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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 computationThu, 09 Dec 2010 20:51:35 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/09/t1291928451ve5qwxa8ulfw6j5.htm/, Retrieved Mon, 29 Apr 2024 04:29:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107409, Retrieved Mon, 29 Apr 2024 04:29:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W51 - Evi Van Dingenen
Estimated Impact146

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] [opdracht 5 verbet...] [2010-12-09 20:51:35] [89ec97ab3733ab465a33f3d446b0a375] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
84.9
81.9
95.9
81
89.2
102.5
89.8
88.8
83.2
90.2
100.4
187.1
87.6
85.4
86.1
86.7
89.1
103.7
86.9
85.2
80.8
91.2
102.8
182.5
80.9
83.1
88.3
86.6
93
105.3
93.8
86.4
87
96.7
100.5
196.7
86.8
88.2
93.8
85
90.4
115.9
94.9
87.7
91.7
95.9
106.8
204.5
90.2
90.5
93.2
97.8
99.4
120
108.2
98.5
104.3
102.9
111.1
188.1
93.8
94.5
112.4
102.5
115.8
136.5
122.1
110.6
116.4
112.6
121.5
199.3
102.1
100.6
119
106.8
121.3
145.5
129.7
117.7
121.3
124.3
135.2
210.1
106.8
110.5
111.5
122.1
126.3
143.2
137.3
121.5
121.9
123.9
131.6
220.9

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=107409&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=107409&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107409&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
0.0180.91089511297070.264140778713976
0.0281.19974723562750.651643324645015
0.0381.6781611220921.04228944179159
0.0482.29352906392631.28668064337723
0.0582.96103305930851.36826399355786
0.0683.60781083230411.33294543119456
0.0784.19192186217121.23228682345921
0.0884.69913144307331.10998304097338
0.0985.13269309596280.997040901372885
0.185.504013882340.906576197622019
0.1185.82629054874680.837270590623005
0.1286.11142346477570.785070379987132
0.1386.36955245347310.751063001651906
0.1486.60978080818260.740582113658735
0.1586.8407198174440.757080403620823
0.1687.07028641631660.798593696431464
0.1787.30499241181750.857999006235907
0.1887.5492821899650.925852332037899
0.1987.80532924956160.993953102797853
0.288.07337759521821.05733241004964
0.2188.35245994596851.11376606913667
0.2288.64123023696351.16467787110283
0.2388.93868015070041.21376345964064
0.2489.24459641721821.26515972112092
0.2589.559704157591.32362141719294
0.2689.88551261688121.39209704363219
0.2790.22393540911551.47096490846190
0.2890.5768013440321.55833054800492
0.2990.94539783711811.64966920632799
0.391.33018369089421.73958698164629
0.3191.730762965431.82382029304934
0.3292.1461329198441.9001127273832
0.3392.57512958684561.96949637692014
0.3493.01692587165222.03576096612150
0.3593.47141513786052.10443080515167
0.3693.93934683419682.18062231391355
0.3794.42215774259452.26740910637006
0.3894.9215356808972.36439160296195
0.3995.43883120519132.4676531570732
0.495.97447424359172.56993478652623
0.4196.52754852351462.66297204413099
0.4297.09563371242832.73854295002671
0.4397.67495962091582.79031739191045
0.4498.2608475481082.81476734605854
0.4598.84835666282722.81251840398302
0.4699.4330177707692.78783171788475
