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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, 29 Jul 2010 11:42:33 +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/Jul/29/t1280403750k2hm148ascvrc3r.htm/, Retrieved Sun, 28 Apr 2024 22:30:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=78162, Retrieved Sun, 28 Apr 2024 22:30:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsVan de Walle Mathias
Estimated Impact155

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] [tijdreeks 1 - stap 2] [2010-07-17 10:32:38] [2b5a188751227050025c4bb07404e527]
- RMPD    [Harrell-Davis Quantiles] [tijdreeks 2 - stap 6] [2010-07-29 11:42:33] [589929edeb20bd59f78e9be1ffd92c80] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
239
238
237
235
233
232
233
235
236
236
237
239
238
237
244
230
237
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239
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230
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231
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225
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238
214
222
233
228
218
203
209
207
203
195
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207
182
181
189
186
174
153
158
153
147
143
156
168
142
146
150
145
133
111
115
109
105
96
112
127
107
116
125
120
107
86
87
79
83
75
89
104
86
98
98
85
74
49
54
47
56

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 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 & 6 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78162&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]6 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=78162&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78162&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 time6 seconds
R Server'George Udny Yule' @ 72.249.76.132






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0148.39729206785173.32078852092622
0.0251.25078297385135.88608524036857
0.0355.24797119317848.54746485027172
0.0459.973518563836910.3992152052567
0.0564.938764349730410.9348620148420
0.0669.671201542051710.2844196771082
0.0773.84571901974639.0037385797956
0.0877.34252312200117.6563750100601
0.0980.2112322068516.58393414377827
0.182.59350152956075.91876236394105
0.1184.6551543033015.67500145989347
0.1286.54556171240065.79533515419111
0.1388.37907705272166.16505715084264
0.1490.2291101420356.64356760950888
0.1592.1295760020137.10246665110091
0.1694.08178294522797.4513430649917
0.1796.06522146627627.64738788887998
0.1898.0498988212117.69464757928098
0.19100.0075734046077.63263180022375
0.2101.9199087971737.52326373614096
0.21103.7827255505927.43676064281819
0.22105.6065781571077.43895443624707
0.23107.4145043953657.58099824425784
0.24109.2379785780347.89200150542173
0.25111.1120102480828.37456315788332
0.26113.0701415579069.00712594326732
0.27115.1399213513159.7471822727101
0.28117.33930787276310.5382007950081
0.29119.67435941495711.3166156690751
0.3122.13847599591812.0196017999583
0.31124.71332121156412.5921082396126
0.32127.37136704689712.9961637668914
0.33130.07977855917613.2147425002519
0.34132.80512909908713.2569707606388
0.35135.51826417882113.1573926692172
