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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, 12 Aug 2011 11:39:03 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Aug/12/t1313163656bmyt4w31odbdp0d.htm/, Retrieved Tue, 21 Apr 2026 01:07:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=123650, Retrieved Tue, 21 Apr 2026 01:07:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact356

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] [Jens Vanpachtenbe...] [2011-08-12 15:39:03] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
940
1070
1060
1070
1070
1040
950
1120
1150
1040
1040
1120
1000
960
1060
1060
1110
1030
960
1130
1150
1030
1040
1030
1070
1000
1020
1100
1080
990
1000
1110
1170
1030
1100
1020
1090
990
1060
1120
1030
1050
1030
1130
1140
980
1150
990
1020
1060
1080
1180
980
960
1020
1170
1150
950
1160
1120
1010
1010
1060
1130
1000
1000
1070
1150
1080
980
1210
1020
980
1030
1050
1190
970
950
1070
1170
1050
960
1300
1080
1030
1030
1070
1260
990
950
1080
1190
1050
950
1250
1140
1080
1020
1140
1320
1100
1040
1090
1280
1030
930
1280
1020

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123650&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123650&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123650&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'Gertrude Mary Cox' @ cox.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01935.5897043989388.77456907320127
0.02942.4747210674166.46528384317274
0.03947.1897755195984.01306475471051
0.04950.0001919417343.26594649266945
0.05952.1311995945564.24116416634447
0.06954.4013750260855.70638274271156
0.07957.0972291149687.10640271114009
0.08960.214007321018.35487050388608
0.09963.6556229028299.43280637457714
0.1967.30841932720410.2235597028882
0.11971.0482724832610.6007881316952
0.12974.74781541744410.556554843924
0.13978.30103963547510.2257308635815
0.14981.6472810469939.79897928923575
0.15984.7769410453069.43039862510678
0.16987.7187827523859.19521110542711
0.17990.5202521706849.10590470600106
0.18993.2312785228449.14888606007116
0.19995.8948726059779.29965922680366
0.2998.5424441270359.52211997907366
0.211001.190883569089.76324744033204
0.221003.84043810629.95244362879535
0.231006.4744324398810.0166574723652
0.241009.062270273059.90516780509864
0.251011.565904763429.60145939961907
0.261013.94818376289.13171819428994
0.271016.180415804068.55371359602307
0.281018.246822210877.93508027624017
0.291020.145007650487.3335699128554
0.31021.883327711356.784097780361
0.311023.477127783466.30212167578545
0.321024.945806680215.88870990676381
0.331026.311703859045.5557529763828
0.341027.600551102845.32513259445543
0.351028.842342018745.22927985218204
0.361030.071324513775.3002966992582
0.371031.324353744025.55081627005466
0.381032.637685347825.96709215453751
0.391034.043000354116.51084430721552
0.41035.563743357327.12908554356182
0.411037.2126826827.7667591689135
0.421038.991133160958.3719862502083
0.431040.889770466318.90463047865379
0.441042.89061333679.33307194683221
0.451044.969633678049.63575126205108
0.461047.099527812119.80788444185508