0.47100.0115260037432.7482555540169
0.48100.5822760190492.70387036716280
0.49101.1456534351992.66561552352997
0.5101.7040383404842.64384077931882
0.51102.261524154842.64672586131304
0.52102.8234010141042.67921985557999
0.53103.3954903101242.74167393235363
0.54103.983439912032.83051188815585
0.55104.5920936415332.93964089884404
0.56105.2250325598523.06034581772522
0.57105.8843519702003.18433260202398
0.58106.5706924683813.30436308614936
0.59107.2834937890623.41481660790639
0.6108.0213953406923.51345931342491
0.61108.7826756405813.59993018230714
0.62109.5656115226743.67559685247639
0.63110.3686516936623.74294562955315
0.64111.1903385828973.80296003123669
0.65112.0289725362983.85468700741477
0.66112.8820825150503.89377489997076
0.67113.7458329131423.91276266607769
0.68114.6145419497033.90199345963149
0.69115.4805018972923.85178624025558
0.7116.3342694307253.75445454111729
0.71117.1655354294953.60738026716368
0.72117.9645917874023.41470972285439
0.73118.7242963402723.18940153062176
0.74119.4423095046182.95439557498417
0.75120.1232584892852.74132686204119
0.76120.7804052206492.59042870478883
0.77121.4363857375912.54482554524060
0.78122.1226878122632.64226410774262
0.79122.8777782873132.90326724060159
0.8123.7442196901693.32554987229399
0.81124.7657413838623.88811985998925
0.82125.9859774196594.56384644640732
0.83127.4511605811495.33702406582236
0.84129.2188339167236.22856165375716
0.85131.3726559437847.32260975978354
0.86134.0388495520868.773921137945
0.87137.39332884175810.7599848920342
0.88141.64343310512213.3569006327108
0.89146.97106582768316.3847124260696
0.9153.44122127406919.3237209505618
0.91160.90956465949621.3975278129383
0.92168.98762554962721.8610441226287
0.93177.11659514273520.3957595072942
0.94184.74724101407217.3678602461699
0.95191.5530339468513.7200002199793
0.96197.58072333621710.517764324444
0.97203.2922203248018.48135007530188
0.98209.4103638725337.91174764136438
0.99216.0486696492808.9817876984224

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 80.9108951129707 & 0.264140778713976 \tabularnewline
0.02 & 81.1997472356275 & 0.651643324645015 \tabularnewline
0.03 & 81.678161122092 & 1.04228944179159 \tabularnewline
0.04 & 82.2935290639263 & 1.28668064337723 \tabularnewline
0.05 & 82.9610330593085 & 1.36826399355786 \tabularnewline
0.06 & 83.6078108323041 & 1.33294543119456 \tabularnewline
0.07 & 84.1919218621712 & 1.23228682345921 \tabularnewline
0.08 & 84.6991314430733 & 1.10998304097338 \tabularnewline
0.09 & 85.1326930959628 & 0.997040901372885 \tabularnewline
0.1 & 85.50401388234 & 0.906576197622019 \tabularnewline
0.11 & 85.8262905487468 & 0.837270590623005 \tabularnewline
0.12 & 86.1114234647757 & 0.785070379987132 \tabularnewline
0.13 & 86.3695524534731 & 0.751063001651906 \tabularnewline
0.14 & 86.6097808081826 & 0.740582113658735 \tabularnewline
0.15 & 86.840719817444 & 0.757080403620823 \tabularnewline
0.16 & 87.0702864163166 & 0.798593696431464 \tabularnewline
0.17 & 87.3049924118175 & 0.857999006235907 \tabularnewline
0.18 & 87.549282189965 & 0.925852332037899 \tabularnewline
