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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 computationMon, 19 Oct 2009 02:04:41 -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/19/t1255939639dcrn556doeamysv.htm/, Retrieved Mon, 29 Apr 2024 22:23:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=47593, Retrieved Mon, 29 Apr 2024 22:23:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W42
Estimated Impact119

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] [opgave 4 oefening...] [2009-10-19 08:04:41] [035dd36315b547f59b9bd3c100d10d7a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
102.5
77.7
82.8
77.3
103.1
99.7
99.5
107.2
96.7
97.1
105.2
151.2
102.7
75.4
87.2
83.7
105.8
111.5
99.7
111.2
101.5
110.9
116.3
164.9
118.1
83.7
84
107.2
113.7
120.7
111.2
112.4
112.5
130.4
130.7
174.3
132.2
91.8
104.2
104.8
131.4
141.2
132.7
135.7
136.9
151.2
144
201.5
149.6
108.7
122.8
126.7
139.9
162.5
142.7
151.6
148.1
159
157.8
226.7
153.7
122.3
117.6
166
154.5
183.9
164.4
173.3
160.2
166.4
170.3
238.4
166.8
122.5
141.8
140.5
173.8
188.8
168
187.4
177.7
183.8
196.1
264.6
193.7
141.3
170.1
163.7
190.1
230.7
195.9
210.3
204.7
210.3
221.2
288.2
203.2
162.4
149.2
195.3
213.7
227.9
212.1
226.8
212.6
220.9
228.1
311.6

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=47593&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=47593&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=47593&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'George Udny Yule' @ 72.249.76.132






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0176.54342556941021.91724833262425
0.0278.40222963547152.68016939206619
0.0380.46650502684723.18728435591477
0.0482.52159990754023.40957518988056
0.0584.55562335421413.9942859595469
0.0686.6897226087284.91489188770748
0.0788.99570299669625.67120029965255
0.0891.39790015614895.91402059088711
0.0993.7272085388225.61344445063876
0.195.82673659962444.96585785590106
0.1197.61670629692144.22608086087682
0.1299.09909353450223.5839753562374
0.13100.3274779889263.1232161382836
0.14101.3725331204952.84412731219813
0.15102.2993719236402.71003032214280
0.16103.1586136825472.68086457888886
0.17103.9861000645722.72582897489916
0.18104.8057624028922.82105630449378
0.19105.6325460143202.94500700813548
0.2106.4746551069703.07955548869451
0.21107.3355478962413.21186396137571
0.22108.2161709303053.33874012088478
0.23109.1174346778863.46782637978254
0.24110.0424420433463.6167719539339
0.25110.9978099370273.80586234565041
0.26111.9936377066454.05034778792359
0.27113.0421352711184.35471925444173
0.28114.1553864997134.7103824124997
0.29115.342974800845.09843097222772
0.3116.6101502027375.49512909914025
0.31117.9569346164125.87702854267327
0.32119.3782042302636.22328879494578
0.33120.8645139849186.51913407921433
0.34122.4033198223666.75434058639183
0.35123.9802940579646.92360121807859
0.36125.5805418971047.0261956979632
0.37127.1896350954227.06513186361722
0.38128.7944430428227.04724630994238
0.39130.3837658330386.98162477747127
0.4131.9487808353406.8802604855925
0.41133.4833189089566.75502874475119
0.42134.9839868683526.61733693903878
