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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 computationThu, 18 Oct 2012 11:23:27 -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/2012/Oct/18/t1350573863gapehkd2tgm8qhq.htm/, Retrieved Mon, 29 Apr 2024 01:26:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=179699, Retrieved Mon, 29 Apr 2024 01:26:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Ontvangsten geïnd...] [2012-10-07 17:57:08] [7e0b1fc7e94581fb4f84255f8aa2fbc5]
- RMP   [Central Tendency] [Centrummaten ontv...] [2012-10-11 15:49:27] [7e0b1fc7e94581fb4f84255f8aa2fbc5]
- RM D    [Mean versus Median] [Gemiddelde versus...] [2012-10-11 16:06:05] [7e0b1fc7e94581fb4f84255f8aa2fbc5]
- RMP       [Histogram] [inkomsten schatki...] [2012-10-11 16:42:04] [7e0b1fc7e94581fb4f84255f8aa2fbc5]
- RMPD          [Harrell-Davis Quantiles] [percentielen inko...] [2012-10-18 15:23:27] [1fc6f30e88849aa85fd62e34f240f44c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6848
5772
5251
11232
5908
6812
9962
6155
5673
7985
5780
11999
6973
5817
5844
11178
5533
6870
9521
5363
6031
9245
5621
11802
8364
6286
5071
10773
5821
7794
10636
6405
5811
8981
6228
11950
7523
6067
4825
12162
6989
8012
10893
6647
5938
9005
6262
12022
7683
6004
4724
10343
6604
7241
9331
6418
7094
10340
6814
12003
7481
5452
6380
11425
5905
8536
10785
6672
7293
9809
5658
12364
8078
5269
7787
11729
6236
8576
11216
6814
6019
9351
5464
12518

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=179699&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=179699&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=179699&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.014786.15753684049144.542600555561
0.024895.4538496257194.399597591791
0.035018.51705767067204.475078374254
0.045131.79747145952185.866877641195
0.055226.66091319351162.913003028598
0.065304.24778629927147.750026049002
0.075369.27329927793140.61137562497
0.085426.18245244716137.830631315206
0.095477.87285108347136.46213188228
0.15525.83176815417134.818823286898
0.115570.64963988161131.95899569087
0.125612.45454611226127.501754690377
0.135651.19781995011121.520567303388
0.145686.83559328303114.525551056625
0.155719.4416751535107.314373410349
0.165749.26344891901100.795760575303
0.175776.7258780146595.8523615796686
0.185802.3934324613193.1251272398868
0.195826.9058434518992.9380276706415
0.25850.9062730055195.1943856478126
0.215874.9786837647399.5125670869428
0.225899.60562321884105.374059424433
0.235925.15020028348112.292572624434
0.245951.85925421842119.842126918956
0.255979.88066244178127.736726167629
0.266009.28707206073135.755517114608
0.276040.10020906236143.766743404015
0.286072.31262256619151.677988287316
0.296105.90571827649159.487009238777
0.36140.86354986413167.263618815192
0.316177.18139430197175.077687688672
0.326214.86757900326183.053869076601
0.336253.93729660498191.225453943185
0.346294.39865433458199.521628760713
0.356336.23364135805207.744632289845
0.366379.37916003401215.53906037933
0.376423.71468040991222.495820337203
0.386469.06265197984228.258644599156
0.396515.20536569849232.576097140029
0.46561.91801944554235.470886229475
