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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 computationSun, 16 Feb 2014 16:40:03 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Feb/16/t1392586815v22x9klx0v14srl.htm/, Retrieved Wed, 15 May 2024 03:19:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=233861, Retrieved Wed, 15 May 2024 03:19:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact76

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] [] [2014-02-16 21:40:03] [e610340e7a3184c9e0a1f377a12e8a83] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3477
2685
2438
1692
4054
3946
3623
2455
2362
2791
2369
3438
3682
2801
2563
3108
2890
3940
4036
1514
3461
2980
2728
3891
3715
2843
1416
2657
1856
2441
3172
2813
3335
2608
5784
4726
3817
2755
2541
3154
2684
3732
4286
2394
1698
3945
2549
3943
3899
2783
2660
1848
4482
4157
4404
2686
2593
3254
2664
4203
3985
2861
2758
1968
4666
4226
4748
2767
2723
3297
2758
4338

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=233861&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=233861&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=233861&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
0.011456.03431870886110.261039811475
0.021522.24147025194128.245349317114
0.031597.58000766452139.012230830445
0.041672.50242203667148.383891984497
0.051745.40207645929165.663206483512
0.061818.29751517606190.912290504383
0.071893.21669814182217.475679388964
0.081970.4698110291237.752294064862
0.092048.47204746472246.308879768681
0.12124.45759793174241.237250155787
0.112195.4770676021224.215755373363
0.122259.24075251427199.419522000524
0.132314.57639292684171.89324015743
0.142361.46745344652146.04367246807
0.152400.78333753948124.711297520043
0.162433.87540445989108.918742262409
0.172462.1951378090198.1771040053524
0.182487.0268662364991.1630798920039
0.192509.3578965331686.4107791859493
0.22529.8609163932482.7738812021409
0.212548.9442915239679.5083952405436
0.222566.8286391199976.2314510931342
0.232583.6213648540972.807968947585
0.242599.3752799165769.2415055447291
0.252614.1279991972165.6264641509269
0.262627.9244900854162.0829879416475
0.272640.8270192947958.7568833647391
0.282652.9165771340255.7686700517808
0.292664.2890545305953.2116738554535
0.32675.0487532447151.1374370143818
0.312685.3013887284849.5353608986166
0.322695.1484429695448.3678691612172
0.332704.6843271737447.5756835250905
0.342713.9972114465947.1231286116325
0.352723.1736103803447.009219824181
0.362732.3060248364447.305816390856
0.372741.5023002985748.1469518608636
0.382750.8949919410149.7529940560353
0.392760.6489644041652.3545484522365
0.42770.9656630421656.2250829108309
0.412782.0828948594861.59342437091
0.422794.2694719771368.6194759307586
0.432807.8146433025277.3760034884194
0.442823.0128429998887.8218312098411
0.452840.1448976868999.7853834234949
0.462859.45742020825112.978722523655
0.472881.14260189806127.006341952624
0.482905.32088854719141.386829236555
0.492932.02897100341155.58455648458
0.52961.21505784852169.077645987272
0.512992.74252221317181.387678128404