0.43136.4501412826046.4799467325597
0.44137.8836978896076.3540985068381
0.45139.2887491012206.24945141449902
0.46140.6709806010706.1726074609689
0.47142.0369311061976.1266010467682
0.48143.3932036243856.10897358459756
0.49144.7457712731176.11400731576997
0.5146.0994941082376.13418048096926
0.51147.4578773480896.16335051623383
0.52148.8229967800416.19508967696318
0.53150.1954536817716.22431127143356
0.54151.5742429258076.24481024269257
0.55152.9565233048906.24831739810264
0.56154.3374192183256.22423580678608
0.57155.7100834011466.16218317010617
0.58157.0662504709566.05523113685836
0.59158.3973953232125.90312447327596
0.6159.6964176494635.71504972457773
0.61160.9595787115845.51035781252536
0.62162.1882944699795.31668161322316
0.63163.3903832394595.16675926769045
0.64164.5804707136235.09365275772835
0.65165.7794237348165.12514195858653
0.66167.0128541184265.27749145312603
0.67168.3088575909905.55437049510388
0.68169.6952189574405.94552958849652
0.69171.1963486323486.42618259512617
0.7172.8302596023756.9600342612491
0.71174.6059720946357.50157781877137
0.72176.5218237859168.00142553264427
0.73178.5651943059758.41274995291277
0.74180.7140324971418.69914687869009
0.75182.9402468503508.8432279271427
0.76185.2145134112008.8501830807086
0.77187.5115055548538.74828162992144
0.78189.8141681015898.582415896062
0.79192.1156688563518.40140538171669
0.8194.4182156170378.24316904010422
0.81196.7290084936788.12146441483675
0.82199.0549249680808.02244208429932
0.83201.3985239376747.91444853860787
0.84203.7578406644117.76931210343428
0.85206.1306778841277.58431506683834
0.86208.5209614695577.39180103901212
0.87210.9418125181747.24141080117943
0.88213.4099230872267.15520403352017
0.89215.9308784699357.08389984278544
0.9218.4851031334546.91296707266132
0.91221.0354190264056.54267445803224
0.92223.5836018839016.02909601270239
0.93226.2978483378685.76495936764808
0.94229.7050622979946.65755091726359
0.95234.8701968246149.78416188438574
0.96243.36200702127815.3363259335014
0.97256.74135546918421.7048536489550
0.98275.46869445196725.3134184052697
0.99296.8488297728524.1788182153593

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 76.5434255694102 & 1.91724833262425 \tabularnewline
0.02 & 78.4022296354715 & 2.68016939206619 \tabularnewline
0.03 & 80.4665050268472 & 3.18728435591477 \tabularnewline
0.04 & 82.5215999075402 & 3.40957518988056 \tabularnewline
0.05 & 84.5556233542141 & 3.9942859595469 \tabularnewline
0.06 & 86.689722608728 & 4.91489188770748 \tabularnewline
0.07 & 88.9957029966962 & 5.67120029965255 \tabularnewline
0.08 & 91.3979001561489 & 5.91402059088711 \tabularnewline
0.09 & 93.727208538822 & 5.61344445063876 \tabularnewline
0.1 & 95.8267365996244 & 4.96585785590106 \tabularnewline
0.11 & 97.6167062969214 & 4.22608086087682 \tabularnewline
0.12 & 99.0990935345022 & 3.5839753562374 \tabularnewline
0.13 & 100.327477988926 & 3.1232161382836 \tabularnewline
0.14 & 101.372533120495 & 2.84412731219813 \tabularnewline
0.15 & 102.299371923640 & 2.71003032214280 \tabularnewline
0.16 & 103.158613682547 & 2.68086457888886 \tabularnewline
0.17 & 103.986100064572 & 2.72582897489916 \tabularnewline