0.416609.01334293898237.253132121509
0.426656.38951276387238.534925731247
0.436704.0712750323240.157883207343
0.446752.2347471531243.111880030471
0.456801.20922340915248.296953007728
0.466851.45381411374256.408532690106
0.476903.51187043906267.752885033593
0.486957.95073857561282.209519688216
0.497015.29746138207299.252667055235
0.57075.9819857801318.074909505537
0.517140.29809046238337.72390536006
0.527208.38892555268357.287649102188
0.537280.25941088151376.024000979432
0.547355.81263569377393.507672878942
0.557434.90275695338409.645839422712
0.567517.39354410706424.686586314023
0.577603.21031652718439.189615223769
0.587692.37394035225453.821795041549
0.597785.00881315178469.23469285038
0.67881.32197029969485.859034320786
0.617981.55676186426503.769268670109
0.628085.93075742305522.598923733269
0.638194.5722032997541.604488599699
0.648307.47110540588559.773958129767
0.658424.45888652143576.112968284202
0.668545.22441273311589.75511354331
0.678669.36491470376600.308507180594
0.688796.45997265294607.855536157605
0.698926.14812906247613.007420847473
0.79058.18182087799616.662897404985
0.719192.43936173003619.721961674113
0.729328.88306937473622.775663132208
0.739467.46836682446625.741061496222
0.749608.02556876065627.802282284055
0.759750.14863747061627.499719901136
0.769893.12853019953623.101290852237
0.7710035.9604596773613.125233211544
0.7810177.4359389258596.753554537396
0.7910316.307210343574.125828381206
0.810451.4909274372546.439279143766
0.8110582.266055979515.781565375946
0.8210708.4201474968484.700657896464
0.8310830.3057407446455.78329491942
0.8410948.7795512658431.142947974761
0.8511065.0088530146411.913556227451
0.8611180.1463990476397.82850227462
0.8711294.907054214386.835505026138
0.8811409.1319298243375.209415497933
0.8911521.4893227666358.311611487045
0.911629.5055551606332.089594533373
0.9111730.1008491079294.885355498713
0.9211820.6908168958248.906410419931
0.9311900.689694105200.787613111931
0.9411972.9342256959161.060770156839
0.9512044.2166584506141.9300070345
0.9612123.9717478742148.412444448902
0.9712220.4060432368167.568319164941
0.9812333.6546251812175.865568582218
0.9912446.0538676396163.516758795141

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 4786.15753684049 & 144.542600555561 \tabularnewline
0.02 & 4895.4538496257 & 194.399597591791 \tabularnewline
0.03 & 5018.51705767067 & 204.475078374254 \tabularnewline
0.04 & 5131.79747145952 & 185.866877641195 \tabularnewline
0.05 & 5226.66091319351 & 162.913003028598 \tabularnewline
0.06 & 5304.24778629927 & 147.750026049002 \tabularnewline
0.07 & 5369.27329927793 & 140.61137562497 \tabularnewline
0.08 & 5426.18245244716 & 137.830631315206 \tabularnewline
0.09 & 5477.87285108347 & 136.46213188228 \tabularnewline
0.1 & 5525.83176815417 & 134.818823286898 \tabularnewline
0.11 & 5570.64963988161 & 131.95899569087 \tabularnewline
0.12 & 5612.45454611226 & 127.501754690377 \tabularnewline
0.13 & 5651.19781995011 & 121.520567303388 \tabularnewline
0.14 & 5686.83559328303 & 114.525551056625 \tabularnewline
0.15 & 5719.4416751535 & 107.314373410349 \tabularnewline
0.16 & 5749.26344891901 & 100.795760575303 \tabularnewline