0.19 & 87.8053292495616 & 0.993953102797853 \tabularnewline
0.2 & 88.0733775952182 & 1.05733241004964 \tabularnewline
0.21 & 88.3524599459685 & 1.11376606913667 \tabularnewline
0.22 & 88.6412302369635 & 1.16467787110283 \tabularnewline
0.23 & 88.9386801507004 & 1.21376345964064 \tabularnewline
0.24 & 89.2445964172182 & 1.26515972112092 \tabularnewline
0.25 & 89.55970415759 & 1.32362141719294 \tabularnewline
0.26 & 89.8855126168812 & 1.39209704363219 \tabularnewline
0.27 & 90.2239354091155 & 1.47096490846190 \tabularnewline
0.28 & 90.576801344032 & 1.55833054800492 \tabularnewline
0.29 & 90.9453978371181 & 1.64966920632799 \tabularnewline
0.3 & 91.3301836908942 & 1.73958698164629 \tabularnewline
0.31 & 91.73076296543 & 1.82382029304934 \tabularnewline
0.32 & 92.146132919844 & 1.9001127273832 \tabularnewline
0.33 & 92.5751295868456 & 1.96949637692014 \tabularnewline
0.34 & 93.0169258716522 & 2.03576096612150 \tabularnewline
0.35 & 93.4714151378605 & 2.10443080515167 \tabularnewline
0.36 & 93.9393468341968 & 2.18062231391355 \tabularnewline
0.37 & 94.4221577425945 & 2.26740910637006 \tabularnewline
0.38 & 94.921535680897 & 2.36439160296195 \tabularnewline
0.39 & 95.4388312051913 & 2.4676531570732 \tabularnewline
0.4 & 95.9744742435917 & 2.56993478652623 \tabularnewline
0.41 & 96.5275485235146 & 2.66297204413099 \tabularnewline
0.42 & 97.0956337124283 & 2.73854295002671 \tabularnewline
0.43 & 97.6749596209158 & 2.79031739191045 \tabularnewline
0.44 & 98.260847548108 & 2.81476734605854 \tabularnewline
0.45 & 98.8483566628272 & 2.81251840398302 \tabularnewline
0.46 & 99.433017770769 & 2.78783171788475 \tabularnewline
0.47 & 100.011526003743 & 2.7482555540169 \tabularnewline
0.48 & 100.582276019049 & 2.70387036716280 \tabularnewline
0.49 & 101.145653435199 & 2.66561552352997 \tabularnewline
0.5 & 101.704038340484 & 2.64384077931882 \tabularnewline
0.51 & 102.26152415484 & 2.64672586131304 \tabularnewline
0.52 & 102.823401014104 & 2.67921985557999 \tabularnewline
0.53 & 103.395490310124 & 2.74167393235363 \tabularnewline
0.54 & 103.98343991203 & 2.83051188815585 \tabularnewline
0.55 & 104.592093641533 & 2.93964089884404 \tabularnewline
0.56 & 105.225032559852 & 3.06034581772522 \tabularnewline
0.57 & 105.884351970200 & 3.18433260202398 \tabularnewline
0.58 & 106.570692468381 & 3.30436308614936 \tabularnewline
0.59 & 107.283493789062 & 3.41481660790639 \tabularnewline
0.6 & 108.021395340692 & 3.51345931342491 \tabularnewline
0.61 & 108.782675640581 & 3.59993018230714 \tabularnewline
0.62 & 109.565611522674 & 3.67559685247639 \tabularnewline
0.63 & 110.368651693662 & 3.74294562955315 \tabularnewline
0.64 & 111.190338582897 & 3.80296003123669 \tabularnewline
0.65 & 112.028972536298 & 3.85468700741477 \tabularnewline
0.66 & 112.882082515050 & 3.89377489997076 \tabularnewline
0.67 & 113.745832913142 & 3.91276266607769 \tabularnewline
0.68 & 114.614541949703 & 3.90199345963149 \tabularnewline
0.69 & 115.480501897292 & 3.85178624025558 \tabularnewline
0.7 & 116.334269430725 & 3.75445454111729 \tabularnewline
0.71 & 117.165535429495 & 3.60738026716368 \tabularnewline