0.523026.40182921004192.142522190107
0.533061.92935466318201.105260756158
0.543099.03055772089208.194426896411
0.553137.40422122898213.472885982869
0.563176.76430133554217.130193343147
0.573216.8563831638219.430137755471
0.583257.46673190143220.662051946555
0.593298.42324803745221.090256415899
0.63339.58900588186220.909470516524
0.613380.85020380663220.216265289641
0.623422.10107961428219.011135907518
0.633463.2285552371217.197716179974
0.643504.09910897557214.618813015358
0.653544.54977581503211.087270058727
0.663584.38445156741206.414543543837
0.673623.37602257683200.460160068849
0.683661.27438395715193.132972878238
0.693697.8201504616184.426674563624
0.73732.76368432553174.435346762487
0.713765.88876360468163.362990185426
0.723797.03960434718151.527611802452
0.733826.14896277986139.398230056408
0.743853.26381630913127.542878664643
0.753878.56401189029116.649767848342
0.763902.36878153756107.449365999008
0.773925.12665621026100.643318068307
0.783947.3863665218696.7526964543115
0.793969.7497514191695.9787657064021
0.83992.812015285698.0745667783576
0.814017.09898122968102.382311083419
0.824043.01412422724107.980934985457
0.834070.80897049425113.88447905668
0.844100.58808392678119.248824442279
0.854132.3541173709123.541206305993
0.864166.0897869092126.657467278145
0.874201.86304076588128.979232091069
0.884239.92993776837131.312928238852
0.894280.79780710275134.687905488821
0.94325.20374362761139.981823226144
0.914373.97843318914147.376944019123
0.924427.85159498044155.773078789826
0.934487.50596444015162.695712709793
0.944554.68439704683165.666598562581
0.954635.65613321153167.248678191389
0.964747.43711426902188.508956815668
0.974921.50749452688281.488492463592
0.985187.91794854024489.053389528214
0.995521.03486118396781.617311342774

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 1456.03431870886 & 110.261039811475 \tabularnewline
0.02 & 1522.24147025194 & 128.245349317114 \tabularnewline
0.03 & 1597.58000766452 & 139.012230830445 \tabularnewline
0.04 & 1672.50242203667 & 148.383891984497 \tabularnewline
0.05 & 1745.40207645929 & 165.663206483512 \tabularnewline
0.06 & 1818.29751517606 & 190.912290504383 \tabularnewline
0.07 & 1893.21669814182 & 217.475679388964 \tabularnewline
0.08 & 1970.4698110291 & 237.752294064862 \tabularnewline
0.09 & 2048.47204746472 & 246.308879768681 \tabularnewline
0.1 & 2124.45759793174 & 241.237250155787 \tabularnewline
0.11 & 2195.4770676021 & 224.215755373363 \tabularnewline
0.12 & 2259.24075251427 & 199.419522000524 \tabularnewline
0.13 & 2314.57639292684 & 171.89324015743 \tabularnewline
0.14 & 2361.46745344652 & 146.04367246807 \tabularnewline
0.15 & 2400.78333753948 & 124.711297520043 \tabularnewline
0.16 & 2433.87540445989 & 108.918742262409 \tabularnewline
0.17 & 2462.19513780901 & 98.1771040053524 \tabularnewline
0.18 & 2487.02686623649 & 91.1630798920039 \tabularnewline
0.19 & 2509.35789653316 & 86.4107791859493 \tabularnewline
0.2 & 2529.86091639324 & 82.7738812021409 \tabularnewline
0.21 & 2548.94429152396 & 79.5083952405436 \tabularnewline
0.22 & 2566.82863911999 & 76.2314510931342 \tabularnewline
