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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 computationFri, 26 Jul 2013 08:59:52 -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/Jul/26/t1374843625z8c9jvw5dm2ryy2.htm/, Retrieved Mon, 29 Apr 2024 04:42:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=210845, Retrieved Mon, 29 Apr 2024 04:42:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsJeroen Biesemans
Estimated Impact155

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] [Tijdreeks B stap 7] [2013-07-26 12:59:52] [09688f513f3d2798cb35a3603f8bd204] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2240
2240
2380
2380
2380
2380
2140
2400
2180
2260
2280
2480
2360
2160
2380
2280
2320
2400
1960
2520
2200
2420
2300
2280
2220
2240
2200
2340
2240
2500
1820
2520
2180
2480
2260
2400
2240
2240
2240
2140
2200
2460
1860
2480
1960
2540
2280
2320
2320
2440
2320
2180
2120
2460
2140
2480
2100
2700
2200
2260
2340
2720
2300
2360
2020
2380
2000
2540
1980
2940
2260
2300
2300
2820
2380
2360
1980
2340
2160
2700
1920
2980
2240
2180
2440
2740
2360
2380
2000
2500
2180
2740
1960
3060
2300
2240
2580
2740
2260
2400
1820
2440
2080
2680
1900
3000
2240
2300

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210845&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210845&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210845&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'Gertrude Mary Cox' @ cox.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.011829.101821138421.5640978888692
0.021851.6756278613240.1794597870167
0.031880.9281583212745.0511647689145
0.041908.970497718441.6727252480616
0.051932.2944989589735.8958134025038
0.061950.9455515437831.6314639156629
0.071966.593456472731.3673018007785
0.081981.2600602088735.4692759444889
0.091996.5884840091242.4092936625597
0.12013.4812419038350.0208396528304
0.112032.033314399956.2446610419144
0.122051.6832081791259.5969712672049
0.132071.4955060207959.4915988795027
0.142090.4802956446856.2789999411213
0.152107.8541980750950.9725569672975
0.162123.177614343844.7981350463903
0.172136.3592811411138.7898188002522
0.182147.5701650890233.595859223417
0.192157.1275504409929.482815686202
0.22165.3962521247126.4733078850967
0.212172.7256310999924.4761663365416
0.222179.4179413547123.3522085529886
0.232185.7143535614422.9174256973193
0.242191.7876528428722.9313801784394
0.252197.7379413269623.1056038236552
0.262203.5934235938523.1573848948408
0.272209.3198274829222.8497679163592
0.282214.839777738922.0623803286718
0.292220.0596535033220.794825755406
0.32224.8983279097819.1617050663408
0.312229.3110926414517.3859087235926
0.322233.3033254754115.7207745476318
0.332236.9314505161514.4091417715561
0.342240.2922988884913.6314286225341
0.352243.5048604505713.4523527119662
0.362246.6897677707213.8154839678305
0.372249.9514683941914.5737894433585
0.382253.3663538469415.5681909811345
0.392256.9779281262616.6402853317531
0.42260.7982170203417.6578895892647
0.412264.8135392847218.5401272036778
0.422268.9925541038919.2310723914072
0.432273.2948957443219.7111687303603
0.442277.6792972842219.9979676963008
0.452282.1105593257220.1367942701907
0.462286.5649104684720.1812854827132
0.472291.0333147206520.2194470228602