0.72 & 117.964591787402 & 3.41470972285439 \tabularnewline
0.73 & 118.724296340272 & 3.18940153062176 \tabularnewline
0.74 & 119.442309504618 & 2.95439557498417 \tabularnewline
0.75 & 120.123258489285 & 2.74132686204119 \tabularnewline
0.76 & 120.780405220649 & 2.59042870478883 \tabularnewline
0.77 & 121.436385737591 & 2.54482554524060 \tabularnewline
0.78 & 122.122687812263 & 2.64226410774262 \tabularnewline
0.79 & 122.877778287313 & 2.90326724060159 \tabularnewline
0.8 & 123.744219690169 & 3.32554987229399 \tabularnewline
0.81 & 124.765741383862 & 3.88811985998925 \tabularnewline
0.82 & 125.985977419659 & 4.56384644640732 \tabularnewline
0.83 & 127.451160581149 & 5.33702406582236 \tabularnewline
0.84 & 129.218833916723 & 6.22856165375716 \tabularnewline
0.85 & 131.372655943784 & 7.32260975978354 \tabularnewline
0.86 & 134.038849552086 & 8.773921137945 \tabularnewline
0.87 & 137.393328841758 & 10.7599848920342 \tabularnewline
0.88 & 141.643433105122 & 13.3569006327108 \tabularnewline
0.89 & 146.971065827683 & 16.3847124260696 \tabularnewline
0.9 & 153.441221274069 & 19.3237209505618 \tabularnewline
0.91 & 160.909564659496 & 21.3975278129383 \tabularnewline
0.92 & 168.987625549627 & 21.8610441226287 \tabularnewline
0.93 & 177.116595142735 & 20.3957595072942 \tabularnewline
0.94 & 184.747241014072 & 17.3678602461699 \tabularnewline
0.95 & 191.55303394685 & 13.7200002199793 \tabularnewline
0.96 & 197.580723336217 & 10.517764324444 \tabularnewline
0.97 & 203.292220324801 & 8.48135007530188 \tabularnewline
0.98 & 209.410363872533 & 7.91174764136438 \tabularnewline
0.99 & 216.048669649280 & 8.9817876984224 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107409&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]80.9108951129707[/C][C]0.264140778713976[/C][/ROW]
[ROW][C]0.02[/C][C]81.1997472356275[/C][C]0.651643324645015[/C][/ROW]
[ROW][C]0.03[/C][C]81.678161122092[/C][C]1.04228944179159[/C][/ROW]
[ROW][C]0.04[/C][C]82.2935290639263[/C][C]1.28668064337723[/C][/ROW]
[ROW][C]0.05[/C][C]82.9610330593085[/C][C]1.36826399355786[/C][/ROW]
[ROW][C]0.06[/C][C]83.6078108323041[/C][C]1.33294543119456[/C][/ROW]
[ROW][C]0.07[/C][C]84.1919218621712[/C][C]1.23228682345921[/C][/ROW]
[ROW][C]0.08[/C][C]84.6991314430733[/C][C]1.10998304097338[/C][/ROW]
[ROW][C]0.09[/C][C]85.1326930959628[/C][C]0.997040901372885[/C][/ROW]
[ROW][C]0.1[/C][C]85.50401388234[/C][C]0.906576197622019[/C][/ROW]
[ROW][C]0.11[/C][C]85.8262905487468[/C][C]0.837270590623005[/C][/ROW]
[ROW][C]0.12[/C][C]86.1114234647757[/C][C]0.785070379987132[/C][/ROW]
[ROW][C]0.13[/C][C]86.3695524534731[/C][C]0.751063001651906[/C][/ROW]
[ROW][C]0.14[/C][C]86.6097808081826[/C][C]0.740582113658735[/C][/ROW]
[ROW][C]0.15[/C][C]86.840719817444[/C][C]0.757080403620823[/C][/ROW]
[ROW][C]0.16[/C][C]87.0702864163166[/C][C]0.798593696431464[/C][/ROW]
[ROW][C]0.17[/C][C]87.3049924118175[/C][C]0.857999006235907[/C][/ROW]
[ROW][C]0.18[/C][C]87.549282189965[/C][C]0.925852332037899[/C][/ROW]
[ROW][C]0.19[/C][C]87.8053292495616[/C][C]0.993953102797853[/C][/ROW]
[ROW][C]0.2[/C][C]88.0733775952182[/C][C]1.05733241004964[/C][/ROW]
