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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, 17 Oct 2009 07:44:37 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Oct/17/t125578730213n2dx7uqa7464f.htm/, Retrieved Tue, 10 Feb 2026 09:35:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=47181, Retrieved Tue, 10 Feb 2026 09:35:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W42
Estimated Impact392

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Evolution of real...] [2009-09-28 22:40:28] [ae313ad3bd3ddca83679957b8289cb77]
- RMPD    [Harrell-Davis Quantiles] [Opgave 4.2] [2009-10-17 13:44:37] [3f12ab8801f7554f488f56dad3cd0b03] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
46.5
47
47.5
48.3
49.1
50.1
51.1
52
53.2
53.9
54.5
55.2
55.6
55.7
56.1
56.8
57.5
58.3
58.9
59.4
59.8
60
60
60.3
60.1
59.7
59.5
59.4
59.3
59.2
59.1
59
59.3
59.5
59.5
59.5
59.7
59.7
60.5
60.7
61.3
61.4
61.8
62.4
62.4
62.9
63.2
63.4
63.9
64.5
65
65.4
66.3
67.7
69
70
71.4
72.5
73.4
74.6
75.2
75.9
76.8
77.9
79.2
80.5
82.6
84.4
85.9
87.6

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 Ronald Aylmer Fisher' @ 193.190.124.24

\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 Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=47181&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 Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=47181&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=47181&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 Ronald Aylmer Fisher' @ 193.190.124.24






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0146.68718510421720.534321523404721
0.0247.01403262958910.68069229044594
0.0347.43084727757610.903615741347505
0.0447.91015145659851.14518746145015
0.0548.44004141212891.37358058412236
0.0649.01122109245891.57416862446203
0.0749.61250363085211.73883703488728
0.0850.23124403162561.86206145725230
0.0950.8546267968341.94069672469196
0.151.47064324254541.97452636654988
0.1152.06883713489621.96715214115328
0.1252.6409494730081.92566124830617
0.1353.18141870485761.86031184045687
0.1453.68762051477451.78301796953015
0.1554.15976097472611.70566529301361
0.1654.60041056435891.63823360353155
0.1755.01374458912541.58696057549090
0.1855.40461621636861.55363131295786
0.1955.77762022490631.53501550863363
0.256.13630404344291.52410502949251
0.2156.48264945649261.51191458622699
0.2256.81689133367131.48959476701335
0.2357.1376718574161.45010278166183
0.2457.44246548496561.38955587941754
0.2557.72816537949131.30725952501269
0.2657.9917050108191.20581938286477
0.2758.23060008930681.09019553673163
0.2858.44332958106920.96665391299968
0.2958.62951914291970.841831179825888
0.358.78993387325560.72173340223927
0.3158.92632030855440.611238717409149
0.3259.04115518859020.513659064995319
0.3359.13736058440830.430811576154266
0.3459.21803511290850.363274778740622
0.3559.28623452294160.310539135122913
0.3659.34481725698340.271584575431174
0.3759.39635566174280.244849957578046
0.3859.44310344640530.228795252442742
0.3959.48700509194430.221984485684546
0.459.5297322579470.223078859738945
0.4159.57273426822950.231129281762821
0.4259.6172929149550.245371443308888