0.471049.252334998079.84999175600126
0.481051.401722753929.77372327550565
0.491053.524831983129.59884543160992
0.51055.603607761819.35011781975403
0.511057.625577949699.05548527454696
0.521059.584108108198.743043860709
0.531061.47824552958.43586181259106
0.541063.312328130178.15705733438121
0.551065.095540362117.9254237088036
0.561066.841543855457.76095032310297
0.571068.568223716237.68093384061098
0.581070.297510334517.70361903081809
0.591072.055180467427.84595414462406
0.61073.870501488678.12082546502106
0.611075.775541389238.53772901123707
0.621077.803929668619.10131585583796
0.631079.988863873629.80419201721417
0.641082.3602727077210.6228364032175
0.651084.941295947811.5182597295158
0.661087.7445755019412.4339292558459
0.671090.7691478961713.2992289310938
0.681093.9988394795514.0450127937585
0.691097.4028940329514.6084404259175
0.71100.9391114457214.9505073841216
0.711104.5591527340515.0591776394212
0.721108.2150427438714.9506131208265
0.731111.8654617249414.6698348988505
0.741115.4803152090414.2792238696773
0.751119.0424021635413.8405893657874
0.761122.5457656761813.4021426481048
0.771125.9913828692912.9882433124795
0.781129.3819576566112.5925773038876
0.791132.718316781912.1929321081209
0.81135.9998208872211.7696840954206
0.811139.2299552297211.3327659046447
0.821142.4259371949610.9362672539251
0.831145.6285850139210.6788221785652
0.841148.9074556236910.6727110152264
0.851152.3581872636410.9959371678171
0.861156.0946423398811.6482334276119
0.871160.2456745559612.5800380205953
0.881164.9700548937113.7927962033773
0.891170.4970658249315.44167324955
0.91177.1801983795517.8685485503268
0.911185.5190906641221.4400708631975
0.921196.0762904271726.1473418850035
0.931209.2298451364431.1340533670821
0.941224.8107351232934.5993067310299
0.951241.8754185840234.527565446531
0.961259.0133014179630.2433973257934
0.971275.3680603988823.8356989604698
0.981291.591080346819.4977206900928
0.991308.2298777050918.8355498914946

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 935.589704398938 & 8.77456907320127 \tabularnewline
0.02 & 942.474721067416 & 6.46528384317274 \tabularnewline
0.03 & 947.189775519598 & 4.01306475471051 \tabularnewline
0.04 & 950.000191941734 & 3.26594649266945 \tabularnewline
0.05 & 952.131199594556 & 4.24116416634447 \tabularnewline
0.06 & 954.401375026085 & 5.70638274271156 \tabularnewline
0.07 & 957.097229114968 & 7.10640271114009 \tabularnewline
0.08 & 960.21400732101 & 8.35487050388608 \tabularnewline
0.09 & 963.655622902829 & 9.43280637457714 \tabularnewline
0.1 & 967.308419327204 & 10.2235597028882 \tabularnewline
0.11 & 971.04827248326 & 10.6007881316952 \tabularnewline
0.12 & 974.747815417444 & 10.556554843924 \tabularnewline
0.13 & 978.301039635475 & 10.2257308635815 \tabularnewline
0.14 & 981.647281046993 & 9.79897928923575 \tabularnewline
0.15 & 984.776941045306 & 9.43039862510678 \tabularnewline
0.16 & 987.718782752385 & 9.19521110542711 \tabularnewline
0.17 & 990.520252170684 & 9.10590470600106 \tabularnewline
0.18 & 993.231278522844 & 9.14888606007116 \tabularnewline
0.19 & 995.894872605977 & 9.29965922680366 \tabularnewline
