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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 computationSat, 05 Oct 2013 11:05:52 -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/Oct/05/t138098564235aelxakrs7sn3r.htm/, Retrieved Thu, 02 May 2024 19:42:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=213321, Retrieved Thu, 02 May 2024 19:42:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116

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] [] [2013-10-05 15:05:52] [6db2c0c963bf82ed406b79886f98dcae] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4309
4303
4177
4117
4065
3983
4091
4067
4024
3868
3800
3804
3862
3792
3674
3560
3489
3412
3674
3672
3463
3429
3400
3533
3578
3544
3435
3352
3213
3235
3460
3385
3283
3295
3331
3520
3668
3714
3691
3604
3581
3675
3833
3810
3663
3704
3810
4053
4152
4139
4055
3928
3821
3811
3999
3954
3724
3731
3697
3818
3897
3888
3754
3647
3564
3498
3704
3678
3599
3507
3484
2612
2926
2918
2833
2791
2762
2728
2831
2839
2775
2540
2625
2669

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'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=213321&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=213321&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=213321&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'Sir Maurice George Kendall' @ kendall.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.012565.3317696004557.4590780731621
0.022600.9089689003248.9547243364587
0.032635.5517863731953.1961163107263
0.042667.6667143329960.1142205410064
0.052698.0516633187363.1869029175173
0.062726.7474916092562.9688204125806
0.072753.683003121963.0368801137961
0.082779.5165347552567.0785624506433
0.092805.6726502537677.2884990480141
0.12833.9158373888493.8179145231376
0.112865.84814131886115.09008219108
0.122902.50225705835138.319874903601
0.132944.09091915951160.092234370376
0.142989.94474894643177.104571573492
0.153038.64632090384186.918270177585
0.163088.32285576075188.493014477438
0.173137.01384015399182.304160962314
0.183183.01163798429170.022514095792
0.193225.09323255872153.965252168902
0.23262.60747175162136.477443029078
0.213295.43139437859119.487571145201
0.223323.84190126597104.243912567759
0.233348.3577925086591.3381230965387
0.243369.5964030914280.8381397731421
0.253388.1691167908872.5074029997352
0.263404.6208875453765.9815023751516
0.273419.4063013244560.8941376039064
0.283432.8897260303756.9385077228668
0.293445.357728189153.872546560522
0.33457.0352702208751.5237120389384
0.313468.100900325449.7550512843468
0.323478.6989767126348.48012472557
0.333488.9486422256647.6312388399989
0.343498.950008503747.1481234154155
0.353508.7881768433846.9957711673058
0.363518.5356076383247.1211043825582
0.373528.2531410905247.4822187239056
0.383537.9897900914448.0271255114729
0.393547.7813578590148.7024428858777
0.43557.6480299420349.4249575235875
0.413567.5913484681750.1032949575975
0.423577.5913191617650.6197280860484
0.433587.6046904505850.8416168595339
0.443597.5655239316450.6328865748887
0.453607.3889377996649.906904160517
0.463616.9783412837848.5983198879129