0.482295.5222947231720.3241241359351
0.492300.0520201929320.5596012872806
0.52304.6517986518620.9560149712002
0.512309.3536039893521.5129795658783
0.522314.1847142201622.1817904928248
0.532319.160745106822.8890433328354
0.542324.2802934342923.5389349577848
0.552329.5220868033124.0355812572346
0.562334.8450976814324.2884456362426
0.572340.1916522233224.2262609767641
0.582345.4932341636423.8207306289843
0.592350.678458400923.075699680826
0.62355.6825121447922.0355750137165
0.612360.4571638326420.7945797488419
0.622364.9801962348119.4785117056117
0.632369.2628878535618.2544292651807
0.642373.3540781991617.3042833518625
0.652377.3395555643416.8034872146791
0.662381.3360778155316.8925723589223
0.672385.4802190554317.6346543525187
0.682389.9132328591118.9980538557425
0.692394.7639773750720.8648300958574
0.72400.1324444847223.0492143814605
0.712406.0764851885325.335936150237
0.722412.6039714273227.4936010100489
0.732419.6720020917229.3133242220825
0.742427.1939686862630.63713191339
0.752435.0544209578931.3767176207289
0.762443.1307663960231.5459354636633
0.772451.3199943177931.2578483229582
0.782459.5680335765230.741349145698
0.792467.8992749753730.3166119511449
0.82476.4441904800330.3976419872162
0.812485.4630486490331.4529827680949
0.822495.3616221241233.9751157480892
0.832506.68864955138.3929187716011
0.842520.095621477744.93326738944
0.852536.2343765448653.3764418570552
0.862555.5801150836462.819640314124
0.872578.2073515103471.5980935723966
0.882603.6072320536377.5998375660748
0.892630.6837900322378.9942721994675
0.92658.0587577441375.2168210007715
0.912684.7217598462867.7866269459602
0.922710.8862747352460.6566621135277
0.932738.6579023441359.7019957001062
0.942771.8313214119669.2153394374706
0.952814.0989975601185.6929177267237
0.962865.9162052000497.1889064009632
0.972922.642528536590.8767532112458
0.982977.7597368170167.532866289502
0.993027.3111526082952.2250933642877

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 1829.1018211384 & 21.5640978888692 \tabularnewline
0.02 & 1851.67562786132 & 40.1794597870167 \tabularnewline
0.03 & 1880.92815832127 & 45.0511647689145 \tabularnewline
0.04 & 1908.9704977184 & 41.6727252480616 \tabularnewline
0.05 & 1932.29449895897 & 35.8958134025038 \tabularnewline
0.06 & 1950.94555154378 & 31.6314639156629 \tabularnewline
0.07 & 1966.5934564727 & 31.3673018007785 \tabularnewline
0.08 & 1981.26006020887 & 35.4692759444889 \tabularnewline
0.09 & 1996.58848400912 & 42.4092936625597 \tabularnewline
0.1 & 2013.48124190383 & 50.0208396528304 \tabularnewline
0.11 & 2032.0333143999 & 56.2446610419144 \tabularnewline
0.12 & 2051.68320817912 & 59.5969712672049 \tabularnewline
0.13 & 2071.49550602079 & 59.4915988795027 \tabularnewline
0.14 & 2090.48029564468 & 56.2789999411213 \tabularnewline
0.15 & 2107.85419807509 & 50.9725569672975 \tabularnewline
0.16 & 2123.1776143438 & 44.7981350463903 \tabularnewline
0.17 & 2136.35928114111 & 38.7898188002522 \tabularnewline
0.18 & 2147.57016508902 & 33.595859223417 \tabularnewline
0.19 & 2157.12755044099 & 29.482815686202 \tabularnewline
0.2 & 2165.39625212471 & 26.4733078850967 \tabularnewline
0.21 & 2172.72563109999 & 24.4761663365416 \tabularnewline
0.22 & 2179.41794135471 & 23.3522085529886 \tabularnewline