0.2 & 998.542444127035 & 9.52211997907366 \tabularnewline
0.21 & 1001.19088356908 & 9.76324744033204 \tabularnewline
0.22 & 1003.8404381062 & 9.95244362879535 \tabularnewline
0.23 & 1006.47443243988 & 10.0166574723652 \tabularnewline
0.24 & 1009.06227027305 & 9.90516780509864 \tabularnewline
0.25 & 1011.56590476342 & 9.60145939961907 \tabularnewline
0.26 & 1013.9481837628 & 9.13171819428994 \tabularnewline
0.27 & 1016.18041580406 & 8.55371359602307 \tabularnewline
0.28 & 1018.24682221087 & 7.93508027624017 \tabularnewline
0.29 & 1020.14500765048 & 7.3335699128554 \tabularnewline
0.3 & 1021.88332771135 & 6.784097780361 \tabularnewline
0.31 & 1023.47712778346 & 6.30212167578545 \tabularnewline
0.32 & 1024.94580668021 & 5.88870990676381 \tabularnewline
0.33 & 1026.31170385904 & 5.5557529763828 \tabularnewline
0.34 & 1027.60055110284 & 5.32513259445543 \tabularnewline
0.35 & 1028.84234201874 & 5.22927985218204 \tabularnewline
0.36 & 1030.07132451377 & 5.3002966992582 \tabularnewline
0.37 & 1031.32435374402 & 5.55081627005466 \tabularnewline
0.38 & 1032.63768534782 & 5.96709215453751 \tabularnewline
0.39 & 1034.04300035411 & 6.51084430721552 \tabularnewline
0.4 & 1035.56374335732 & 7.12908554356182 \tabularnewline
0.41 & 1037.212682682 & 7.7667591689135 \tabularnewline
0.42 & 1038.99113316095 & 8.3719862502083 \tabularnewline
0.43 & 1040.88977046631 & 8.90463047865379 \tabularnewline
0.44 & 1042.8906133367 & 9.33307194683221 \tabularnewline
0.45 & 1044.96963367804 & 9.63575126205108 \tabularnewline
0.46 & 1047.09952781211 & 9.80788444185508 \tabularnewline
0.47 & 1049.25233499807 & 9.84999175600126 \tabularnewline
0.48 & 1051.40172275392 & 9.77372327550565 \tabularnewline
0.49 & 1053.52483198312 & 9.59884543160992 \tabularnewline
0.5 & 1055.60360776181 & 9.35011781975403 \tabularnewline
0.51 & 1057.62557794969 & 9.05548527454696 \tabularnewline
0.52 & 1059.58410810819 & 8.743043860709 \tabularnewline
0.53 & 1061.4782455295 & 8.43586181259106 \tabularnewline
0.54 & 1063.31232813017 & 8.15705733438121 \tabularnewline
0.55 & 1065.09554036211 & 7.9254237088036 \tabularnewline
0.56 & 1066.84154385545 & 7.76095032310297 \tabularnewline
0.57 & 1068.56822371623 & 7.68093384061098 \tabularnewline
0.58 & 1070.29751033451 & 7.70361903081809 \tabularnewline
0.59 & 1072.05518046742 & 7.84595414462406 \tabularnewline
0.6 & 1073.87050148867 & 8.12082546502106 \tabularnewline
0.61 & 1075.77554138923 & 8.53772901123707 \tabularnewline
0.62 & 1077.80392966861 & 9.10131585583796 \tabularnewline
0.63 & 1079.98886387362 & 9.80419201721417 \tabularnewline
0.64 & 1082.36027270772 & 10.6228364032175 \tabularnewline
0.65 & 1084.9412959478 & 11.5182597295158 \tabularnewline
0.66 & 1087.74457550194 & 12.4339292558459 \tabularnewline
0.67 & 1090.76914789617 & 13.2992289310938 \tabularnewline
0.68 & 1093.99883947955 & 14.0450127937585 \tabularnewline
0.69 & 1097.40289403295 & 14.6084404259175 \tabularnewline
0.7 & 1100.93911144572 & 14.9505073841216 \tabularnewline
0.71 & 1104.55915273405 & 15.0591776394212 \tabularnewline
