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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_harrell_davies.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationMon, 27 Oct 2008 03:04:02 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/27/t1225099258j96au3pf4lzloxr.htm/, Retrieved Thu, 06 Nov 2025 17:04:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19131, Retrieved Thu, 06 Nov 2025 17:04:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact400

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Tukey lambda PPCC Plot] [Investigating dis...] [2007-10-22 19:59:15] [b9964c45117f7aac638ab9056d451faa]
F RMPD    [Harrell-Davis Quantiles] [Opdracht 3 Q9 Har...] [2008-10-27 09:04:02] [73ec5abea95a9c3c8c3a1ac44cab1f72] [Current]
Feedback Forum
2008-10-29 15:37:21 [Nathalie Koulouris] [reply] 
De student heeft hier gebruik gemaakt van de juiste methode en heeft zijn antwoord correct toegelicht.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2490
3266
3475
3127
2955
3870
2852
3142
3029
3180
2560
2733
2452
2553
2777
2520
2318
2873
2311
2395
2099
2268
2316
2181
2175
2627
2578
3090
2634
3225
2938
3174
3350
2588
2061
2691
2061
2918
2223
2651
2379
3146
2883
2768
3258
2839
2470
5072
1463
1600
2203
2013
2169
2640
2411
2528
2292
1988
1774
2279

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 4 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19131&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19131&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19131&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 time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Harrell-Davis Quantiles
quantilesvaluestandard error
0.011504.53440829486144.077440933825
0.021573.38056980526163.331199624564
0.031655.32417796443180.134086116254
0.041738.36533793569183.423734941644
0.051815.00881232635172.088724879728
0.061881.51797882900151.303230629955
0.071936.82867149792127.671872990006
0.081981.66144472390106.399129837212
0.092017.7438716441690.2671858109141
0.12047.1394909950779.7203604780967
0.112071.7650586235273.6060854869235
0.122093.1373408630870.219269683459
0.132112.3164349939468.131022335863
0.142129.9716438658566.4850273092658
0.152146.4958525666464.931176303635
0.162162.1166311230463.4556230037377
0.172176.9786152765362.1623935006968
0.182191.192159479261.1506039557135
0.192204.8549957179160.4484000668078
0.22218.0577361936460.0114813293908
0.212230.8830506207359.7793958937588
0.222243.4048661503559.6971875861718
0.232255.6900822973159.7610375466149
0.242267.8023779415960.0189121215403
0.252279.8062318111360.5573587954647
0.262291.7691777251961.44498492636
0.272303.7611056023562.7313834046458
0.282315.8505345453164.4043492165663
0.292328.0987575704166.3945733450255
0.32340.5533159573868.5840303179757
0.312353.2423362419270.8149725591811
0.322366.1709411001872.9261682827083
0.332379.3203951990674.7651647613429
0.342392.6500494695576.2197385619378
0.352406.1016463751877.2004750020112
0.362419.6052279072177.670501879251
0.372433.0857681302877.6294470739801
0.382446.4697054803477.1134845777021
0.392459.6907214761276.1957052543861