0.23 & 2185.71435356144 & 22.9174256973193 \tabularnewline
0.24 & 2191.78765284287 & 22.9313801784394 \tabularnewline
0.25 & 2197.73794132696 & 23.1056038236552 \tabularnewline
0.26 & 2203.59342359385 & 23.1573848948408 \tabularnewline
0.27 & 2209.31982748292 & 22.8497679163592 \tabularnewline
0.28 & 2214.8397777389 & 22.0623803286718 \tabularnewline
0.29 & 2220.05965350332 & 20.794825755406 \tabularnewline
0.3 & 2224.89832790978 & 19.1617050663408 \tabularnewline
0.31 & 2229.31109264145 & 17.3859087235926 \tabularnewline
0.32 & 2233.30332547541 & 15.7207745476318 \tabularnewline
0.33 & 2236.93145051615 & 14.4091417715561 \tabularnewline
0.34 & 2240.29229888849 & 13.6314286225341 \tabularnewline
0.35 & 2243.50486045057 & 13.4523527119662 \tabularnewline
0.36 & 2246.68976777072 & 13.8154839678305 \tabularnewline
0.37 & 2249.95146839419 & 14.5737894433585 \tabularnewline
0.38 & 2253.36635384694 & 15.5681909811345 \tabularnewline
0.39 & 2256.97792812626 & 16.6402853317531 \tabularnewline
0.4 & 2260.79821702034 & 17.6578895892647 \tabularnewline
0.41 & 2264.81353928472 & 18.5401272036778 \tabularnewline
0.42 & 2268.99255410389 & 19.2310723914072 \tabularnewline
0.43 & 2273.29489574432 & 19.7111687303603 \tabularnewline
0.44 & 2277.67929728422 & 19.9979676963008 \tabularnewline
0.45 & 2282.11055932572 & 20.1367942701907 \tabularnewline
0.46 & 2286.56491046847 & 20.1812854827132 \tabularnewline
0.47 & 2291.03331472065 & 20.2194470228602 \tabularnewline
0.48 & 2295.52229472317 & 20.3241241359351 \tabularnewline
0.49 & 2300.05202019293 & 20.5596012872806 \tabularnewline
0.5 & 2304.65179865186 & 20.9560149712002 \tabularnewline
0.51 & 2309.35360398935 & 21.5129795658783 \tabularnewline
0.52 & 2314.18471422016 & 22.1817904928248 \tabularnewline
0.53 & 2319.1607451068 & 22.8890433328354 \tabularnewline
0.54 & 2324.28029343429 & 23.5389349577848 \tabularnewline
0.55 & 2329.52208680331 & 24.0355812572346 \tabularnewline
0.56 & 2334.84509768143 & 24.2884456362426 \tabularnewline
0.57 & 2340.19165222332 & 24.2262609767641 \tabularnewline
0.58 & 2345.49323416364 & 23.8207306289843 \tabularnewline
0.59 & 2350.6784584009 & 23.075699680826 \tabularnewline
0.6 & 2355.68251214479 & 22.0355750137165 \tabularnewline
0.61 & 2360.45716383264 & 20.7945797488419 \tabularnewline
0.62 & 2364.98019623481 & 19.4785117056117 \tabularnewline
0.63 & 2369.26288785356 & 18.2544292651807 \tabularnewline
0.64 & 2373.35407819916 & 17.3042833518625 \tabularnewline
0.65 & 2377.33955556434 & 16.8034872146791 \tabularnewline
0.66 & 2381.33607781553 & 16.8925723589223 \tabularnewline
0.67 & 2385.48021905543 & 17.6346543525187 \tabularnewline
0.68 & 2389.91323285911 & 18.9980538557425 \tabularnewline
0.69 & 2394.76397737507 & 20.8648300958574 \tabularnewline
0.7 & 2400.13244448472 & 23.0492143814605 \tabularnewline
0.71 & 2406.07648518853 & 25.335936150237 \tabularnewline
0.72 & 2412.60397142732 & 27.4936010100489 \tabularnewline
0.73 & 2419.67200209172 & 29.3133242220825 \tabularnewline
0.74 & 2427.19396868626 & 30.63713191339 \tabularnewline
0.75 & 2435.05442095789 & 31.3767176207289 \tabularnewline
0.76 & 2443.13076639602 & 31.5459354636633 \tabularnewline
0.77 & 2451.31999431779 & 31.2578483229582 \tabularnewline