0.72 & 1108.21504274387 & 14.9506131208265 \tabularnewline
0.73 & 1111.86546172494 & 14.6698348988505 \tabularnewline
0.74 & 1115.48031520904 & 14.2792238696773 \tabularnewline
0.75 & 1119.04240216354 & 13.8405893657874 \tabularnewline
0.76 & 1122.54576567618 & 13.4021426481048 \tabularnewline
0.77 & 1125.99138286929 & 12.9882433124795 \tabularnewline
0.78 & 1129.38195765661 & 12.5925773038876 \tabularnewline
0.79 & 1132.7183167819 & 12.1929321081209 \tabularnewline
0.8 & 1135.99982088722 & 11.7696840954206 \tabularnewline
0.81 & 1139.22995522972 & 11.3327659046447 \tabularnewline
0.82 & 1142.42593719496 & 10.9362672539251 \tabularnewline
0.83 & 1145.62858501392 & 10.6788221785652 \tabularnewline
0.84 & 1148.90745562369 & 10.6727110152264 \tabularnewline
0.85 & 1152.35818726364 & 10.9959371678171 \tabularnewline
0.86 & 1156.09464233988 & 11.6482334276119 \tabularnewline
0.87 & 1160.24567455596 & 12.5800380205953 \tabularnewline
0.88 & 1164.97005489371 & 13.7927962033773 \tabularnewline
0.89 & 1170.49706582493 & 15.44167324955 \tabularnewline
0.9 & 1177.18019837955 & 17.8685485503268 \tabularnewline
0.91 & 1185.51909066412 & 21.4400708631975 \tabularnewline
0.92 & 1196.07629042717 & 26.1473418850035 \tabularnewline
0.93 & 1209.22984513644 & 31.1340533670821 \tabularnewline
0.94 & 1224.81073512329 & 34.5993067310299 \tabularnewline
0.95 & 1241.87541858402 & 34.527565446531 \tabularnewline
0.96 & 1259.01330141796 & 30.2433973257934 \tabularnewline
0.97 & 1275.36806039888 & 23.8356989604698 \tabularnewline
0.98 & 1291.5910803468 & 19.4977206900928 \tabularnewline
0.99 & 1308.22987770509 & 18.8355498914946 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123650&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]935.589704398938[/C][C]8.77456907320127[/C][/ROW]
[ROW][C]0.02[/C][C]942.474721067416[/C][C]6.46528384317274[/C][/ROW]
[ROW][C]0.03[/C][C]947.189775519598[/C][C]4.01306475471051[/C][/ROW]
[ROW][C]0.04[/C][C]950.000191941734[/C][C]3.26594649266945[/C][/ROW]
[ROW][C]0.05[/C][C]952.131199594556[/C][C]4.24116416634447[/C][/ROW]
[ROW][C]0.06[/C][C]954.401375026085[/C][C]5.70638274271156[/C][/ROW]
[ROW][C]0.07[/C][C]957.097229114968[/C][C]7.10640271114009[/C][/ROW]
[ROW][C]0.08[/C][C]960.21400732101[/C][C]8.35487050388608[/C][/ROW]
[ROW][C]0.09[/C][C]963.655622902829[/C][C]9.43280637457714[/C][/ROW]
[ROW][C]0.1[/C][C]967.308419327204[/C][C]10.2235597028882[/C][/ROW]
[ROW][C]0.11[/C][C]971.04827248326[/C][C]10.6007881316952[/C][/ROW]
[ROW][C]0.12[/C][C]974.747815417444[/C][C]10.556554843924[/C][/ROW]
[ROW][C]0.13[/C][C]978.301039635475[/C][C]10.2257308635815[/C][/ROW]
[ROW][C]0.14[/C][C]981.647281046993[/C][C]9.79897928923575[/C][/ROW]
[ROW][C]0.15[/C][C]984.776941045306[/C][C]9.43039862510678[/C][/ROW]
[ROW][C]0.16[/C][C]987.718782752385[/C][C]9.19521110542711[/C][/ROW]
[ROW][C]0.17[/C][C]990.520252170684[/C][C]9.10590470600106[/C][/ROW]
[ROW][C]0.18[/C][C]993.231278522844[/C][C]9.14888606007116[/C][/ROW]
[ROW][C]0.19[/C][C]995.894872605977[/C][C]9.29965922680366[/C][/ROW]
[ROW][C]0.2[/C][C]998.542444127035[/C][C]9.52211997907366[/C][/ROW]