0.23 & 2583.62136485409 & 72.807968947585 \tabularnewline
0.24 & 2599.37527991657 & 69.2415055447291 \tabularnewline
0.25 & 2614.12799919721 & 65.6264641509269 \tabularnewline
0.26 & 2627.92449008541 & 62.0829879416475 \tabularnewline
0.27 & 2640.82701929479 & 58.7568833647391 \tabularnewline
0.28 & 2652.91657713402 & 55.7686700517808 \tabularnewline
0.29 & 2664.28905453059 & 53.2116738554535 \tabularnewline
0.3 & 2675.04875324471 & 51.1374370143818 \tabularnewline
0.31 & 2685.30138872848 & 49.5353608986166 \tabularnewline
0.32 & 2695.14844296954 & 48.3678691612172 \tabularnewline
0.33 & 2704.68432717374 & 47.5756835250905 \tabularnewline
0.34 & 2713.99721144659 & 47.1231286116325 \tabularnewline
0.35 & 2723.17361038034 & 47.009219824181 \tabularnewline
0.36 & 2732.30602483644 & 47.305816390856 \tabularnewline
0.37 & 2741.50230029857 & 48.1469518608636 \tabularnewline
0.38 & 2750.89499194101 & 49.7529940560353 \tabularnewline
0.39 & 2760.64896440416 & 52.3545484522365 \tabularnewline
0.4 & 2770.96566304216 & 56.2250829108309 \tabularnewline
0.41 & 2782.08289485948 & 61.59342437091 \tabularnewline
0.42 & 2794.26947197713 & 68.6194759307586 \tabularnewline
0.43 & 2807.81464330252 & 77.3760034884194 \tabularnewline
0.44 & 2823.01284299988 & 87.8218312098411 \tabularnewline
0.45 & 2840.14489768689 & 99.7853834234949 \tabularnewline
0.46 & 2859.45742020825 & 112.978722523655 \tabularnewline
0.47 & 2881.14260189806 & 127.006341952624 \tabularnewline
0.48 & 2905.32088854719 & 141.386829236555 \tabularnewline
0.49 & 2932.02897100341 & 155.58455648458 \tabularnewline
0.5 & 2961.21505784852 & 169.077645987272 \tabularnewline
0.51 & 2992.74252221317 & 181.387678128404 \tabularnewline
0.52 & 3026.40182921004 & 192.142522190107 \tabularnewline
0.53 & 3061.92935466318 & 201.105260756158 \tabularnewline
0.54 & 3099.03055772089 & 208.194426896411 \tabularnewline
0.55 & 3137.40422122898 & 213.472885982869 \tabularnewline
0.56 & 3176.76430133554 & 217.130193343147 \tabularnewline
0.57 & 3216.8563831638 & 219.430137755471 \tabularnewline
0.58 & 3257.46673190143 & 220.662051946555 \tabularnewline
0.59 & 3298.42324803745 & 221.090256415899 \tabularnewline
0.6 & 3339.58900588186 & 220.909470516524 \tabularnewline
0.61 & 3380.85020380663 & 220.216265289641 \tabularnewline
0.62 & 3422.10107961428 & 219.011135907518 \tabularnewline
0.63 & 3463.2285552371 & 217.197716179974 \tabularnewline
0.64 & 3504.09910897557 & 214.618813015358 \tabularnewline
0.65 & 3544.54977581503 & 211.087270058727 \tabularnewline
0.66 & 3584.38445156741 & 206.414543543837 \tabularnewline
0.67 & 3623.37602257683 & 200.460160068849 \tabularnewline
0.68 & 3661.27438395715 & 193.132972878238 \tabularnewline
0.69 & 3697.8201504616 & 184.426674563624 \tabularnewline
0.7 & 3732.76368432553 & 174.435346762487 \tabularnewline
0.71 & 3765.88876360468 & 163.362990185426 \tabularnewline
0.72 & 3797.03960434718 & 151.527611802452 \tabularnewline
0.73 & 3826.14896277986 & 139.398230056408 \tabularnewline
0.74 & 3853.26381630913 & 127.542878664643 \tabularnewline