0.17 & 5776.72587801465 & 95.8523615796686 \tabularnewline
0.18 & 5802.39343246131 & 93.1251272398868 \tabularnewline
0.19 & 5826.90584345189 & 92.9380276706415 \tabularnewline
0.2 & 5850.90627300551 & 95.1943856478126 \tabularnewline
0.21 & 5874.97868376473 & 99.5125670869428 \tabularnewline
0.22 & 5899.60562321884 & 105.374059424433 \tabularnewline
0.23 & 5925.15020028348 & 112.292572624434 \tabularnewline
0.24 & 5951.85925421842 & 119.842126918956 \tabularnewline
0.25 & 5979.88066244178 & 127.736726167629 \tabularnewline
0.26 & 6009.28707206073 & 135.755517114608 \tabularnewline
0.27 & 6040.10020906236 & 143.766743404015 \tabularnewline
0.28 & 6072.31262256619 & 151.677988287316 \tabularnewline
0.29 & 6105.90571827649 & 159.487009238777 \tabularnewline
0.3 & 6140.86354986413 & 167.263618815192 \tabularnewline
0.31 & 6177.18139430197 & 175.077687688672 \tabularnewline
0.32 & 6214.86757900326 & 183.053869076601 \tabularnewline
0.33 & 6253.93729660498 & 191.225453943185 \tabularnewline
0.34 & 6294.39865433458 & 199.521628760713 \tabularnewline
0.35 & 6336.23364135805 & 207.744632289845 \tabularnewline
0.36 & 6379.37916003401 & 215.53906037933 \tabularnewline
0.37 & 6423.71468040991 & 222.495820337203 \tabularnewline
0.38 & 6469.06265197984 & 228.258644599156 \tabularnewline
0.39 & 6515.20536569849 & 232.576097140029 \tabularnewline
0.4 & 6561.91801944554 & 235.470886229475 \tabularnewline
0.41 & 6609.01334293898 & 237.253132121509 \tabularnewline
0.42 & 6656.38951276387 & 238.534925731247 \tabularnewline
0.43 & 6704.0712750323 & 240.157883207343 \tabularnewline
0.44 & 6752.2347471531 & 243.111880030471 \tabularnewline
0.45 & 6801.20922340915 & 248.296953007728 \tabularnewline
0.46 & 6851.45381411374 & 256.408532690106 \tabularnewline
0.47 & 6903.51187043906 & 267.752885033593 \tabularnewline
0.48 & 6957.95073857561 & 282.209519688216 \tabularnewline
0.49 & 7015.29746138207 & 299.252667055235 \tabularnewline
0.5 & 7075.9819857801 & 318.074909505537 \tabularnewline
0.51 & 7140.29809046238 & 337.72390536006 \tabularnewline
0.52 & 7208.38892555268 & 357.287649102188 \tabularnewline
0.53 & 7280.25941088151 & 376.024000979432 \tabularnewline
0.54 & 7355.81263569377 & 393.507672878942 \tabularnewline
0.55 & 7434.90275695338 & 409.645839422712 \tabularnewline
0.56 & 7517.39354410706 & 424.686586314023 \tabularnewline
0.57 & 7603.21031652718 & 439.189615223769 \tabularnewline
0.58 & 7692.37394035225 & 453.821795041549 \tabularnewline
0.59 & 7785.00881315178 & 469.23469285038 \tabularnewline
0.6 & 7881.32197029969 & 485.859034320786 \tabularnewline
0.61 & 7981.55676186426 & 503.769268670109 \tabularnewline
0.62 & 8085.93075742305 & 522.598923733269 \tabularnewline
0.63 & 8194.5722032997 & 541.604488599699 \tabularnewline
0.64 & 8307.47110540588 & 559.773958129767 \tabularnewline
0.65 & 8424.45888652143 & 576.112968284202 \tabularnewline
0.66 & 8545.22441273311 & 589.75511354331 \tabularnewline
0.67 & 8669.36491470376 & 600.308507180594 \tabularnewline
0.68 & 8796.45997265294 & 607.855536157605 \tabularnewline
0.69 & 8926.14812906247 & 613.007420847473 \tabularnewline
