002218 \tabularnewline
0.28 & 87.86835566815 & 0.777945298792063 \tabularnewline
0.29 & 88.0579197437091 & 0.785497449578924 \tabularnewline
0.3 & 88.2454785826364 & 0.780090548135774 \tabularnewline
0.31 & 88.4284412761235 & 0.759237850588095 \tabularnewline
0.32 & 88.6040511674665 & 0.725111605642573 \tabularnewline
0.33 & 88.7701488699994 & 0.682293522532522 \tabularnewline
0.34 & 88.9256974167287 & 0.63741965436791 \tabularnewline
0.35 & 89.0709756749944 & 0.596771180294985 \tabularnewline
0.36 & 89.207451876415 & 0.565984330676843 \tabularnewline
0.37 & 89.337428450794 & 0.547584001686926 \tabularnewline
0.38 & 89.463585940184 & 0.54203498290202 \tabularnewline
0.39 & 89.588548584844 & 0.547668838764447 \tabularnewline
0.4 & 89.7145597206245 & 0.561972393072286 \tabularnewline
0.41 & 89.8433077886267 & 0.581505533256405 \tabularnewline
0.42 & 89.9758980867273 & 0.60364190191886 \tabularnewline
0.43 & 90.1129314915213 & 0.626622694342686 \tabularnewline
0.44 & 90.2546344864861 & 0.64930667543319 \tabularnewline
0.45 & 90.4009857890695 & 0.671469750293694 \tabularnewline
0.46 & 90.551800755777 & 0.692257020284956 \tabularnewline
0.47 & 90.7067596859066 & 0.711441662858544 \tabularnewline
0.48 & 90.8653925363454 & 0.728143988050216 \tabularnewline
0.49 & 91.027052743071 & 0.741418573345679 \tabularnewline
0.5 & 91.1909209504186 & 0.750160580606917 \tabularnewline
0.51 & 91.3560729309579 & 0.753515200163779 \tabularnewline
0.52 & 91.5216263754142 & 0.752267916219485 \tabularnewline
0.53 & 91.6869538712664 & 0.747707923933819 \tabularnewline
0.54 & 91.8519220547568 & 0.742809487572869 \tabularnewline
0.55 & 92.0170978315528 & 0.74130223734212 \tabularnewline
0.56 & 92.1838582139237 & 0.747731427949398 \tabularnewline
0.57 & 92.3543537525695 & 0.766016772445319 \tabularnewline
0.58 & 92.5313053238468 & 0.798533125169052 \tabularnewline
0.59 & 92.7176541677466 & 0.845331696715724 \tabularnewline
0.6 & 92.9161258699626 & 0.903688917989196 \tabularnewline
0.61 & 93.128799099037 & 0.969084357696842 \tabularnewline
0.62 & 93.3567794356322 & 1.03550424681753 \tabularnewline
0.63 & 93.600062484406 & 1.09765573657017 \tabularnewline
0.64 & 93.8576306693731 & 1.15091136424627 \tabularnewline
0.65 & 94.1277736029945 & 1.19299480562409 \tabularnewline
0.66 & 94.4085656000116 & 1.22422030231628 \tabularnewline
0.67 & 94.6983886537217 & 1.24728208907771 \tabularnewline
0.68 & 94.9963650665856 & 1.26658727545034 \tabularnewline
0.69 & 95.3025678505222 & 1.28724261667325 \tabularnewline
0.7 & 95.6179135056927 & 1.3132425289614 \tabularnewline
0.71 & 95.9437117714598 & 1.34594713663343 \tabularnewline
0.72 & 96.2809431282237 & 1.38258824990766 \tabularnewline
0.73 & 96.6294364661533 & 1.4166484735601 \tabularnewline
0.74 & 96.9871925491338 & 1.43849508425737 \tabularnewline
0.75 & 97.3501071927809 & 1.43906575770388 \tabularnewline
0.76 & 97.7122704807203 & 1.41116496096201 \tabularnewline
0.77 & 98.0668648942301 & 1.35300517432196 \tabularnewline
0.78 & 98.4074982118619 & 1.26886515164501 \tabularnewline
