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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 computationMon, 03 Mar 2008 03:21:11 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Mar/03/t120453972918nrcwfq3h0pr8p.htm/, Retrieved Sun, 19 May 2024 03:06:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=9822, Retrieved Sun, 19 May 2024 03:06:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact244

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] [Aantal personenwa...] [2008-03-03 10:11:54] [447a393a477391846fb1ef840a8b4411]
-   PD    [Harrell-Davis Quantiles] [percentielen aant...] [2008-03-03 10:21:11] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
11835
39690
43129
37863
35953
29133
24693
22205
21725
27192
21790
13253
37702
30364
32609
30212
29965
28352
25814
22414
20506
28806
22228
13971
36845
35338
35022
34777
26887
23970
22780
17351
21382
24561
17409
11514
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698

Tables (Output of Computation)





Summary of compuational 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 compuational 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=9822&T=0

[TABLE]
[ROW][C]Summary of compuational 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=9822&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=9822&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 compuational 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
0.0110969.6041847839761.196027891038
0.0211409.6021304793830.407593913784
0.0311925.57328299681018.52169392409
0.0412476.04615522031217.92131384483
0.0513047.93083573461382.21107930060
0.0613632.98946219931516.10080600385
0.0714221.42041994791619.70764336783
0.0814801.1771361451673.11701247477
0.0915357.82968655051654.75468041442
0.115875.9005772731560.16291210511
0.1116342.01914051031406.12293780503
0.1216748.28545622971223.14928429075
0.1317094.04133261251044.44207269141
0.1417385.4177791130896.959661210733
0.1517633.2264935713796.758283842694
0.1617850.2652790648747.691387414837
0.1718048.9502519771743.347665697252
0.1818239.7390245808771.72104089991
0.1918430.3943998048819.964341892786
0.218625.9015087222877.247373449057
0.2118828.7863210973935.251352446579
0.2219039.619427757987.939114329518
0.2319257.55780363671031.40525185701
0.2419480.83997566491063.36552464184
0.2519707.19465240191082.84666703127
0.2619934.15156977251089.82818235341
0.2720159.26137371701084.75087833948
0.2820380.24220352061068.59599913265
0.2920595.07542025891042.45720925072
0.320802.07210809251007.83189048083
0.3120999.9266535397966.40881522735
0.3221187.7658908728920.3440177939
0.3321365.1943801252872.11515019808
0.3421532.3303381881824.549255483106
0.3521689.8236176237780.715922449289
0.3621838.8469711986743.646101645753
0.3721981.0540237211716.331703941726
0.3822118.5010361742701.234197468494
0.3922253.5339331689700.070997909285
0.422388.6466222651713.543132770011
0.4122526.3209212294741.05823898853
0.4222668.8619349939780.933109849127
0.4322818.2448713917830.411591631067
0.4422975.9894049006886.22249300769
0.4523143.0753443230944.772207563235