0.7 & 9058.18182087799 & 616.662897404985 \tabularnewline
0.71 & 9192.43936173003 & 619.721961674113 \tabularnewline
0.72 & 9328.88306937473 & 622.775663132208 \tabularnewline
0.73 & 9467.46836682446 & 625.741061496222 \tabularnewline
0.74 & 9608.02556876065 & 627.802282284055 \tabularnewline
0.75 & 9750.14863747061 & 627.499719901136 \tabularnewline
0.76 & 9893.12853019953 & 623.101290852237 \tabularnewline
0.77 & 10035.9604596773 & 613.125233211544 \tabularnewline
0.78 & 10177.4359389258 & 596.753554537396 \tabularnewline
0.79 & 10316.307210343 & 574.125828381206 \tabularnewline
0.8 & 10451.4909274372 & 546.439279143766 \tabularnewline
0.81 & 10582.266055979 & 515.781565375946 \tabularnewline
0.82 & 10708.4201474968 & 484.700657896464 \tabularnewline
0.83 & 10830.3057407446 & 455.78329491942 \tabularnewline
0.84 & 10948.7795512658 & 431.142947974761 \tabularnewline
0.85 & 11065.0088530146 & 411.913556227451 \tabularnewline
0.86 & 11180.1463990476 & 397.82850227462 \tabularnewline
0.87 & 11294.907054214 & 386.835505026138 \tabularnewline
0.88 & 11409.1319298243 & 375.209415497933 \tabularnewline
0.89 & 11521.4893227666 & 358.311611487045 \tabularnewline
0.9 & 11629.5055551606 & 332.089594533373 \tabularnewline
0.91 & 11730.1008491079 & 294.885355498713 \tabularnewline
0.92 & 11820.6908168958 & 248.906410419931 \tabularnewline
0.93 & 11900.689694105 & 200.787613111931 \tabularnewline
0.94 & 11972.9342256959 & 161.060770156839 \tabularnewline
0.95 & 12044.2166584506 & 141.9300070345 \tabularnewline
0.96 & 12123.9717478742 & 148.412444448902 \tabularnewline
0.97 & 12220.4060432368 & 167.568319164941 \tabularnewline
0.98 & 12333.6546251812 & 175.865568582218 \tabularnewline
0.99 & 12446.0538676396 & 163.516758795141 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=179699&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]4786.15753684049[/C][C]144.542600555561[/C][/ROW]
[ROW][C]0.02[/C][C]4895.4538496257[/C][C]194.399597591791[/C][/ROW]
[ROW][C]0.03[/C][C]5018.51705767067[/C][C]204.475078374254[/C][/ROW]
[ROW][C]0.04[/C][C]5131.79747145952[/C][C]185.866877641195[/C][/ROW]
[ROW][C]0.05[/C][C]5226.66091319351[/C][C]162.913003028598[/C][/ROW]
[ROW][C]0.06[/C][C]5304.24778629927[/C][C]147.750026049002[/C][/ROW]
[ROW][C]0.07[/C][C]5369.27329927793[/C][C]140.61137562497[/C][/ROW]
[ROW][C]0.08[/C][C]5426.18245244716[/C][C]137.830631315206[/C][/ROW]
[ROW][C]0.09[/C][C]5477.87285108347[/C][C]136.46213188228[/C][/ROW]
[ROW][C]0.1[/C][C]5525.83176815417[/C][C]134.818823286898[/C][/ROW]
[ROW][C]0.11[/C][C]5570.64963988161[/C][C]131.95899569087[/C][/ROW]
[ROW][C]0.12[/C][C]5612.45454611226[/C][C]127.501754690377[/C][/ROW]
[ROW][C]0.13[/C][C]5651.19781995011[/C][C]121.520567303388[/C][/ROW]
[ROW][C]0.14[/C][C]5686.83559328303[/C][C]114.525551056625[/C][/ROW]
[ROW][C]0.15[/C][C]5719.4416751535[/C][C]107.314373410349[/C][/ROW]
[ROW][C]0.16[/C][C]5749.26344891901[/C][C]100.795760575303[/C][/ROW]
[ROW][C]0.17[/C][C]5776.72587801465[/C][C]95.8523615796686[/C][/ROW]
[ROW][C]0.18[/C][C]5802.39343246131[/C][C]93.1251272398868[/C][/ROW]
[ROW][C]0.19[/C][C]5826.90584345189[/C][C]92.9380276706415[/C][/ROW]