0.42472.6943400005874.9562249888781
0.412485.4411513891473.4991322716099
0.422497.9086614161271.9328918468232
0.432510.0919078416970.3631931338712
0.442522.0030716219868.8981724846497
0.452533.6703402619767.6229767683815
0.462545.1362655389166.6279311596992
0.472556.4558073131265.9726458218983
0.482567.6941813678965.7230147667432
0.492578.9245465642665.9153039056856
0.52590.2254921587266.5757748541887
0.512601.6782384215767.7213453957473
0.522613.3634593061469.3414364476995
0.532625.3576848988671.3992058858141
0.542637.7293427730773.8381434517616
0.552650.5346367703676.5625718101325
0.562663.8136121599279.4619625109706
0.572677.5868825834982.3881473795237
0.582691.8535610050185.1947549078887
0.592706.5909159312887.7301607622449
0.62721.7561517505289.8662149380664
0.612737.2904925300291.502188358449
0.622753.1254541424292.5876527615942
0.632769.1908561912293.1248651108522
0.642785.4237970592493.1800626909703
0.652801.7775390119092.8720391684198
0.662818.2290700645692.3770264315958
0.672834.7840649196791.8920267598964
0.682851.4780916545891.6317490963669
0.692868.3732271275391.776163936584
0.72885.5497592929392.4516661825441
0.712903.0933495282893.678823742115
0.722921.0788448465195.3757911889988
0.732939.5527622913497.3300572418542
0.742958.5171610042499.2316536528887
0.752977.9179842354100.708363151413
0.762997.64081161068101.382670859932
0.773017.51618910097100.92584106164
0.783037.3353007033199.129426097638
0.793056.8748850834895.9391767070069
0.83075.9283451102291.4928941283016
0.813094.3384656208886.1022239029977
0.823112.0266236458880.2408070429982
0.833129.0143442435874.4706589817598
0.843145.4357796479369.3651914630604
0.853161.5440457285565.4374210460453
0.863177.7197955791963.0822569033708
0.873194.4961426395262.596765864683
0.883212.6194835691164.309925920505
0.893233.171511593868.8124891832161
0.93257.7870597872677.2209629475094
0.913289.0228132362391.3835679197636
0.923330.97173246766114.051479252386
0.933390.26239132814149.122577186089
0.943477.51456026538202.131017002998
0.953608.77775980414281.114701668315
0.963804.82277382054397.447741981691
0.974083.29237534354563.506526189349
0.984437.72571387042780.0317590432
0.994807.490161482551012.44999205790

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 1504.53440829486 & 144.077440933825 \tabularnewline
0.02 & 1573.38056980526 & 163.331199624564 \tabularnewline
0.03 & 1655.32417796443 & 180.134086116254 \tabularnewline
0.04 & 1738.36533793569 & 183.423734941644 \tabularnewline
0.05 & 1815.00881232635 & 172.088724879728 \tabularnewline
0.06 & 1881.51797882900 & 151.303230629955 \tabularnewline
0.07 & 1936.82867149792 & 127.671872990006 \tabularnewline
0.08 & 1981.66144472390 & 106.399129837212 \tabularnewline
0.09 & 2017.74387164416 & 90.2671858109141 \tabularnewline
0.1 & 2047.13949099507 & 79.7203604780967 \tabularnewline
0.11 & 2071.76505862352 & 73.6060854869235 \tabularnewline
0.12 & 2093.13734086308 & 70.219269683459 \tabularnewline
0.13 & 2112.31643499394 & 68.131022335863 \tabularnewline
0.14 & 2129.97164386585 & 66.4850273092658 \tabularnewline
0.15 & 2146.49585256664 & 64.931176303635 \tabularnewline