[ROW][C]0.21[/C][C]88.3524599459685[/C][C]1.11376606913667[/C][/ROW]
[ROW][C]0.22[/C][C]88.6412302369635[/C][C]1.16467787110283[/C][/ROW]
[ROW][C]0.23[/C][C]88.9386801507004[/C][C]1.21376345964064[/C][/ROW]
[ROW][C]0.24[/C][C]89.2445964172182[/C][C]1.26515972112092[/C][/ROW]
[ROW][C]0.25[/C][C]89.55970415759[/C][C]1.32362141719294[/C][/ROW]
[ROW][C]0.26[/C][C]89.8855126168812[/C][C]1.39209704363219[/C][/ROW]
[ROW][C]0.27[/C][C]90.2239354091155[/C][C]1.47096490846190[/C][/ROW]
[ROW][C]0.28[/C][C]90.576801344032[/C][C]1.55833054800492[/C][/ROW]
[ROW][C]0.29[/C][C]90.9453978371181[/C][C]1.64966920632799[/C][/ROW]
[ROW][C]0.3[/C][C]91.3301836908942[/C][C]1.73958698164629[/C][/ROW]
[ROW][C]0.31[/C][C]91.73076296543[/C][C]1.82382029304934[/C][/ROW]
[ROW][C]0.32[/C][C]92.146132919844[/C][C]1.9001127273832[/C][/ROW]
[ROW][C]0.33[/C][C]92.5751295868456[/C][C]1.96949637692014[/C][/ROW]
[ROW][C]0.34[/C][C]93.0169258716522[/C][C]2.03576096612150[/C][/ROW]
[ROW][C]0.35[/C][C]93.4714151378605[/C][C]2.10443080515167[/C][/ROW]
[ROW][C]0.36[/C][C]93.9393468341968[/C][C]2.18062231391355[/C][/ROW]
[ROW][C]0.37[/C][C]94.4221577425945[/C][C]2.26740910637006[/C][/ROW]
[ROW][C]0.38[/C][C]94.921535680897[/C][C]2.36439160296195[/C][/ROW]
[ROW][C]0.39[/C][C]95.4388312051913[/C][C]2.4676531570732[/C][/ROW]
[ROW][C]0.4[/C][C]95.9744742435917[/C][C]2.56993478652623[/C][/ROW]
[ROW][C]0.41[/C][C]96.5275485235146[/C][C]2.66297204413099[/C][/ROW]
[ROW][C]0.42[/C][C]97.0956337124283[/C][C]2.73854295002671[/C][/ROW]
[ROW][C]0.43[/C][C]97.6749596209158[/C][C]2.79031739191045[/C][/ROW]
[ROW][C]0.44[/C][C]98.260847548108[/C][C]2.81476734605854[/C][/ROW]
[ROW][C]0.45[/C][C]98.8483566628272[/C][C]2.81251840398302[/C][/ROW]
[ROW][C]0.46[/C][C]99.433017770769[/C][C]2.78783171788475[/C][/ROW]
[ROW][C]0.47[/C][C]100.011526003743[/C][C]2.7482555540169[/C][/ROW]
[ROW][C]0.48[/C][C]100.582276019049[/C][C]2.70387036716280[/C][/ROW]
[ROW][C]0.49[/C][C]101.145653435199[/C][C]2.66561552352997[/C][/ROW]
[ROW][C]0.5[/C][C]101.704038340484[/C][C]2.64384077931882[/C][/ROW]
[ROW][C]0.51[/C][C]102.26152415484[/C][C]2.64672586131304[/C][/ROW]
[ROW][C]0.52[/C][C]102.823401014104[/C][C]2.67921985557999[/C][/ROW]
[ROW][C]0.53[/C][C]103.395490310124[/C][C]2.74167393235363[/C][/ROW]
[ROW][C]0.54[/C][C]103.98343991203[/C][C]2.83051188815585[/C][/ROW]
[ROW][C]0.55[/C][C]104.592093641533[/C][C]2.93964089884404[/C][/ROW]
[ROW][C]0.56[/C][C]105.225032559852[/C][C]3.06034581772522[/C][/ROW]
[ROW][C]0.57[/C][C]105.884351970200[/C][C]3.18433260202398[/C][/ROW]
[ROW][C]0.58[/C][C]106.570692468381[/C][C]3.30436308614936[/C][/ROW]
[ROW][C]0.59[/C][C]107.283493789062[/C][C]3.41481660790639[/C][/ROW]
[ROW][C]0.6[/C][C]108.021395340692[/C][C]3.51345931342491[/C][/ROW]
[ROW][C]0.61[/C][C]108.782675640581[/C][C]3.59993018230714[/C][/ROW]
[ROW][C]0.62[/C][C]109.565611522674[/C][C]3.67559685247639[/C][/ROW]
[ROW][C]0.63[/C][C]110.368651693662[/C][C]3.74294562955315[/C][/ROW]
[ROW][C]0.64[/C][C]111.190338582897[/C][C]3.80296003123669[/C][/ROW]
[ROW][C]0.65[/C][C]112.028972536298[/C][C]3.85468700741477[/C][/ROW]