0.473626.2357007688746.7183501890607
0.483635.0735925570544.3458258830294
0.493643.4272353425541.6327741746193
0.53651.2645344604138.7764073401814
0.513658.5924665001536.0122154359355
0.523665.4588010493733.5753351199913
0.533671.9489981567331.6830375169675
0.543678.1788974834930.4937718588566
0.553684.2843356279930.0954912932816
0.563690.4090111502530.5070343604979
0.573696.6918142844731.6390827215834
0.583703.2546017559833.3673094219741
0.593710.1912044518435.4953498728022
0.63717.5584270149837.8024865744178
0.613725.3699356040740.0493607944958
0.623733.5941069984541.9890277163149
0.633742.1569234810943.4071120722371
0.643750.9506499498944.1467035724626
0.653759.8482400819144.1246519748981
0.663768.7222817542643.3823749425525
0.673777.4660806210542.0579689876607
0.683786.0135713096140.4008099249994
0.693794.3544916773138.7350141147052
0.73802.5418501936837.4159264428108
0.713810.6900975601936.7754746977797
0.723818.9642519701437.0479887561257
0.733827.5620132467338.328768976323
0.743836.6921080072940.5678892732726
0.753846.5523815369443.6023441357592
0.763857.3104542242847.1944202972456
0.773869.0884066773651.0817644271605
0.783881.9515172488754.9872840929642
0.793895.9001614307658.6292291695435
0.83910.8640109701761.7239343491379
0.813926.6986951986963.9903233944277
0.823943.1867690627765.1567849985584
0.833960.0465260243765.0122172117918
0.843976.9530571658263.4447516120361
0.853993.5750321022760.4889203875749
0.864009.6270491452956.3805950707234
0.874024.9307260130851.5803258468768
0.884039.4692932737446.7541804267124
0.894053.4146437227742.6557985328093
0.94067.1104063281439.9094821162286
0.914081.0185921962238.7200231635721
0.924095.682814915438.7801943904098
0.934111.8061316573939.7040440260393
0.944130.5136059810741.9469319461799
0.954153.6392046206947.5442599050333
0.964183.3875291981258.3763131295208
0.974220.4090282926970.1558204838015
0.984260.4741134264268.5355843626298
0.994293.309048895540.747488957567

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 2565.33176960045 & 57.4590780731621 \tabularnewline
0.02 & 2600.90896890032 & 48.9547243364587 \tabularnewline
0.03 & 2635.55178637319 & 53.1961163107263 \tabularnewline
0.04 & 2667.66671433299 & 60.1142205410064 \tabularnewline
0.05 & 2698.05166331873 & 63.1869029175173 \tabularnewline
0.06 & 2726.74749160925 & 62.9688204125806 \tabularnewline
0.07 & 2753.6830031219 & 63.0368801137961 \tabularnewline
0.08 & 2779.51653475525 & 67.0785624506433 \tabularnewline
0.09 & 2805.67265025376 & 77.2884990480141 \tabularnewline
0.1 & 2833.91583738884 & 93.8179145231376 \tabularnewline
0.11 & 2865.84814131886 & 115.09008219108 \tabularnewline
0.12 & 2902.50225705835 & 138.319874903601 \tabularnewline
0.13 & 2944.09091915951 & 160.092234370376 \tabularnewline
0.14 & 2989.94474894643 & 177.104571573492 \tabularnewline
0.15 & 3038.64632090384 & 186.918270177585 \tabularnewline
0.16 & 3088.32285576075 & 188.493014477438 \tabularnewline
0.17 & 3137.01384015399 & 182.304160962314 \tabularnewline
0.18 & 3183.01163798429 & 170.022514095792 \tabularnewline
0.19 & 3225.09323255872 & 153.965252168902 \tabularnewline