0.4359.66457490064320.265276826265445
0.4459.71567756658090.290788403755227
0.4559.77166497365190.321831874200288
0.4659.8335921212370.358602538796863
0.4759.90251551785520.401098821089184
0.4859.97948887771340.449400295201417
0.4960.0655437179510.50322679609793
0.560.16165618347470.562231233543042
0.5160.26870342153330.625677035485538
0.5260.38741496567910.692342526447136
0.5360.5183264435560.760943671688653
0.5460.66174404224980.82994029497558
0.5560.81772817472040.897710548447285
0.5660.98610349175490.96272929746455
0.5761.16649981467461.02398300000877
0.5861.35842501457671.08076736920662
0.5961.56136682913821.13301323686921
0.661.77491668748081.18159267396523
0.6161.99890537606661.22805157116148
0.6262.2335382253611.27471135600272
0.6362.47951656502511.32443647270810
0.6462.73813234023811.38080193027827
0.6563.01132366393121.44723812225812
0.6663.30168034676551.52706618714849
0.6763.61238995952731.62316985956379
0.6863.94711699451651.73745814593135
0.6964.30981087268721.87045092000812
0.764.70444376755482.02136931973062
0.7165.13468713320972.18709879170459
0.7265.6035463209122.36289138389039
0.7366.11298448037822.54201239331390
0.7466.6635776410062.71629588660576
0.7567.25424939779052.87657496416305
0.7667.88213328084053.01361787973485
0.7768.54260239138223.1191241873276
0.7869.22949005943823.18648447877179
0.7969.93550484233243.21173237979801
0.870.65282166252633.19407123742764
0.8171.37381105801443.13625702633498
0.8272.09185135349733.04447902500636
0.8372.80215350057972.92827605635892
0.8473.50251514916912.79990684282748
0.8574.19391158183652.67335427375452
0.8674.88083189034882.56310884431610
0.8775.57128400264982.48209507634219
0.8876.27641869222072.43966950219491
0.8977.00974383417932.43952158588362
0.977.785892780292.47861915777550
0.9178.61887440102842.54688178605313
0.9279.51973577767472.6265755948381
0.9380.49377628333792.69148394816447
0.9481.53803798407472.70731674889038
0.9582.6405513672372.6375559549276
0.9683.78222815860172.45779363054338
0.9784.93694421904052.17817896255544
0.9886.05446282557721.87418951388106
0.9987.01368486929131.68974453601427

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 46.6871851042172 & 0.534321523404721 \tabularnewline
0.02 & 47.0140326295891 & 0.68069229044594 \tabularnewline
0.03 & 47.4308472775761 & 0.903615741347505 \tabularnewline
0.04 & 47.9101514565985 & 1.14518746145015 \tabularnewline
0.05 & 48.4400414121289 & 1.37358058412236 \tabularnewline
0.06 & 49.0112210924589 & 1.57416862446203 \tabularnewline
0.07 & 49.6125036308521 & 1.73883703488728 \tabularnewline
0.08 & 50.2312440316256 & 1.86206145725230 \tabularnewline
0.09 & 50.854626796834 & 1.94069672469196 \tabularnewline
0.1 & 51.4706432425454 & 1.97452636654988 \tabularnewline
0.11 & 52.0688371348962 & 1.96715214115328 \tabularnewline
0.12 & 52.640949473008 & 1.92566124830617 \tabularnewline
0.13 & 53.1814187048576 & 1.86031184045687 \tabularnewline
0.14 & 53.6876205147745 & 1.78301796953015 \tabularnewline
0.15 & 54.1597609747261 & 1.70566529301361 \tabularnewline
0.16 & 54.6004105643589 & 1.63823360353155 \tabularnewline