0.4623319.90855460421002.60838600023
0.4723506.33946760421056.71450223952
0.4823701.72929972661104.64407965619
0.4923905.05277002441144.75848214349
0.524115.02204153971176.20996357116
0.5124330.21560402341198.78393497398
0.5224549.19788209151212.99301181662
0.5324770.61967478961219.69854102891
0.5424993.29472663701220.05302997344
0.5525216.25227386671215.33294337329
0.5625438.76811641131206.91710294698
0.5725660.37715758271196.23415527121
0.5825880.86881176871184.59677539106
0.5926100.26433364651173.33781508622
0.626318.77348367981163.49415766843
0.6126536.72840149461155.80466517966
0.6226754.49585252851150.40232703808
0.6326972.37487116211146.82094330242
0.6427190.4938811191143.75871141365
0.6527408.7274619131139.45659200193
0.6627626.65568688761131.82405389446
0.6727843.58660972591118.98507170526
0.6828058.65452789541099.73619601220
0.6928270.99422360521073.97399585614
0.728479.97700791881043.11688999281
0.7128685.48128359671010.08575705263
0.7228888.1613510165979.286389665548
0.7329089.6748477122956.457396667082
0.7429292.8312835175947.810259453968
0.7529501.6298264869959.564951686908
0.7629721.1614722651996.77563112138
0.7729957.35749067271062.40205370697
0.7830216.57321148971156.54600889185
0.7930505.00710829611276.03127076961
0.830827.97505448981414.26289939636
0.8131189.09337069921561.25465046972
0.8231589.47211379401704.11875627573
0.8332027.07308405831827.89043964419
0.8432496.42468098591917.40686262216
0.8532988.87890809561959.75964243682
0.8633493.51831291541947.21835143037
0.8733998.66756561501879.59830047561
0.8834493.77023954441765.43487350277
0.8934971.23683177811620.96088873255
0.935427.86865287111466.71405554645
0.9135865.72398532311322.8115305862
0.9236292.86475498381204.91363025951
0.9336725.19954950601124.35175255210
0.9437191.21714269151095.81697709636
0.9537740.66688673221151.42348886928
0.9638453.18850634791342.41038254292
0.9739427.68428389931711.10801850017
0.9840708.39872835952259.51892817824
0.9942116.2492866392903.95141681403

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 10969.6041847839 & 761.196027891038 \tabularnewline
0.02 & 11409.6021304793 & 830.407593913784 \tabularnewline
0.03 & 11925.5732829968 & 1018.52169392409 \tabularnewline
0.04 & 12476.0461552203 & 1217.92131384483 \tabularnewline
0.05 & 13047.9308357346 & 1382.21107930060 \tabularnewline
0.06 & 13632.9894621993 & 1516.10080600385 \tabularnewline
0.07 & 14221.4204199479 & 1619.70764336783 \tabularnewline
0.08 & 14801.177136145 & 1673.11701247477 \tabularnewline
0.09 & 15357.8296865505 & 1654.75468041442 \tabularnewline
0.1 & 15875.900577273 & 1560.16291210511 \tabularnewline
0.11 & 16342.0191405103 & 1406.12293780503 \tabularnewline
0.12 & 16748.2854562297 & 1223.14928429075 \tabularnewline
0.13 & 17094.0413326125 & 1044.44207269141 \tabularnewline
0.14 & 17385.4177791130 & 896.959661210733 \tabularnewline
0.15 & 17633.2264935713 & 796.758283842694 \tabularnewline
0.16 & 17850.2652790648 & 747.691387414837 \tabularnewline
0.17 & 18048.9502519771 & 743.347665697252 \tabularnewline
0.18 & 18239.7390245808 & 771.72104089991 \tabularnewline