0.75 & 3878.56401189029 & 116.649767848342 \tabularnewline
0.76 & 3902.36878153756 & 107.449365999008 \tabularnewline
0.77 & 3925.12665621026 & 100.643318068307 \tabularnewline
0.78 & 3947.38636652186 & 96.7526964543115 \tabularnewline
0.79 & 3969.74975141916 & 95.9787657064021 \tabularnewline
0.8 & 3992.8120152856 & 98.0745667783576 \tabularnewline
0.81 & 4017.09898122968 & 102.382311083419 \tabularnewline
0.82 & 4043.01412422724 & 107.980934985457 \tabularnewline
0.83 & 4070.80897049425 & 113.88447905668 \tabularnewline
0.84 & 4100.58808392678 & 119.248824442279 \tabularnewline
0.85 & 4132.3541173709 & 123.541206305993 \tabularnewline
0.86 & 4166.0897869092 & 126.657467278145 \tabularnewline
0.87 & 4201.86304076588 & 128.979232091069 \tabularnewline
0.88 & 4239.92993776837 & 131.312928238852 \tabularnewline
0.89 & 4280.79780710275 & 134.687905488821 \tabularnewline
0.9 & 4325.20374362761 & 139.981823226144 \tabularnewline
0.91 & 4373.97843318914 & 147.376944019123 \tabularnewline
0.92 & 4427.85159498044 & 155.773078789826 \tabularnewline
0.93 & 4487.50596444015 & 162.695712709793 \tabularnewline
0.94 & 4554.68439704683 & 165.666598562581 \tabularnewline
0.95 & 4635.65613321153 & 167.248678191389 \tabularnewline
0.96 & 4747.43711426902 & 188.508956815668 \tabularnewline
0.97 & 4921.50749452688 & 281.488492463592 \tabularnewline
0.98 & 5187.91794854024 & 489.053389528214 \tabularnewline
0.99 & 5521.03486118396 & 781.617311342774 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=233861&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]1456.03431870886[/C][C]110.261039811475[/C][/ROW]
[ROW][C]0.02[/C][C]1522.24147025194[/C][C]128.245349317114[/C][/ROW]
[ROW][C]0.03[/C][C]1597.58000766452[/C][C]139.012230830445[/C][/ROW]
[ROW][C]0.04[/C][C]1672.50242203667[/C][C]148.383891984497[/C][/ROW]
[ROW][C]0.05[/C][C]1745.40207645929[/C][C]165.663206483512[/C][/ROW]
[ROW][C]0.06[/C][C]1818.29751517606[/C][C]190.912290504383[/C][/ROW]
[ROW][C]0.07[/C][C]1893.21669814182[/C][C]217.475679388964[/C][/ROW]
[ROW][C]0.08[/C][C]1970.4698110291[/C][C]237.752294064862[/C][/ROW]
[ROW][C]0.09[/C][C]2048.47204746472[/C][C]246.308879768681[/C][/ROW]
[ROW][C]0.1[/C][C]2124.45759793174[/C][C]241.237250155787[/C][/ROW]
[ROW][C]0.11[/C][C]2195.4770676021[/C][C]224.215755373363[/C][/ROW]
[ROW][C]0.12[/C][C]2259.24075251427[/C][C]199.419522000524[/C][/ROW]
[ROW][C]0.13[/C][C]2314.57639292684[/C][C]171.89324015743[/C][/ROW]
[ROW][C]0.14[/C][C]2361.46745344652[/C][C]146.04367246807[/C][/ROW]
[ROW][C]0.15[/C][C]2400.78333753948[/C][C]124.711297520043[/C][/ROW]
[ROW][C]0.16[/C][C]2433.87540445989[/C][C]108.918742262409[/C][/ROW]
[ROW][C]0.17[/C][C]2462.19513780901[/C][C]98.1771040053524[/C][/ROW]
[ROW][C]0.18[/C][C]2487.02686623649[/C][C]91.1630798920039[/C][/ROW]
[ROW][C]0.19[/C][C]2509.35789653316[/C][C]86.4107791859493[/C][/ROW]
[ROW][C]0.2[/C][C]2529.86091639324[/C][C]82.7738812021409[/C][/ROW]
[ROW][C]0.21[/C][C]2548.94429152396[/C][C]79.5083952405436[/C][/ROW]
[ROW][C]0.22[/C][C]2566.82863911999[/C][C]76.2314510931342[/C][/ROW]