0.2 & 3262.60747175162 & 136.477443029078 \tabularnewline
0.21 & 3295.43139437859 & 119.487571145201 \tabularnewline
0.22 & 3323.84190126597 & 104.243912567759 \tabularnewline
0.23 & 3348.35779250865 & 91.3381230965387 \tabularnewline
0.24 & 3369.59640309142 & 80.8381397731421 \tabularnewline
0.25 & 3388.16911679088 & 72.5074029997352 \tabularnewline
0.26 & 3404.62088754537 & 65.9815023751516 \tabularnewline
0.27 & 3419.40630132445 & 60.8941376039064 \tabularnewline
0.28 & 3432.88972603037 & 56.9385077228668 \tabularnewline
0.29 & 3445.3577281891 & 53.872546560522 \tabularnewline
0.3 & 3457.03527022087 & 51.5237120389384 \tabularnewline
0.31 & 3468.1009003254 & 49.7550512843468 \tabularnewline
0.32 & 3478.69897671263 & 48.48012472557 \tabularnewline
0.33 & 3488.94864222566 & 47.6312388399989 \tabularnewline
0.34 & 3498.9500085037 & 47.1481234154155 \tabularnewline
0.35 & 3508.78817684338 & 46.9957711673058 \tabularnewline
0.36 & 3518.53560763832 & 47.1211043825582 \tabularnewline
0.37 & 3528.25314109052 & 47.4822187239056 \tabularnewline
0.38 & 3537.98979009144 & 48.0271255114729 \tabularnewline
0.39 & 3547.78135785901 & 48.7024428858777 \tabularnewline
0.4 & 3557.64802994203 & 49.4249575235875 \tabularnewline
0.41 & 3567.59134846817 & 50.1032949575975 \tabularnewline
0.42 & 3577.59131916176 & 50.6197280860484 \tabularnewline
0.43 & 3587.60469045058 & 50.8416168595339 \tabularnewline
0.44 & 3597.56552393164 & 50.6328865748887 \tabularnewline
0.45 & 3607.38893779966 & 49.906904160517 \tabularnewline
0.46 & 3616.97834128378 & 48.5983198879129 \tabularnewline
0.47 & 3626.23570076887 & 46.7183501890607 \tabularnewline
0.48 & 3635.07359255705 & 44.3458258830294 \tabularnewline
0.49 & 3643.42723534255 & 41.6327741746193 \tabularnewline
0.5 & 3651.26453446041 & 38.7764073401814 \tabularnewline
0.51 & 3658.59246650015 & 36.0122154359355 \tabularnewline
0.52 & 3665.45880104937 & 33.5753351199913 \tabularnewline
0.53 & 3671.94899815673 & 31.6830375169675 \tabularnewline
0.54 & 3678.17889748349 & 30.4937718588566 \tabularnewline
0.55 & 3684.28433562799 & 30.0954912932816 \tabularnewline
0.56 & 3690.40901115025 & 30.5070343604979 \tabularnewline
0.57 & 3696.69181428447 & 31.6390827215834 \tabularnewline
0.58 & 3703.25460175598 & 33.3673094219741 \tabularnewline
0.59 & 3710.19120445184 & 35.4953498728022 \tabularnewline
0.6 & 3717.55842701498 & 37.8024865744178 \tabularnewline
0.61 & 3725.36993560407 & 40.0493607944958 \tabularnewline
0.62 & 3733.59410699845 & 41.9890277163149 \tabularnewline
0.63 & 3742.15692348109 & 43.4071120722371 \tabularnewline
0.64 & 3750.95064994989 & 44.1467035724626 \tabularnewline
0.65 & 3759.84824008191 & 44.1246519748981 \tabularnewline
0.66 & 3768.72228175426 & 43.3823749425525 \tabularnewline
0.67 & 3777.46608062105 & 42.0579689876607 \tabularnewline
0.68 & 3786.01357130961 & 40.4008099249994 \tabularnewline
0.69 & 3794.35449167731 & 38.7350141147052 \tabularnewline
0.7 & 3802.54185019368 & 37.4159264428108 \tabularnewline
0.71 & 3810.69009756019 & 36.7754746977797 \tabularnewline