0.19 & 18430.3943998048 & 819.964341892786 \tabularnewline
0.2 & 18625.9015087222 & 877.247373449057 \tabularnewline
0.21 & 18828.7863210973 & 935.251352446579 \tabularnewline
0.22 & 19039.619427757 & 987.939114329518 \tabularnewline
0.23 & 19257.5578036367 & 1031.40525185701 \tabularnewline
0.24 & 19480.8399756649 & 1063.36552464184 \tabularnewline
0.25 & 19707.1946524019 & 1082.84666703127 \tabularnewline
0.26 & 19934.1515697725 & 1089.82818235341 \tabularnewline
0.27 & 20159.2613737170 & 1084.75087833948 \tabularnewline
0.28 & 20380.2422035206 & 1068.59599913265 \tabularnewline
0.29 & 20595.0754202589 & 1042.45720925072 \tabularnewline
0.3 & 20802.0721080925 & 1007.83189048083 \tabularnewline
0.31 & 20999.9266535397 & 966.40881522735 \tabularnewline
0.32 & 21187.7658908728 & 920.3440177939 \tabularnewline
0.33 & 21365.1943801252 & 872.11515019808 \tabularnewline
0.34 & 21532.3303381881 & 824.549255483106 \tabularnewline
0.35 & 21689.8236176237 & 780.715922449289 \tabularnewline
0.36 & 21838.8469711986 & 743.646101645753 \tabularnewline
0.37 & 21981.0540237211 & 716.331703941726 \tabularnewline
0.38 & 22118.5010361742 & 701.234197468494 \tabularnewline
0.39 & 22253.5339331689 & 700.070997909285 \tabularnewline
0.4 & 22388.6466222651 & 713.543132770011 \tabularnewline
0.41 & 22526.3209212294 & 741.05823898853 \tabularnewline
0.42 & 22668.8619349939 & 780.933109849127 \tabularnewline
0.43 & 22818.2448713917 & 830.411591631067 \tabularnewline
0.44 & 22975.9894049006 & 886.22249300769 \tabularnewline
0.45 & 23143.0753443230 & 944.772207563235 \tabularnewline
0.46 & 23319.9085546042 & 1002.60838600023 \tabularnewline
0.47 & 23506.3394676042 & 1056.71450223952 \tabularnewline
0.48 & 23701.7292997266 & 1104.64407965619 \tabularnewline
0.49 & 23905.0527700244 & 1144.75848214349 \tabularnewline
0.5 & 24115.0220415397 & 1176.20996357116 \tabularnewline
0.51 & 24330.2156040234 & 1198.78393497398 \tabularnewline
0.52 & 24549.1978820915 & 1212.99301181662 \tabularnewline
0.53 & 24770.6196747896 & 1219.69854102891 \tabularnewline
0.54 & 24993.2947266370 & 1220.05302997344 \tabularnewline
0.55 & 25216.2522738667 & 1215.33294337329 \tabularnewline
0.56 & 25438.7681164113 & 1206.91710294698 \tabularnewline
0.57 & 25660.3771575827 & 1196.23415527121 \tabularnewline
0.58 & 25880.8688117687 & 1184.59677539106 \tabularnewline
0.59 & 26100.2643336465 & 1173.33781508622 \tabularnewline
0.6 & 26318.7734836798 & 1163.49415766843 \tabularnewline
0.61 & 26536.7284014946 & 1155.80466517966 \tabularnewline
0.62 & 26754.4958525285 & 1150.40232703808 \tabularnewline
0.63 & 26972.3748711621 & 1146.82094330242 \tabularnewline
0.64 & 27190.493881119 & 1143.75871141365 \tabularnewline
0.65 & 27408.727461913 & 1139.45659200193 \tabularnewline
0.66 & 27626.6556868876 & 1131.82405389446 \tabularnewline
0.67 & 27843.5866097259 & 1118.98507170526 \tabularnewline
0.68 & 28058.6545278954 & 1099.73619601220 \tabularnewline
0.69 & 28270.9942236052 & 1073.97399585614 \tabularnewline
0.7 & 28479.9770079188 & 1043.11688999281 \tabularnewline
0.71 & 28685.4812835967 & 1010.08575705263 \tabularnewline