[ROW][C]0.23[/C][C]2583.62136485409[/C][C]72.807968947585[/C][/ROW]
[ROW][C]0.24[/C][C]2599.37527991657[/C][C]69.2415055447291[/C][/ROW]
[ROW][C]0.25[/C][C]2614.12799919721[/C][C]65.6264641509269[/C][/ROW]
[ROW][C]0.26[/C][C]2627.92449008541[/C][C]62.0829879416475[/C][/ROW]
[ROW][C]0.27[/C][C]2640.82701929479[/C][C]58.7568833647391[/C][/ROW]
[ROW][C]0.28[/C][C]2652.91657713402[/C][C]55.7686700517808[/C][/ROW]
[ROW][C]0.29[/C][C]2664.28905453059[/C][C]53.2116738554535[/C][/ROW]
[ROW][C]0.3[/C][C]2675.04875324471[/C][C]51.1374370143818[/C][/ROW]
[ROW][C]0.31[/C][C]2685.30138872848[/C][C]49.5353608986166[/C][/ROW]
[ROW][C]0.32[/C][C]2695.14844296954[/C][C]48.3678691612172[/C][/ROW]
[ROW][C]0.33[/C][C]2704.68432717374[/C][C]47.5756835250905[/C][/ROW]
[ROW][C]0.34[/C][C]2713.99721144659[/C][C]47.1231286116325[/C][/ROW]
[ROW][C]0.35[/C][C]2723.17361038034[/C][C]47.009219824181[/C][/ROW]
[ROW][C]0.36[/C][C]2732.30602483644[/C][C]47.305816390856[/C][/ROW]
[ROW][C]0.37[/C][C]2741.50230029857[/C][C]48.1469518608636[/C][/ROW]
[ROW][C]0.38[/C][C]2750.89499194101[/C][C]49.7529940560353[/C][/ROW]
[ROW][C]0.39[/C][C]2760.64896440416[/C][C]52.3545484522365[/C][/ROW]
[ROW][C]0.4[/C][C]2770.96566304216[/C][C]56.2250829108309[/C][/ROW]
[ROW][C]0.41[/C][C]2782.08289485948[/C][C]61.59342437091[/C][/ROW]
[ROW][C]0.42[/C][C]2794.26947197713[/C][C]68.6194759307586[/C][/ROW]
[ROW][C]0.43[/C][C]2807.81464330252[/C][C]77.3760034884194[/C][/ROW]
[ROW][C]0.44[/C][C]2823.01284299988[/C][C]87.8218312098411[/C][/ROW]
[ROW][C]0.45[/C][C]2840.14489768689[/C][C]99.7853834234949[/C][/ROW]
[ROW][C]0.46[/C][C]2859.45742020825[/C][C]112.978722523655[/C][/ROW]
[ROW][C]0.47[/C][C]2881.14260189806[/C][C]127.006341952624[/C][/ROW]
[ROW][C]0.48[/C][C]2905.32088854719[/C][C]141.386829236555[/C][/ROW]
[ROW][C]0.49[/C][C]2932.02897100341[/C][C]155.58455648458[/C][/ROW]
[ROW][C]0.5[/C][C]2961.21505784852[/C][C]169.077645987272[/C][/ROW]
[ROW][C]0.51[/C][C]2992.74252221317[/C][C]181.387678128404[/C][/ROW]
[ROW][C]0.52[/C][C]3026.40182921004[/C][C]192.142522190107[/C][/ROW]
[ROW][C]0.53[/C][C]3061.92935466318[/C][C]201.105260756158[/C][/ROW]
[ROW][C]0.54[/C][C]3099.03055772089[/C][C]208.194426896411[/C][/ROW]
[ROW][C]0.55[/C][C]3137.40422122898[/C][C]213.472885982869[/C][/ROW]
[ROW][C]0.56[/C][C]3176.76430133554[/C][C]217.130193343147[/C][/ROW]
[ROW][C]0.57[/C][C]3216.8563831638[/C][C]219.430137755471[/C][/ROW]
[ROW][C]0.58[/C][C]3257.46673190143[/C][C]220.662051946555[/C][/ROW]
[ROW][C]0.59[/C][C]3298.42324803745[/C][C]221.090256415899[/C][/ROW]
[ROW][C]0.6[/C][C]3339.58900588186[/C][C]220.909470516524[/C][/ROW]
[ROW][C]0.61[/C][C]3380.85020380663[/C][C]220.216265289641[/C][/ROW]
[ROW][C]0.62[/C][C]3422.10107961428[/C][C]219.011135907518[/C][/ROW]
[ROW][C]0.63[/C][C]3463.2285552371[/C][C]217.197716179974[/C][/ROW]
[ROW][C]0.64[/C][C]3504.09910897557[/C][C]214.618813015358[/C][/ROW]
[ROW][C]0.65[/C][C]3544.54977581503[/C][C]211.087270058727[/C][/ROW]
[ROW][C]0.66[/C][C]3584.38445156741[/C][C]206.414543543837[/C][/ROW]
[ROW][C]0.67[/C][C]3623.37602257683[/C][C]200.460160068849[/C][/ROW]