0.18 & 104.805762402892 & 2.82105630449378 \tabularnewline
0.19 & 105.632546014320 & 2.94500700813548 \tabularnewline
0.2 & 106.474655106970 & 3.07955548869451 \tabularnewline
0.21 & 107.335547896241 & 3.21186396137571 \tabularnewline
0.22 & 108.216170930305 & 3.33874012088478 \tabularnewline
0.23 & 109.117434677886 & 3.46782637978254 \tabularnewline
0.24 & 110.042442043346 & 3.6167719539339 \tabularnewline
0.25 & 110.997809937027 & 3.80586234565041 \tabularnewline
0.26 & 111.993637706645 & 4.05034778792359 \tabularnewline
0.27 & 113.042135271118 & 4.35471925444173 \tabularnewline
0.28 & 114.155386499713 & 4.7103824124997 \tabularnewline
0.29 & 115.34297480084 & 5.09843097222772 \tabularnewline
0.3 & 116.610150202737 & 5.49512909914025 \tabularnewline
0.31 & 117.956934616412 & 5.87702854267327 \tabularnewline
0.32 & 119.378204230263 & 6.22328879494578 \tabularnewline
0.33 & 120.864513984918 & 6.51913407921433 \tabularnewline
0.34 & 122.403319822366 & 6.75434058639183 \tabularnewline
0.35 & 123.980294057964 & 6.92360121807859 \tabularnewline
0.36 & 125.580541897104 & 7.0261956979632 \tabularnewline
0.37 & 127.189635095422 & 7.06513186361722 \tabularnewline
0.38 & 128.794443042822 & 7.04724630994238 \tabularnewline
0.39 & 130.383765833038 & 6.98162477747127 \tabularnewline
0.4 & 131.948780835340 & 6.8802604855925 \tabularnewline
0.41 & 133.483318908956 & 6.75502874475119 \tabularnewline
0.42 & 134.983986868352 & 6.61733693903878 \tabularnewline
0.43 & 136.450141282604 & 6.4799467325597 \tabularnewline
0.44 & 137.883697889607 & 6.3540985068381 \tabularnewline
0.45 & 139.288749101220 & 6.24945141449902 \tabularnewline
0.46 & 140.670980601070 & 6.1726074609689 \tabularnewline
0.47 & 142.036931106197 & 6.1266010467682 \tabularnewline
0.48 & 143.393203624385 & 6.10897358459756 \tabularnewline
0.49 & 144.745771273117 & 6.11400731576997 \tabularnewline
0.5 & 146.099494108237 & 6.13418048096926 \tabularnewline
0.51 & 147.457877348089 & 6.16335051623383 \tabularnewline
0.52 & 148.822996780041 & 6.19508967696318 \tabularnewline
0.53 & 150.195453681771 & 6.22431127143356 \tabularnewline
0.54 & 151.574242925807 & 6.24481024269257 \tabularnewline
0.55 & 152.956523304890 & 6.24831739810264 \tabularnewline
0.56 & 154.337419218325 & 6.22423580678608 \tabularnewline
0.57 & 155.710083401146 & 6.16218317010617 \tabularnewline
0.58 & 157.066250470956 & 6.05523113685836 \tabularnewline
0.59 & 158.397395323212 & 5.90312447327596 \tabularnewline
0.6 & 159.696417649463 & 5.71504972457773 \tabularnewline
0.61 & 160.959578711584 & 5.51035781252536 \tabularnewline
0.62 & 162.188294469979 & 5.31668161322316 \tabularnewline
0.63 & 163.390383239459 & 5.16675926769045 \tabularnewline
0.64 & 164.580470713623 & 5.09365275772835 \tabularnewline
0.65 & 165.779423734816 & 5.12514195858653 \tabularnewline
0.66 & 167.012854118426 & 5.27749145312603 \tabularnewline
0.67 & 168.308857590990 & 5.55437049510388 \tabularnewline
0.68 & 169.695218957440 & 5.94552958849652 \tabularnewline
0.69 & 171.196348632348 & 6.42618259512617 \tabularnewline
0.7 & 172.830259602375 & 6.9600342612491 \tabularnewline