0.72 & 28888.1613510165 & 979.286389665548 \tabularnewline
0.73 & 29089.6748477122 & 956.457396667082 \tabularnewline
0.74 & 29292.8312835175 & 947.810259453968 \tabularnewline
0.75 & 29501.6298264869 & 959.564951686908 \tabularnewline
0.76 & 29721.1614722651 & 996.77563112138 \tabularnewline
0.77 & 29957.3574906727 & 1062.40205370697 \tabularnewline
0.78 & 30216.5732114897 & 1156.54600889185 \tabularnewline
0.79 & 30505.0071082961 & 1276.03127076961 \tabularnewline
0.8 & 30827.9750544898 & 1414.26289939636 \tabularnewline
0.81 & 31189.0933706992 & 1561.25465046972 \tabularnewline
0.82 & 31589.4721137940 & 1704.11875627573 \tabularnewline
0.83 & 32027.0730840583 & 1827.89043964419 \tabularnewline
0.84 & 32496.4246809859 & 1917.40686262216 \tabularnewline
0.85 & 32988.8789080956 & 1959.75964243682 \tabularnewline
0.86 & 33493.5183129154 & 1947.21835143037 \tabularnewline
0.87 & 33998.6675656150 & 1879.59830047561 \tabularnewline
0.88 & 34493.7702395444 & 1765.43487350277 \tabularnewline
0.89 & 34971.2368317781 & 1620.96088873255 \tabularnewline
0.9 & 35427.8686528711 & 1466.71405554645 \tabularnewline
0.91 & 35865.7239853231 & 1322.8115305862 \tabularnewline
0.92 & 36292.8647549838 & 1204.91363025951 \tabularnewline
0.93 & 36725.1995495060 & 1124.35175255210 \tabularnewline
0.94 & 37191.2171426915 & 1095.81697709636 \tabularnewline
0.95 & 37740.6668867322 & 1151.42348886928 \tabularnewline
0.96 & 38453.1885063479 & 1342.41038254292 \tabularnewline
0.97 & 39427.6842838993 & 1711.10801850017 \tabularnewline
0.98 & 40708.3987283595 & 2259.51892817824 \tabularnewline
0.99 & 42116.249286639 & 2903.95141681403 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=9822&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]10969.6041847839[/C][C]761.196027891038[/C][/ROW]
[ROW][C]0.02[/C][C]11409.6021304793[/C][C]830.407593913784[/C][/ROW]
[ROW][C]0.03[/C][C]11925.5732829968[/C][C]1018.52169392409[/C][/ROW]
[ROW][C]0.04[/C][C]12476.0461552203[/C][C]1217.92131384483[/C][/ROW]
[ROW][C]0.05[/C][C]13047.9308357346[/C][C]1382.21107930060[/C][/ROW]
[ROW][C]0.06[/C][C]13632.9894621993[/C][C]1516.10080600385[/C][/ROW]
[ROW][C]0.07[/C][C]14221.4204199479[/C][C]1619.70764336783[/C][/ROW]
[ROW][C]0.08[/C][C]14801.177136145[/C][C]1673.11701247477[/C][/ROW]
[ROW][C]0.09[/C][C]15357.8296865505[/C][C]1654.75468041442[/C][/ROW]
[ROW][C]0.1[/C][C]15875.900577273[/C][C]1560.16291210511[/C][/ROW]
[ROW][C]0.11[/C][C]16342.0191405103[/C][C]1406.12293780503[/C][/ROW]
[ROW][C]0.12[/C][C]16748.2854562297[/C][C]1223.14928429075[/C][/ROW]
[ROW][C]0.13[/C][C]17094.0413326125[/C][C]1044.44207269141[/C][/ROW]
[ROW][C]0.14[/C][C]17385.4177791130[/C][C]896.959661210733[/C][/ROW]
[ROW][C]0.15[/C][C]17633.2264935713[/C][C]796.758283842694[/C][/ROW]
[ROW][C]0.16[/C][C]17850.2652790648[/C][C]747.691387414837[/C][/ROW]
[ROW][C]0.17[/C][C]18048.9502519771[/C][C]743.347665697252[/C][/ROW]
[ROW][C]0.18[/C][C]18239.7390245808[/C][C]771.72104089991[/C][/ROW]
[ROW][C]0.19[/C][C]18430.3943998048[/C][C]819.964341892786[/C][/ROW]
[ROW][C]0.2[/C][C]18625.9015087222[/C][C]877.247373449057[/C][/ROW]