[ROW][C]0.66[/C][C]112.882082515050[/C][C]3.89377489997076[/C][/ROW]
[ROW][C]0.67[/C][C]113.745832913142[/C][C]3.91276266607769[/C][/ROW]
[ROW][C]0.68[/C][C]114.614541949703[/C][C]3.90199345963149[/C][/ROW]
[ROW][C]0.69[/C][C]115.480501897292[/C][C]3.85178624025558[/C][/ROW]
[ROW][C]0.7[/C][C]116.334269430725[/C][C]3.75445454111729[/C][/ROW]
[ROW][C]0.71[/C][C]117.165535429495[/C][C]3.60738026716368[/C][/ROW]
[ROW][C]0.72[/C][C]117.964591787402[/C][C]3.41470972285439[/C][/ROW]
[ROW][C]0.73[/C][C]118.724296340272[/C][C]3.18940153062176[/C][/ROW]
[ROW][C]0.74[/C][C]119.442309504618[/C][C]2.95439557498417[/C][/ROW]
[ROW][C]0.75[/C][C]120.123258489285[/C][C]2.74132686204119[/C][/ROW]
[ROW][C]0.76[/C][C]120.780405220649[/C][C]2.59042870478883[/C][/ROW]
[ROW][C]0.77[/C][C]121.436385737591[/C][C]2.54482554524060[/C][/ROW]
[ROW][C]0.78[/C][C]122.122687812263[/C][C]2.64226410774262[/C][/ROW]
[ROW][C]0.79[/C][C]122.877778287313[/C][C]2.90326724060159[/C][/ROW]
[ROW][C]0.8[/C][C]123.744219690169[/C][C]3.32554987229399[/C][/ROW]
[ROW][C]0.81[/C][C]124.765741383862[/C][C]3.88811985998925[/C][/ROW]
[ROW][C]0.82[/C][C]125.985977419659[/C][C]4.56384644640732[/C][/ROW]
[ROW][C]0.83[/C][C]127.451160581149[/C][C]5.33702406582236[/C][/ROW]
[ROW][C]0.84[/C][C]129.218833916723[/C][C]6.22856165375716[/C][/ROW]
[ROW][C]0.85[/C][C]131.372655943784[/C][C]7.32260975978354[/C][/ROW]
[ROW][C]0.86[/C][C]134.038849552086[/C][C]8.773921137945[/C][/ROW]
[ROW][C]0.87[/C][C]137.393328841758[/C][C]10.7599848920342[/C][/ROW]
[ROW][C]0.88[/C][C]141.643433105122[/C][C]13.3569006327108[/C][/ROW]
[ROW][C]0.89[/C][C]146.971065827683[/C][C]16.3847124260696[/C][/ROW]
[ROW][C]0.9[/C][C]153.441221274069[/C][C]19.3237209505618[/C][/ROW]
[ROW][C]0.91[/C][C]160.909564659496[/C][C]21.3975278129383[/C][/ROW]
[ROW][C]0.92[/C][C]168.987625549627[/C][C]21.8610441226287[/C][/ROW]
[ROW][C]0.93[/C][C]177.116595142735[/C][C]20.3957595072942[/C][/ROW]
[ROW][C]0.94[/C][C]184.747241014072[/C][C]17.3678602461699[/C][/ROW]
[ROW][C]0.95[/C][C]191.55303394685[/C][C]13.7200002199793[/C][/ROW]
[ROW][C]0.96[/C][C]197.580723336217[/C][C]10.517764324444[/C][/ROW]
[ROW][C]0.97[/C][C]203.292220324801[/C][C]8.48135007530188[/C][/ROW]
[ROW][C]0.98[/C][C]209.410363872533[/C][C]7.91174764136438[/C][/ROW]
[ROW][C]0.99[/C][C]216.048669649280[/C][C]8.9817876984224[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107409&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107409&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
0.0180.91089511297070.264140778713976
0.0281.19974723562750.651643324645015
0.0381.6781611220921.04228944179159
0.0482.29352906392631.28668064337723
0.0582.96103305930851.36826399355786
0.0683.60781083230411.33294543119456
0.0784.19192186217121.23228682345921
0.0884.69913144307331.10998304097338
0.0985.13269309596280.997040901372885
0.185.504013882340.906576197622019
0.1185.82629054874680.837270590623005
0.1286.11142346477570.785070379987132
0.1386.36955245347310.751063001651906
0.1486.60978080818260.740582113658735
0.1586.8407198174440.757080403620823
0.1687.07028641631660.798593696431464