0.78 & 2459.56803357652 & 30.741349145698 \tabularnewline
0.79 & 2467.89927497537 & 30.3166119511449 \tabularnewline
0.8 & 2476.44419048003 & 30.3976419872162 \tabularnewline
0.81 & 2485.46304864903 & 31.4529827680949 \tabularnewline
0.82 & 2495.36162212412 & 33.9751157480892 \tabularnewline
0.83 & 2506.688649551 & 38.3929187716011 \tabularnewline
0.84 & 2520.0956214777 & 44.93326738944 \tabularnewline
0.85 & 2536.23437654486 & 53.3764418570552 \tabularnewline
0.86 & 2555.58011508364 & 62.819640314124 \tabularnewline
0.87 & 2578.20735151034 & 71.5980935723966 \tabularnewline
0.88 & 2603.60723205363 & 77.5998375660748 \tabularnewline
0.89 & 2630.68379003223 & 78.9942721994675 \tabularnewline
0.9 & 2658.05875774413 & 75.2168210007715 \tabularnewline
0.91 & 2684.72175984628 & 67.7866269459602 \tabularnewline
0.92 & 2710.88627473524 & 60.6566621135277 \tabularnewline
0.93 & 2738.65790234413 & 59.7019957001062 \tabularnewline
0.94 & 2771.83132141196 & 69.2153394374706 \tabularnewline
0.95 & 2814.09899756011 & 85.6929177267237 \tabularnewline
0.96 & 2865.91620520004 & 97.1889064009632 \tabularnewline
0.97 & 2922.6425285365 & 90.8767532112458 \tabularnewline
0.98 & 2977.75973681701 & 67.532866289502 \tabularnewline
0.99 & 3027.31115260829 & 52.2250933642877 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210845&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]1829.1018211384[/C][C]21.5640978888692[/C][/ROW]
[ROW][C]0.02[/C][C]1851.67562786132[/C][C]40.1794597870167[/C][/ROW]
[ROW][C]0.03[/C][C]1880.92815832127[/C][C]45.0511647689145[/C][/ROW]
[ROW][C]0.04[/C][C]1908.9704977184[/C][C]41.6727252480616[/C][/ROW]
[ROW][C]0.05[/C][C]1932.29449895897[/C][C]35.8958134025038[/C][/ROW]
[ROW][C]0.06[/C][C]1950.94555154378[/C][C]31.6314639156629[/C][/ROW]
[ROW][C]0.07[/C][C]1966.5934564727[/C][C]31.3673018007785[/C][/ROW]
[ROW][C]0.08[/C][C]1981.26006020887[/C][C]35.4692759444889[/C][/ROW]
[ROW][C]0.09[/C][C]1996.58848400912[/C][C]42.4092936625597[/C][/ROW]
[ROW][C]0.1[/C][C]2013.48124190383[/C][C]50.0208396528304[/C][/ROW]
[ROW][C]0.11[/C][C]2032.0333143999[/C][C]56.2446610419144[/C][/ROW]
[ROW][C]0.12[/C][C]2051.68320817912[/C][C]59.5969712672049[/C][/ROW]
[ROW][C]0.13[/C][C]2071.49550602079[/C][C]59.4915988795027[/C][/ROW]
[ROW][C]0.14[/C][C]2090.48029564468[/C][C]56.2789999411213[/C][/ROW]
[ROW][C]0.15[/C][C]2107.85419807509[/C][C]50.9725569672975[/C][/ROW]
[ROW][C]0.16[/C][C]2123.1776143438[/C][C]44.7981350463903[/C][/ROW]
[ROW][C]0.17[/C][C]2136.35928114111[/C][C]38.7898188002522[/C][/ROW]
[ROW][C]0.18[/C][C]2147.57016508902[/C][C]33.595859223417[/C][/ROW]
[ROW][C]0.19[/C][C]2157.12755044099[/C][C]29.482815686202[/C][/ROW]
[ROW][C]0.2[/C][C]2165.39625212471[/C][C]26.4733078850967[/C][/ROW]
[ROW][C]0.21[/C][C]2172.72563109999[/C][C]24.4761663365416[/C][/ROW]
[ROW][C]0.22[/C][C]2179.41794135471[/C][C]23.3522085529886[/C][/ROW]
[ROW][C]0.23[/C][C]2185.71435356144[/C][C]22.9174256973193[/C][/ROW]
[ROW][C]0.24[/C][C]2191.78765284287[/C][C]22.9313801784394[/C][/ROW]
[ROW][C]0.25[/C][C]2197.73794132696[/C][C]23.1056038236552[/C][/ROW]
[ROW][C]0.26[/C][C]2203.59342359385[/C][C]23.1573848948408[/C][/ROW]
[ROW][C]0.27[/C][C]2209.31982748292[/C][C]22.8497679163592[/C][/ROW]
