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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, 30 Sep 2013 08:57:26 -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/2013/Sep/30/t1380545857o8l92489scxj0fu.htm/, Retrieved Thu, 02 May 2024 13:08:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=212468, Retrieved Thu, 02 May 2024 13:08:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110

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] [] [2013-09-30 12:57:26] [0f9b748f6fe1dd88ddc67537cf760c5a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9244
7074
7044
6492
6362
8287
18177
10379
11130
9606
7294
7415
9230
7423
6927
7572
5877
8878
16706
9611
12714
10549
8421
9993
12384
9798
11738
9011
7673
10736
18316
10973
14027
10242
8547
8187
11101
8685
9790
8003
7412
9397
17774
11230
13321
9432
7653
7651
10762
8614
8748
7235
7735
8360
16202
11053
13593
9738
8226
7866
11606
9456
8471
7553
8259
9009
13968
12844
14388
12048
9167
7733

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=212468&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=212468&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=212468&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 time3 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.016020.29938781438409.68815594727
0.026228.42048925723348.268993625243
0.036435.90202124744327.755925514166
0.046617.43464992858319.960630095079
0.056770.95913728424300.028468648432
0.066899.73161549649268.945612552628
0.077007.14895995471237.187133113612
0.087096.78946834563211.753757759181
0.097172.432847804193.443790532359
0.17237.51699168472180.001141037698
0.117294.72986191113169.347728198703
0.127345.99506607141160.639820577179
0.137392.68846560072153.888715949739
0.147435.87122694175149.275462425687
0.157476.44201329884146.883298600007
0.167515.21224042828146.73991020303
0.177552.94124025392148.95998335952
0.187590.3561056651153.827593275166
0.197628.15944555526161.642155115859
0.27667.01742627111172.499208150516
0.217707.52337721073186.049498714959
0.227750.14258031839201.470743446344
0.237795.15362449547217.536876523744
0.247842.60558003181232.875314201341
0.257892.30689502982246.17604661677
0.267943.85320066352256.457131154816
0.277996.69061293179263.163028962522
0.288050.20214129204266.326055075493
0.298103.79987329898266.424711377352
0.38157.00552350681264.367452658373
0.318209.50602974037261.251957838995
0.328261.17744977756258.217289553623
0.338312.07741825383256.213651761911
0.348362.41212496065255.943279931537
0.358412.48713975026257.736227120333
0.368462.65223177257261.561465695415
0.378513.24908483249267.153052483371
0.388564.56833666786274.034344323331
0.398616.81954215346281.61435069589
0.48670.11514108049289.292425839166
0.418724.46764557868296.514052156166
0.428779.79810594102302.791293068304
0.438835.95333955273307.772244910623
0.448892.7292296521311.26326236873
0.458949.89746308771313.210803613493
0.469007.23328850129313.709878636273
0.479064.54219934745313.018910253037
0.489121.68385467813311.52913796158
0.499178.59199952131309.692574340172
0.59235.28955983948308.076253218462