0.79 & 98.7296450430056 & 1.16863015548179 \tabularnewline
0.8 & 99.0317853580483 & 1.06619280626799 \tabularnewline
0.81 & 99.3158483533203 & 0.976418649280295 \tabularnewline
0.82 & 99.5867021859733 & 0.910711362569965 \tabularnewline
0.83 & 99.8506656866267 & 0.873461619875012 \tabularnewline
0.84 & 100.113327858603 & 0.858504411779439 \tabularnewline
0.85 & 100.37727428193 & 0.850834025470908 \tabularnewline
0.86 & 100.640512223922 & 0.831517812840143 \tabularnewline
0.87 & 100.896315621297 & 0.784688550785962 \tabularnewline
0.88 & 101.134808211837 & 0.703683703958416 \tabularnewline
0.89 & 101.345965890887 & 0.593111310539217 \tabularnewline
0.9 & 101.523112796353 & 0.46826204943805 \tabularnewline
0.91 & 101.665709328153 & 0.349676240545672 \tabularnewline
0.92 & 101.780437216757 & 0.257629538899896 \tabularnewline
0.93 & 101.880194453709 & 0.207242478459176 \tabularnewline
0.94 & 101.981327832849 & 0.201758602025563 \tabularnewline
0.95 & 102.099763880911 & 0.227853822536926 \tabularnewline
0.96 & 102.246252925966 & 0.262814364456816 \tabularnewline
0.97 & 102.420864556159 & 0.278216965225492 \tabularnewline
0.98 & 102.609622527455 & 0.245188077080856 \tabularnewline
0.99 & 102.783969998952 & 0.179771804231946 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281904&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]83.4196331928068[/C][C]0.114950260653807[/C][/ROW]
[ROW][C]0.02[/C][C]83.5361347736585[/C][C]0.182612049220676[/C][/ROW]
[ROW][C]0.03[/C][C]83.6756009913816[/C][C]0.217288836648873[/C][/ROW]
[ROW][C]0.04[/C][C]83.8128108638843[/C][C]0.220243909742539[/C][/ROW]
[ROW][C]0.05[/C][C]83.9334255565432[/C][C]0.196469024413591[/C][/ROW]
[ROW][C]0.06[/C][C]84.0321863905176[/C][C]0.165881797084564[/C][/ROW]
[ROW][C]0.07[/C][C]84.1122457747284[/C][C]0.149272661502234[/C][/ROW]
[ROW][C]0.08[/C][C]84.1820578262205[/C][C]0.155929371630939[/C][/ROW]
[ROW][C]0.09[/C][C]84.2512968470467[/C][C]0.185108925880167[/C][/ROW]
[ROW][C]0.1[/C][C]84.3284255264043[/C][C]0.233657912166159[/C][/ROW]
[ROW][C]0.11[/C][C]84.4201267495385[/C][C]0.299313705332873[/C][/ROW]
[ROW][C]0.12[/C][C]84.5315057733691[/C][C]0.379518265130788[/C][/ROW]
[ROW][C]0.13[/C][C]84.6662533223483[/C][C]0.471249479804184[/C][/ROW]
[ROW][C]0.14[/C][C]84.8265465595688[/C][C]0.570161169061951[/C][/ROW]
[ROW][C]0.15[/C][C]85.0127578578474[/C][C]0.669322821465253[/C][/ROW]
[ROW][C]0.16[/C][C]85.2231304314035[/C][C]0.760693686794421[/C][/ROW]
[ROW][C]0.17[/C][C]85.4536254607778[/C][C]0.834776309947532[/C][/ROW]
[ROW][C]0.18[/C][C]85.6981519706554[/C][C]0.883913859170449[/C][/ROW]
[ROW][C]0.19[/C][C]85.9492976396952[/C][C]0.903870779472623[/C][/ROW]
[ROW][C]0.2[/C][C]86.1994872153333[/C][C]0.895892279190724[/C][/ROW]
[ROW][C]0.21[/C][C]86.4422934700346[/C][C]0.866334644646699[/C][/ROW]
[ROW][C]0.22[/C][C]86.6735231449088[/C][C]0.826179317441675[/C][/ROW]
[ROW][C]0.23[/C][C]86.8917513920944[/C][C]0.786479386440045[/C][/ROW]
[ROW][C]0.24[/C][C]87.09815581736[/C][C]0.757921119155301[/C][/ROW]