0.72 & 3818.96425197014 & 37.0479887561257 \tabularnewline
0.73 & 3827.56201324673 & 38.328768976323 \tabularnewline
0.74 & 3836.69210800729 & 40.5678892732726 \tabularnewline
0.75 & 3846.55238153694 & 43.6023441357592 \tabularnewline
0.76 & 3857.31045422428 & 47.1944202972456 \tabularnewline
0.77 & 3869.08840667736 & 51.0817644271605 \tabularnewline
0.78 & 3881.95151724887 & 54.9872840929642 \tabularnewline
0.79 & 3895.90016143076 & 58.6292291695435 \tabularnewline
0.8 & 3910.86401097017 & 61.7239343491379 \tabularnewline
0.81 & 3926.69869519869 & 63.9903233944277 \tabularnewline
0.82 & 3943.18676906277 & 65.1567849985584 \tabularnewline
0.83 & 3960.04652602437 & 65.0122172117918 \tabularnewline
0.84 & 3976.95305716582 & 63.4447516120361 \tabularnewline
0.85 & 3993.57503210227 & 60.4889203875749 \tabularnewline
0.86 & 4009.62704914529 & 56.3805950707234 \tabularnewline
0.87 & 4024.93072601308 & 51.5803258468768 \tabularnewline
0.88 & 4039.46929327374 & 46.7541804267124 \tabularnewline
0.89 & 4053.41464372277 & 42.6557985328093 \tabularnewline
0.9 & 4067.11040632814 & 39.9094821162286 \tabularnewline
0.91 & 4081.01859219622 & 38.7200231635721 \tabularnewline
0.92 & 4095.6828149154 & 38.7801943904098 \tabularnewline
0.93 & 4111.80613165739 & 39.7040440260393 \tabularnewline
0.94 & 4130.51360598107 & 41.9469319461799 \tabularnewline
0.95 & 4153.63920462069 & 47.5442599050333 \tabularnewline
0.96 & 4183.38752919812 & 58.3763131295208 \tabularnewline
0.97 & 4220.40902829269 & 70.1558204838015 \tabularnewline
0.98 & 4260.47411342642 & 68.5355843626298 \tabularnewline
0.99 & 4293.3090488955 & 40.747488957567 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=213321&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]2565.33176960045[/C][C]57.4590780731621[/C][/ROW]
[ROW][C]0.02[/C][C]2600.90896890032[/C][C]48.9547243364587[/C][/ROW]
[ROW][C]0.03[/C][C]2635.55178637319[/C][C]53.1961163107263[/C][/ROW]
[ROW][C]0.04[/C][C]2667.66671433299[/C][C]60.1142205410064[/C][/ROW]
[ROW][C]0.05[/C][C]2698.05166331873[/C][C]63.1869029175173[/C][/ROW]
[ROW][C]0.06[/C][C]2726.74749160925[/C][C]62.9688204125806[/C][/ROW]
[ROW][C]0.07[/C][C]2753.6830031219[/C][C]63.0368801137961[/C][/ROW]
[ROW][C]0.08[/C][C]2779.51653475525[/C][C]67.0785624506433[/C][/ROW]
[ROW][C]0.09[/C][C]2805.67265025376[/C][C]77.2884990480141[/C][/ROW]
[ROW][C]0.1[/C][C]2833.91583738884[/C][C]93.8179145231376[/C][/ROW]
[ROW][C]0.11[/C][C]2865.84814131886[/C][C]115.09008219108[/C][/ROW]
[ROW][C]0.12[/C][C]2902.50225705835[/C][C]138.319874903601[/C][/ROW]
[ROW][C]0.13[/C][C]2944.09091915951[/C][C]160.092234370376[/C][/ROW]
[ROW][C]0.14[/C][C]2989.94474894643[/C][C]177.104571573492[/C][/ROW]
[ROW][C]0.15[/C][C]3038.64632090384[/C][C]186.918270177585[/C][/ROW]
[ROW][C]0.16[/C][C]3088.32285576075[/C][C]188.493014477438[/C][/ROW]
[ROW][C]0.17[/C][C]3137.01384015399[/C][C]182.304160962314[/C][/ROW]
[ROW][C]0.18[/C][C]3183.01163798429[/C][C]170.022514095792[/C][/ROW]
[ROW][C]0.19[/C][C]3225.09323255872[/C][C]153.965252168902[/C][/ROW]
[ROW][C]0.2[/C][C]3262.60747175162[/C][C]136.477443029078[/C][/ROW]