0.519291.89837455692307.242957112731
0.529348.64312260313307.796984839748
0.539405.84890407602310.302855204432
0.549463.93172856637315.257705386135
0.559523.38102215664323.081635195419
0.569584.73340424798333.963744748995
0.579648.53759929548347.914689440943
0.589715.31152727448364.621150769293
0.599785.49428409105383.475472429521
0.69859.3976129497403.577125876262
0.619937.16315767228423.772066378899
0.6210018.7327914495442.808800882013
0.6310103.8392017398459.412495818077
0.6410192.0224390511472.469780672451
0.6510282.67532271481.256258937077
0.6610375.1167355632485.442157720153
0.6710468.6874492153485.304661928193
0.6810562.8588462542481.756105532196
0.6910657.341419137476.251176447791
0.710752.17785581470.784515119247
0.7110847.8054055069467.661032895401
0.7210945.074444512469.18703287746
0.7311045.2148815489477.351710490876
0.7411149.7490222811493.433973898466
0.7511260.3579828797517.713717293774
0.7611378.7173409277549.338187341694
0.7711506.3246426344586.533473638771
0.7811644.3448866572626.804636832705
0.7911793.4991955096667.376745505373
0.811954.0171829288705.51787308831
0.8112125.6676899033738.967571860322
0.8212307.8797012103766.140861832252
0.8312499.9686047431786.407531308675
0.8412701.4906975407800.451071715527
0.8512912.7494375209810.609369810501
0.8613135.4479112467821.575975739903
0.8713373.3982132857840.93042208376
0.8813633.0543573498878.923724713827
0.8913923.4755812932945.771859551156
0.914255.26154122921045.74862183398
0.9114638.16835571821170.543544022
0.9215077.5749805541296.69005113209
0.9315570.58562086831389.83150277755
0.9416103.00168267131414.37067043282
0.9516648.40865873511344.12506225775
0.9617170.27495853481169.5405551081
0.9717627.4899457881901.888087495842
0.9817982.9024837171580.908202014911
0.9918212.8591613583287.368892400776

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 6020.29938781438 & 409.68815594727 \tabularnewline
0.02 & 6228.42048925723 & 348.268993625243 \tabularnewline
0.03 & 6435.90202124744 & 327.755925514166 \tabularnewline
0.04 & 6617.43464992858 & 319.960630095079 \tabularnewline
0.05 & 6770.95913728424 & 300.028468648432 \tabularnewline
0.06 & 6899.73161549649 & 268.945612552628 \tabularnewline
0.07 & 7007.14895995471 & 237.187133113612 \tabularnewline
0.08 & 7096.78946834563 & 211.753757759181 \tabularnewline
0.09 & 7172.432847804 & 193.443790532359 \tabularnewline
0.1 & 7237.51699168472 & 180.001141037698 \tabularnewline
0.11 & 7294.72986191113 & 169.347728198703 \tabularnewline
0.12 & 7345.99506607141 & 160.639820577179 \tabularnewline
0.13 & 7392.68846560072 & 153.888715949739 \tabularnewline
0.14 & 7435.87122694175 & 149.275462425687 \tabularnewline
0.15 & 7476.44201329884 & 146.883298600007 \tabularnewline
0.16 & 7515.21224042828 & 146.73991020303 \tabularnewline
0.17 & 7552.94124025392 & 148.95998335952 \tabularnewline
0.18 & 7590.3561056651 & 153.827593275166 \tabularnewline
0.19 & 7628.15944555526 & 161.642155115859 \tabularnewline
0.2 & 7667.01742627111 & 172.499208150516 \tabularnewline
0.21 & 7707.52337721073 & 186.049498714959 \tabularnewline