[ROW][C]0.25[/C][C]87.2957250725632[/C][C]0.745691459379977[/C][/ROW]
[ROW][C]0.26[/C][C]87.4881012970015[/C][C]0.749364447216998[/C][/ROW]
[ROW][C]0.27[/C][C]87.6784036989143[/C][C]0.763026736002218[/C][/ROW]
[ROW][C]0.28[/C][C]87.86835566815[/C][C]0.777945298792063[/C][/ROW]
[ROW][C]0.29[/C][C]88.0579197437091[/C][C]0.785497449578924[/C][/ROW]
[ROW][C]0.3[/C][C]88.2454785826364[/C][C]0.780090548135774[/C][/ROW]
[ROW][C]0.31[/C][C]88.4284412761235[/C][C]0.759237850588095[/C][/ROW]
[ROW][C]0.32[/C][C]88.6040511674665[/C][C]0.725111605642573[/C][/ROW]
[ROW][C]0.33[/C][C]88.7701488699994[/C][C]0.682293522532522[/C][/ROW]
[ROW][C]0.34[/C][C]88.9256974167287[/C][C]0.63741965436791[/C][/ROW]
[ROW][C]0.35[/C][C]89.0709756749944[/C][C]0.596771180294985[/C][/ROW]
[ROW][C]0.36[/C][C]89.207451876415[/C][C]0.565984330676843[/C][/ROW]
[ROW][C]0.37[/C][C]89.337428450794[/C][C]0.547584001686926[/C][/ROW]
[ROW][C]0.38[/C][C]89.463585940184[/C][C]0.54203498290202[/C][/ROW]
[ROW][C]0.39[/C][C]89.588548584844[/C][C]0.547668838764447[/C][/ROW]
[ROW][C]0.4[/C][C]89.7145597206245[/C][C]0.561972393072286[/C][/ROW]
[ROW][C]0.41[/C][C]89.8433077886267[/C][C]0.581505533256405[/C][/ROW]
[ROW][C]0.42[/C][C]89.9758980867273[/C][C]0.60364190191886[/C][/ROW]
[ROW][C]0.43[/C][C]90.1129314915213[/C][C]0.626622694342686[/C][/ROW]
[ROW][C]0.44[/C][C]90.2546344864861[/C][C]0.64930667543319[/C][/ROW]
[ROW][C]0.45[/C][C]90.4009857890695[/C][C]0.671469750293694[/C][/ROW]
[ROW][C]0.46[/C][C]90.551800755777[/C][C]0.692257020284956[/C][/ROW]
[ROW][C]0.47[/C][C]90.7067596859066[/C][C]0.711441662858544[/C][/ROW]
[ROW][C]0.48[/C][C]90.8653925363454[/C][C]0.728143988050216[/C][/ROW]
[ROW][C]0.49[/C][C]91.027052743071[/C][C]0.741418573345679[/C][/ROW]
[ROW][C]0.5[/C][C]91.1909209504186[/C][C]0.750160580606917[/C][/ROW]
[ROW][C]0.51[/C][C]91.3560729309579[/C][C]0.753515200163779[/C][/ROW]
[ROW][C]0.52[/C][C]91.5216263754142[/C][C]0.752267916219485[/C][/ROW]
[ROW][C]0.53[/C][C]91.6869538712664[/C][C]0.747707923933819[/C][/ROW]
[ROW][C]0.54[/C][C]91.8519220547568[/C][C]0.742809487572869[/C][/ROW]
[ROW][C]0.55[/C][C]92.0170978315528[/C][C]0.74130223734212[/C][/ROW]
[ROW][C]0.56[/C][C]92.1838582139237[/C][C]0.747731427949398[/C][/ROW]
[ROW][C]0.57[/C][C]92.3543537525695[/C][C]0.766016772445319[/C][/ROW]
[ROW][C]0.58[/C][C]92.5313053238468[/C][C]0.798533125169052[/C][/ROW]
[ROW][C]0.59[/C][C]92.7176541677466[/C][C]0.845331696715724[/C][/ROW]
[ROW][C]0.6[/C][C]92.9161258699626[/C][C]0.903688917989196[/C][/ROW]
[ROW][C]0.61[/C][C]93.128799099037[/C][C]0.969084357696842[/C][/ROW]
[ROW][C]0.62[/C][C]93.3567794356322[/C][C]1.03550424681753[/C][/ROW]
[ROW][C]0.63[/C][C]93.600062484406[/C][C]1.09765573657017[/C][/ROW]
[ROW][C]0.64[/C][C]93.8576306693731[/C][C]1.15091136424627[/C][/ROW]
[ROW][C]0.65[/C][C]94.1277736029945[/C][C]1.19299480562409[/C][/ROW]
[ROW][C]0.66[/C][C]94.4085656000116[/C][C]1.22422030231628[/C][/ROW]
[ROW][C]0.67[/C][C]94.6983886537217[/C][C]1.24728208907771[/C][/ROW]
[ROW][C]0.68[/C][C]94.9963650665856[/C][C]1.26658727545034[/C][/ROW]