[ROW][C]0.68[/C][C]3661.27438395715[/C][C]193.132972878238[/C][/ROW]
[ROW][C]0.69[/C][C]3697.8201504616[/C][C]184.426674563624[/C][/ROW]
[ROW][C]0.7[/C][C]3732.76368432553[/C][C]174.435346762487[/C][/ROW]
[ROW][C]0.71[/C][C]3765.88876360468[/C][C]163.362990185426[/C][/ROW]
[ROW][C]0.72[/C][C]3797.03960434718[/C][C]151.527611802452[/C][/ROW]
[ROW][C]0.73[/C][C]3826.14896277986[/C][C]139.398230056408[/C][/ROW]
[ROW][C]0.74[/C][C]3853.26381630913[/C][C]127.542878664643[/C][/ROW]
[ROW][C]0.75[/C][C]3878.56401189029[/C][C]116.649767848342[/C][/ROW]
[ROW][C]0.76[/C][C]3902.36878153756[/C][C]107.449365999008[/C][/ROW]
[ROW][C]0.77[/C][C]3925.12665621026[/C][C]100.643318068307[/C][/ROW]
[ROW][C]0.78[/C][C]3947.38636652186[/C][C]96.7526964543115[/C][/ROW]
[ROW][C]0.79[/C][C]3969.74975141916[/C][C]95.9787657064021[/C][/ROW]
[ROW][C]0.8[/C][C]3992.8120152856[/C][C]98.0745667783576[/C][/ROW]
[ROW][C]0.81[/C][C]4017.09898122968[/C][C]102.382311083419[/C][/ROW]
[ROW][C]0.82[/C][C]4043.01412422724[/C][C]107.980934985457[/C][/ROW]
[ROW][C]0.83[/C][C]4070.80897049425[/C][C]113.88447905668[/C][/ROW]
[ROW][C]0.84[/C][C]4100.58808392678[/C][C]119.248824442279[/C][/ROW]
[ROW][C]0.85[/C][C]4132.3541173709[/C][C]123.541206305993[/C][/ROW]
[ROW][C]0.86[/C][C]4166.0897869092[/C][C]126.657467278145[/C][/ROW]
[ROW][C]0.87[/C][C]4201.86304076588[/C][C]128.979232091069[/C][/ROW]
[ROW][C]0.88[/C][C]4239.92993776837[/C][C]131.312928238852[/C][/ROW]
[ROW][C]0.89[/C][C]4280.79780710275[/C][C]134.687905488821[/C][/ROW]
[ROW][C]0.9[/C][C]4325.20374362761[/C][C]139.981823226144[/C][/ROW]
[ROW][C]0.91[/C][C]4373.97843318914[/C][C]147.376944019123[/C][/ROW]
[ROW][C]0.92[/C][C]4427.85159498044[/C][C]155.773078789826[/C][/ROW]
[ROW][C]0.93[/C][C]4487.50596444015[/C][C]162.695712709793[/C][/ROW]
[ROW][C]0.94[/C][C]4554.68439704683[/C][C]165.666598562581[/C][/ROW]
[ROW][C]0.95[/C][C]4635.65613321153[/C][C]167.248678191389[/C][/ROW]
[ROW][C]0.96[/C][C]4747.43711426902[/C][C]188.508956815668[/C][/ROW]
[ROW][C]0.97[/C][C]4921.50749452688[/C][C]281.488492463592[/C][/ROW]
[ROW][C]0.98[/C][C]5187.91794854024[/C][C]489.053389528214[/C][/ROW]
[ROW][C]0.99[/C][C]5521.03486118396[/C][C]781.617311342774[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=233861&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=233861&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
0.011456.03431870886110.261039811475
0.021522.24147025194128.245349317114
0.031597.58000766452139.012230830445
0.041672.50242203667148.383891984497
0.051745.40207645929165.663206483512
0.061818.29751517606190.912290504383
0.071893.21669814182217.475679388964
0.081970.4698110291237.752294064862
0.092048.47204746472246.308879768681
0.12124.45759793174241.237250155787
0.112195.4770676021224.215755373363
0.122259.24075251427199.419522000524
0.132314.57639292684171.89324015743
0.142361.46745344652146.04367246807
0.152400.78333753948124.711297520043
0.162433.87540445989108.918742262409
0.172462.1951378090198.1771040053524
0.182487.0268662364991.1630798920039
0.192509.3578965331686.4107791859493