0.22 & 7750.14258031839 & 201.470743446344 \tabularnewline
0.23 & 7795.15362449547 & 217.536876523744 \tabularnewline
0.24 & 7842.60558003181 & 232.875314201341 \tabularnewline
0.25 & 7892.30689502982 & 246.17604661677 \tabularnewline
0.26 & 7943.85320066352 & 256.457131154816 \tabularnewline
0.27 & 7996.69061293179 & 263.163028962522 \tabularnewline
0.28 & 8050.20214129204 & 266.326055075493 \tabularnewline
0.29 & 8103.79987329898 & 266.424711377352 \tabularnewline
0.3 & 8157.00552350681 & 264.367452658373 \tabularnewline
0.31 & 8209.50602974037 & 261.251957838995 \tabularnewline
0.32 & 8261.17744977756 & 258.217289553623 \tabularnewline
0.33 & 8312.07741825383 & 256.213651761911 \tabularnewline
0.34 & 8362.41212496065 & 255.943279931537 \tabularnewline
0.35 & 8412.48713975026 & 257.736227120333 \tabularnewline
0.36 & 8462.65223177257 & 261.561465695415 \tabularnewline
0.37 & 8513.24908483249 & 267.153052483371 \tabularnewline
0.38 & 8564.56833666786 & 274.034344323331 \tabularnewline
0.39 & 8616.81954215346 & 281.61435069589 \tabularnewline
0.4 & 8670.11514108049 & 289.292425839166 \tabularnewline
0.41 & 8724.46764557868 & 296.514052156166 \tabularnewline
0.42 & 8779.79810594102 & 302.791293068304 \tabularnewline
0.43 & 8835.95333955273 & 307.772244910623 \tabularnewline
0.44 & 8892.7292296521 & 311.26326236873 \tabularnewline
0.45 & 8949.89746308771 & 313.210803613493 \tabularnewline
0.46 & 9007.23328850129 & 313.709878636273 \tabularnewline
0.47 & 9064.54219934745 & 313.018910253037 \tabularnewline
0.48 & 9121.68385467813 & 311.52913796158 \tabularnewline
0.49 & 9178.59199952131 & 309.692574340172 \tabularnewline
0.5 & 9235.28955983948 & 308.076253218462 \tabularnewline
0.51 & 9291.89837455692 & 307.242957112731 \tabularnewline
0.52 & 9348.64312260313 & 307.796984839748 \tabularnewline
0.53 & 9405.84890407602 & 310.302855204432 \tabularnewline
0.54 & 9463.93172856637 & 315.257705386135 \tabularnewline
0.55 & 9523.38102215664 & 323.081635195419 \tabularnewline
0.56 & 9584.73340424798 & 333.963744748995 \tabularnewline
0.57 & 9648.53759929548 & 347.914689440943 \tabularnewline
0.58 & 9715.31152727448 & 364.621150769293 \tabularnewline
0.59 & 9785.49428409105 & 383.475472429521 \tabularnewline
0.6 & 9859.3976129497 & 403.577125876262 \tabularnewline
0.61 & 9937.16315767228 & 423.772066378899 \tabularnewline
0.62 & 10018.7327914495 & 442.808800882013 \tabularnewline
0.63 & 10103.8392017398 & 459.412495818077 \tabularnewline
0.64 & 10192.0224390511 & 472.469780672451 \tabularnewline
0.65 & 10282.67532271 & 481.256258937077 \tabularnewline
0.66 & 10375.1167355632 & 485.442157720153 \tabularnewline
0.67 & 10468.6874492153 & 485.304661928193 \tabularnewline
0.68 & 10562.8588462542 & 481.756105532196 \tabularnewline
0.69 & 10657.341419137 & 476.251176447791 \tabularnewline
0.7 & 10752.17785581 & 470.784515119247 \tabularnewline
0.71 & 10847.8054055069 & 467.661032895401 \tabularnewline
0.72 & 10945.074444512 & 469.18703287746 \tabularnewline
0.73 & 11045.2148815489 & 477.351710490876 \tabularnewline