[ROW][C]0.2[/C][C]5850.90627300551[/C][C]95.1943856478126[/C][/ROW]
[ROW][C]0.21[/C][C]5874.97868376473[/C][C]99.5125670869428[/C][/ROW]
[ROW][C]0.22[/C][C]5899.60562321884[/C][C]105.374059424433[/C][/ROW]
[ROW][C]0.23[/C][C]5925.15020028348[/C][C]112.292572624434[/C][/ROW]
[ROW][C]0.24[/C][C]5951.85925421842[/C][C]119.842126918956[/C][/ROW]
[ROW][C]0.25[/C][C]5979.88066244178[/C][C]127.736726167629[/C][/ROW]
[ROW][C]0.26[/C][C]6009.28707206073[/C][C]135.755517114608[/C][/ROW]
[ROW][C]0.27[/C][C]6040.10020906236[/C][C]143.766743404015[/C][/ROW]
[ROW][C]0.28[/C][C]6072.31262256619[/C][C]151.677988287316[/C][/ROW]
[ROW][C]0.29[/C][C]6105.90571827649[/C][C]159.487009238777[/C][/ROW]
[ROW][C]0.3[/C][C]6140.86354986413[/C][C]167.263618815192[/C][/ROW]
[ROW][C]0.31[/C][C]6177.18139430197[/C][C]175.077687688672[/C][/ROW]
[ROW][C]0.32[/C][C]6214.86757900326[/C][C]183.053869076601[/C][/ROW]
[ROW][C]0.33[/C][C]6253.93729660498[/C][C]191.225453943185[/C][/ROW]
[ROW][C]0.34[/C][C]6294.39865433458[/C][C]199.521628760713[/C][/ROW]
[ROW][C]0.35[/C][C]6336.23364135805[/C][C]207.744632289845[/C][/ROW]
[ROW][C]0.36[/C][C]6379.37916003401[/C][C]215.53906037933[/C][/ROW]
[ROW][C]0.37[/C][C]6423.71468040991[/C][C]222.495820337203[/C][/ROW]
[ROW][C]0.38[/C][C]6469.06265197984[/C][C]228.258644599156[/C][/ROW]
[ROW][C]0.39[/C][C]6515.20536569849[/C][C]232.576097140029[/C][/ROW]
[ROW][C]0.4[/C][C]6561.91801944554[/C][C]235.470886229475[/C][/ROW]
[ROW][C]0.41[/C][C]6609.01334293898[/C][C]237.253132121509[/C][/ROW]
[ROW][C]0.42[/C][C]6656.38951276387[/C][C]238.534925731247[/C][/ROW]
[ROW][C]0.43[/C][C]6704.0712750323[/C][C]240.157883207343[/C][/ROW]
[ROW][C]0.44[/C][C]6752.2347471531[/C][C]243.111880030471[/C][/ROW]
[ROW][C]0.45[/C][C]6801.20922340915[/C][C]248.296953007728[/C][/ROW]
[ROW][C]0.46[/C][C]6851.45381411374[/C][C]256.408532690106[/C][/ROW]
[ROW][C]0.47[/C][C]6903.51187043906[/C][C]267.752885033593[/C][/ROW]
[ROW][C]0.48[/C][C]6957.95073857561[/C][C]282.209519688216[/C][/ROW]
[ROW][C]0.49[/C][C]7015.29746138207[/C][C]299.252667055235[/C][/ROW]
[ROW][C]0.5[/C][C]7075.9819857801[/C][C]318.074909505537[/C][/ROW]
[ROW][C]0.51[/C][C]7140.29809046238[/C][C]337.72390536006[/C][/ROW]
[ROW][C]0.52[/C][C]7208.38892555268[/C][C]357.287649102188[/C][/ROW]
[ROW][C]0.53[/C][C]7280.25941088151[/C][C]376.024000979432[/C][/ROW]
[ROW][C]0.54[/C][C]7355.81263569377[/C][C]393.507672878942[/C][/ROW]
[ROW][C]0.55[/C][C]7434.90275695338[/C][C]409.645839422712[/C][/ROW]
[ROW][C]0.56[/C][C]7517.39354410706[/C][C]424.686586314023[/C][/ROW]
[ROW][C]0.57[/C][C]7603.21031652718[/C][C]439.189615223769[/C][/ROW]
[ROW][C]0.58[/C][C]7692.37394035225[/C][C]453.821795041549[/C][/ROW]
[ROW][C]0.59[/C][C]7785.00881315178[/C][C]469.23469285038[/C][/ROW]
[ROW][C]0.6[/C][C]7881.32197029969[/C][C]485.859034320786[/C][/ROW]
[ROW][C]0.61[/C][C]7981.55676186426[/C][C]503.769268670109[/C][/ROW]
[ROW][C]0.62[/C][C]8085.93075742305[/C][C]522.598923733269[/C][/ROW]
[ROW][C]0.63[/C][C]8194.5722032997[/C][C]541.604488599699[/C][/ROW]
[ROW][C]0.64[/C][C]8307.47110540588[/C][C]559.773958129767[/C][/ROW]
[ROW][C]0.65[/C][C]8424.45888652143[/C][C]576.112968284202[/C][/ROW]