0.16 & 2162.11663112304 & 63.4556230037377 \tabularnewline
0.17 & 2176.97861527653 & 62.1623935006968 \tabularnewline
0.18 & 2191.1921594792 & 61.1506039557135 \tabularnewline
0.19 & 2204.85499571791 & 60.4484000668078 \tabularnewline
0.2 & 2218.05773619364 & 60.0114813293908 \tabularnewline
0.21 & 2230.88305062073 & 59.7793958937588 \tabularnewline
0.22 & 2243.40486615035 & 59.6971875861718 \tabularnewline
0.23 & 2255.69008229731 & 59.7610375466149 \tabularnewline
0.24 & 2267.80237794159 & 60.0189121215403 \tabularnewline
0.25 & 2279.80623181113 & 60.5573587954647 \tabularnewline
0.26 & 2291.76917772519 & 61.44498492636 \tabularnewline
0.27 & 2303.76110560235 & 62.7313834046458 \tabularnewline
0.28 & 2315.85053454531 & 64.4043492165663 \tabularnewline
0.29 & 2328.09875757041 & 66.3945733450255 \tabularnewline
0.3 & 2340.55331595738 & 68.5840303179757 \tabularnewline
0.31 & 2353.24233624192 & 70.8149725591811 \tabularnewline
0.32 & 2366.17094110018 & 72.9261682827083 \tabularnewline
0.33 & 2379.32039519906 & 74.7651647613429 \tabularnewline
0.34 & 2392.65004946955 & 76.2197385619378 \tabularnewline
0.35 & 2406.10164637518 & 77.2004750020112 \tabularnewline
0.36 & 2419.60522790721 & 77.670501879251 \tabularnewline
0.37 & 2433.08576813028 & 77.6294470739801 \tabularnewline
0.38 & 2446.46970548034 & 77.1134845777021 \tabularnewline
0.39 & 2459.69072147612 & 76.1957052543861 \tabularnewline
0.4 & 2472.69434000058 & 74.9562249888781 \tabularnewline
0.41 & 2485.44115138914 & 73.4991322716099 \tabularnewline
0.42 & 2497.90866141612 & 71.9328918468232 \tabularnewline
0.43 & 2510.09190784169 & 70.3631931338712 \tabularnewline
0.44 & 2522.00307162198 & 68.8981724846497 \tabularnewline
0.45 & 2533.67034026197 & 67.6229767683815 \tabularnewline
0.46 & 2545.13626553891 & 66.6279311596992 \tabularnewline
0.47 & 2556.45580731312 & 65.9726458218983 \tabularnewline
0.48 & 2567.69418136789 & 65.7230147667432 \tabularnewline
0.49 & 2578.92454656426 & 65.9153039056856 \tabularnewline
0.5 & 2590.22549215872 & 66.5757748541887 \tabularnewline
0.51 & 2601.67823842157 & 67.7213453957473 \tabularnewline
0.52 & 2613.36345930614 & 69.3414364476995 \tabularnewline
0.53 & 2625.35768489886 & 71.3992058858141 \tabularnewline
0.54 & 2637.72934277307 & 73.8381434517616 \tabularnewline
0.55 & 2650.53463677036 & 76.5625718101325 \tabularnewline
0.56 & 2663.81361215992 & 79.4619625109706 \tabularnewline
0.57 & 2677.58688258349 & 82.3881473795237 \tabularnewline
0.58 & 2691.85356100501 & 85.1947549078887 \tabularnewline
0.59 & 2706.59091593128 & 87.7301607622449 \tabularnewline
0.6 & 2721.75615175052 & 89.8662149380664 \tabularnewline
0.61 & 2737.29049253002 & 91.502188358449 \tabularnewline
0.62 & 2753.12545414242 & 92.5876527615942 \tabularnewline
0.63 & 2769.19085619122 & 93.1248651108522 \tabularnewline
0.64 & 2785.42379705924 & 93.1800626909703 \tabularnewline
0.65 & 2801.77753901190 & 92.8720391684198 \tabularnewline
0.66 & 2818.22907006456 & 92.3770264315958 \tabularnewline
0.67 & 2834.78406491967 & 91.8920267598964 \tabularnewline
0.68 & 2851.47809165458 & 91.6317490963669 \tabularnewline