0.74 & 11149.7490222811 & 493.433973898466 \tabularnewline
0.75 & 11260.3579828797 & 517.713717293774 \tabularnewline
0.76 & 11378.7173409277 & 549.338187341694 \tabularnewline
0.77 & 11506.3246426344 & 586.533473638771 \tabularnewline
0.78 & 11644.3448866572 & 626.804636832705 \tabularnewline
0.79 & 11793.4991955096 & 667.376745505373 \tabularnewline
0.8 & 11954.0171829288 & 705.51787308831 \tabularnewline
0.81 & 12125.6676899033 & 738.967571860322 \tabularnewline
0.82 & 12307.8797012103 & 766.140861832252 \tabularnewline
0.83 & 12499.9686047431 & 786.407531308675 \tabularnewline
0.84 & 12701.4906975407 & 800.451071715527 \tabularnewline
0.85 & 12912.7494375209 & 810.609369810501 \tabularnewline
0.86 & 13135.4479112467 & 821.575975739903 \tabularnewline
0.87 & 13373.3982132857 & 840.93042208376 \tabularnewline
0.88 & 13633.0543573498 & 878.923724713827 \tabularnewline
0.89 & 13923.4755812932 & 945.771859551156 \tabularnewline
0.9 & 14255.2615412292 & 1045.74862183398 \tabularnewline
0.91 & 14638.1683557182 & 1170.543544022 \tabularnewline
0.92 & 15077.574980554 & 1296.69005113209 \tabularnewline
0.93 & 15570.5856208683 & 1389.83150277755 \tabularnewline
0.94 & 16103.0016826713 & 1414.37067043282 \tabularnewline
0.95 & 16648.4086587351 & 1344.12506225775 \tabularnewline
0.96 & 17170.2749585348 & 1169.5405551081 \tabularnewline
0.97 & 17627.4899457881 & 901.888087495842 \tabularnewline
0.98 & 17982.9024837171 & 580.908202014911 \tabularnewline
0.99 & 18212.8591613583 & 287.368892400776 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=212468&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]6020.29938781438[/C][C]409.68815594727[/C][/ROW]
[ROW][C]0.02[/C][C]6228.42048925723[/C][C]348.268993625243[/C][/ROW]
[ROW][C]0.03[/C][C]6435.90202124744[/C][C]327.755925514166[/C][/ROW]
[ROW][C]0.04[/C][C]6617.43464992858[/C][C]319.960630095079[/C][/ROW]
[ROW][C]0.05[/C][C]6770.95913728424[/C][C]300.028468648432[/C][/ROW]
[ROW][C]0.06[/C][C]6899.73161549649[/C][C]268.945612552628[/C][/ROW]
[ROW][C]0.07[/C][C]7007.14895995471[/C][C]237.187133113612[/C][/ROW]
[ROW][C]0.08[/C][C]7096.78946834563[/C][C]211.753757759181[/C][/ROW]
[ROW][C]0.09[/C][C]7172.432847804[/C][C]193.443790532359[/C][/ROW]
[ROW][C]0.1[/C][C]7237.51699168472[/C][C]180.001141037698[/C][/ROW]
[ROW][C]0.11[/C][C]7294.72986191113[/C][C]169.347728198703[/C][/ROW]
[ROW][C]0.12[/C][C]7345.99506607141[/C][C]160.639820577179[/C][/ROW]
[ROW][C]0.13[/C][C]7392.68846560072[/C][C]153.888715949739[/C][/ROW]
[ROW][C]0.14[/C][C]7435.87122694175[/C][C]149.275462425687[/C][/ROW]
[ROW][C]0.15[/C][C]7476.44201329884[/C][C]146.883298600007[/C][/ROW]
[ROW][C]0.16[/C][C]7515.21224042828[/C][C]146.73991020303[/C][/ROW]
[ROW][C]0.17[/C][C]7552.94124025392[/C][C]148.95998335952[/C][/ROW]
[ROW][C]0.18[/C][C]7590.3561056651[/C][C]153.827593275166[/C][/ROW]
[ROW][C]0.19[/C][C]7628.15944555526[/C][C]161.642155115859[/C][/ROW]
[ROW][C]0.2[/C][C]7667.01742627111[/C][C]172.499208150516[/C][/ROW]
[ROW][C]0.21[/C][C]7707.52337721073[/C][C]186.049498714959[/C][/ROW]
[ROW][C]0.22[/C][C]7750.14258031839[/C][C]201.470743446344[/C][/ROW]