[ROW][C]0.21[/C][C]3295.43139437859[/C][C]119.487571145201[/C][/ROW]
[ROW][C]0.22[/C][C]3323.84190126597[/C][C]104.243912567759[/C][/ROW]
[ROW][C]0.23[/C][C]3348.35779250865[/C][C]91.3381230965387[/C][/ROW]
[ROW][C]0.24[/C][C]3369.59640309142[/C][C]80.8381397731421[/C][/ROW]
[ROW][C]0.25[/C][C]3388.16911679088[/C][C]72.5074029997352[/C][/ROW]
[ROW][C]0.26[/C][C]3404.62088754537[/C][C]65.9815023751516[/C][/ROW]
[ROW][C]0.27[/C][C]3419.40630132445[/C][C]60.8941376039064[/C][/ROW]
[ROW][C]0.28[/C][C]3432.88972603037[/C][C]56.9385077228668[/C][/ROW]
[ROW][C]0.29[/C][C]3445.3577281891[/C][C]53.872546560522[/C][/ROW]
[ROW][C]0.3[/C][C]3457.03527022087[/C][C]51.5237120389384[/C][/ROW]
[ROW][C]0.31[/C][C]3468.1009003254[/C][C]49.7550512843468[/C][/ROW]
[ROW][C]0.32[/C][C]3478.69897671263[/C][C]48.48012472557[/C][/ROW]
[ROW][C]0.33[/C][C]3488.94864222566[/C][C]47.6312388399989[/C][/ROW]
[ROW][C]0.34[/C][C]3498.9500085037[/C][C]47.1481234154155[/C][/ROW]
[ROW][C]0.35[/C][C]3508.78817684338[/C][C]46.9957711673058[/C][/ROW]
[ROW][C]0.36[/C][C]3518.53560763832[/C][C]47.1211043825582[/C][/ROW]
[ROW][C]0.37[/C][C]3528.25314109052[/C][C]47.4822187239056[/C][/ROW]
[ROW][C]0.38[/C][C]3537.98979009144[/C][C]48.0271255114729[/C][/ROW]
[ROW][C]0.39[/C][C]3547.78135785901[/C][C]48.7024428858777[/C][/ROW]
[ROW][C]0.4[/C][C]3557.64802994203[/C][C]49.4249575235875[/C][/ROW]
[ROW][C]0.41[/C][C]3567.59134846817[/C][C]50.1032949575975[/C][/ROW]
[ROW][C]0.42[/C][C]3577.59131916176[/C][C]50.6197280860484[/C][/ROW]
[ROW][C]0.43[/C][C]3587.60469045058[/C][C]50.8416168595339[/C][/ROW]
[ROW][C]0.44[/C][C]3597.56552393164[/C][C]50.6328865748887[/C][/ROW]
[ROW][C]0.45[/C][C]3607.38893779966[/C][C]49.906904160517[/C][/ROW]
[ROW][C]0.46[/C][C]3616.97834128378[/C][C]48.5983198879129[/C][/ROW]
[ROW][C]0.47[/C][C]3626.23570076887[/C][C]46.7183501890607[/C][/ROW]
[ROW][C]0.48[/C][C]3635.07359255705[/C][C]44.3458258830294[/C][/ROW]
[ROW][C]0.49[/C][C]3643.42723534255[/C][C]41.6327741746193[/C][/ROW]
[ROW][C]0.5[/C][C]3651.26453446041[/C][C]38.7764073401814[/C][/ROW]
[ROW][C]0.51[/C][C]3658.59246650015[/C][C]36.0122154359355[/C][/ROW]
[ROW][C]0.52[/C][C]3665.45880104937[/C][C]33.5753351199913[/C][/ROW]
[ROW][C]0.53[/C][C]3671.94899815673[/C][C]31.6830375169675[/C][/ROW]
[ROW][C]0.54[/C][C]3678.17889748349[/C][C]30.4937718588566[/C][/ROW]
[ROW][C]0.55[/C][C]3684.28433562799[/C][C]30.0954912932816[/C][/ROW]
[ROW][C]0.56[/C][C]3690.40901115025[/C][C]30.5070343604979[/C][/ROW]
[ROW][C]0.57[/C][C]3696.69181428447[/C][C]31.6390827215834[/C][/ROW]
[ROW][C]0.58[/C][C]3703.25460175598[/C][C]33.3673094219741[/C][/ROW]
[ROW][C]0.59[/C][C]3710.19120445184[/C][C]35.4953498728022[/C][/ROW]
[ROW][C]0.6[/C][C]3717.55842701498[/C][C]37.8024865744178[/C][/ROW]
[ROW][C]0.61[/C][C]3725.36993560407[/C][C]40.0493607944958[/C][/ROW]
[ROW][C]0.62[/C][C]3733.59410699845[/C][C]41.9890277163149[/C][/ROW]
[ROW][C]0.63[/C][C]3742.15692348109[/C][C]43.4071120722371[/C][/ROW]
[ROW][C]0.64[/C][C]3750.95064994989[/C][C]44.1467035724626[/C][/ROW]
[ROW][C]0.65[/C][C]3759.84824008191[/C][C]44.1246519748981[/C][/ROW]