0.1787.30499241181750.857999006235907
0.1887.5492821899650.925852332037899
0.1987.80532924956160.993953102797853
0.288.07337759521821.05733241004964
0.2188.35245994596851.11376606913667
0.2288.64123023696351.16467787110283
0.2388.93868015070041.21376345964064
0.2489.24459641721821.26515972112092
0.2589.559704157591.32362141719294
0.2689.88551261688121.39209704363219
0.2790.22393540911551.47096490846190
0.2890.5768013440321.55833054800492
0.2990.94539783711811.64966920632799
0.391.33018369089421.73958698164629
0.3191.730762965431.82382029304934
0.3292.1461329198441.9001127273832
0.3392.57512958684561.96949637692014
0.3493.01692587165222.03576096612150
0.3593.47141513786052.10443080515167
0.3693.93934683419682.18062231391355
0.3794.42215774259452.26740910637006
0.3894.9215356808972.36439160296195
0.3995.43883120519132.4676531570732
0.495.97447424359172.56993478652623
0.4196.52754852351462.66297204413099
0.4297.09563371242832.73854295002671
0.4397.67495962091582.79031739191045
0.4498.2608475481082.81476734605854
0.4598.84835666282722.81251840398302
0.4699.4330177707692.78783171788475
0.47100.0115260037432.7482555540169
0.48100.5822760190492.70387036716280
0.49101.1456534351992.66561552352997
0.5101.7040383404842.64384077931882
0.51102.261524154842.64672586131304
0.52102.8234010141042.67921985557999
0.53103.3954903101242.74167393235363
0.54103.983439912032.83051188815585
0.55104.5920936415332.93964089884404
0.56105.2250325598523.06034581772522
0.57105.8843519702003.18433260202398
0.58106.5706924683813.30436308614936
0.59107.2834937890623.41481660790639
0.6108.0213953406923.51345931342491
0.61108.7826756405813.59993018230714
0.62109.5656115226743.67559685247639
0.63110.3686516936623.74294562955315
0.64111.1903385828973.80296003123669
0.65112.0289725362983.85468700741477
0.66112.8820825150503.89377489997076
0.67113.7458329131423.91276266607769
0.68114.6145419497033.90199345963149
0.69115.4805018972923.85178624025558
0.7116.3342694307253.75445454111729
0.71117.1655354294953.60738026716368
0.72117.9645917874023.41470972285439
0.73118.7242963402723.18940153062176
0.74119.4423095046182.95439557498417
0.75120.1232584892852.74132686204119
0.76120.7804052206492.59042870478883
0.77121.4363857375912.54482554524060
0.78122.1226878122632.64226410774262
0.79122.8777782873132.90326724060159
0.8123.7442196901693.32554987229399
0.81124.7657413838623.88811985998925
0.82125.9859774196594.56384644640732
0.83127.4511605811495.33702406582236
0.84129.2188339167236.22856165375716
0.85131.3726559437847.32260975978354
0.86134.0388495520868.773921137945
0.87137.39332884175810.7599848920342
0.88141.64343310512213.3569006327108
0.89146.97106582768316.3847124260696
0.9153.44122127406919.3237209505618
0.91160.90956465949621.3975278129383
0.92168.98762554962721.8610441226287
0.93177.11659514273520.3957595072942
0.94184.74724101407217.3678602461699
0.95191.5530339468513.7200002199793
0.96197.58072333621710.517764324444
0.97203.2922203248018.48135007530188
0.98209.4103638725337.91174764136438
0.99216.0486696492808.9817876984224


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')