[ROW][C]0.23[/C][C]7795.15362449547[/C][C]217.536876523744[/C][/ROW]
[ROW][C]0.24[/C][C]7842.60558003181[/C][C]232.875314201341[/C][/ROW]
[ROW][C]0.25[/C][C]7892.30689502982[/C][C]246.17604661677[/C][/ROW]
[ROW][C]0.26[/C][C]7943.85320066352[/C][C]256.457131154816[/C][/ROW]
[ROW][C]0.27[/C][C]7996.69061293179[/C][C]263.163028962522[/C][/ROW]
[ROW][C]0.28[/C][C]8050.20214129204[/C][C]266.326055075493[/C][/ROW]
[ROW][C]0.29[/C][C]8103.79987329898[/C][C]266.424711377352[/C][/ROW]
[ROW][C]0.3[/C][C]8157.00552350681[/C][C]264.367452658373[/C][/ROW]
[ROW][C]0.31[/C][C]8209.50602974037[/C][C]261.251957838995[/C][/ROW]
[ROW][C]0.32[/C][C]8261.17744977756[/C][C]258.217289553623[/C][/ROW]
[ROW][C]0.33[/C][C]8312.07741825383[/C][C]256.213651761911[/C][/ROW]
[ROW][C]0.34[/C][C]8362.41212496065[/C][C]255.943279931537[/C][/ROW]
[ROW][C]0.35[/C][C]8412.48713975026[/C][C]257.736227120333[/C][/ROW]
[ROW][C]0.36[/C][C]8462.65223177257[/C][C]261.561465695415[/C][/ROW]
[ROW][C]0.37[/C][C]8513.24908483249[/C][C]267.153052483371[/C][/ROW]
[ROW][C]0.38[/C][C]8564.56833666786[/C][C]274.034344323331[/C][/ROW]
[ROW][C]0.39[/C][C]8616.81954215346[/C][C]281.61435069589[/C][/ROW]
[ROW][C]0.4[/C][C]8670.11514108049[/C][C]289.292425839166[/C][/ROW]
[ROW][C]0.41[/C][C]8724.46764557868[/C][C]296.514052156166[/C][/ROW]
[ROW][C]0.42[/C][C]8779.79810594102[/C][C]302.791293068304[/C][/ROW]
[ROW][C]0.43[/C][C]8835.95333955273[/C][C]307.772244910623[/C][/ROW]
[ROW][C]0.44[/C][C]8892.7292296521[/C][C]311.26326236873[/C][/ROW]
[ROW][C]0.45[/C][C]8949.89746308771[/C][C]313.210803613493[/C][/ROW]
[ROW][C]0.46[/C][C]9007.23328850129[/C][C]313.709878636273[/C][/ROW]
[ROW][C]0.47[/C][C]9064.54219934745[/C][C]313.018910253037[/C][/ROW]
[ROW][C]0.48[/C][C]9121.68385467813[/C][C]311.52913796158[/C][/ROW]
[ROW][C]0.49[/C][C]9178.59199952131[/C][C]309.692574340172[/C][/ROW]
[ROW][C]0.5[/C][C]9235.28955983948[/C][C]308.076253218462[/C][/ROW]
[ROW][C]0.51[/C][C]9291.89837455692[/C][C]307.242957112731[/C][/ROW]
[ROW][C]0.52[/C][C]9348.64312260313[/C][C]307.796984839748[/C][/ROW]
[ROW][C]0.53[/C][C]9405.84890407602[/C][C]310.302855204432[/C][/ROW]
[ROW][C]0.54[/C][C]9463.93172856637[/C][C]315.257705386135[/C][/ROW]
[ROW][C]0.55[/C][C]9523.38102215664[/C][C]323.081635195419[/C][/ROW]
[ROW][C]0.56[/C][C]9584.73340424798[/C][C]333.963744748995[/C][/ROW]
[ROW][C]0.57[/C][C]9648.53759929548[/C][C]347.914689440943[/C][/ROW]
[ROW][C]0.58[/C][C]9715.31152727448[/C][C]364.621150769293[/C][/ROW]
[ROW][C]0.59[/C][C]9785.49428409105[/C][C]383.475472429521[/C][/ROW]
[ROW][C]0.6[/C][C]9859.3976129497[/C][C]403.577125876262[/C][/ROW]
[ROW][C]0.61[/C][C]9937.16315767228[/C][C]423.772066378899[/C][/ROW]
[ROW][C]0.62[/C][C]10018.7327914495[/C][C]442.808800882013[/C][/ROW]
[ROW][C]0.63[/C][C]10103.8392017398[/C][C]459.412495818077[/C][/ROW]
[ROW][C]0.64[/C][C]10192.0224390511[/C][C]472.469780672451[/C][/ROW]
[ROW][C]0.65[/C][C]10282.67532271[/C][C]481.256258937077[/C][/ROW]
[ROW][C]0.66[/C][C]10375.1167355632[/C][C]485.442157720153[/C][/ROW]
[ROW][C]0.67[/C][C]10468.6874492153[/C][C]485.304661928193[/C][/ROW]