[ROW][C]0.69[/C][C]95.3025678505222[/C][C]1.28724261667325[/C][/ROW]
[ROW][C]0.7[/C][C]95.6179135056927[/C][C]1.3132425289614[/C][/ROW]
[ROW][C]0.71[/C][C]95.9437117714598[/C][C]1.34594713663343[/C][/ROW]
[ROW][C]0.72[/C][C]96.2809431282237[/C][C]1.38258824990766[/C][/ROW]
[ROW][C]0.73[/C][C]96.6294364661533[/C][C]1.4166484735601[/C][/ROW]
[ROW][C]0.74[/C][C]96.9871925491338[/C][C]1.43849508425737[/C][/ROW]
[ROW][C]0.75[/C][C]97.3501071927809[/C][C]1.43906575770388[/C][/ROW]
[ROW][C]0.76[/C][C]97.7122704807203[/C][C]1.41116496096201[/C][/ROW]
[ROW][C]0.77[/C][C]98.0668648942301[/C][C]1.35300517432196[/C][/ROW]
[ROW][C]0.78[/C][C]98.4074982118619[/C][C]1.26886515164501[/C][/ROW]
[ROW][C]0.79[/C][C]98.7296450430056[/C][C]1.16863015548179[/C][/ROW]
[ROW][C]0.8[/C][C]99.0317853580483[/C][C]1.06619280626799[/C][/ROW]
[ROW][C]0.81[/C][C]99.3158483533203[/C][C]0.976418649280295[/C][/ROW]
[ROW][C]0.82[/C][C]99.5867021859733[/C][C]0.910711362569965[/C][/ROW]
[ROW][C]0.83[/C][C]99.8506656866267[/C][C]0.873461619875012[/C][/ROW]
[ROW][C]0.84[/C][C]100.113327858603[/C][C]0.858504411779439[/C][/ROW]
[ROW][C]0.85[/C][C]100.37727428193[/C][C]0.850834025470908[/C][/ROW]
[ROW][C]0.86[/C][C]100.640512223922[/C][C]0.831517812840143[/C][/ROW]
[ROW][C]0.87[/C][C]100.896315621297[/C][C]0.784688550785962[/C][/ROW]
[ROW][C]0.88[/C][C]101.134808211837[/C][C]0.703683703958416[/C][/ROW]
[ROW][C]0.89[/C][C]101.345965890887[/C][C]0.593111310539217[/C][/ROW]
[ROW][C]0.9[/C][C]101.523112796353[/C][C]0.46826204943805[/C][/ROW]
[ROW][C]0.91[/C][C]101.665709328153[/C][C]0.349676240545672[/C][/ROW]
[ROW][C]0.92[/C][C]101.780437216757[/C][C]0.257629538899896[/C][/ROW]
[ROW][C]0.93[/C][C]101.880194453709[/C][C]0.207242478459176[/C][/ROW]
[ROW][C]0.94[/C][C]101.981327832849[/C][C]0.201758602025563[/C][/ROW]
[ROW][C]0.95[/C][C]102.099763880911[/C][C]0.227853822536926[/C][/ROW]
[ROW][C]0.96[/C][C]102.246252925966[/C][C]0.262814364456816[/C][/ROW]
[ROW][C]0.97[/C][C]102.420864556159[/C][C]0.278216965225492[/C][/ROW]
[ROW][C]0.98[/C][C]102.609622527455[/C][C]0.245188077080856[/C][/ROW]
[ROW][C]0.99[/C][C]102.783969998952[/C][C]0.179771804231946[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=281904&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281904&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
0.0183.41963319280680.114950260653807
0.0283.53613477365850.182612049220676
0.0383.67560099138160.217288836648873
0.0483.81281086388430.220243909742539
0.0583.93342555654320.196469024413591
0.0684.03218639051760.165881797084564
0.0784.11224577472840.149272661502234
0.0884.18205782622050.155929371630939
0.0984.25129684704670.185108925880167
0.184.32842552640430.233657912166159
0.1184.42012674953850.299313705332873
0.1284.53150577336910.379518265130788
0.1384.66625332234830.471249479804184
0.1484.82654655956880.570161169061951
0.1585.01275785784740.669322821465253
0.1685.22313043140350.760693686794421
0.1785.45362546077780.834776309947532
0.1885.69815197065540.883913859170449
0.1985.94929763969520.903870779472623