0.36138.19856420925912.9717242306038
0.37140.83692275987212.7697518401502
0.38143.43695469353412.6252468827970
0.39146.01424144300312.6033932229948
0.4148.59374996537012.7496728866331
0.41151.20586195967013.0810534592546
0.42153.88166448284113.5826424753531
0.43156.64824650932614.2133320085127
0.44159.52470816880414.9123801515397
0.45162.51943508264615.6107182295535
0.46165.62895419172116.2408666462139
0.47168.83841726025416.7449132183744
0.48172.12350493342617.0810299664282
0.49175.45335219613117.2266156648196
0.5178.79399347470917.1774724769796
0.51182.11181835498216.9483938087049
0.52185.37660078500216.5663518223319
0.53188.56378452755916.0687313666233
0.54191.65584125379415.4961116265916
0.55194.64263962239614.8893302536551
0.56197.52086432918714.2834862254293
0.57200.29260829683413.7058640627431
0.58202.96333961832013.1712889479595
0.59205.5395226526212.6805930894758
0.6208.02624106167212.2216417495457
0.61210.42520690899611.7702897748560
0.62212.73351647867711.2971012566729
0.63214.94341167285910.7736199984241
0.64217.0431294371110.1782720381041
0.65219.0187020109309.5028010803472
0.66220.856360990538.75328843531929
0.67222.5450570678037.94964657539894
0.68224.0785791300167.12258624829726
0.69225.4568539638256.30803878226598
0.7226.6862059186675.54097826842836
0.71227.778598295164.8496147064882
0.72228.7500959101224.25288443118554
0.73229.6189226217843.75719915272804
0.74230.4035098250763.35818453605168
0.75231.1208516295953.04367442076978
0.76231.7853417204592.79642154041082
0.77232.4081226106912.59830385502398
0.78232.9968789748522.43195445843611
0.79233.5559753940302.28215730498007
0.8234.0868642626942.13643135245119
0.81234.5887351398581.98571010039023
0.82235.059398529531.82482062748339
0.83235.4963658075041.65368907739229
0.84235.8980052251921.47716457555267
0.85236.2645594109501.30435023394840
0.86236.5987616668081.14633945285885
0.87236.905837680751.01379628920234
0.88237.1928407226570.913042593179137
0.89237.4675233012100.843626634505233
0.9237.7372971380890.79869719836645
0.91238.0093454579990.768949630982236
0.92238.2936384710060.749851380651964
0.93238.6108786960750.756062776226341
0.94239.0051725812920.844932121514183
0.95239.5528548609421.11459350467815
0.96240.3438955987341.59746096830952
0.97241.4068260107102.09196239273806
0.98242.5940814633862.09610976117713
0.99243.5597105103591.19621208597006

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 48.3972920678517 & 3.32078852092622 \tabularnewline
0.02 & 51.2507829738513 & 5.88608524036857 \tabularnewline
0.03 & 55.2479711931784 & 8.54746485027172 \tabularnewline
0.04 & 59.9735185638369 & 10.3992152052567 \tabularnewline
0.05 & 64.9387643497304 & 10.9348620148420 \tabularnewline
0.06 & 69.6712015420517 & 10.2844196771082 \tabularnewline
0.07 & 73.8457190197463 & 9.0037385797956 \tabularnewline
0.08 & 77.3425231220011 & 7.6563750100601 \tabularnewline
0.09 & 80.211232206851 & 6.58393414377827 \tabularnewline
0.1 & 82.5935015295607 & 5.91876236394105 \tabularnewline
0.11 & 84.655154303301 & 5.67500145989347 \tabularnewline
0.12 & 86.5455617124006 & 5.79533515419111 \tabularnewline
0.13 & 88.3790770527216 & 6.16505715084264 \tabularnewline