[ROW][C]0.68[/C][C]10562.8588462542[/C][C]481.756105532196[/C][/ROW]
[ROW][C]0.69[/C][C]10657.341419137[/C][C]476.251176447791[/C][/ROW]
[ROW][C]0.7[/C][C]10752.17785581[/C][C]470.784515119247[/C][/ROW]
[ROW][C]0.71[/C][C]10847.8054055069[/C][C]467.661032895401[/C][/ROW]
[ROW][C]0.72[/C][C]10945.074444512[/C][C]469.18703287746[/C][/ROW]
[ROW][C]0.73[/C][C]11045.2148815489[/C][C]477.351710490876[/C][/ROW]
[ROW][C]0.74[/C][C]11149.7490222811[/C][C]493.433973898466[/C][/ROW]
[ROW][C]0.75[/C][C]11260.3579828797[/C][C]517.713717293774[/C][/ROW]
[ROW][C]0.76[/C][C]11378.7173409277[/C][C]549.338187341694[/C][/ROW]
[ROW][C]0.77[/C][C]11506.3246426344[/C][C]586.533473638771[/C][/ROW]
[ROW][C]0.78[/C][C]11644.3448866572[/C][C]626.804636832705[/C][/ROW]
[ROW][C]0.79[/C][C]11793.4991955096[/C][C]667.376745505373[/C][/ROW]
[ROW][C]0.8[/C][C]11954.0171829288[/C][C]705.51787308831[/C][/ROW]
[ROW][C]0.81[/C][C]12125.6676899033[/C][C]738.967571860322[/C][/ROW]
[ROW][C]0.82[/C][C]12307.8797012103[/C][C]766.140861832252[/C][/ROW]
[ROW][C]0.83[/C][C]12499.9686047431[/C][C]786.407531308675[/C][/ROW]
[ROW][C]0.84[/C][C]12701.4906975407[/C][C]800.451071715527[/C][/ROW]
[ROW][C]0.85[/C][C]12912.7494375209[/C][C]810.609369810501[/C][/ROW]
[ROW][C]0.86[/C][C]13135.4479112467[/C][C]821.575975739903[/C][/ROW]
[ROW][C]0.87[/C][C]13373.3982132857[/C][C]840.93042208376[/C][/ROW]
[ROW][C]0.88[/C][C]13633.0543573498[/C][C]878.923724713827[/C][/ROW]
[ROW][C]0.89[/C][C]13923.4755812932[/C][C]945.771859551156[/C][/ROW]
[ROW][C]0.9[/C][C]14255.2615412292[/C][C]1045.74862183398[/C][/ROW]
[ROW][C]0.91[/C][C]14638.1683557182[/C][C]1170.543544022[/C][/ROW]
[ROW][C]0.92[/C][C]15077.574980554[/C][C]1296.69005113209[/C][/ROW]
[ROW][C]0.93[/C][C]15570.5856208683[/C][C]1389.83150277755[/C][/ROW]
[ROW][C]0.94[/C][C]16103.0016826713[/C][C]1414.37067043282[/C][/ROW]
[ROW][C]0.95[/C][C]16648.4086587351[/C][C]1344.12506225775[/C][/ROW]
[ROW][C]0.96[/C][C]17170.2749585348[/C][C]1169.5405551081[/C][/ROW]
[ROW][C]0.97[/C][C]17627.4899457881[/C][C]901.888087495842[/C][/ROW]
[ROW][C]0.98[/C][C]17982.9024837171[/C][C]580.908202014911[/C][/ROW]
[ROW][C]0.99[/C][C]18212.8591613583[/C][C]287.368892400776[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=212468&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=212468&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
0.016020.29938781438409.68815594727
0.026228.42048925723348.268993625243
0.036435.90202124744327.755925514166
0.046617.43464992858319.960630095079
0.056770.95913728424300.028468648432
0.066899.73161549649268.945612552628
0.077007.14895995471237.187133113612
0.087096.78946834563211.753757759181
0.097172.432847804193.443790532359
0.17237.51699168472180.001141037698
0.117294.72986191113169.347728198703
0.127345.99506607141160.639820577179
0.137392.68846560072153.888715949739
0.147435.87122694175149.275462425687
0.157476.44201329884146.883298600007
0.167515.21224042828146.73991020303
0.177552.94124025392148.95998335952
0.187590.3561056651153.827593275166
0.197628.15944555526161.642155115859