[ROW][C]0.21[/C][C]1001.19088356908[/C][C]9.76324744033204[/C][/ROW]
[ROW][C]0.22[/C][C]1003.8404381062[/C][C]9.95244362879535[/C][/ROW]
[ROW][C]0.23[/C][C]1006.47443243988[/C][C]10.0166574723652[/C][/ROW]
[ROW][C]0.24[/C][C]1009.06227027305[/C][C]9.90516780509864[/C][/ROW]
[ROW][C]0.25[/C][C]1011.56590476342[/C][C]9.60145939961907[/C][/ROW]
[ROW][C]0.26[/C][C]1013.9481837628[/C][C]9.13171819428994[/C][/ROW]
[ROW][C]0.27[/C][C]1016.18041580406[/C][C]8.55371359602307[/C][/ROW]
[ROW][C]0.28[/C][C]1018.24682221087[/C][C]7.93508027624017[/C][/ROW]
[ROW][C]0.29[/C][C]1020.14500765048[/C][C]7.3335699128554[/C][/ROW]
[ROW][C]0.3[/C][C]1021.88332771135[/C][C]6.784097780361[/C][/ROW]
[ROW][C]0.31[/C][C]1023.47712778346[/C][C]6.30212167578545[/C][/ROW]
[ROW][C]0.32[/C][C]1024.94580668021[/C][C]5.88870990676381[/C][/ROW]
[ROW][C]0.33[/C][C]1026.31170385904[/C][C]5.5557529763828[/C][/ROW]
[ROW][C]0.34[/C][C]1027.60055110284[/C][C]5.32513259445543[/C][/ROW]
[ROW][C]0.35[/C][C]1028.84234201874[/C][C]5.22927985218204[/C][/ROW]
[ROW][C]0.36[/C][C]1030.07132451377[/C][C]5.3002966992582[/C][/ROW]
[ROW][C]0.37[/C][C]1031.32435374402[/C][C]5.55081627005466[/C][/ROW]
[ROW][C]0.38[/C][C]1032.63768534782[/C][C]5.96709215453751[/C][/ROW]
[ROW][C]0.39[/C][C]1034.04300035411[/C][C]6.51084430721552[/C][/ROW]
[ROW][C]0.4[/C][C]1035.56374335732[/C][C]7.12908554356182[/C][/ROW]
[ROW][C]0.41[/C][C]1037.212682682[/C][C]7.7667591689135[/C][/ROW]
[ROW][C]0.42[/C][C]1038.99113316095[/C][C]8.3719862502083[/C][/ROW]
[ROW][C]0.43[/C][C]1040.88977046631[/C][C]8.90463047865379[/C][/ROW]
[ROW][C]0.44[/C][C]1042.8906133367[/C][C]9.33307194683221[/C][/ROW]
[ROW][C]0.45[/C][C]1044.96963367804[/C][C]9.63575126205108[/C][/ROW]
[ROW][C]0.46[/C][C]1047.09952781211[/C][C]9.80788444185508[/C][/ROW]
[ROW][C]0.47[/C][C]1049.25233499807[/C][C]9.84999175600126[/C][/ROW]
[ROW][C]0.48[/C][C]1051.40172275392[/C][C]9.77372327550565[/C][/ROW]
[ROW][C]0.49[/C][C]1053.52483198312[/C][C]9.59884543160992[/C][/ROW]
[ROW][C]0.5[/C][C]1055.60360776181[/C][C]9.35011781975403[/C][/ROW]
[ROW][C]0.51[/C][C]1057.62557794969[/C][C]9.05548527454696[/C][/ROW]
[ROW][C]0.52[/C][C]1059.58410810819[/C][C]8.743043860709[/C][/ROW]
[ROW][C]0.53[/C][C]1061.4782455295[/C][C]8.43586181259106[/C][/ROW]
[ROW][C]0.54[/C][C]1063.31232813017[/C][C]8.15705733438121[/C][/ROW]
[ROW][C]0.55[/C][C]1065.09554036211[/C][C]7.9254237088036[/C][/ROW]
[ROW][C]0.56[/C][C]1066.84154385545[/C][C]7.76095032310297[/C][/ROW]
[ROW][C]0.57[/C][C]1068.56822371623[/C][C]7.68093384061098[/C][/ROW]
[ROW][C]0.58[/C][C]1070.29751033451[/C][C]7.70361903081809[/C][/ROW]
[ROW][C]0.59[/C][C]1072.05518046742[/C][C]7.84595414462406[/C][/ROW]
[ROW][C]0.6[/C][C]1073.87050148867[/C][C]8.12082546502106[/C][/ROW]
[ROW][C]0.61[/C][C]1075.77554138923[/C][C]8.53772901123707[/C][/ROW]
[ROW][C]0.62[/C][C]1077.80392966861[/C][C]9.10131585583796[/C][/ROW]
[ROW][C]0.63[/C][C]1079.98886387362[/C][C]9.80419201721417[/C][/ROW]
[ROW][C]0.64[/C][C]1082.36027270772[/C][C]10.6228364032175[/C][/ROW]
[ROW][C]0.65[/C][C]1084.9412959478[/C][C]11.5182597295158[/C][/ROW]