0.22529.8609163932482.7738812021409
0.212548.9442915239679.5083952405436
0.222566.8286391199976.2314510931342
0.232583.6213648540972.807968947585
0.242599.3752799165769.2415055447291
0.252614.1279991972165.6264641509269
0.262627.9244900854162.0829879416475
0.272640.8270192947958.7568833647391
0.282652.9165771340255.7686700517808
0.292664.2890545305953.2116738554535
0.32675.0487532447151.1374370143818
0.312685.3013887284849.5353608986166
0.322695.1484429695448.3678691612172
0.332704.6843271737447.5756835250905
0.342713.9972114465947.1231286116325
0.352723.1736103803447.009219824181
0.362732.3060248364447.305816390856
0.372741.5023002985748.1469518608636
0.382750.8949919410149.7529940560353
0.392760.6489644041652.3545484522365
0.42770.9656630421656.2250829108309
0.412782.0828948594861.59342437091
0.422794.2694719771368.6194759307586
0.432807.8146433025277.3760034884194
0.442823.0128429998887.8218312098411
0.452840.1448976868999.7853834234949
0.462859.45742020825112.978722523655
0.472881.14260189806127.006341952624
0.482905.32088854719141.386829236555
0.492932.02897100341155.58455648458
0.52961.21505784852169.077645987272
0.512992.74252221317181.387678128404
0.523026.40182921004192.142522190107
0.533061.92935466318201.105260756158
0.543099.03055772089208.194426896411
0.553137.40422122898213.472885982869
0.563176.76430133554217.130193343147
0.573216.8563831638219.430137755471
0.583257.46673190143220.662051946555
0.593298.42324803745221.090256415899
0.63339.58900588186220.909470516524
0.613380.85020380663220.216265289641
0.623422.10107961428219.011135907518
0.633463.2285552371217.197716179974
0.643504.09910897557214.618813015358
0.653544.54977581503211.087270058727
0.663584.38445156741206.414543543837
0.673623.37602257683200.460160068849
0.683661.27438395715193.132972878238
0.693697.8201504616184.426674563624
0.73732.76368432553174.435346762487
0.713765.88876360468163.362990185426
0.723797.03960434718151.527611802452
0.733826.14896277986139.398230056408
0.743853.26381630913127.542878664643
0.753878.56401189029116.649767848342
0.763902.36878153756107.449365999008
0.773925.12665621026100.643318068307
0.783947.3863665218696.7526964543115
0.793969.7497514191695.9787657064021
0.83992.812015285698.0745667783576
0.814017.09898122968102.382311083419
0.824043.01412422724107.980934985457
0.834070.80897049425113.88447905668
0.844100.58808392678119.248824442279
0.854132.3541173709123.541206305993
0.864166.0897869092126.657467278145
0.874201.86304076588128.979232091069
0.884239.92993776837131.312928238852
0.894280.79780710275134.687905488821
0.94325.20374362761139.981823226144
0.914373.97843318914147.376944019123
0.924427.85159498044155.773078789826
0.934487.50596444015162.695712709793
0.944554.68439704683165.666598562581
0.954635.65613321153167.248678191389
0.964747.43711426902188.508956815668
0.974921.50749452688281.488492463592
0.985187.91794854024489.053389528214
0.995521.03486118396781.617311342774


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 <- '0.01'
par2 <- '0.99'
par1 <- '0.01'
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')