0.71 & 174.605972094635 & 7.50157781877137 \tabularnewline
0.72 & 176.521823785916 & 8.00142553264427 \tabularnewline
0.73 & 178.565194305975 & 8.41274995291277 \tabularnewline
0.74 & 180.714032497141 & 8.69914687869009 \tabularnewline
0.75 & 182.940246850350 & 8.8432279271427 \tabularnewline
0.76 & 185.214513411200 & 8.8501830807086 \tabularnewline
0.77 & 187.511505554853 & 8.74828162992144 \tabularnewline
0.78 & 189.814168101589 & 8.582415896062 \tabularnewline
0.79 & 192.115668856351 & 8.40140538171669 \tabularnewline
0.8 & 194.418215617037 & 8.24316904010422 \tabularnewline
0.81 & 196.729008493678 & 8.12146441483675 \tabularnewline
0.82 & 199.054924968080 & 8.02244208429932 \tabularnewline
0.83 & 201.398523937674 & 7.91444853860787 \tabularnewline
0.84 & 203.757840664411 & 7.76931210343428 \tabularnewline
0.85 & 206.130677884127 & 7.58431506683834 \tabularnewline
0.86 & 208.520961469557 & 7.39180103901212 \tabularnewline
0.87 & 210.941812518174 & 7.24141080117943 \tabularnewline
0.88 & 213.409923087226 & 7.15520403352017 \tabularnewline
0.89 & 215.930878469935 & 7.08389984278544 \tabularnewline
0.9 & 218.485103133454 & 6.91296707266132 \tabularnewline
0.91 & 221.035419026405 & 6.54267445803224 \tabularnewline
0.92 & 223.583601883901 & 6.02909601270239 \tabularnewline
0.93 & 226.297848337868 & 5.76495936764808 \tabularnewline
0.94 & 229.705062297994 & 6.65755091726359 \tabularnewline
0.95 & 234.870196824614 & 9.78416188438574 \tabularnewline
0.96 & 243.362007021278 & 15.3363259335014 \tabularnewline
0.97 & 256.741355469184 & 21.7048536489550 \tabularnewline
0.98 & 275.468694451967 & 25.3134184052697 \tabularnewline
0.99 & 296.84882977285 & 24.1788182153593 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=47593&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]76.5434255694102[/C][C]1.91724833262425[/C][/ROW]
[ROW][C]0.02[/C][C]78.4022296354715[/C][C]2.68016939206619[/C][/ROW]
[ROW][C]0.03[/C][C]80.4665050268472[/C][C]3.18728435591477[/C][/ROW]
[ROW][C]0.04[/C][C]82.5215999075402[/C][C]3.40957518988056[/C][/ROW]
[ROW][C]0.05[/C][C]84.5556233542141[/C][C]3.9942859595469[/C][/ROW]
[ROW][C]0.06[/C][C]86.689722608728[/C][C]4.91489188770748[/C][/ROW]
[ROW][C]0.07[/C][C]88.9957029966962[/C][C]5.67120029965255[/C][/ROW]
[ROW][C]0.08[/C][C]91.3979001561489[/C][C]5.91402059088711[/C][/ROW]
[ROW][C]0.09[/C][C]93.727208538822[/C][C]5.61344445063876[/C][/ROW]
[ROW][C]0.1[/C][C]95.8267365996244[/C][C]4.96585785590106[/C][/ROW]
[ROW][C]0.11[/C][C]97.6167062969214[/C][C]4.22608086087682[/C][/ROW]
[ROW][C]0.12[/C][C]99.0990935345022[/C][C]3.5839753562374[/C][/ROW]
[ROW][C]0.13[/C][C]100.327477988926[/C][C]3.1232161382836[/C][/ROW]
[ROW][C]0.14[/C][C]101.372533120495[/C][C]2.84412731219813[/C][/ROW]
[ROW][C]0.15[/C][C]102.299371923640[/C][C]2.71003032214280[/C][/ROW]
[ROW][C]0.16[/C][C]103.158613682547[/C][C]2.68086457888886[/C][/ROW]
[ROW][C]0.17[/C][C]103.986100064572[/C][C]2.72582897489916[/C][/ROW]
[ROW][C]0.18[/C][C]104.805762402892[/C][C]2.82105630449378[/C][/ROW]
[ROW][C]0.19[/C][C]105.632546014320[/C][C]2.94500700813548[/C][/ROW]