0.17 & 55.0137445891254 & 1.58696057549090 \tabularnewline
0.18 & 55.4046162163686 & 1.55363131295786 \tabularnewline
0.19 & 55.7776202249063 & 1.53501550863363 \tabularnewline
0.2 & 56.1363040434429 & 1.52410502949251 \tabularnewline
0.21 & 56.4826494564926 & 1.51191458622699 \tabularnewline
0.22 & 56.8168913336713 & 1.48959476701335 \tabularnewline
0.23 & 57.137671857416 & 1.45010278166183 \tabularnewline
0.24 & 57.4424654849656 & 1.38955587941754 \tabularnewline
0.25 & 57.7281653794913 & 1.30725952501269 \tabularnewline
0.26 & 57.991705010819 & 1.20581938286477 \tabularnewline
0.27 & 58.2306000893068 & 1.09019553673163 \tabularnewline
0.28 & 58.4433295810692 & 0.96665391299968 \tabularnewline
0.29 & 58.6295191429197 & 0.841831179825888 \tabularnewline
0.3 & 58.7899338732556 & 0.72173340223927 \tabularnewline
0.31 & 58.9263203085544 & 0.611238717409149 \tabularnewline
0.32 & 59.0411551885902 & 0.513659064995319 \tabularnewline
0.33 & 59.1373605844083 & 0.430811576154266 \tabularnewline
0.34 & 59.2180351129085 & 0.363274778740622 \tabularnewline
0.35 & 59.2862345229416 & 0.310539135122913 \tabularnewline
0.36 & 59.3448172569834 & 0.271584575431174 \tabularnewline
0.37 & 59.3963556617428 & 0.244849957578046 \tabularnewline
0.38 & 59.4431034464053 & 0.228795252442742 \tabularnewline
0.39 & 59.4870050919443 & 0.221984485684546 \tabularnewline
0.4 & 59.529732257947 & 0.223078859738945 \tabularnewline
0.41 & 59.5727342682295 & 0.231129281762821 \tabularnewline
0.42 & 59.617292914955 & 0.245371443308888 \tabularnewline
0.43 & 59.6645749006432 & 0.265276826265445 \tabularnewline
0.44 & 59.7156775665809 & 0.290788403755227 \tabularnewline
0.45 & 59.7716649736519 & 0.321831874200288 \tabularnewline
0.46 & 59.833592121237 & 0.358602538796863 \tabularnewline
0.47 & 59.9025155178552 & 0.401098821089184 \tabularnewline
0.48 & 59.9794888777134 & 0.449400295201417 \tabularnewline
0.49 & 60.065543717951 & 0.50322679609793 \tabularnewline
0.5 & 60.1616561834747 & 0.562231233543042 \tabularnewline
0.51 & 60.2687034215333 & 0.625677035485538 \tabularnewline
0.52 & 60.3874149656791 & 0.692342526447136 \tabularnewline
0.53 & 60.518326443556 & 0.760943671688653 \tabularnewline
0.54 & 60.6617440422498 & 0.82994029497558 \tabularnewline
0.55 & 60.8177281747204 & 0.897710548447285 \tabularnewline
0.56 & 60.9861034917549 & 0.96272929746455 \tabularnewline
0.57 & 61.1664998146746 & 1.02398300000877 \tabularnewline
0.58 & 61.3584250145767 & 1.08076736920662 \tabularnewline
0.59 & 61.5613668291382 & 1.13301323686921 \tabularnewline
0.6 & 61.7749166874808 & 1.18159267396523 \tabularnewline
0.61 & 61.9989053760666 & 1.22805157116148 \tabularnewline
0.62 & 62.233538225361 & 1.27471135600272 \tabularnewline
0.63 & 62.4795165650251 & 1.32443647270810 \tabularnewline
0.64 & 62.7381323402381 & 1.38080193027827 \tabularnewline
0.65 & 63.0113236639312 & 1.44723812225812 \tabularnewline
0.66 & 63.3016803467655 & 1.52706618714849 \tabularnewline
0.67 & 63.6123899595273 & 1.62316985956379 \tabularnewline
0.68 & 63.9471169945165 & 1.73745814593135 \tabularnewline
0.69 & 64.3098108726872 & 1.87045092000812 \tabularnewline