0.69 & 2868.37322712753 & 91.776163936584 \tabularnewline
0.7 & 2885.54975929293 & 92.4516661825441 \tabularnewline
0.71 & 2903.09334952828 & 93.678823742115 \tabularnewline
0.72 & 2921.07884484651 & 95.3757911889988 \tabularnewline
0.73 & 2939.55276229134 & 97.3300572418542 \tabularnewline
0.74 & 2958.51716100424 & 99.2316536528887 \tabularnewline
0.75 & 2977.9179842354 & 100.708363151413 \tabularnewline
0.76 & 2997.64081161068 & 101.382670859932 \tabularnewline
0.77 & 3017.51618910097 & 100.92584106164 \tabularnewline
0.78 & 3037.33530070331 & 99.129426097638 \tabularnewline
0.79 & 3056.87488508348 & 95.9391767070069 \tabularnewline
0.8 & 3075.92834511022 & 91.4928941283016 \tabularnewline
0.81 & 3094.33846562088 & 86.1022239029977 \tabularnewline
0.82 & 3112.02662364588 & 80.2408070429982 \tabularnewline
0.83 & 3129.01434424358 & 74.4706589817598 \tabularnewline
0.84 & 3145.43577964793 & 69.3651914630604 \tabularnewline
0.85 & 3161.54404572855 & 65.4374210460453 \tabularnewline
0.86 & 3177.71979557919 & 63.0822569033708 \tabularnewline
0.87 & 3194.49614263952 & 62.596765864683 \tabularnewline
0.88 & 3212.61948356911 & 64.309925920505 \tabularnewline
0.89 & 3233.1715115938 & 68.8124891832161 \tabularnewline
0.9 & 3257.78705978726 & 77.2209629475094 \tabularnewline
0.91 & 3289.02281323623 & 91.3835679197636 \tabularnewline
0.92 & 3330.97173246766 & 114.051479252386 \tabularnewline
0.93 & 3390.26239132814 & 149.122577186089 \tabularnewline
0.94 & 3477.51456026538 & 202.131017002998 \tabularnewline
0.95 & 3608.77775980414 & 281.114701668315 \tabularnewline
0.96 & 3804.82277382054 & 397.447741981691 \tabularnewline
0.97 & 4083.29237534354 & 563.506526189349 \tabularnewline
0.98 & 4437.72571387042 & 780.0317590432 \tabularnewline
0.99 & 4807.49016148255 & 1012.44999205790 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19131&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]1504.53440829486[/C][C]144.077440933825[/C][/ROW]
[ROW][C]0.02[/C][C]1573.38056980526[/C][C]163.331199624564[/C][/ROW]
[ROW][C]0.03[/C][C]1655.32417796443[/C][C]180.134086116254[/C][/ROW]
[ROW][C]0.04[/C][C]1738.36533793569[/C][C]183.423734941644[/C][/ROW]
[ROW][C]0.05[/C][C]1815.00881232635[/C][C]172.088724879728[/C][/ROW]
[ROW][C]0.06[/C][C]1881.51797882900[/C][C]151.303230629955[/C][/ROW]
[ROW][C]0.07[/C][C]1936.82867149792[/C][C]127.671872990006[/C][/ROW]
[ROW][C]0.08[/C][C]1981.66144472390[/C][C]106.399129837212[/C][/ROW]
[ROW][C]0.09[/C][C]2017.74387164416[/C][C]90.2671858109141[/C][/ROW]
[ROW][C]0.1[/C][C]2047.13949099507[/C][C]79.7203604780967[/C][/ROW]
[ROW][C]0.11[/C][C]2071.76505862352[/C][C]73.6060854869235[/C][/ROW]
[ROW][C]0.12[/C][C]2093.13734086308[/C][C]70.219269683459[/C][/ROW]
[ROW][C]0.13[/C][C]2112.31643499394[/C][C]68.131022335863[/C][/ROW]
[ROW][C]0.14[/C][C]2129.97164386585[/C][C]66.4850273092658[/C][/ROW]
[ROW][C]0.15[/C][C]2146.49585256664[/C][C]64.931176303635[/C][/ROW]
[ROW][C]0.16[/C][C]2162.11663112304[/C][C]63.4556230037377[/C][/ROW]
[ROW][C]0.17[/C][C]2176.97861527653[/C][C]62.1623935006968[/C][/ROW]
[ROW][C]0.18[/C][C]2191.1921594792[/C][C]61.1506039557135[/C][/ROW]