[ROW][C]0.2[/C][C]106.474655106970[/C][C]3.07955548869451[/C][/ROW]
[ROW][C]0.21[/C][C]107.335547896241[/C][C]3.21186396137571[/C][/ROW]
[ROW][C]0.22[/C][C]108.216170930305[/C][C]3.33874012088478[/C][/ROW]
[ROW][C]0.23[/C][C]109.117434677886[/C][C]3.46782637978254[/C][/ROW]
[ROW][C]0.24[/C][C]110.042442043346[/C][C]3.6167719539339[/C][/ROW]
[ROW][C]0.25[/C][C]110.997809937027[/C][C]3.80586234565041[/C][/ROW]
[ROW][C]0.26[/C][C]111.993637706645[/C][C]4.05034778792359[/C][/ROW]
[ROW][C]0.27[/C][C]113.042135271118[/C][C]4.35471925444173[/C][/ROW]
[ROW][C]0.28[/C][C]114.155386499713[/C][C]4.7103824124997[/C][/ROW]
[ROW][C]0.29[/C][C]115.34297480084[/C][C]5.09843097222772[/C][/ROW]
[ROW][C]0.3[/C][C]116.610150202737[/C][C]5.49512909914025[/C][/ROW]
[ROW][C]0.31[/C][C]117.956934616412[/C][C]5.87702854267327[/C][/ROW]
[ROW][C]0.32[/C][C]119.378204230263[/C][C]6.22328879494578[/C][/ROW]
[ROW][C]0.33[/C][C]120.864513984918[/C][C]6.51913407921433[/C][/ROW]
[ROW][C]0.34[/C][C]122.403319822366[/C][C]6.75434058639183[/C][/ROW]
[ROW][C]0.35[/C][C]123.980294057964[/C][C]6.92360121807859[/C][/ROW]
[ROW][C]0.36[/C][C]125.580541897104[/C][C]7.0261956979632[/C][/ROW]
[ROW][C]0.37[/C][C]127.189635095422[/C][C]7.06513186361722[/C][/ROW]
[ROW][C]0.38[/C][C]128.794443042822[/C][C]7.04724630994238[/C][/ROW]
[ROW][C]0.39[/C][C]130.383765833038[/C][C]6.98162477747127[/C][/ROW]
[ROW][C]0.4[/C][C]131.948780835340[/C][C]6.8802604855925[/C][/ROW]
[ROW][C]0.41[/C][C]133.483318908956[/C][C]6.75502874475119[/C][/ROW]
[ROW][C]0.42[/C][C]134.983986868352[/C][C]6.61733693903878[/C][/ROW]
[ROW][C]0.43[/C][C]136.450141282604[/C][C]6.4799467325597[/C][/ROW]
[ROW][C]0.44[/C][C]137.883697889607[/C][C]6.3540985068381[/C][/ROW]
[ROW][C]0.45[/C][C]139.288749101220[/C][C]6.24945141449902[/C][/ROW]
[ROW][C]0.46[/C][C]140.670980601070[/C][C]6.1726074609689[/C][/ROW]
[ROW][C]0.47[/C][C]142.036931106197[/C][C]6.1266010467682[/C][/ROW]
[ROW][C]0.48[/C][C]143.393203624385[/C][C]6.10897358459756[/C][/ROW]
[ROW][C]0.49[/C][C]144.745771273117[/C][C]6.11400731576997[/C][/ROW]
[ROW][C]0.5[/C][C]146.099494108237[/C][C]6.13418048096926[/C][/ROW]
[ROW][C]0.51[/C][C]147.457877348089[/C][C]6.16335051623383[/C][/ROW]
[ROW][C]0.52[/C][C]148.822996780041[/C][C]6.19508967696318[/C][/ROW]
[ROW][C]0.53[/C][C]150.195453681771[/C][C]6.22431127143356[/C][/ROW]
[ROW][C]0.54[/C][C]151.574242925807[/C][C]6.24481024269257[/C][/ROW]
[ROW][C]0.55[/C][C]152.956523304890[/C][C]6.24831739810264[/C][/ROW]
[ROW][C]0.56[/C][C]154.337419218325[/C][C]6.22423580678608[/C][/ROW]
[ROW][C]0.57[/C][C]155.710083401146[/C][C]6.16218317010617[/C][/ROW]
[ROW][C]0.58[/C][C]157.066250470956[/C][C]6.05523113685836[/C][/ROW]
[ROW][C]0.59[/C][C]158.397395323212[/C][C]5.90312447327596[/C][/ROW]
[ROW][C]0.6[/C][C]159.696417649463[/C][C]5.71504972457773[/C][/ROW]
[ROW][C]0.61[/C][C]160.959578711584[/C][C]5.51035781252536[/C][/ROW]
[ROW][C]0.62[/C][C]162.188294469979[/C][C]5.31668161322316[/C][/ROW]
[ROW][C]0.63[/C][C]163.390383239459[/C][C]5.16675926769045[/C][/ROW]
[ROW][C]0.64[/C][C]164.580470713623[/C][C]5.09365275772835[/C][/ROW]