0.7 & 64.7044437675548 & 2.02136931973062 \tabularnewline
0.71 & 65.1346871332097 & 2.18709879170459 \tabularnewline
0.72 & 65.603546320912 & 2.36289138389039 \tabularnewline
0.73 & 66.1129844803782 & 2.54201239331390 \tabularnewline
0.74 & 66.663577641006 & 2.71629588660576 \tabularnewline
0.75 & 67.2542493977905 & 2.87657496416305 \tabularnewline
0.76 & 67.8821332808405 & 3.01361787973485 \tabularnewline
0.77 & 68.5426023913822 & 3.1191241873276 \tabularnewline
0.78 & 69.2294900594382 & 3.18648447877179 \tabularnewline
0.79 & 69.9355048423324 & 3.21173237979801 \tabularnewline
0.8 & 70.6528216625263 & 3.19407123742764 \tabularnewline
0.81 & 71.3738110580144 & 3.13625702633498 \tabularnewline
0.82 & 72.0918513534973 & 3.04447902500636 \tabularnewline
0.83 & 72.8021535005797 & 2.92827605635892 \tabularnewline
0.84 & 73.5025151491691 & 2.79990684282748 \tabularnewline
0.85 & 74.1939115818365 & 2.67335427375452 \tabularnewline
0.86 & 74.8808318903488 & 2.56310884431610 \tabularnewline
0.87 & 75.5712840026498 & 2.48209507634219 \tabularnewline
0.88 & 76.2764186922207 & 2.43966950219491 \tabularnewline
0.89 & 77.0097438341793 & 2.43952158588362 \tabularnewline
0.9 & 77.78589278029 & 2.47861915777550 \tabularnewline
0.91 & 78.6188744010284 & 2.54688178605313 \tabularnewline
0.92 & 79.5197357776747 & 2.6265755948381 \tabularnewline
0.93 & 80.4937762833379 & 2.69148394816447 \tabularnewline
0.94 & 81.5380379840747 & 2.70731674889038 \tabularnewline
0.95 & 82.640551367237 & 2.6375559549276 \tabularnewline
0.96 & 83.7822281586017 & 2.45779363054338 \tabularnewline
0.97 & 84.9369442190405 & 2.17817896255544 \tabularnewline
0.98 & 86.0544628255772 & 1.87418951388106 \tabularnewline
0.99 & 87.0136848692913 & 1.68974453601427 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=47181&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]46.6871851042172[/C][C]0.534321523404721[/C][/ROW]
[ROW][C]0.02[/C][C]47.0140326295891[/C][C]0.68069229044594[/C][/ROW]
[ROW][C]0.03[/C][C]47.4308472775761[/C][C]0.903615741347505[/C][/ROW]
[ROW][C]0.04[/C][C]47.9101514565985[/C][C]1.14518746145015[/C][/ROW]
[ROW][C]0.05[/C][C]48.4400414121289[/C][C]1.37358058412236[/C][/ROW]
[ROW][C]0.06[/C][C]49.0112210924589[/C][C]1.57416862446203[/C][/ROW]
[ROW][C]0.07[/C][C]49.6125036308521[/C][C]1.73883703488728[/C][/ROW]
[ROW][C]0.08[/C][C]50.2312440316256[/C][C]1.86206145725230[/C][/ROW]
[ROW][C]0.09[/C][C]50.854626796834[/C][C]1.94069672469196[/C][/ROW]
[ROW][C]0.1[/C][C]51.4706432425454[/C][C]1.97452636654988[/C][/ROW]
[ROW][C]0.11[/C][C]52.0688371348962[/C][C]1.96715214115328[/C][/ROW]
[ROW][C]0.12[/C][C]52.640949473008[/C][C]1.92566124830617[/C][/ROW]
[ROW][C]0.13[/C][C]53.1814187048576[/C][C]1.86031184045687[/C][/ROW]
[ROW][C]0.14[/C][C]53.6876205147745[/C][C]1.78301796953015[/C][/ROW]
[ROW][C]0.15[/C][C]54.1597609747261[/C][C]1.70566529301361[/C][/ROW]
[ROW][C]0.16[/C][C]54.6004105643589[/C][C]1.63823360353155[/C][/ROW]
[ROW][C]0.17[/C][C]55.0137445891254[/C][C]1.58696057549090[/C][/ROW]
[ROW][C]0.18[/C][C]55.4046162163686[/C][C]1.55363131295786[/C][/ROW]
[ROW][C]0.19[/C][C]55.7776202249063[/C][C]1.53501550863363[/C][/ROW]