0.14 & 90.229110142035 & 6.64356760950888 \tabularnewline
0.15 & 92.129576002013 & 7.10246665110091 \tabularnewline
0.16 & 94.0817829452279 & 7.4513430649917 \tabularnewline
0.17 & 96.0652214662762 & 7.64738788887998 \tabularnewline
0.18 & 98.049898821211 & 7.69464757928098 \tabularnewline
0.19 & 100.007573404607 & 7.63263180022375 \tabularnewline
0.2 & 101.919908797173 & 7.52326373614096 \tabularnewline
0.21 & 103.782725550592 & 7.43676064281819 \tabularnewline
0.22 & 105.606578157107 & 7.43895443624707 \tabularnewline
0.23 & 107.414504395365 & 7.58099824425784 \tabularnewline
0.24 & 109.237978578034 & 7.89200150542173 \tabularnewline
0.25 & 111.112010248082 & 8.37456315788332 \tabularnewline
0.26 & 113.070141557906 & 9.00712594326732 \tabularnewline
0.27 & 115.139921351315 & 9.7471822727101 \tabularnewline
0.28 & 117.339307872763 & 10.5382007950081 \tabularnewline
0.29 & 119.674359414957 & 11.3166156690751 \tabularnewline
0.3 & 122.138475995918 & 12.0196017999583 \tabularnewline
0.31 & 124.713321211564 & 12.5921082396126 \tabularnewline
0.32 & 127.371367046897 & 12.9961637668914 \tabularnewline
0.33 & 130.079778559176 & 13.2147425002519 \tabularnewline
0.34 & 132.805129099087 & 13.2569707606388 \tabularnewline
0.35 & 135.518264178821 & 13.1573926692172 \tabularnewline
0.36 & 138.198564209259 & 12.9717242306038 \tabularnewline
0.37 & 140.836922759872 & 12.7697518401502 \tabularnewline
0.38 & 143.436954693534 & 12.6252468827970 \tabularnewline
0.39 & 146.014241443003 & 12.6033932229948 \tabularnewline
0.4 & 148.593749965370 & 12.7496728866331 \tabularnewline
0.41 & 151.205861959670 & 13.0810534592546 \tabularnewline
0.42 & 153.881664482841 & 13.5826424753531 \tabularnewline
0.43 & 156.648246509326 & 14.2133320085127 \tabularnewline
0.44 & 159.524708168804 & 14.9123801515397 \tabularnewline
0.45 & 162.519435082646 & 15.6107182295535 \tabularnewline
0.46 & 165.628954191721 & 16.2408666462139 \tabularnewline
0.47 & 168.838417260254 & 16.7449132183744 \tabularnewline
0.48 & 172.123504933426 & 17.0810299664282 \tabularnewline
0.49 & 175.453352196131 & 17.2266156648196 \tabularnewline
0.5 & 178.793993474709 & 17.1774724769796 \tabularnewline
0.51 & 182.111818354982 & 16.9483938087049 \tabularnewline
0.52 & 185.376600785002 & 16.5663518223319 \tabularnewline
0.53 & 188.563784527559 & 16.0687313666233 \tabularnewline
0.54 & 191.655841253794 & 15.4961116265916 \tabularnewline
0.55 & 194.642639622396 & 14.8893302536551 \tabularnewline
0.56 & 197.520864329187 & 14.2834862254293 \tabularnewline
0.57 & 200.292608296834 & 13.7058640627431 \tabularnewline
0.58 & 202.963339618320 & 13.1712889479595 \tabularnewline
0.59 & 205.53952265262 & 12.6805930894758 \tabularnewline
0.6 & 208.026241061672 & 12.2216417495457 \tabularnewline
0.61 & 210.425206908996 & 11.7702897748560 \tabularnewline
0.62 & 212.733516478677 & 11.2971012566729 \tabularnewline
0.63 & 214.943411672859 & 10.7736199984241 \tabularnewline
0.64 & 217.04312943711 & 10.1782720381041 \tabularnewline
0.65 & 219.018702010930 & 9.5028010803472 \tabularnewline
0.66 & 220.85636099053 & 8.75328843531929 \tabularnewline
0.67 & 222.545057067803 & 7.94964657539894 \tabularnewline