0.27667.01742627111172.499208150516
0.217707.52337721073186.049498714959
0.227750.14258031839201.470743446344
0.237795.15362449547217.536876523744
0.247842.60558003181232.875314201341
0.257892.30689502982246.17604661677
0.267943.85320066352256.457131154816
0.277996.69061293179263.163028962522
0.288050.20214129204266.326055075493
0.298103.79987329898266.424711377352
0.38157.00552350681264.367452658373
0.318209.50602974037261.251957838995
0.328261.17744977756258.217289553623
0.338312.07741825383256.213651761911
0.348362.41212496065255.943279931537
0.358412.48713975026257.736227120333
0.368462.65223177257261.561465695415
0.378513.24908483249267.153052483371
0.388564.56833666786274.034344323331
0.398616.81954215346281.61435069589
0.48670.11514108049289.292425839166
0.418724.46764557868296.514052156166
0.428779.79810594102302.791293068304
0.438835.95333955273307.772244910623
0.448892.7292296521311.26326236873
0.458949.89746308771313.210803613493
0.469007.23328850129313.709878636273
0.479064.54219934745313.018910253037
0.489121.68385467813311.52913796158
0.499178.59199952131309.692574340172
0.59235.28955983948308.076253218462
0.519291.89837455692307.242957112731
0.529348.64312260313307.796984839748
0.539405.84890407602310.302855204432
0.549463.93172856637315.257705386135
0.559523.38102215664323.081635195419
0.569584.73340424798333.963744748995
0.579648.53759929548347.914689440943
0.589715.31152727448364.621150769293
0.599785.49428409105383.475472429521
0.69859.3976129497403.577125876262
0.619937.16315767228423.772066378899
0.6210018.7327914495442.808800882013
0.6310103.8392017398459.412495818077
0.6410192.0224390511472.469780672451
0.6510282.67532271481.256258937077
0.6610375.1167355632485.442157720153
0.6710468.6874492153485.304661928193
0.6810562.8588462542481.756105532196
0.6910657.341419137476.251176447791
0.710752.17785581470.784515119247
0.7110847.8054055069467.661032895401
0.7210945.074444512469.18703287746
0.7311045.2148815489477.351710490876
0.7411149.7490222811493.433973898466
0.7511260.3579828797517.713717293774
0.7611378.7173409277549.338187341694
0.7711506.3246426344586.533473638771
0.7811644.3448866572626.804636832705
0.7911793.4991955096667.376745505373
0.811954.0171829288705.51787308831
0.8112125.6676899033738.967571860322
0.8212307.8797012103766.140861832252
0.8312499.9686047431786.407531308675
0.8412701.4906975407800.451071715527
0.8512912.7494375209810.609369810501
0.8613135.4479112467821.575975739903
0.8713373.3982132857840.93042208376
0.8813633.0543573498878.923724713827
0.8913923.4755812932945.771859551156
0.914255.26154122921045.74862183398
0.9114638.16835571821170.543544022
0.9215077.5749805541296.69005113209
0.9315570.58562086831389.83150277755
0.9416103.00168267131414.37067043282
0.9516648.40865873511344.12506225775
0.9617170.27495853481169.5405551081
0.9717627.4899457881901.888087495842
0.9817982.9024837171580.908202014911
0.9918212.8591613583287.368892400776


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):
par3 <- '0.1'
par2 <- '0.9'
par1 <- '0.1'
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')