[ROW][C]0.2[/C][C]56.1363040434429[/C][C]1.52410502949251[/C][/ROW]
[ROW][C]0.21[/C][C]56.4826494564926[/C][C]1.51191458622699[/C][/ROW]
[ROW][C]0.22[/C][C]56.8168913336713[/C][C]1.48959476701335[/C][/ROW]
[ROW][C]0.23[/C][C]57.137671857416[/C][C]1.45010278166183[/C][/ROW]
[ROW][C]0.24[/C][C]57.4424654849656[/C][C]1.38955587941754[/C][/ROW]
[ROW][C]0.25[/C][C]57.7281653794913[/C][C]1.30725952501269[/C][/ROW]
[ROW][C]0.26[/C][C]57.991705010819[/C][C]1.20581938286477[/C][/ROW]
[ROW][C]0.27[/C][C]58.2306000893068[/C][C]1.09019553673163[/C][/ROW]
[ROW][C]0.28[/C][C]58.4433295810692[/C][C]0.96665391299968[/C][/ROW]
[ROW][C]0.29[/C][C]58.6295191429197[/C][C]0.841831179825888[/C][/ROW]
[ROW][C]0.3[/C][C]58.7899338732556[/C][C]0.72173340223927[/C][/ROW]
[ROW][C]0.31[/C][C]58.9263203085544[/C][C]0.611238717409149[/C][/ROW]
[ROW][C]0.32[/C][C]59.0411551885902[/C][C]0.513659064995319[/C][/ROW]
[ROW][C]0.33[/C][C]59.1373605844083[/C][C]0.430811576154266[/C][/ROW]
[ROW][C]0.34[/C][C]59.2180351129085[/C][C]0.363274778740622[/C][/ROW]
[ROW][C]0.35[/C][C]59.2862345229416[/C][C]0.310539135122913[/C][/ROW]
[ROW][C]0.36[/C][C]59.3448172569834[/C][C]0.271584575431174[/C][/ROW]
[ROW][C]0.37[/C][C]59.3963556617428[/C][C]0.244849957578046[/C][/ROW]
[ROW][C]0.38[/C][C]59.4431034464053[/C][C]0.228795252442742[/C][/ROW]
[ROW][C]0.39[/C][C]59.4870050919443[/C][C]0.221984485684546[/C][/ROW]
[ROW][C]0.4[/C][C]59.529732257947[/C][C]0.223078859738945[/C][/ROW]
[ROW][C]0.41[/C][C]59.5727342682295[/C][C]0.231129281762821[/C][/ROW]
[ROW][C]0.42[/C][C]59.617292914955[/C][C]0.245371443308888[/C][/ROW]
[ROW][C]0.43[/C][C]59.6645749006432[/C][C]0.265276826265445[/C][/ROW]
[ROW][C]0.44[/C][C]59.7156775665809[/C][C]0.290788403755227[/C][/ROW]
[ROW][C]0.45[/C][C]59.7716649736519[/C][C]0.321831874200288[/C][/ROW]
[ROW][C]0.46[/C][C]59.833592121237[/C][C]0.358602538796863[/C][/ROW]
[ROW][C]0.47[/C][C]59.9025155178552[/C][C]0.401098821089184[/C][/ROW]
[ROW][C]0.48[/C][C]59.9794888777134[/C][C]0.449400295201417[/C][/ROW]
[ROW][C]0.49[/C][C]60.065543717951[/C][C]0.50322679609793[/C][/ROW]
[ROW][C]0.5[/C][C]60.1616561834747[/C][C]0.562231233543042[/C][/ROW]
[ROW][C]0.51[/C][C]60.2687034215333[/C][C]0.625677035485538[/C][/ROW]
[ROW][C]0.52[/C][C]60.3874149656791[/C][C]0.692342526447136[/C][/ROW]
[ROW][C]0.53[/C][C]60.518326443556[/C][C]0.760943671688653[/C][/ROW]
[ROW][C]0.54[/C][C]60.6617440422498[/C][C]0.82994029497558[/C][/ROW]
[ROW][C]0.55[/C][C]60.8177281747204[/C][C]0.897710548447285[/C][/ROW]
[ROW][C]0.56[/C][C]60.9861034917549[/C][C]0.96272929746455[/C][/ROW]
[ROW][C]0.57[/C][C]61.1664998146746[/C][C]1.02398300000877[/C][/ROW]
[ROW][C]0.58[/C][C]61.3584250145767[/C][C]1.08076736920662[/C][/ROW]
[ROW][C]0.59[/C][C]61.5613668291382[/C][C]1.13301323686921[/C][/ROW]
[ROW][C]0.6[/C][C]61.7749166874808[/C][C]1.18159267396523[/C][/ROW]
[ROW][C]0.61[/C][C]61.9989053760666[/C][C]1.22805157116148[/C][/ROW]
[ROW][C]0.62[/C][C]62.233538225361[/C][C]1.27471135600272[/C][/ROW]
[ROW][C]0.63[/C][C]62.4795165650251[/C][C]1.32443647270810[/C][/ROW]
[ROW][C]0.64[/C][C]62.7381323402381[/C][C]1.38080193027827[/C][/ROW]