0.68 & 224.078579130016 & 7.12258624829726 \tabularnewline
0.69 & 225.456853963825 & 6.30803878226598 \tabularnewline
0.7 & 226.686205918667 & 5.54097826842836 \tabularnewline
0.71 & 227.77859829516 & 4.8496147064882 \tabularnewline
0.72 & 228.750095910122 & 4.25288443118554 \tabularnewline
0.73 & 229.618922621784 & 3.75719915272804 \tabularnewline
0.74 & 230.403509825076 & 3.35818453605168 \tabularnewline
0.75 & 231.120851629595 & 3.04367442076978 \tabularnewline
0.76 & 231.785341720459 & 2.79642154041082 \tabularnewline
0.77 & 232.408122610691 & 2.59830385502398 \tabularnewline
0.78 & 232.996878974852 & 2.43195445843611 \tabularnewline
0.79 & 233.555975394030 & 2.28215730498007 \tabularnewline
0.8 & 234.086864262694 & 2.13643135245119 \tabularnewline
0.81 & 234.588735139858 & 1.98571010039023 \tabularnewline
0.82 & 235.05939852953 & 1.82482062748339 \tabularnewline
0.83 & 235.496365807504 & 1.65368907739229 \tabularnewline
0.84 & 235.898005225192 & 1.47716457555267 \tabularnewline
0.85 & 236.264559410950 & 1.30435023394840 \tabularnewline
0.86 & 236.598761666808 & 1.14633945285885 \tabularnewline
0.87 & 236.90583768075 & 1.01379628920234 \tabularnewline
0.88 & 237.192840722657 & 0.913042593179137 \tabularnewline
0.89 & 237.467523301210 & 0.843626634505233 \tabularnewline
0.9 & 237.737297138089 & 0.79869719836645 \tabularnewline
0.91 & 238.009345457999 & 0.768949630982236 \tabularnewline
0.92 & 238.293638471006 & 0.749851380651964 \tabularnewline
0.93 & 238.610878696075 & 0.756062776226341 \tabularnewline
0.94 & 239.005172581292 & 0.844932121514183 \tabularnewline
0.95 & 239.552854860942 & 1.11459350467815 \tabularnewline
0.96 & 240.343895598734 & 1.59746096830952 \tabularnewline
0.97 & 241.406826010710 & 2.09196239273806 \tabularnewline
0.98 & 242.594081463386 & 2.09610976117713 \tabularnewline
0.99 & 243.559710510359 & 1.19621208597006 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78162&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]48.3972920678517[/C][C]3.32078852092622[/C][/ROW]
[ROW][C]0.02[/C][C]51.2507829738513[/C][C]5.88608524036857[/C][/ROW]
[ROW][C]0.03[/C][C]55.2479711931784[/C][C]8.54746485027172[/C][/ROW]
[ROW][C]0.04[/C][C]59.9735185638369[/C][C]10.3992152052567[/C][/ROW]
[ROW][C]0.05[/C][C]64.9387643497304[/C][C]10.9348620148420[/C][/ROW]
[ROW][C]0.06[/C][C]69.6712015420517[/C][C]10.2844196771082[/C][/ROW]
[ROW][C]0.07[/C][C]73.8457190197463[/C][C]9.0037385797956[/C][/ROW]
[ROW][C]0.08[/C][C]77.3425231220011[/C][C]7.6563750100601[/C][/ROW]
[ROW][C]0.09[/C][C]80.211232206851[/C][C]6.58393414377827[/C][/ROW]
[ROW][C]0.1[/C][C]82.5935015295607[/C][C]5.91876236394105[/C][/ROW]
[ROW][C]0.11[/C][C]84.655154303301[/C][C]5.67500145989347[/C][/ROW]
[ROW][C]0.12[/C][C]86.5455617124006[/C][C]5.79533515419111[/C][/ROW]
[ROW][C]0.13[/C][C]88.3790770527216[/C][C]6.16505715084264[/C][/ROW]
[ROW][C]0.14[/C][C]90.229110142035[/C][C]6.64356760950888[/C][/ROW]
[ROW][C]0.15[/C][C]92.129576002013[/C][C]7.10246665110091[/C][/ROW]
[ROW][C]0.16[/C][C]94.0817829452279[/C][C]7.4513430649917[/C][/ROW]
[ROW][C]0.17[/C][C]96.0652214662762[/C][C]7.64738788887998[/C][/ROW]