[ROW][C]0.66[/C][C]8545.22441273311[/C][C]589.75511354331[/C][/ROW]
[ROW][C]0.67[/C][C]8669.36491470376[/C][C]600.308507180594[/C][/ROW]
[ROW][C]0.68[/C][C]8796.45997265294[/C][C]607.855536157605[/C][/ROW]
[ROW][C]0.69[/C][C]8926.14812906247[/C][C]613.007420847473[/C][/ROW]
[ROW][C]0.7[/C][C]9058.18182087799[/C][C]616.662897404985[/C][/ROW]
[ROW][C]0.71[/C][C]9192.43936173003[/C][C]619.721961674113[/C][/ROW]
[ROW][C]0.72[/C][C]9328.88306937473[/C][C]622.775663132208[/C][/ROW]
[ROW][C]0.73[/C][C]9467.46836682446[/C][C]625.741061496222[/C][/ROW]
[ROW][C]0.74[/C][C]9608.02556876065[/C][C]627.802282284055[/C][/ROW]
[ROW][C]0.75[/C][C]9750.14863747061[/C][C]627.499719901136[/C][/ROW]
[ROW][C]0.76[/C][C]9893.12853019953[/C][C]623.101290852237[/C][/ROW]
[ROW][C]0.77[/C][C]10035.9604596773[/C][C]613.125233211544[/C][/ROW]
[ROW][C]0.78[/C][C]10177.4359389258[/C][C]596.753554537396[/C][/ROW]
[ROW][C]0.79[/C][C]10316.307210343[/C][C]574.125828381206[/C][/ROW]
[ROW][C]0.8[/C][C]10451.4909274372[/C][C]546.439279143766[/C][/ROW]
[ROW][C]0.81[/C][C]10582.266055979[/C][C]515.781565375946[/C][/ROW]
[ROW][C]0.82[/C][C]10708.4201474968[/C][C]484.700657896464[/C][/ROW]
[ROW][C]0.83[/C][C]10830.3057407446[/C][C]455.78329491942[/C][/ROW]
[ROW][C]0.84[/C][C]10948.7795512658[/C][C]431.142947974761[/C][/ROW]
[ROW][C]0.85[/C][C]11065.0088530146[/C][C]411.913556227451[/C][/ROW]
[ROW][C]0.86[/C][C]11180.1463990476[/C][C]397.82850227462[/C][/ROW]
[ROW][C]0.87[/C][C]11294.907054214[/C][C]386.835505026138[/C][/ROW]
[ROW][C]0.88[/C][C]11409.1319298243[/C][C]375.209415497933[/C][/ROW]
[ROW][C]0.89[/C][C]11521.4893227666[/C][C]358.311611487045[/C][/ROW]
[ROW][C]0.9[/C][C]11629.5055551606[/C][C]332.089594533373[/C][/ROW]
[ROW][C]0.91[/C][C]11730.1008491079[/C][C]294.885355498713[/C][/ROW]
[ROW][C]0.92[/C][C]11820.6908168958[/C][C]248.906410419931[/C][/ROW]
[ROW][C]0.93[/C][C]11900.689694105[/C][C]200.787613111931[/C][/ROW]
[ROW][C]0.94[/C][C]11972.9342256959[/C][C]161.060770156839[/C][/ROW]
[ROW][C]0.95[/C][C]12044.2166584506[/C][C]141.9300070345[/C][/ROW]
[ROW][C]0.96[/C][C]12123.9717478742[/C][C]148.412444448902[/C][/ROW]
[ROW][C]0.97[/C][C]12220.4060432368[/C][C]167.568319164941[/C][/ROW]
[ROW][C]0.98[/C][C]12333.6546251812[/C][C]175.865568582218[/C][/ROW]
[ROW][C]0.99[/C][C]12446.0538676396[/C][C]163.516758795141[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=179699&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=179699&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
0.014786.15753684049144.542600555561
0.024895.4538496257194.399597591791
0.035018.51705767067204.475078374254
0.045131.79747145952185.866877641195
0.055226.66091319351162.913003028598
0.065304.24778629927147.750026049002
0.075369.27329927793140.61137562497
0.085426.18245244716137.830631315206
0.095477.87285108347136.46213188228
0.15525.83176815417134.818823286898
0.115570.64963988161131.95899569087
0.125612.45454611226127.501754690377
0.135651.19781995011121.520567303388
0.145686.83559328303114.525551056625
0.155719.4416751535107.314373410349
0.165749.26344891901100.795760575303
0.175776.7258780146595.8523615796686