[ROW][C]0.66[/C][C]1087.74457550194[/C][C]12.4339292558459[/C][/ROW]
[ROW][C]0.67[/C][C]1090.76914789617[/C][C]13.2992289310938[/C][/ROW]
[ROW][C]0.68[/C][C]1093.99883947955[/C][C]14.0450127937585[/C][/ROW]
[ROW][C]0.69[/C][C]1097.40289403295[/C][C]14.6084404259175[/C][/ROW]
[ROW][C]0.7[/C][C]1100.93911144572[/C][C]14.9505073841216[/C][/ROW]
[ROW][C]0.71[/C][C]1104.55915273405[/C][C]15.0591776394212[/C][/ROW]
[ROW][C]0.72[/C][C]1108.21504274387[/C][C]14.9506131208265[/C][/ROW]
[ROW][C]0.73[/C][C]1111.86546172494[/C][C]14.6698348988505[/C][/ROW]
[ROW][C]0.74[/C][C]1115.48031520904[/C][C]14.2792238696773[/C][/ROW]
[ROW][C]0.75[/C][C]1119.04240216354[/C][C]13.8405893657874[/C][/ROW]
[ROW][C]0.76[/C][C]1122.54576567618[/C][C]13.4021426481048[/C][/ROW]
[ROW][C]0.77[/C][C]1125.99138286929[/C][C]12.9882433124795[/C][/ROW]
[ROW][C]0.78[/C][C]1129.38195765661[/C][C]12.5925773038876[/C][/ROW]
[ROW][C]0.79[/C][C]1132.7183167819[/C][C]12.1929321081209[/C][/ROW]
[ROW][C]0.8[/C][C]1135.99982088722[/C][C]11.7696840954206[/C][/ROW]
[ROW][C]0.81[/C][C]1139.22995522972[/C][C]11.3327659046447[/C][/ROW]
[ROW][C]0.82[/C][C]1142.42593719496[/C][C]10.9362672539251[/C][/ROW]
[ROW][C]0.83[/C][C]1145.62858501392[/C][C]10.6788221785652[/C][/ROW]
[ROW][C]0.84[/C][C]1148.90745562369[/C][C]10.6727110152264[/C][/ROW]
[ROW][C]0.85[/C][C]1152.35818726364[/C][C]10.9959371678171[/C][/ROW]
[ROW][C]0.86[/C][C]1156.09464233988[/C][C]11.6482334276119[/C][/ROW]
[ROW][C]0.87[/C][C]1160.24567455596[/C][C]12.5800380205953[/C][/ROW]
[ROW][C]0.88[/C][C]1164.97005489371[/C][C]13.7927962033773[/C][/ROW]
[ROW][C]0.89[/C][C]1170.49706582493[/C][C]15.44167324955[/C][/ROW]
[ROW][C]0.9[/C][C]1177.18019837955[/C][C]17.8685485503268[/C][/ROW]
[ROW][C]0.91[/C][C]1185.51909066412[/C][C]21.4400708631975[/C][/ROW]
[ROW][C]0.92[/C][C]1196.07629042717[/C][C]26.1473418850035[/C][/ROW]
[ROW][C]0.93[/C][C]1209.22984513644[/C][C]31.1340533670821[/C][/ROW]
[ROW][C]0.94[/C][C]1224.81073512329[/C][C]34.5993067310299[/C][/ROW]
[ROW][C]0.95[/C][C]1241.87541858402[/C][C]34.527565446531[/C][/ROW]
[ROW][C]0.96[/C][C]1259.01330141796[/C][C]30.2433973257934[/C][/ROW]
[ROW][C]0.97[/C][C]1275.36806039888[/C][C]23.8356989604698[/C][/ROW]
[ROW][C]0.98[/C][C]1291.5910803468[/C][C]19.4977206900928[/C][/ROW]
[ROW][C]0.99[/C][C]1308.22987770509[/C][C]18.8355498914946[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123650&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123650&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
0.01935.5897043989388.77456907320127
0.02942.4747210674166.46528384317274
0.03947.1897755195984.01306475471051
0.04950.0001919417343.26594649266945
0.05952.1311995945564.24116416634447
0.06954.4013750260855.70638274271156
0.07957.0972291149687.10640271114009
0.08960.214007321018.35487050388608
0.09963.6556229028299.43280637457714
0.1967.30841932720410.2235597028882
0.11971.0482724832610.6007881316952
0.12974.74781541744410.556554843924
0.13978.30103963547510.2257308635815
0.14981.6472810469939.79897928923575
0.15984.7769410453069.43039862510678
0.16987.7187827523859.19521110542711