[ROW][C]0.18[/C][C]98.049898821211[/C][C]7.69464757928098[/C][/ROW]
[ROW][C]0.19[/C][C]100.007573404607[/C][C]7.63263180022375[/C][/ROW]
[ROW][C]0.2[/C][C]101.919908797173[/C][C]7.52326373614096[/C][/ROW]
[ROW][C]0.21[/C][C]103.782725550592[/C][C]7.43676064281819[/C][/ROW]
[ROW][C]0.22[/C][C]105.606578157107[/C][C]7.43895443624707[/C][/ROW]
[ROW][C]0.23[/C][C]107.414504395365[/C][C]7.58099824425784[/C][/ROW]
[ROW][C]0.24[/C][C]109.237978578034[/C][C]7.89200150542173[/C][/ROW]
[ROW][C]0.25[/C][C]111.112010248082[/C][C]8.37456315788332[/C][/ROW]
[ROW][C]0.26[/C][C]113.070141557906[/C][C]9.00712594326732[/C][/ROW]
[ROW][C]0.27[/C][C]115.139921351315[/C][C]9.7471822727101[/C][/ROW]
[ROW][C]0.28[/C][C]117.339307872763[/C][C]10.5382007950081[/C][/ROW]
[ROW][C]0.29[/C][C]119.674359414957[/C][C]11.3166156690751[/C][/ROW]
[ROW][C]0.3[/C][C]122.138475995918[/C][C]12.0196017999583[/C][/ROW]
[ROW][C]0.31[/C][C]124.713321211564[/C][C]12.5921082396126[/C][/ROW]
[ROW][C]0.32[/C][C]127.371367046897[/C][C]12.9961637668914[/C][/ROW]
[ROW][C]0.33[/C][C]130.079778559176[/C][C]13.2147425002519[/C][/ROW]
[ROW][C]0.34[/C][C]132.805129099087[/C][C]13.2569707606388[/C][/ROW]
[ROW][C]0.35[/C][C]135.518264178821[/C][C]13.1573926692172[/C][/ROW]
[ROW][C]0.36[/C][C]138.198564209259[/C][C]12.9717242306038[/C][/ROW]
[ROW][C]0.37[/C][C]140.836922759872[/C][C]12.7697518401502[/C][/ROW]
[ROW][C]0.38[/C][C]143.436954693534[/C][C]12.6252468827970[/C][/ROW]
[ROW][C]0.39[/C][C]146.014241443003[/C][C]12.6033932229948[/C][/ROW]
[ROW][C]0.4[/C][C]148.593749965370[/C][C]12.7496728866331[/C][/ROW]
[ROW][C]0.41[/C][C]151.205861959670[/C][C]13.0810534592546[/C][/ROW]
[ROW][C]0.42[/C][C]153.881664482841[/C][C]13.5826424753531[/C][/ROW]
[ROW][C]0.43[/C][C]156.648246509326[/C][C]14.2133320085127[/C][/ROW]
[ROW][C]0.44[/C][C]159.524708168804[/C][C]14.9123801515397[/C][/ROW]
[ROW][C]0.45[/C][C]162.519435082646[/C][C]15.6107182295535[/C][/ROW]
[ROW][C]0.46[/C][C]165.628954191721[/C][C]16.2408666462139[/C][/ROW]
[ROW][C]0.47[/C][C]168.838417260254[/C][C]16.7449132183744[/C][/ROW]
[ROW][C]0.48[/C][C]172.123504933426[/C][C]17.0810299664282[/C][/ROW]
[ROW][C]0.49[/C][C]175.453352196131[/C][C]17.2266156648196[/C][/ROW]
[ROW][C]0.5[/C][C]178.793993474709[/C][C]17.1774724769796[/C][/ROW]
[ROW][C]0.51[/C][C]182.111818354982[/C][C]16.9483938087049[/C][/ROW]
[ROW][C]0.52[/C][C]185.376600785002[/C][C]16.5663518223319[/C][/ROW]
[ROW][C]0.53[/C][C]188.563784527559[/C][C]16.0687313666233[/C][/ROW]
[ROW][C]0.54[/C][C]191.655841253794[/C][C]15.4961116265916[/C][/ROW]
[ROW][C]0.55[/C][C]194.642639622396[/C][C]14.8893302536551[/C][/ROW]
[ROW][C]0.56[/C][C]197.520864329187[/C][C]14.2834862254293[/C][/ROW]
[ROW][C]0.57[/C][C]200.292608296834[/C][C]13.7058640627431[/C][/ROW]
[ROW][C]0.58[/C][C]202.963339618320[/C][C]13.1712889479595[/C][/ROW]
[ROW][C]0.59[/C][C]205.53952265262[/C][C]12.6805930894758[/C][/ROW]
[ROW][C]0.6[/C][C]208.026241061672[/C][C]12.2216417495457[/C][/ROW]
[ROW][C]0.61[/C][C]210.425206908996[/C][C]11.7702897748560[/C][/ROW]
[ROW][C]0.62[/C][C]212.733516478677[/C][C]11.2971012566729[/C][/ROW]
[ROW][C]0.63[/C][C]214.943411672859[/C][C]10.7736199984241[/C][/ROW]