[ROW][C]0.28[/C][C]2214.8397777389[/C][C]22.0623803286718[/C][/ROW]
[ROW][C]0.29[/C][C]2220.05965350332[/C][C]20.794825755406[/C][/ROW]
[ROW][C]0.3[/C][C]2224.89832790978[/C][C]19.1617050663408[/C][/ROW]
[ROW][C]0.31[/C][C]2229.31109264145[/C][C]17.3859087235926[/C][/ROW]
[ROW][C]0.32[/C][C]2233.30332547541[/C][C]15.7207745476318[/C][/ROW]
[ROW][C]0.33[/C][C]2236.93145051615[/C][C]14.4091417715561[/C][/ROW]
[ROW][C]0.34[/C][C]2240.29229888849[/C][C]13.6314286225341[/C][/ROW]
[ROW][C]0.35[/C][C]2243.50486045057[/C][C]13.4523527119662[/C][/ROW]
[ROW][C]0.36[/C][C]2246.68976777072[/C][C]13.8154839678305[/C][/ROW]
[ROW][C]0.37[/C][C]2249.95146839419[/C][C]14.5737894433585[/C][/ROW]
[ROW][C]0.38[/C][C]2253.36635384694[/C][C]15.5681909811345[/C][/ROW]
[ROW][C]0.39[/C][C]2256.97792812626[/C][C]16.6402853317531[/C][/ROW]
[ROW][C]0.4[/C][C]2260.79821702034[/C][C]17.6578895892647[/C][/ROW]
[ROW][C]0.41[/C][C]2264.81353928472[/C][C]18.5401272036778[/C][/ROW]
[ROW][C]0.42[/C][C]2268.99255410389[/C][C]19.2310723914072[/C][/ROW]
[ROW][C]0.43[/C][C]2273.29489574432[/C][C]19.7111687303603[/C][/ROW]
[ROW][C]0.44[/C][C]2277.67929728422[/C][C]19.9979676963008[/C][/ROW]
[ROW][C]0.45[/C][C]2282.11055932572[/C][C]20.1367942701907[/C][/ROW]
[ROW][C]0.46[/C][C]2286.56491046847[/C][C]20.1812854827132[/C][/ROW]
[ROW][C]0.47[/C][C]2291.03331472065[/C][C]20.2194470228602[/C][/ROW]
[ROW][C]0.48[/C][C]2295.52229472317[/C][C]20.3241241359351[/C][/ROW]
[ROW][C]0.49[/C][C]2300.05202019293[/C][C]20.5596012872806[/C][/ROW]
[ROW][C]0.5[/C][C]2304.65179865186[/C][C]20.9560149712002[/C][/ROW]
[ROW][C]0.51[/C][C]2309.35360398935[/C][C]21.5129795658783[/C][/ROW]
[ROW][C]0.52[/C][C]2314.18471422016[/C][C]22.1817904928248[/C][/ROW]
[ROW][C]0.53[/C][C]2319.1607451068[/C][C]22.8890433328354[/C][/ROW]
[ROW][C]0.54[/C][C]2324.28029343429[/C][C]23.5389349577848[/C][/ROW]
[ROW][C]0.55[/C][C]2329.52208680331[/C][C]24.0355812572346[/C][/ROW]
[ROW][C]0.56[/C][C]2334.84509768143[/C][C]24.2884456362426[/C][/ROW]
[ROW][C]0.57[/C][C]2340.19165222332[/C][C]24.2262609767641[/C][/ROW]
[ROW][C]0.58[/C][C]2345.49323416364[/C][C]23.8207306289843[/C][/ROW]
[ROW][C]0.59[/C][C]2350.6784584009[/C][C]23.075699680826[/C][/ROW]
[ROW][C]0.6[/C][C]2355.68251214479[/C][C]22.0355750137165[/C][/ROW]
[ROW][C]0.61[/C][C]2360.45716383264[/C][C]20.7945797488419[/C][/ROW]
[ROW][C]0.62[/C][C]2364.98019623481[/C][C]19.4785117056117[/C][/ROW]
[ROW][C]0.63[/C][C]2369.26288785356[/C][C]18.2544292651807[/C][/ROW]
[ROW][C]0.64[/C][C]2373.35407819916[/C][C]17.3042833518625[/C][/ROW]
[ROW][C]0.65[/C][C]2377.33955556434[/C][C]16.8034872146791[/C][/ROW]
[ROW][C]0.66[/C][C]2381.33607781553[/C][C]16.8925723589223[/C][/ROW]
[ROW][C]0.67[/C][C]2385.48021905543[/C][C]17.6346543525187[/C][/ROW]
[ROW][C]0.68[/C][C]2389.91323285911[/C][C]18.9980538557425[/C][/ROW]
[ROW][C]0.69[/C][C]2394.76397737507[/C][C]20.8648300958574[/C][/ROW]
[ROW][C]0.7[/C][C]2400.13244448472[/C][C]23.0492143814605[/C][/ROW]
[ROW][C]0.71[/C][C]2406.07648518853[/C][C]25.335936150237[/C][/ROW]
[ROW][C]0.72[/C][C]2412.60397142732[/C][C]27.4936010100489[/C][/ROW]
[ROW][C]0.73[/C][C]2419.67200209172[/C][C]29.3133242220825[/C][/ROW]
[ROW][C]0.74[/C][C]2427.19396868626[/C][C]30.63713191339[/C][/ROW]