0.185802.3934324613193.1251272398868
0.195826.9058434518992.9380276706415
0.25850.9062730055195.1943856478126
0.215874.9786837647399.5125670869428
0.225899.60562321884105.374059424433
0.235925.15020028348112.292572624434
0.245951.85925421842119.842126918956
0.255979.88066244178127.736726167629
0.266009.28707206073135.755517114608
0.276040.10020906236143.766743404015
0.286072.31262256619151.677988287316
0.296105.90571827649159.487009238777
0.36140.86354986413167.263618815192
0.316177.18139430197175.077687688672
0.326214.86757900326183.053869076601
0.336253.93729660498191.225453943185
0.346294.39865433458199.521628760713
0.356336.23364135805207.744632289845
0.366379.37916003401215.53906037933
0.376423.71468040991222.495820337203
0.386469.06265197984228.258644599156
0.396515.20536569849232.576097140029
0.46561.91801944554235.470886229475
0.416609.01334293898237.253132121509
0.426656.38951276387238.534925731247
0.436704.0712750323240.157883207343
0.446752.2347471531243.111880030471
0.456801.20922340915248.296953007728
0.466851.45381411374256.408532690106
0.476903.51187043906267.752885033593
0.486957.95073857561282.209519688216
0.497015.29746138207299.252667055235
0.57075.9819857801318.074909505537
0.517140.29809046238337.72390536006
0.527208.38892555268357.287649102188
0.537280.25941088151376.024000979432
0.547355.81263569377393.507672878942
0.557434.90275695338409.645839422712
0.567517.39354410706424.686586314023
0.577603.21031652718439.189615223769
0.587692.37394035225453.821795041549
0.597785.00881315178469.23469285038
0.67881.32197029969485.859034320786
0.617981.55676186426503.769268670109
0.628085.93075742305522.598923733269
0.638194.5722032997541.604488599699
0.648307.47110540588559.773958129767
0.658424.45888652143576.112968284202
0.668545.22441273311589.75511354331
0.678669.36491470376600.308507180594
0.688796.45997265294607.855536157605
0.698926.14812906247613.007420847473
0.79058.18182087799616.662897404985
0.719192.43936173003619.721961674113
0.729328.88306937473622.775663132208
0.739467.46836682446625.741061496222
0.749608.02556876065627.802282284055
0.759750.14863747061627.499719901136
0.769893.12853019953623.101290852237
0.7710035.9604596773613.125233211544
0.7810177.4359389258596.753554537396
0.7910316.307210343574.125828381206
0.810451.4909274372546.439279143766
0.8110582.266055979515.781565375946
0.8210708.4201474968484.700657896464
0.8310830.3057407446455.78329491942
0.8410948.7795512658431.142947974761
0.8511065.0088530146411.913556227451
0.8611180.1463990476397.82850227462
0.8711294.907054214386.835505026138
0.8811409.1319298243375.209415497933
0.8911521.4893227666358.311611487045
0.911629.5055551606332.089594533373
0.9111730.1008491079294.885355498713
0.9211820.6908168958248.906410419931
0.9311900.689694105200.787613111931
0.9411972.9342256959161.060770156839
0.9512044.2166584506141.9300070345
0.9612123.9717478742148.412444448902
0.9712220.4060432368167.568319164941
0.9812333.6546251812175.865568582218
0.9912446.0538676396163.516758795141


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.01 ; par2 = 0.09 ; 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')