[ROW][C]0.21[/C][C]18828.7863210973[/C][C]935.251352446579[/C][/ROW]
[ROW][C]0.22[/C][C]19039.619427757[/C][C]987.939114329518[/C][/ROW]
[ROW][C]0.23[/C][C]19257.5578036367[/C][C]1031.40525185701[/C][/ROW]
[ROW][C]0.24[/C][C]19480.8399756649[/C][C]1063.36552464184[/C][/ROW]
[ROW][C]0.25[/C][C]19707.1946524019[/C][C]1082.84666703127[/C][/ROW]
[ROW][C]0.26[/C][C]19934.1515697725[/C][C]1089.82818235341[/C][/ROW]
[ROW][C]0.27[/C][C]20159.2613737170[/C][C]1084.75087833948[/C][/ROW]
[ROW][C]0.28[/C][C]20380.2422035206[/C][C]1068.59599913265[/C][/ROW]
[ROW][C]0.29[/C][C]20595.0754202589[/C][C]1042.45720925072[/C][/ROW]
[ROW][C]0.3[/C][C]20802.0721080925[/C][C]1007.83189048083[/C][/ROW]
[ROW][C]0.31[/C][C]20999.9266535397[/C][C]966.40881522735[/C][/ROW]
[ROW][C]0.32[/C][C]21187.7658908728[/C][C]920.3440177939[/C][/ROW]
[ROW][C]0.33[/C][C]21365.1943801252[/C][C]872.11515019808[/C][/ROW]
[ROW][C]0.34[/C][C]21532.3303381881[/C][C]824.549255483106[/C][/ROW]
[ROW][C]0.35[/C][C]21689.8236176237[/C][C]780.715922449289[/C][/ROW]
[ROW][C]0.36[/C][C]21838.8469711986[/C][C]743.646101645753[/C][/ROW]
[ROW][C]0.37[/C][C]21981.0540237211[/C][C]716.331703941726[/C][/ROW]
[ROW][C]0.38[/C][C]22118.5010361742[/C][C]701.234197468494[/C][/ROW]
[ROW][C]0.39[/C][C]22253.5339331689[/C][C]700.070997909285[/C][/ROW]
[ROW][C]0.4[/C][C]22388.6466222651[/C][C]713.543132770011[/C][/ROW]
[ROW][C]0.41[/C][C]22526.3209212294[/C][C]741.05823898853[/C][/ROW]
[ROW][C]0.42[/C][C]22668.8619349939[/C][C]780.933109849127[/C][/ROW]
[ROW][C]0.43[/C][C]22818.2448713917[/C][C]830.411591631067[/C][/ROW]
[ROW][C]0.44[/C][C]22975.9894049006[/C][C]886.22249300769[/C][/ROW]
[ROW][C]0.45[/C][C]23143.0753443230[/C][C]944.772207563235[/C][/ROW]
[ROW][C]0.46[/C][C]23319.9085546042[/C][C]1002.60838600023[/C][/ROW]
[ROW][C]0.47[/C][C]23506.3394676042[/C][C]1056.71450223952[/C][/ROW]
[ROW][C]0.48[/C][C]23701.7292997266[/C][C]1104.64407965619[/C][/ROW]
[ROW][C]0.49[/C][C]23905.0527700244[/C][C]1144.75848214349[/C][/ROW]
[ROW][C]0.5[/C][C]24115.0220415397[/C][C]1176.20996357116[/C][/ROW]
[ROW][C]0.51[/C][C]24330.2156040234[/C][C]1198.78393497398[/C][/ROW]
[ROW][C]0.52[/C][C]24549.1978820915[/C][C]1212.99301181662[/C][/ROW]
[ROW][C]0.53[/C][C]24770.6196747896[/C][C]1219.69854102891[/C][/ROW]
[ROW][C]0.54[/C][C]24993.2947266370[/C][C]1220.05302997344[/C][/ROW]
[ROW][C]0.55[/C][C]25216.2522738667[/C][C]1215.33294337329[/C][/ROW]
[ROW][C]0.56[/C][C]25438.7681164113[/C][C]1206.91710294698[/C][/ROW]
[ROW][C]0.57[/C][C]25660.3771575827[/C][C]1196.23415527121[/C][/ROW]
[ROW][C]0.58[/C][C]25880.8688117687[/C][C]1184.59677539106[/C][/ROW]
[ROW][C]0.59[/C][C]26100.2643336465[/C][C]1173.33781508622[/C][/ROW]
[ROW][C]0.6[/C][C]26318.7734836798[/C][C]1163.49415766843[/C][/ROW]
[ROW][C]0.61[/C][C]26536.7284014946[/C][C]1155.80466517966[/C][/ROW]
[ROW][C]0.62[/C][C]26754.4958525285[/C][C]1150.40232703808[/C][/ROW]
[ROW][C]0.63[/C][C]26972.3748711621[/C][C]1146.82094330242[/C][/ROW]
[ROW][C]0.64[/C][C]27190.493881119[/C][C]1143.75871141365[/C][/ROW]
[ROW][C]0.65[/C][C]27408.727461913[/C][C]1139.45659200193[/C][/ROW]