[ROW][C]0.65[/C][C]165.779423734816[/C][C]5.12514195858653[/C][/ROW]
[ROW][C]0.66[/C][C]167.012854118426[/C][C]5.27749145312603[/C][/ROW]
[ROW][C]0.67[/C][C]168.308857590990[/C][C]5.55437049510388[/C][/ROW]
[ROW][C]0.68[/C][C]169.695218957440[/C][C]5.94552958849652[/C][/ROW]
[ROW][C]0.69[/C][C]171.196348632348[/C][C]6.42618259512617[/C][/ROW]
[ROW][C]0.7[/C][C]172.830259602375[/C][C]6.9600342612491[/C][/ROW]
[ROW][C]0.71[/C][C]174.605972094635[/C][C]7.50157781877137[/C][/ROW]
[ROW][C]0.72[/C][C]176.521823785916[/C][C]8.00142553264427[/C][/ROW]
[ROW][C]0.73[/C][C]178.565194305975[/C][C]8.41274995291277[/C][/ROW]
[ROW][C]0.74[/C][C]180.714032497141[/C][C]8.69914687869009[/C][/ROW]
[ROW][C]0.75[/C][C]182.940246850350[/C][C]8.8432279271427[/C][/ROW]
[ROW][C]0.76[/C][C]185.214513411200[/C][C]8.8501830807086[/C][/ROW]
[ROW][C]0.77[/C][C]187.511505554853[/C][C]8.74828162992144[/C][/ROW]
[ROW][C]0.78[/C][C]189.814168101589[/C][C]8.582415896062[/C][/ROW]
[ROW][C]0.79[/C][C]192.115668856351[/C][C]8.40140538171669[/C][/ROW]
[ROW][C]0.8[/C][C]194.418215617037[/C][C]8.24316904010422[/C][/ROW]
[ROW][C]0.81[/C][C]196.729008493678[/C][C]8.12146441483675[/C][/ROW]
[ROW][C]0.82[/C][C]199.054924968080[/C][C]8.02244208429932[/C][/ROW]
[ROW][C]0.83[/C][C]201.398523937674[/C][C]7.91444853860787[/C][/ROW]
[ROW][C]0.84[/C][C]203.757840664411[/C][C]7.76931210343428[/C][/ROW]
[ROW][C]0.85[/C][C]206.130677884127[/C][C]7.58431506683834[/C][/ROW]
[ROW][C]0.86[/C][C]208.520961469557[/C][C]7.39180103901212[/C][/ROW]
[ROW][C]0.87[/C][C]210.941812518174[/C][C]7.24141080117943[/C][/ROW]
[ROW][C]0.88[/C][C]213.409923087226[/C][C]7.15520403352017[/C][/ROW]
[ROW][C]0.89[/C][C]215.930878469935[/C][C]7.08389984278544[/C][/ROW]
[ROW][C]0.9[/C][C]218.485103133454[/C][C]6.91296707266132[/C][/ROW]
[ROW][C]0.91[/C][C]221.035419026405[/C][C]6.54267445803224[/C][/ROW]
[ROW][C]0.92[/C][C]223.583601883901[/C][C]6.02909601270239[/C][/ROW]
[ROW][C]0.93[/C][C]226.297848337868[/C][C]5.76495936764808[/C][/ROW]
[ROW][C]0.94[/C][C]229.705062297994[/C][C]6.65755091726359[/C][/ROW]
[ROW][C]0.95[/C][C]234.870196824614[/C][C]9.78416188438574[/C][/ROW]
[ROW][C]0.96[/C][C]243.362007021278[/C][C]15.3363259335014[/C][/ROW]
[ROW][C]0.97[/C][C]256.741355469184[/C][C]21.7048536489550[/C][/ROW]
[ROW][C]0.98[/C][C]275.468694451967[/C][C]25.3134184052697[/C][/ROW]
[ROW][C]0.99[/C][C]296.84882977285[/C][C]24.1788182153593[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=47593&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=47593&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
0.0176.54342556941021.91724833262425
0.0278.40222963547152.68016939206619
0.0380.46650502684723.18728435591477
0.0482.52159990754023.40957518988056
0.0584.55562335421413.9942859595469
0.0686.6897226087284.91489188770748
0.0788.99570299669625.67120029965255
0.0891.39790015614895.91402059088711
0.0993.7272085388225.61344445063876
0.195.82673659962444.96585785590106
0.1197.61670629692144.22608086087682
0.1299.09909353450223.5839753562374
0.13100.3274779889263.1232161382836
0.14101.3725331204952.84412731219813
0.15102.2993719236402.71003032214280
0.16103.1586136825472.68086457888886