0.17990.5202521706849.10590470600106
0.18993.2312785228449.14888606007116
0.19995.8948726059779.29965922680366
0.2998.5424441270359.52211997907366
0.211001.190883569089.76324744033204
0.221003.84043810629.95244362879535
0.231006.4744324398810.0166574723652
0.241009.062270273059.90516780509864
0.251011.565904763429.60145939961907
0.261013.94818376289.13171819428994
0.271016.180415804068.55371359602307
0.281018.246822210877.93508027624017
0.291020.145007650487.3335699128554
0.31021.883327711356.784097780361
0.311023.477127783466.30212167578545
0.321024.945806680215.88870990676381
0.331026.311703859045.5557529763828
0.341027.600551102845.32513259445543
0.351028.842342018745.22927985218204
0.361030.071324513775.3002966992582
0.371031.324353744025.55081627005466
0.381032.637685347825.96709215453751
0.391034.043000354116.51084430721552
0.41035.563743357327.12908554356182
0.411037.2126826827.7667591689135
0.421038.991133160958.3719862502083
0.431040.889770466318.90463047865379
0.441042.89061333679.33307194683221
0.451044.969633678049.63575126205108
0.461047.099527812119.80788444185508
0.471049.252334998079.84999175600126
0.481051.401722753929.77372327550565
0.491053.524831983129.59884543160992
0.51055.603607761819.35011781975403
0.511057.625577949699.05548527454696
0.521059.584108108198.743043860709
0.531061.47824552958.43586181259106
0.541063.312328130178.15705733438121
0.551065.095540362117.9254237088036
0.561066.841543855457.76095032310297
0.571068.568223716237.68093384061098
0.581070.297510334517.70361903081809
0.591072.055180467427.84595414462406
0.61073.870501488678.12082546502106
0.611075.775541389238.53772901123707
0.621077.803929668619.10131585583796
0.631079.988863873629.80419201721417
0.641082.3602727077210.6228364032175
0.651084.941295947811.5182597295158
0.661087.7445755019412.4339292558459
0.671090.7691478961713.2992289310938
0.681093.9988394795514.0450127937585
0.691097.4028940329514.6084404259175
0.71100.9391114457214.9505073841216
0.711104.5591527340515.0591776394212
0.721108.2150427438714.9506131208265
0.731111.8654617249414.6698348988505
0.741115.4803152090414.2792238696773
0.751119.0424021635413.8405893657874
0.761122.5457656761813.4021426481048
0.771125.9913828692912.9882433124795
0.781129.3819576566112.5925773038876
0.791132.718316781912.1929321081209
0.81135.9998208872211.7696840954206
0.811139.2299552297211.3327659046447
0.821142.4259371949610.9362672539251
0.831145.6285850139210.6788221785652
0.841148.9074556236910.6727110152264
0.851152.3581872636410.9959371678171
0.861156.0946423398811.6482334276119
0.871160.2456745559612.5800380205953
0.881164.9700548937113.7927962033773
0.891170.4970658249315.44167324955
0.91177.1801983795517.8685485503268
0.911185.5190906641221.4400708631975
0.921196.0762904271726.1473418850035
0.931209.2298451364431.1340533670821
0.941224.8107351232934.5993067310299
0.951241.8754185840234.527565446531
0.961259.0133014179630.2433973257934
0.971275.3680603988823.8356989604698
0.981291.591080346819.4977206900928
0.991308.2298777050918.8355498914946


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')