[ROW][C]0.66[/C][C]3768.72228175426[/C][C]43.3823749425525[/C][/ROW]
[ROW][C]0.67[/C][C]3777.46608062105[/C][C]42.0579689876607[/C][/ROW]
[ROW][C]0.68[/C][C]3786.01357130961[/C][C]40.4008099249994[/C][/ROW]
[ROW][C]0.69[/C][C]3794.35449167731[/C][C]38.7350141147052[/C][/ROW]
[ROW][C]0.7[/C][C]3802.54185019368[/C][C]37.4159264428108[/C][/ROW]
[ROW][C]0.71[/C][C]3810.69009756019[/C][C]36.7754746977797[/C][/ROW]
[ROW][C]0.72[/C][C]3818.96425197014[/C][C]37.0479887561257[/C][/ROW]
[ROW][C]0.73[/C][C]3827.56201324673[/C][C]38.328768976323[/C][/ROW]
[ROW][C]0.74[/C][C]3836.69210800729[/C][C]40.5678892732726[/C][/ROW]
[ROW][C]0.75[/C][C]3846.55238153694[/C][C]43.6023441357592[/C][/ROW]
[ROW][C]0.76[/C][C]3857.31045422428[/C][C]47.1944202972456[/C][/ROW]
[ROW][C]0.77[/C][C]3869.08840667736[/C][C]51.0817644271605[/C][/ROW]
[ROW][C]0.78[/C][C]3881.95151724887[/C][C]54.9872840929642[/C][/ROW]
[ROW][C]0.79[/C][C]3895.90016143076[/C][C]58.6292291695435[/C][/ROW]
[ROW][C]0.8[/C][C]3910.86401097017[/C][C]61.7239343491379[/C][/ROW]
[ROW][C]0.81[/C][C]3926.69869519869[/C][C]63.9903233944277[/C][/ROW]
[ROW][C]0.82[/C][C]3943.18676906277[/C][C]65.1567849985584[/C][/ROW]
[ROW][C]0.83[/C][C]3960.04652602437[/C][C]65.0122172117918[/C][/ROW]
[ROW][C]0.84[/C][C]3976.95305716582[/C][C]63.4447516120361[/C][/ROW]
[ROW][C]0.85[/C][C]3993.57503210227[/C][C]60.4889203875749[/C][/ROW]
[ROW][C]0.86[/C][C]4009.62704914529[/C][C]56.3805950707234[/C][/ROW]
[ROW][C]0.87[/C][C]4024.93072601308[/C][C]51.5803258468768[/C][/ROW]
[ROW][C]0.88[/C][C]4039.46929327374[/C][C]46.7541804267124[/C][/ROW]
[ROW][C]0.89[/C][C]4053.41464372277[/C][C]42.6557985328093[/C][/ROW]
[ROW][C]0.9[/C][C]4067.11040632814[/C][C]39.9094821162286[/C][/ROW]
[ROW][C]0.91[/C][C]4081.01859219622[/C][C]38.7200231635721[/C][/ROW]
[ROW][C]0.92[/C][C]4095.6828149154[/C][C]38.7801943904098[/C][/ROW]
[ROW][C]0.93[/C][C]4111.80613165739[/C][C]39.7040440260393[/C][/ROW]
[ROW][C]0.94[/C][C]4130.51360598107[/C][C]41.9469319461799[/C][/ROW]
[ROW][C]0.95[/C][C]4153.63920462069[/C][C]47.5442599050333[/C][/ROW]
[ROW][C]0.96[/C][C]4183.38752919812[/C][C]58.3763131295208[/C][/ROW]
[ROW][C]0.97[/C][C]4220.40902829269[/C][C]70.1558204838015[/C][/ROW]
[ROW][C]0.98[/C][C]4260.47411342642[/C][C]68.5355843626298[/C][/ROW]
[ROW][C]0.99[/C][C]4293.3090488955[/C][C]40.747488957567[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=213321&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=213321&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
0.012565.3317696004557.4590780731621
0.022600.9089689003248.9547243364587
0.032635.5517863731953.1961163107263
0.042667.6667143329960.1142205410064
0.052698.0516633187363.1869029175173
0.062726.7474916092562.9688204125806
0.072753.683003121963.0368801137961
0.082779.5165347552567.0785624506433
0.092805.6726502537677.2884990480141
0.12833.9158373888493.8179145231376
0.112865.84814131886115.09008219108
0.122902.50225705835138.319874903601
0.132944.09091915951160.092234370376
0.142989.94474894643177.104571573492
0.153038.64632090384186.918270177585
0.163088.32285576075188.493014477438