[ROW][C]0.19[/C][C]2204.85499571791[/C][C]60.4484000668078[/C][/ROW]
[ROW][C]0.2[/C][C]2218.05773619364[/C][C]60.0114813293908[/C][/ROW]
[ROW][C]0.21[/C][C]2230.88305062073[/C][C]59.7793958937588[/C][/ROW]
[ROW][C]0.22[/C][C]2243.40486615035[/C][C]59.6971875861718[/C][/ROW]
[ROW][C]0.23[/C][C]2255.69008229731[/C][C]59.7610375466149[/C][/ROW]
[ROW][C]0.24[/C][C]2267.80237794159[/C][C]60.0189121215403[/C][/ROW]
[ROW][C]0.25[/C][C]2279.80623181113[/C][C]60.5573587954647[/C][/ROW]
[ROW][C]0.26[/C][C]2291.76917772519[/C][C]61.44498492636[/C][/ROW]
[ROW][C]0.27[/C][C]2303.76110560235[/C][C]62.7313834046458[/C][/ROW]
[ROW][C]0.28[/C][C]2315.85053454531[/C][C]64.4043492165663[/C][/ROW]
[ROW][C]0.29[/C][C]2328.09875757041[/C][C]66.3945733450255[/C][/ROW]
[ROW][C]0.3[/C][C]2340.55331595738[/C][C]68.5840303179757[/C][/ROW]
[ROW][C]0.31[/C][C]2353.24233624192[/C][C]70.8149725591811[/C][/ROW]
[ROW][C]0.32[/C][C]2366.17094110018[/C][C]72.9261682827083[/C][/ROW]
[ROW][C]0.33[/C][C]2379.32039519906[/C][C]74.7651647613429[/C][/ROW]
[ROW][C]0.34[/C][C]2392.65004946955[/C][C]76.2197385619378[/C][/ROW]
[ROW][C]0.35[/C][C]2406.10164637518[/C][C]77.2004750020112[/C][/ROW]
[ROW][C]0.36[/C][C]2419.60522790721[/C][C]77.670501879251[/C][/ROW]
[ROW][C]0.37[/C][C]2433.08576813028[/C][C]77.6294470739801[/C][/ROW]
[ROW][C]0.38[/C][C]2446.46970548034[/C][C]77.1134845777021[/C][/ROW]
[ROW][C]0.39[/C][C]2459.69072147612[/C][C]76.1957052543861[/C][/ROW]
[ROW][C]0.4[/C][C]2472.69434000058[/C][C]74.9562249888781[/C][/ROW]
[ROW][C]0.41[/C][C]2485.44115138914[/C][C]73.4991322716099[/C][/ROW]
[ROW][C]0.42[/C][C]2497.90866141612[/C][C]71.9328918468232[/C][/ROW]
[ROW][C]0.43[/C][C]2510.09190784169[/C][C]70.3631931338712[/C][/ROW]
[ROW][C]0.44[/C][C]2522.00307162198[/C][C]68.8981724846497[/C][/ROW]
[ROW][C]0.45[/C][C]2533.67034026197[/C][C]67.6229767683815[/C][/ROW]
[ROW][C]0.46[/C][C]2545.13626553891[/C][C]66.6279311596992[/C][/ROW]
[ROW][C]0.47[/C][C]2556.45580731312[/C][C]65.9726458218983[/C][/ROW]
[ROW][C]0.48[/C][C]2567.69418136789[/C][C]65.7230147667432[/C][/ROW]
[ROW][C]0.49[/C][C]2578.92454656426[/C][C]65.9153039056856[/C][/ROW]
[ROW][C]0.5[/C][C]2590.22549215872[/C][C]66.5757748541887[/C][/ROW]
[ROW][C]0.51[/C][C]2601.67823842157[/C][C]67.7213453957473[/C][/ROW]
[ROW][C]0.52[/C][C]2613.36345930614[/C][C]69.3414364476995[/C][/ROW]
[ROW][C]0.53[/C][C]2625.35768489886[/C][C]71.3992058858141[/C][/ROW]
[ROW][C]0.54[/C][C]2637.72934277307[/C][C]73.8381434517616[/C][/ROW]
[ROW][C]0.55[/C][C]2650.53463677036[/C][C]76.5625718101325[/C][/ROW]
[ROW][C]0.56[/C][C]2663.81361215992[/C][C]79.4619625109706[/C][/ROW]
[ROW][C]0.57[/C][C]2677.58688258349[/C][C]82.3881473795237[/C][/ROW]
[ROW][C]0.58[/C][C]2691.85356100501[/C][C]85.1947549078887[/C][/ROW]
[ROW][C]0.59[/C][C]2706.59091593128[/C][C]87.7301607622449[/C][/ROW]
[ROW][C]0.6[/C][C]2721.75615175052[/C][C]89.8662149380664[/C][/ROW]
[ROW][C]0.61[/C][C]2737.29049253002[/C][C]91.502188358449[/C][/ROW]
[ROW][C]0.62[/C][C]2753.12545414242[/C][C]92.5876527615942[/C][/ROW]
[ROW][C]0.63[/C][C]2769.19085619122[/C][C]93.1248651108522[/C][/ROW]
[ROW][C]0.64[/C][C]2785.42379705924[/C][C]93.1800626909703[/C][/ROW]