[ROW][C]0.66[/C][C]27626.6556868876[/C][C]1131.82405389446[/C][/ROW]
[ROW][C]0.67[/C][C]27843.5866097259[/C][C]1118.98507170526[/C][/ROW]
[ROW][C]0.68[/C][C]28058.6545278954[/C][C]1099.73619601220[/C][/ROW]
[ROW][C]0.69[/C][C]28270.9942236052[/C][C]1073.97399585614[/C][/ROW]
[ROW][C]0.7[/C][C]28479.9770079188[/C][C]1043.11688999281[/C][/ROW]
[ROW][C]0.71[/C][C]28685.4812835967[/C][C]1010.08575705263[/C][/ROW]
[ROW][C]0.72[/C][C]28888.1613510165[/C][C]979.286389665548[/C][/ROW]
[ROW][C]0.73[/C][C]29089.6748477122[/C][C]956.457396667082[/C][/ROW]
[ROW][C]0.74[/C][C]29292.8312835175[/C][C]947.810259453968[/C][/ROW]
[ROW][C]0.75[/C][C]29501.6298264869[/C][C]959.564951686908[/C][/ROW]
[ROW][C]0.76[/C][C]29721.1614722651[/C][C]996.77563112138[/C][/ROW]
[ROW][C]0.77[/C][C]29957.3574906727[/C][C]1062.40205370697[/C][/ROW]
[ROW][C]0.78[/C][C]30216.5732114897[/C][C]1156.54600889185[/C][/ROW]
[ROW][C]0.79[/C][C]30505.0071082961[/C][C]1276.03127076961[/C][/ROW]
[ROW][C]0.8[/C][C]30827.9750544898[/C][C]1414.26289939636[/C][/ROW]
[ROW][C]0.81[/C][C]31189.0933706992[/C][C]1561.25465046972[/C][/ROW]
[ROW][C]0.82[/C][C]31589.4721137940[/C][C]1704.11875627573[/C][/ROW]
[ROW][C]0.83[/C][C]32027.0730840583[/C][C]1827.89043964419[/C][/ROW]
[ROW][C]0.84[/C][C]32496.4246809859[/C][C]1917.40686262216[/C][/ROW]
[ROW][C]0.85[/C][C]32988.8789080956[/C][C]1959.75964243682[/C][/ROW]
[ROW][C]0.86[/C][C]33493.5183129154[/C][C]1947.21835143037[/C][/ROW]
[ROW][C]0.87[/C][C]33998.6675656150[/C][C]1879.59830047561[/C][/ROW]
[ROW][C]0.88[/C][C]34493.7702395444[/C][C]1765.43487350277[/C][/ROW]
[ROW][C]0.89[/C][C]34971.2368317781[/C][C]1620.96088873255[/C][/ROW]
[ROW][C]0.9[/C][C]35427.8686528711[/C][C]1466.71405554645[/C][/ROW]
[ROW][C]0.91[/C][C]35865.7239853231[/C][C]1322.8115305862[/C][/ROW]
[ROW][C]0.92[/C][C]36292.8647549838[/C][C]1204.91363025951[/C][/ROW]
[ROW][C]0.93[/C][C]36725.1995495060[/C][C]1124.35175255210[/C][/ROW]
[ROW][C]0.94[/C][C]37191.2171426915[/C][C]1095.81697709636[/C][/ROW]
[ROW][C]0.95[/C][C]37740.6668867322[/C][C]1151.42348886928[/C][/ROW]
[ROW][C]0.96[/C][C]38453.1885063479[/C][C]1342.41038254292[/C][/ROW]
[ROW][C]0.97[/C][C]39427.6842838993[/C][C]1711.10801850017[/C][/ROW]
[ROW][C]0.98[/C][C]40708.3987283595[/C][C]2259.51892817824[/C][/ROW]
[ROW][C]0.99[/C][C]42116.249286639[/C][C]2903.95141681403[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=9822&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=9822&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
0.0110969.6041847839761.196027891038
0.0211409.6021304793830.407593913784
0.0311925.57328299681018.52169392409
0.0412476.04615522031217.92131384483
0.0513047.93083573461382.21107930060
0.0613632.98946219931516.10080600385
0.0714221.42041994791619.70764336783
0.0814801.1771361451673.11701247477
0.0915357.82968655051654.75468041442
0.115875.9005772731560.16291210511
0.1116342.01914051031406.12293780503
0.1216748.28545622971223.14928429075
0.1317094.04133261251044.44207269141
0.1417385.4177791130896.959661210733
0.1517633.2264935713796.758283842694
0.1617850.2652790648747.691387414837