[ROW][C]0.75[/C][C]2435.05442095789[/C][C]31.3767176207289[/C][/ROW]
[ROW][C]0.76[/C][C]2443.13076639602[/C][C]31.5459354636633[/C][/ROW]
[ROW][C]0.77[/C][C]2451.31999431779[/C][C]31.2578483229582[/C][/ROW]
[ROW][C]0.78[/C][C]2459.56803357652[/C][C]30.741349145698[/C][/ROW]
[ROW][C]0.79[/C][C]2467.89927497537[/C][C]30.3166119511449[/C][/ROW]
[ROW][C]0.8[/C][C]2476.44419048003[/C][C]30.3976419872162[/C][/ROW]
[ROW][C]0.81[/C][C]2485.46304864903[/C][C]31.4529827680949[/C][/ROW]
[ROW][C]0.82[/C][C]2495.36162212412[/C][C]33.9751157480892[/C][/ROW]
[ROW][C]0.83[/C][C]2506.688649551[/C][C]38.3929187716011[/C][/ROW]
[ROW][C]0.84[/C][C]2520.0956214777[/C][C]44.93326738944[/C][/ROW]
[ROW][C]0.85[/C][C]2536.23437654486[/C][C]53.3764418570552[/C][/ROW]
[ROW][C]0.86[/C][C]2555.58011508364[/C][C]62.819640314124[/C][/ROW]
[ROW][C]0.87[/C][C]2578.20735151034[/C][C]71.5980935723966[/C][/ROW]
[ROW][C]0.88[/C][C]2603.60723205363[/C][C]77.5998375660748[/C][/ROW]
[ROW][C]0.89[/C][C]2630.68379003223[/C][C]78.9942721994675[/C][/ROW]
[ROW][C]0.9[/C][C]2658.05875774413[/C][C]75.2168210007715[/C][/ROW]
[ROW][C]0.91[/C][C]2684.72175984628[/C][C]67.7866269459602[/C][/ROW]
[ROW][C]0.92[/C][C]2710.88627473524[/C][C]60.6566621135277[/C][/ROW]
[ROW][C]0.93[/C][C]2738.65790234413[/C][C]59.7019957001062[/C][/ROW]
[ROW][C]0.94[/C][C]2771.83132141196[/C][C]69.2153394374706[/C][/ROW]
[ROW][C]0.95[/C][C]2814.09899756011[/C][C]85.6929177267237[/C][/ROW]
[ROW][C]0.96[/C][C]2865.91620520004[/C][C]97.1889064009632[/C][/ROW]
[ROW][C]0.97[/C][C]2922.6425285365[/C][C]90.8767532112458[/C][/ROW]
[ROW][C]0.98[/C][C]2977.75973681701[/C][C]67.532866289502[/C][/ROW]
[ROW][C]0.99[/C][C]3027.31115260829[/C][C]52.2250933642877[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210845&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210845&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
0.011829.101821138421.5640978888692
0.021851.6756278613240.1794597870167
0.031880.9281583212745.0511647689145
0.041908.970497718441.6727252480616
0.051932.2944989589735.8958134025038
0.061950.9455515437831.6314639156629
0.071966.593456472731.3673018007785
0.081981.2600602088735.4692759444889
0.091996.5884840091242.4092936625597
0.12013.4812419038350.0208396528304
0.112032.033314399956.2446610419144
0.122051.6832081791259.5969712672049
0.132071.4955060207959.4915988795027
0.142090.4802956446856.2789999411213
0.152107.8541980750950.9725569672975
0.162123.177614343844.7981350463903
0.172136.3592811411138.7898188002522
0.182147.5701650890233.595859223417
0.192157.1275504409929.482815686202
0.22165.3962521247126.4733078850967
0.212172.7256310999924.4761663365416
0.222179.4179413547123.3522085529886
0.232185.7143535614422.9174256973193
0.242191.7876528428722.9313801784394
0.252197.7379413269623.1056038236552
0.262203.5934235938523.1573848948408
0.272209.3198274829222.8497679163592
0.282214.839777738922.0623803286718
0.292220.0596535033220.794825755406
0.32224.8983279097819.1617050663408
0.312229.3110926414517.3859087235926
0.322233.3033254754115.7207745476318
0.332236.9314505161514.4091417715561
0.342240.2922988884913.6314286225341
0.352243.5048604505713.4523527119662
0.362246.6897677707213.8154839678305
0.372249.9514683941914.5737894433585
0.382253.3663538469415.5681909811345