[ROW][C]0.65[/C][C]2801.77753901190[/C][C]92.8720391684198[/C][/ROW]
[ROW][C]0.66[/C][C]2818.22907006456[/C][C]92.3770264315958[/C][/ROW]
[ROW][C]0.67[/C][C]2834.78406491967[/C][C]91.8920267598964[/C][/ROW]
[ROW][C]0.68[/C][C]2851.47809165458[/C][C]91.6317490963669[/C][/ROW]
[ROW][C]0.69[/C][C]2868.37322712753[/C][C]91.776163936584[/C][/ROW]
[ROW][C]0.7[/C][C]2885.54975929293[/C][C]92.4516661825441[/C][/ROW]
[ROW][C]0.71[/C][C]2903.09334952828[/C][C]93.678823742115[/C][/ROW]
[ROW][C]0.72[/C][C]2921.07884484651[/C][C]95.3757911889988[/C][/ROW]
[ROW][C]0.73[/C][C]2939.55276229134[/C][C]97.3300572418542[/C][/ROW]
[ROW][C]0.74[/C][C]2958.51716100424[/C][C]99.2316536528887[/C][/ROW]
[ROW][C]0.75[/C][C]2977.9179842354[/C][C]100.708363151413[/C][/ROW]
[ROW][C]0.76[/C][C]2997.64081161068[/C][C]101.382670859932[/C][/ROW]
[ROW][C]0.77[/C][C]3017.51618910097[/C][C]100.92584106164[/C][/ROW]
[ROW][C]0.78[/C][C]3037.33530070331[/C][C]99.129426097638[/C][/ROW]
[ROW][C]0.79[/C][C]3056.87488508348[/C][C]95.9391767070069[/C][/ROW]
[ROW][C]0.8[/C][C]3075.92834511022[/C][C]91.4928941283016[/C][/ROW]
[ROW][C]0.81[/C][C]3094.33846562088[/C][C]86.1022239029977[/C][/ROW]
[ROW][C]0.82[/C][C]3112.02662364588[/C][C]80.2408070429982[/C][/ROW]
[ROW][C]0.83[/C][C]3129.01434424358[/C][C]74.4706589817598[/C][/ROW]
[ROW][C]0.84[/C][C]3145.43577964793[/C][C]69.3651914630604[/C][/ROW]
[ROW][C]0.85[/C][C]3161.54404572855[/C][C]65.4374210460453[/C][/ROW]
[ROW][C]0.86[/C][C]3177.71979557919[/C][C]63.0822569033708[/C][/ROW]
[ROW][C]0.87[/C][C]3194.49614263952[/C][C]62.596765864683[/C][/ROW]
[ROW][C]0.88[/C][C]3212.61948356911[/C][C]64.309925920505[/C][/ROW]
[ROW][C]0.89[/C][C]3233.1715115938[/C][C]68.8124891832161[/C][/ROW]
[ROW][C]0.9[/C][C]3257.78705978726[/C][C]77.2209629475094[/C][/ROW]
[ROW][C]0.91[/C][C]3289.02281323623[/C][C]91.3835679197636[/C][/ROW]
[ROW][C]0.92[/C][C]3330.97173246766[/C][C]114.051479252386[/C][/ROW]
[ROW][C]0.93[/C][C]3390.26239132814[/C][C]149.122577186089[/C][/ROW]
[ROW][C]0.94[/C][C]3477.51456026538[/C][C]202.131017002998[/C][/ROW]
[ROW][C]0.95[/C][C]3608.77775980414[/C][C]281.114701668315[/C][/ROW]
[ROW][C]0.96[/C][C]3804.82277382054[/C][C]397.447741981691[/C][/ROW]
[ROW][C]0.97[/C][C]4083.29237534354[/C][C]563.506526189349[/C][/ROW]
[ROW][C]0.98[/C][C]4437.72571387042[/C][C]780.0317590432[/C][/ROW]
[ROW][C]0.99[/C][C]4807.49016148255[/C][C]1012.44999205790[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19131&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19131&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
0.011504.53440829486144.077440933825
0.021573.38056980526163.331199624564
0.031655.32417796443180.134086116254
0.041738.36533793569183.423734941644
0.051815.00881232635172.088724879728
0.061881.51797882900151.303230629955
0.071936.82867149792127.671872990006
0.081981.66144472390106.399129837212
0.092017.7438716441690.2671858109141
0.12047.1394909950779.7203604780967
0.112071.7650586235273.6060854869235
0.122093.1373408630870.219269683459
0.132112.3164349939468.131022335863
0.142129.9716438658566.4850273092658
0.152146.4958525666464.931176303635