[ROW][C]0.65[/C][C]63.0113236639312[/C][C]1.44723812225812[/C][/ROW]
[ROW][C]0.66[/C][C]63.3016803467655[/C][C]1.52706618714849[/C][/ROW]
[ROW][C]0.67[/C][C]63.6123899595273[/C][C]1.62316985956379[/C][/ROW]
[ROW][C]0.68[/C][C]63.9471169945165[/C][C]1.73745814593135[/C][/ROW]
[ROW][C]0.69[/C][C]64.3098108726872[/C][C]1.87045092000812[/C][/ROW]
[ROW][C]0.7[/C][C]64.7044437675548[/C][C]2.02136931973062[/C][/ROW]
[ROW][C]0.71[/C][C]65.1346871332097[/C][C]2.18709879170459[/C][/ROW]
[ROW][C]0.72[/C][C]65.603546320912[/C][C]2.36289138389039[/C][/ROW]
[ROW][C]0.73[/C][C]66.1129844803782[/C][C]2.54201239331390[/C][/ROW]
[ROW][C]0.74[/C][C]66.663577641006[/C][C]2.71629588660576[/C][/ROW]
[ROW][C]0.75[/C][C]67.2542493977905[/C][C]2.87657496416305[/C][/ROW]
[ROW][C]0.76[/C][C]67.8821332808405[/C][C]3.01361787973485[/C][/ROW]
[ROW][C]0.77[/C][C]68.5426023913822[/C][C]3.1191241873276[/C][/ROW]
[ROW][C]0.78[/C][C]69.2294900594382[/C][C]3.18648447877179[/C][/ROW]
[ROW][C]0.79[/C][C]69.9355048423324[/C][C]3.21173237979801[/C][/ROW]
[ROW][C]0.8[/C][C]70.6528216625263[/C][C]3.19407123742764[/C][/ROW]
[ROW][C]0.81[/C][C]71.3738110580144[/C][C]3.13625702633498[/C][/ROW]
[ROW][C]0.82[/C][C]72.0918513534973[/C][C]3.04447902500636[/C][/ROW]
[ROW][C]0.83[/C][C]72.8021535005797[/C][C]2.92827605635892[/C][/ROW]
[ROW][C]0.84[/C][C]73.5025151491691[/C][C]2.79990684282748[/C][/ROW]
[ROW][C]0.85[/C][C]74.1939115818365[/C][C]2.67335427375452[/C][/ROW]
[ROW][C]0.86[/C][C]74.8808318903488[/C][C]2.56310884431610[/C][/ROW]
[ROW][C]0.87[/C][C]75.5712840026498[/C][C]2.48209507634219[/C][/ROW]
[ROW][C]0.88[/C][C]76.2764186922207[/C][C]2.43966950219491[/C][/ROW]
[ROW][C]0.89[/C][C]77.0097438341793[/C][C]2.43952158588362[/C][/ROW]
[ROW][C]0.9[/C][C]77.78589278029[/C][C]2.47861915777550[/C][/ROW]
[ROW][C]0.91[/C][C]78.6188744010284[/C][C]2.54688178605313[/C][/ROW]
[ROW][C]0.92[/C][C]79.5197357776747[/C][C]2.6265755948381[/C][/ROW]
[ROW][C]0.93[/C][C]80.4937762833379[/C][C]2.69148394816447[/C][/ROW]
[ROW][C]0.94[/C][C]81.5380379840747[/C][C]2.70731674889038[/C][/ROW]
[ROW][C]0.95[/C][C]82.640551367237[/C][C]2.6375559549276[/C][/ROW]
[ROW][C]0.96[/C][C]83.7822281586017[/C][C]2.45779363054338[/C][/ROW]
[ROW][C]0.97[/C][C]84.9369442190405[/C][C]2.17817896255544[/C][/ROW]
[ROW][C]0.98[/C][C]86.0544628255772[/C][C]1.87418951388106[/C][/ROW]
[ROW][C]0.99[/C][C]87.0136848692913[/C][C]1.68974453601427[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=47181&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=47181&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
0.0146.68718510421720.534321523404721
0.0247.01403262958910.68069229044594
0.0347.43084727757610.903615741347505
0.0447.91015145659851.14518746145015
0.0548.44004141212891.37358058412236
0.0649.01122109245891.57416862446203
0.0749.61250363085211.73883703488728
0.0850.23124403162561.86206145725230
0.0950.8546267968341.94069672469196
0.151.47064324254541.97452636654988
0.1152.06883713489621.96715214115328
0.1252.6409494730081.92566124830617
0.1353.18141870485761.86031184045687
0.1453.68762051477451.78301796953015
0.1554.15976097472611.70566529301361
0.1654.60041056435891.63823360353155