0.392256.9779281262616.6402853317531
0.42260.7982170203417.6578895892647
0.412264.8135392847218.5401272036778
0.422268.9925541038919.2310723914072
0.432273.2948957443219.7111687303603
0.442277.6792972842219.9979676963008
0.452282.1105593257220.1367942701907
0.462286.5649104684720.1812854827132
0.472291.0333147206520.2194470228602
0.482295.5222947231720.3241241359351
0.492300.0520201929320.5596012872806
0.52304.6517986518620.9560149712002
0.512309.3536039893521.5129795658783
0.522314.1847142201622.1817904928248
0.532319.160745106822.8890433328354
0.542324.2802934342923.5389349577848
0.552329.5220868033124.0355812572346
0.562334.8450976814324.2884456362426
0.572340.1916522233224.2262609767641
0.582345.4932341636423.8207306289843
0.592350.678458400923.075699680826
0.62355.6825121447922.0355750137165
0.612360.4571638326420.7945797488419
0.622364.9801962348119.4785117056117
0.632369.2628878535618.2544292651807
0.642373.3540781991617.3042833518625
0.652377.3395555643416.8034872146791
0.662381.3360778155316.8925723589223
0.672385.4802190554317.6346543525187
0.682389.9132328591118.9980538557425
0.692394.7639773750720.8648300958574
0.72400.1324444847223.0492143814605
0.712406.0764851885325.335936150237
0.722412.6039714273227.4936010100489
0.732419.6720020917229.3133242220825
0.742427.1939686862630.63713191339
0.752435.0544209578931.3767176207289
0.762443.1307663960231.5459354636633
0.772451.3199943177931.2578483229582
0.782459.5680335765230.741349145698
0.792467.8992749753730.3166119511449
0.82476.4441904800330.3976419872162
0.812485.4630486490331.4529827680949
0.822495.3616221241233.9751157480892
0.832506.68864955138.3929187716011
0.842520.095621477744.93326738944
0.852536.2343765448653.3764418570552
0.862555.5801150836462.819640314124
0.872578.2073515103471.5980935723966
0.882603.6072320536377.5998375660748
0.892630.6837900322378.9942721994675
0.92658.0587577441375.2168210007715
0.912684.7217598462867.7866269459602
0.922710.8862747352460.6566621135277
0.932738.6579023441359.7019957001062
0.942771.8313214119669.2153394374706
0.952814.0989975601185.6929177267237
0.962865.9162052000497.1889064009632
0.972922.642528536590.8767532112458
0.982977.7597368170167.532866289502
0.993027.3111526082952.2250933642877


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
Parameters (R input):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
R code (references can be found in the software module):
par1 <- as(par1,'numeric')
par2 <- as(par2,'numeric')
par3 <- as(par3,'numeric')
library(Hmisc)
myseq <- seq(par1, par2, par3)
hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE)
bitmap(file='test1.png')
plot(myseq,hd,col=2,main=main,xlab=xlab,ylab=ylab)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Harrell-Davis Quantiles',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'quantiles',header=TRUE)
a<-table.element(a,'value',header=TRUE)
a<-table.element(a,'standard error',header=TRUE)
a<-table.row.end(a)
length(hd)
for (i in 1:length(hd))
{
a<-table.row.start(a)
a<-table.element(a,as(labels(hd)[i],'numeric'),header=TRUE)
a<-table.element(a,as.matrix(hd[i])[1,1])
a<-table.element(a,as.matrix(attr(hd,'se')[i])[1,1])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')