0.1718048.9502519771743.347665697252
0.1818239.7390245808771.72104089991
0.1918430.3943998048819.964341892786
0.218625.9015087222877.247373449057
0.2118828.7863210973935.251352446579
0.2219039.619427757987.939114329518
0.2319257.55780363671031.40525185701
0.2419480.83997566491063.36552464184
0.2519707.19465240191082.84666703127
0.2619934.15156977251089.82818235341
0.2720159.26137371701084.75087833948
0.2820380.24220352061068.59599913265
0.2920595.07542025891042.45720925072
0.320802.07210809251007.83189048083
0.3120999.9266535397966.40881522735
0.3221187.7658908728920.3440177939
0.3321365.1943801252872.11515019808
0.3421532.3303381881824.549255483106
0.3521689.8236176237780.715922449289
0.3621838.8469711986743.646101645753
0.3721981.0540237211716.331703941726
0.3822118.5010361742701.234197468494
0.3922253.5339331689700.070997909285
0.422388.6466222651713.543132770011
0.4122526.3209212294741.05823898853
0.4222668.8619349939780.933109849127
0.4322818.2448713917830.411591631067
0.4422975.9894049006886.22249300769
0.4523143.0753443230944.772207563235
0.4623319.90855460421002.60838600023
0.4723506.33946760421056.71450223952
0.4823701.72929972661104.64407965619
0.4923905.05277002441144.75848214349
0.524115.02204153971176.20996357116
0.5124330.21560402341198.78393497398
0.5224549.19788209151212.99301181662
0.5324770.61967478961219.69854102891
0.5424993.29472663701220.05302997344
0.5525216.25227386671215.33294337329
0.5625438.76811641131206.91710294698
0.5725660.37715758271196.23415527121
0.5825880.86881176871184.59677539106
0.5926100.26433364651173.33781508622
0.626318.77348367981163.49415766843
0.6126536.72840149461155.80466517966
0.6226754.49585252851150.40232703808
0.6326972.37487116211146.82094330242
0.6427190.4938811191143.75871141365
0.6527408.7274619131139.45659200193
0.6627626.65568688761131.82405389446
0.6727843.58660972591118.98507170526
0.6828058.65452789541099.73619601220
0.6928270.99422360521073.97399585614
0.728479.97700791881043.11688999281
0.7128685.48128359671010.08575705263
0.7228888.1613510165979.286389665548
0.7329089.6748477122956.457396667082
0.7429292.8312835175947.810259453968
0.7529501.6298264869959.564951686908
0.7629721.1614722651996.77563112138
0.7729957.35749067271062.40205370697
0.7830216.57321148971156.54600889185
0.7930505.00710829611276.03127076961
0.830827.97505448981414.26289939636
0.8131189.09337069921561.25465046972
0.8231589.47211379401704.11875627573
0.8332027.07308405831827.89043964419
0.8432496.42468098591917.40686262216
0.8532988.87890809561959.75964243682
0.8633493.51831291541947.21835143037
0.8733998.66756561501879.59830047561
0.8834493.77023954441765.43487350277
0.8934971.23683177811620.96088873255
0.935427.86865287111466.71405554645
0.9135865.72398532311322.8115305862
0.9236292.86475498381204.91363025951
0.9336725.19954950601124.35175255210
0.9437191.21714269151095.81697709636
0.9537740.66688673221151.42348886928
0.9638453.18850634791342.41038254292
0.9739427.68428389931711.10801850017
0.9840708.39872835952259.51892817824
0.9942116.2492866392903.95141681403


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')