0.173137.01384015399182.304160962314
0.183183.01163798429170.022514095792
0.193225.09323255872153.965252168902
0.23262.60747175162136.477443029078
0.213295.43139437859119.487571145201
0.223323.84190126597104.243912567759
0.233348.3577925086591.3381230965387
0.243369.5964030914280.8381397731421
0.253388.1691167908872.5074029997352
0.263404.6208875453765.9815023751516
0.273419.4063013244560.8941376039064
0.283432.8897260303756.9385077228668
0.293445.357728189153.872546560522
0.33457.0352702208751.5237120389384
0.313468.100900325449.7550512843468
0.323478.6989767126348.48012472557
0.333488.9486422256647.6312388399989
0.343498.950008503747.1481234154155
0.353508.7881768433846.9957711673058
0.363518.5356076383247.1211043825582
0.373528.2531410905247.4822187239056
0.383537.9897900914448.0271255114729
0.393547.7813578590148.7024428858777
0.43557.6480299420349.4249575235875
0.413567.5913484681750.1032949575975
0.423577.5913191617650.6197280860484
0.433587.6046904505850.8416168595339
0.443597.5655239316450.6328865748887
0.453607.3889377996649.906904160517
0.463616.9783412837848.5983198879129
0.473626.2357007688746.7183501890607
0.483635.0735925570544.3458258830294
0.493643.4272353425541.6327741746193
0.53651.2645344604138.7764073401814
0.513658.5924665001536.0122154359355
0.523665.4588010493733.5753351199913
0.533671.9489981567331.6830375169675
0.543678.1788974834930.4937718588566
0.553684.2843356279930.0954912932816
0.563690.4090111502530.5070343604979
0.573696.6918142844731.6390827215834
0.583703.2546017559833.3673094219741
0.593710.1912044518435.4953498728022
0.63717.5584270149837.8024865744178
0.613725.3699356040740.0493607944958
0.623733.5941069984541.9890277163149
0.633742.1569234810943.4071120722371
0.643750.9506499498944.1467035724626
0.653759.8482400819144.1246519748981
0.663768.7222817542643.3823749425525
0.673777.4660806210542.0579689876607
0.683786.0135713096140.4008099249994
0.693794.3544916773138.7350141147052
0.73802.5418501936837.4159264428108
0.713810.6900975601936.7754746977797
0.723818.9642519701437.0479887561257
0.733827.5620132467338.328768976323
0.743836.6921080072940.5678892732726
0.753846.5523815369443.6023441357592
0.763857.3104542242847.1944202972456
0.773869.0884066773651.0817644271605
0.783881.9515172488754.9872840929642
0.793895.9001614307658.6292291695435
0.83910.8640109701761.7239343491379
0.813926.6986951986963.9903233944277
0.823943.1867690627765.1567849985584
0.833960.0465260243765.0122172117918
0.843976.9530571658263.4447516120361
0.853993.5750321022760.4889203875749
0.864009.6270491452956.3805950707234
0.874024.9307260130851.5803258468768
0.884039.4692932737446.7541804267124
0.894053.4146437227742.6557985328093
0.94067.1104063281439.9094821162286
0.914081.0185921962238.7200231635721
0.924095.682814915438.7801943904098
0.934111.8061316573939.7040440260393
0.944130.5136059810741.9469319461799
0.954153.6392046206947.5442599050333
0.964183.3875291981258.3763131295208
0.974220.4090282926970.1558204838015
0.984260.4741134264268.5355843626298
0.994293.309048895540.747488957567


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')