[ROW][C]0.64[/C][C]217.04312943711[/C][C]10.1782720381041[/C][/ROW]
[ROW][C]0.65[/C][C]219.018702010930[/C][C]9.5028010803472[/C][/ROW]
[ROW][C]0.66[/C][C]220.85636099053[/C][C]8.75328843531929[/C][/ROW]
[ROW][C]0.67[/C][C]222.545057067803[/C][C]7.94964657539894[/C][/ROW]
[ROW][C]0.68[/C][C]224.078579130016[/C][C]7.12258624829726[/C][/ROW]
[ROW][C]0.69[/C][C]225.456853963825[/C][C]6.30803878226598[/C][/ROW]
[ROW][C]0.7[/C][C]226.686205918667[/C][C]5.54097826842836[/C][/ROW]
[ROW][C]0.71[/C][C]227.77859829516[/C][C]4.8496147064882[/C][/ROW]
[ROW][C]0.72[/C][C]228.750095910122[/C][C]4.25288443118554[/C][/ROW]
[ROW][C]0.73[/C][C]229.618922621784[/C][C]3.75719915272804[/C][/ROW]
[ROW][C]0.74[/C][C]230.403509825076[/C][C]3.35818453605168[/C][/ROW]
[ROW][C]0.75[/C][C]231.120851629595[/C][C]3.04367442076978[/C][/ROW]
[ROW][C]0.76[/C][C]231.785341720459[/C][C]2.79642154041082[/C][/ROW]
[ROW][C]0.77[/C][C]232.408122610691[/C][C]2.59830385502398[/C][/ROW]
[ROW][C]0.78[/C][C]232.996878974852[/C][C]2.43195445843611[/C][/ROW]
[ROW][C]0.79[/C][C]233.555975394030[/C][C]2.28215730498007[/C][/ROW]
[ROW][C]0.8[/C][C]234.086864262694[/C][C]2.13643135245119[/C][/ROW]
[ROW][C]0.81[/C][C]234.588735139858[/C][C]1.98571010039023[/C][/ROW]
[ROW][C]0.82[/C][C]235.05939852953[/C][C]1.82482062748339[/C][/ROW]
[ROW][C]0.83[/C][C]235.496365807504[/C][C]1.65368907739229[/C][/ROW]
[ROW][C]0.84[/C][C]235.898005225192[/C][C]1.47716457555267[/C][/ROW]
[ROW][C]0.85[/C][C]236.264559410950[/C][C]1.30435023394840[/C][/ROW]
[ROW][C]0.86[/C][C]236.598761666808[/C][C]1.14633945285885[/C][/ROW]
[ROW][C]0.87[/C][C]236.90583768075[/C][C]1.01379628920234[/C][/ROW]
[ROW][C]0.88[/C][C]237.192840722657[/C][C]0.913042593179137[/C][/ROW]
[ROW][C]0.89[/C][C]237.467523301210[/C][C]0.843626634505233[/C][/ROW]
[ROW][C]0.9[/C][C]237.737297138089[/C][C]0.79869719836645[/C][/ROW]
[ROW][C]0.91[/C][C]238.009345457999[/C][C]0.768949630982236[/C][/ROW]
[ROW][C]0.92[/C][C]238.293638471006[/C][C]0.749851380651964[/C][/ROW]
[ROW][C]0.93[/C][C]238.610878696075[/C][C]0.756062776226341[/C][/ROW]
[ROW][C]0.94[/C][C]239.005172581292[/C][C]0.844932121514183[/C][/ROW]
[ROW][C]0.95[/C][C]239.552854860942[/C][C]1.11459350467815[/C][/ROW]
[ROW][C]0.96[/C][C]240.343895598734[/C][C]1.59746096830952[/C][/ROW]
[ROW][C]0.97[/C][C]241.406826010710[/C][C]2.09196239273806[/C][/ROW]
[ROW][C]0.98[/C][C]242.594081463386[/C][C]2.09610976117713[/C][/ROW]
[ROW][C]0.99[/C][C]243.559710510359[/C][C]1.19621208597006[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78162&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78162&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
0.0148.39729206785173.32078852092622
0.0251.25078297385135.88608524036857
0.0355.24797119317848.54746485027172
0.0459.973518563836910.3992152052567
0.0564.938764349730410.9348620148420
0.0669.671201542051710.2844196771082
0.0773.84571901974639.0037385797956
0.0877.34252312200117.6563750100601
0.0980.2112322068516.58393414377827
0.182.59350152956075.91876236394105
0.1184.6551543033015.67500145989347
0.1286.54556171240065.79533515419111
0.1388.37907705272166.16505715084264
0.1490.2291101420356.64356760950888
0.1592.1295760020137.10246665110091