0.17103.9861000645722.72582897489916
0.18104.8057624028922.82105630449378
0.19105.6325460143202.94500700813548
0.2106.4746551069703.07955548869451
0.21107.3355478962413.21186396137571
0.22108.2161709303053.33874012088478
0.23109.1174346778863.46782637978254
0.24110.0424420433463.6167719539339
0.25110.9978099370273.80586234565041
0.26111.9936377066454.05034778792359
0.27113.0421352711184.35471925444173
0.28114.1553864997134.7103824124997
0.29115.342974800845.09843097222772
0.3116.6101502027375.49512909914025
0.31117.9569346164125.87702854267327
0.32119.3782042302636.22328879494578
0.33120.8645139849186.51913407921433
0.34122.4033198223666.75434058639183
0.35123.9802940579646.92360121807859
0.36125.5805418971047.0261956979632
0.37127.1896350954227.06513186361722
0.38128.7944430428227.04724630994238
0.39130.3837658330386.98162477747127
0.4131.9487808353406.8802604855925
0.41133.4833189089566.75502874475119
0.42134.9839868683526.61733693903878
0.43136.4501412826046.4799467325597
0.44137.8836978896076.3540985068381
0.45139.2887491012206.24945141449902
0.46140.6709806010706.1726074609689
0.47142.0369311061976.1266010467682
0.48143.3932036243856.10897358459756
0.49144.7457712731176.11400731576997
0.5146.0994941082376.13418048096926
0.51147.4578773480896.16335051623383
0.52148.8229967800416.19508967696318
0.53150.1954536817716.22431127143356
0.54151.5742429258076.24481024269257
0.55152.9565233048906.24831739810264
0.56154.3374192183256.22423580678608
0.57155.7100834011466.16218317010617
0.58157.0662504709566.05523113685836
0.59158.3973953232125.90312447327596
0.6159.6964176494635.71504972457773
0.61160.9595787115845.51035781252536
0.62162.1882944699795.31668161322316
0.63163.3903832394595.16675926769045
0.64164.5804707136235.09365275772835
0.65165.7794237348165.12514195858653
0.66167.0128541184265.27749145312603
0.67168.3088575909905.55437049510388
0.68169.6952189574405.94552958849652
0.69171.1963486323486.42618259512617
0.7172.8302596023756.9600342612491
0.71174.6059720946357.50157781877137
0.72176.5218237859168.00142553264427
0.73178.5651943059758.41274995291277
0.74180.7140324971418.69914687869009
0.75182.9402468503508.8432279271427
0.76185.2145134112008.8501830807086
0.77187.5115055548538.74828162992144
0.78189.8141681015898.582415896062
0.79192.1156688563518.40140538171669
0.8194.4182156170378.24316904010422
0.81196.7290084936788.12146441483675
0.82199.0549249680808.02244208429932
0.83201.3985239376747.91444853860787
0.84203.7578406644117.76931210343428
0.85206.1306778841277.58431506683834
0.86208.5209614695577.39180103901212
0.87210.9418125181747.24141080117943
0.88213.4099230872267.15520403352017
0.89215.9308784699357.08389984278544
0.9218.4851031334546.91296707266132
0.91221.0354190264056.54267445803224
0.92223.5836018839016.02909601270239
0.93226.2978483378685.76495936764808
0.94229.7050622979946.65755091726359
0.95234.8701968246149.78416188438574
0.96243.36200702127815.3363259335014
0.97256.74135546918421.7048536489550
0.98275.46869445196725.3134184052697
0.99296.8488297728524.1788182153593


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')