0.1755.01374458912541.58696057549090
0.1855.40461621636861.55363131295786
0.1955.77762022490631.53501550863363
0.256.13630404344291.52410502949251
0.2156.48264945649261.51191458622699
0.2256.81689133367131.48959476701335
0.2357.1376718574161.45010278166183
0.2457.44246548496561.38955587941754
0.2557.72816537949131.30725952501269
0.2657.9917050108191.20581938286477
0.2758.23060008930681.09019553673163
0.2858.44332958106920.96665391299968
0.2958.62951914291970.841831179825888
0.358.78993387325560.72173340223927
0.3158.92632030855440.611238717409149
0.3259.04115518859020.513659064995319
0.3359.13736058440830.430811576154266
0.3459.21803511290850.363274778740622
0.3559.28623452294160.310539135122913
0.3659.34481725698340.271584575431174
0.3759.39635566174280.244849957578046
0.3859.44310344640530.228795252442742
0.3959.48700509194430.221984485684546
0.459.5297322579470.223078859738945
0.4159.57273426822950.231129281762821
0.4259.6172929149550.245371443308888
0.4359.66457490064320.265276826265445
0.4459.71567756658090.290788403755227
0.4559.77166497365190.321831874200288
0.4659.8335921212370.358602538796863
0.4759.90251551785520.401098821089184
0.4859.97948887771340.449400295201417
0.4960.0655437179510.50322679609793
0.560.16165618347470.562231233543042
0.5160.26870342153330.625677035485538
0.5260.38741496567910.692342526447136
0.5360.5183264435560.760943671688653
0.5460.66174404224980.82994029497558
0.5560.81772817472040.897710548447285
0.5660.98610349175490.96272929746455
0.5761.16649981467461.02398300000877
0.5861.35842501457671.08076736920662
0.5961.56136682913821.13301323686921
0.661.77491668748081.18159267396523
0.6161.99890537606661.22805157116148
0.6262.2335382253611.27471135600272
0.6362.47951656502511.32443647270810
0.6462.73813234023811.38080193027827
0.6563.01132366393121.44723812225812
0.6663.30168034676551.52706618714849
0.6763.61238995952731.62316985956379
0.6863.94711699451651.73745814593135
0.6964.30981087268721.87045092000812
0.764.70444376755482.02136931973062
0.7165.13468713320972.18709879170459
0.7265.6035463209122.36289138389039
0.7366.11298448037822.54201239331390
0.7466.6635776410062.71629588660576
0.7567.25424939779052.87657496416305
0.7667.88213328084053.01361787973485
0.7768.54260239138223.1191241873276
0.7869.22949005943823.18648447877179
0.7969.93550484233243.21173237979801
0.870.65282166252633.19407123742764
0.8171.37381105801443.13625702633498
0.8272.09185135349733.04447902500636
0.8372.80215350057972.92827605635892
0.8473.50251514916912.79990684282748
0.8574.19391158183652.67335427375452
0.8674.88083189034882.56310884431610
0.8775.57128400264982.48209507634219
0.8876.27641869222072.43966950219491
0.8977.00974383417932.43952158588362
0.977.785892780292.47861915777550
0.9178.61887440102842.54688178605313
0.9279.51973577767472.6265755948381
0.9380.49377628333792.69148394816447
0.9481.53803798407472.70731674889038
0.9582.6405513672372.6375559549276
0.9683.78222815860172.45779363054338
0.9784.93694421904052.17817896255544
0.9886.05446282557721.87418951388106
0.9987.01368486929131.68974453601427


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')