0.1694.08178294522797.4513430649917
0.1796.06522146627627.64738788887998
0.1898.0498988212117.69464757928098
0.19100.0075734046077.63263180022375
0.2101.9199087971737.52326373614096
0.21103.7827255505927.43676064281819
0.22105.6065781571077.43895443624707
0.23107.4145043953657.58099824425784
0.24109.2379785780347.89200150542173
0.25111.1120102480828.37456315788332
0.26113.0701415579069.00712594326732
0.27115.1399213513159.7471822727101
0.28117.33930787276310.5382007950081
0.29119.67435941495711.3166156690751
0.3122.13847599591812.0196017999583
0.31124.71332121156412.5921082396126
0.32127.37136704689712.9961637668914
0.33130.07977855917613.2147425002519
0.34132.80512909908713.2569707606388
0.35135.51826417882113.1573926692172
0.36138.19856420925912.9717242306038
0.37140.83692275987212.7697518401502
0.38143.43695469353412.6252468827970
0.39146.01424144300312.6033932229948
0.4148.59374996537012.7496728866331
0.41151.20586195967013.0810534592546
0.42153.88166448284113.5826424753531
0.43156.64824650932614.2133320085127
0.44159.52470816880414.9123801515397
0.45162.51943508264615.6107182295535
0.46165.62895419172116.2408666462139
0.47168.83841726025416.7449132183744
0.48172.12350493342617.0810299664282
0.49175.45335219613117.2266156648196
0.5178.79399347470917.1774724769796
0.51182.11181835498216.9483938087049
0.52185.37660078500216.5663518223319
0.53188.56378452755916.0687313666233
0.54191.65584125379415.4961116265916
0.55194.64263962239614.8893302536551
0.56197.52086432918714.2834862254293
0.57200.29260829683413.7058640627431
0.58202.96333961832013.1712889479595
0.59205.5395226526212.6805930894758
0.6208.02624106167212.2216417495457
0.61210.42520690899611.7702897748560
0.62212.73351647867711.2971012566729
0.63214.94341167285910.7736199984241
0.64217.0431294371110.1782720381041
0.65219.0187020109309.5028010803472
0.66220.856360990538.75328843531929
0.67222.5450570678037.94964657539894
0.68224.0785791300167.12258624829726
0.69225.4568539638256.30803878226598
0.7226.6862059186675.54097826842836
0.71227.778598295164.8496147064882
0.72228.7500959101224.25288443118554
0.73229.6189226217843.75719915272804
0.74230.4035098250763.35818453605168
0.75231.1208516295953.04367442076978
0.76231.7853417204592.79642154041082
0.77232.4081226106912.59830385502398
0.78232.9968789748522.43195445843611
0.79233.5559753940302.28215730498007
0.8234.0868642626942.13643135245119
0.81234.5887351398581.98571010039023
0.82235.059398529531.82482062748339
0.83235.4963658075041.65368907739229
0.84235.8980052251921.47716457555267
0.85236.2645594109501.30435023394840
0.86236.5987616668081.14633945285885
0.87236.905837680751.01379628920234
0.88237.1928407226570.913042593179137
0.89237.4675233012100.843626634505233
0.9237.7372971380890.79869719836645
0.91238.0093454579990.768949630982236
0.92238.2936384710060.749851380651964
0.93238.6108786960750.756062776226341
0.94239.0051725812920.844932121514183
0.95239.5528548609421.11459350467815
0.96240.3438955987341.59746096830952
0.97241.4068260107102.09196239273806
0.98242.5940814633862.09610976117713
0.99243.5597105103591.19621208597006


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')