0.162162.1166311230463.4556230037377
0.172176.9786152765362.1623935006968
0.182191.192159479261.1506039557135
0.192204.8549957179160.4484000668078
0.22218.0577361936460.0114813293908
0.212230.8830506207359.7793958937588
0.222243.4048661503559.6971875861718
0.232255.6900822973159.7610375466149
0.242267.8023779415960.0189121215403
0.252279.8062318111360.5573587954647
0.262291.7691777251961.44498492636
0.272303.7611056023562.7313834046458
0.282315.8505345453164.4043492165663
0.292328.0987575704166.3945733450255
0.32340.5533159573868.5840303179757
0.312353.2423362419270.8149725591811
0.322366.1709411001872.9261682827083
0.332379.3203951990674.7651647613429
0.342392.6500494695576.2197385619378
0.352406.1016463751877.2004750020112
0.362419.6052279072177.670501879251
0.372433.0857681302877.6294470739801
0.382446.4697054803477.1134845777021
0.392459.6907214761276.1957052543861
0.42472.6943400005874.9562249888781
0.412485.4411513891473.4991322716099
0.422497.9086614161271.9328918468232
0.432510.0919078416970.3631931338712
0.442522.0030716219868.8981724846497
0.452533.6703402619767.6229767683815
0.462545.1362655389166.6279311596992
0.472556.4558073131265.9726458218983
0.482567.6941813678965.7230147667432
0.492578.9245465642665.9153039056856
0.52590.2254921587266.5757748541887
0.512601.6782384215767.7213453957473
0.522613.3634593061469.3414364476995
0.532625.3576848988671.3992058858141
0.542637.7293427730773.8381434517616
0.552650.5346367703676.5625718101325
0.562663.8136121599279.4619625109706
0.572677.5868825834982.3881473795237
0.582691.8535610050185.1947549078887
0.592706.5909159312887.7301607622449
0.62721.7561517505289.8662149380664
0.612737.2904925300291.502188358449
0.622753.1254541424292.5876527615942
0.632769.1908561912293.1248651108522
0.642785.4237970592493.1800626909703
0.652801.7775390119092.8720391684198
0.662818.2290700645692.3770264315958
0.672834.7840649196791.8920267598964
0.682851.4780916545891.6317490963669
0.692868.3732271275391.776163936584
0.72885.5497592929392.4516661825441
0.712903.0933495282893.678823742115
0.722921.0788448465195.3757911889988
0.732939.5527622913497.3300572418542
0.742958.5171610042499.2316536528887
0.752977.9179842354100.708363151413
0.762997.64081161068101.382670859932
0.773017.51618910097100.92584106164
0.783037.3353007033199.129426097638
0.793056.8748850834895.9391767070069
0.83075.9283451102291.4928941283016
0.813094.3384656208886.1022239029977
0.823112.0266236458880.2408070429982
0.833129.0143442435874.4706589817598
0.843145.4357796479369.3651914630604
0.853161.5440457285565.4374210460453
0.863177.7197955791963.0822569033708
0.873194.4961426395262.596765864683
0.883212.6194835691164.309925920505
0.893233.171511593868.8124891832161
0.93257.7870597872677.2209629475094
0.913289.0228132362391.3835679197636
0.923330.97173246766114.051479252386
0.933390.26239132814149.122577186089
0.943477.51456026538202.131017002998
0.953608.77775980414281.114701668315
0.963804.82277382054397.447741981691
0.974083.29237534354563.506526189349
0.984437.72571387042780.0317590432
0.994807.490161482551012.44999205790


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')