0.286.19948721533330.895892279190724
0.2186.44229347003460.866334644646699
0.2286.67352314490880.826179317441675
0.2386.89175139209440.786479386440045
0.2487.098155817360.757921119155301
0.2587.29572507256320.745691459379977
0.2687.48810129700150.749364447216998
0.2787.67840369891430.763026736002218
0.2887.868355668150.777945298792063
0.2988.05791974370910.785497449578924
0.388.24547858263640.780090548135774
0.3188.42844127612350.759237850588095
0.3288.60405116746650.725111605642573
0.3388.77014886999940.682293522532522
0.3488.92569741672870.63741965436791
0.3589.07097567499440.596771180294985
0.3689.2074518764150.565984330676843
0.3789.3374284507940.547584001686926
0.3889.4635859401840.54203498290202
0.3989.5885485848440.547668838764447
0.489.71455972062450.561972393072286
0.4189.84330778862670.581505533256405
0.4289.97589808672730.60364190191886
0.4390.11293149152130.626622694342686
0.4490.25463448648610.64930667543319
0.4590.40098578906950.671469750293694
0.4690.5518007557770.692257020284956
0.4790.70675968590660.711441662858544
0.4890.86539253634540.728143988050216
0.4991.0270527430710.741418573345679
0.591.19092095041860.750160580606917
0.5191.35607293095790.753515200163779
0.5291.52162637541420.752267916219485
0.5391.68695387126640.747707923933819
0.5491.85192205475680.742809487572869
0.5592.01709783155280.74130223734212
0.5692.18385821392370.747731427949398
0.5792.35435375256950.766016772445319
0.5892.53130532384680.798533125169052
0.5992.71765416774660.845331696715724
0.692.91612586996260.903688917989196
0.6193.1287990990370.969084357696842
0.6293.35677943563221.03550424681753
0.6393.6000624844061.09765573657017
0.6493.85763066937311.15091136424627
0.6594.12777360299451.19299480562409
0.6694.40856560001161.22422030231628
0.6794.69838865372171.24728208907771
0.6894.99636506658561.26658727545034
0.6995.30256785052221.28724261667325
0.795.61791350569271.3132425289614
0.7195.94371177145981.34594713663343
0.7296.28094312822371.38258824990766
0.7396.62943646615331.4166484735601
0.7496.98719254913381.43849508425737
0.7597.35010719278091.43906575770388
0.7697.71227048072031.41116496096201
0.7798.06686489423011.35300517432196
0.7898.40749821186191.26886515164501
0.7998.72964504300561.16863015548179
0.899.03178535804831.06619280626799
0.8199.31584835332030.976418649280295
0.8299.58670218597330.910711362569965
0.8399.85066568662670.873461619875012
0.84100.1133278586030.858504411779439
0.85100.377274281930.850834025470908
0.86100.6405122239220.831517812840143
0.87100.8963156212970.784688550785962
0.88101.1348082118370.703683703958416
0.89101.3459658908870.593111310539217
0.9101.5231127963530.46826204943805
0.91101.6657093281530.349676240545672
0.92101.7804372167570.257629538899896
0.93101.8801944537090.207242478459176
0.94101.9813278328490.201758602025563
0.95102.0997638809110.227853822536926
0.96102.2462529259660.262814364456816
0.97102.4208645561590.278216965225492
0.98102.6096225274550.245188077080856
0.99102.7839699989520.179771804231946


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')