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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davies.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationSat, 10 Nov 2007 10:19:04 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Nov/10/t1194714895ghokarulr022tik.htm/, Retrieved Tue, 30 Apr 2024 03:31:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=5058, Retrieved Tue, 30 Apr 2024 03:31:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsConsumptiegoederen
Estimated Impact182

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] [Paper Harell – Da...] [2007-11-10 17:19:04] [d06427f3e67cec1f6334fc93f511b0b4] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
115,9
112,9
126,3
116,8
112
129,7
113,6
115,7
119,5
125,8
129,6
128
112,8
101,6
123,9
118,8
109,1
130,6
112,4
111
116,2
119,8
117,2
127,3
107,7
97,5
120,1
110,6
111,3
119,8
105,5
108,7
128,7
119,5
121,1
128,4
108,8
107,5
125,6
102,9
107,5
120,4
104,3
100,6
121,9
112,7
124,9
123,9
102,2
104,9
109,8
98,9
107,3
112,6
104
110,6
100,8
103,8
117
108,4
95,5
96,9
103,9
101,1
100,6
104,3
98
99,5
97,4
105,6
117,5
107,4
97,8
91,5
107,7
100,1
96,6
106,8
98
98,6

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5058&T=0

[TABLE]
[ROW][C]Summary of compuational 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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5058&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5058&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0192.75152892481633.08640528769207
0.0294.34904338038172.02972635044677
0.0395.60178072365881.27212061990743
0.0496.40409462784480.860085051321878
0.0596.90322353315780.667937622506312
0.0697.2436252779470.592154968317179
0.0797.5109285262530.583225941810971
0.0897.74966939725150.621592407073007
0.0997.98374976758610.695118368779659
0.198.22665247241830.790277235349132
0.1198.48528113330740.89202321054661
0.1298.76154399209840.986598883955582
0.1399.0536482853761.06443942213087
0.1499.3576420410911.12249618693110
0.1599.66905372185931.16323233497905
0.1699.98425730874621.19430019536560
0.17100.3012475521321.22429397027843
0.18100.6197120565631.26025731839266
0.19100.9405157694551.30466883086245
0.2101.2648774484241.35512942319352
0.21101.5935679614581.40562226035190
0.22101.9263967423741.44935153735305
0.23102.2621140888931.48071403745564
0.24102.5987003156911.49759224614887
0.25102.9338911461711.50103228172252
0.26103.2657347112011.49509592366059
0.27103.5929946238501.48563938533259
0.28103.9152876949741.47776261286888
0.29104.2329423235071.47478323041976
0.3104.5466514530121.47690522134481
0.31104.8570478770361.48175707311005
0.32105.1643392510241.48499690344007
0.33105.4681093516131.48183557563193
0.34105.7673353544031.46892095742490
0.35106.0606072807041.44452473061678
0.36106.3464831287251.40988404664635
0.37106.6238836792341.36833406228273
0.38106.8924288255831.32538154279382
0.39107.1526392031511.28731004841309
0.4107.4059641027051.25954154858745
0.41107.6546380487171.24680331754857
0.42107.9014037828381.25092188501175
0.43108.1491617633481.27162339270103
0.44108.4006131095301.30598628691964
0.45108.6579557558811.34993140837904
0.46108.9226768400921.39848435132797
0.47109.1954634874821.44685306082138
0.48109.4762340208171.49108646396612
0.49109.7642753716961.52783293139274
0.5110.0584612411191.55595561879263
0.51110.3575188728331.57536874006998
0.52110.6603088985251.58760062297502
0.53110.9660814890991.59553201969881
0.54111.2746727915571.60321539041704
0.55111.5866092605811.61495426083765
0.56111.9030956494901.63502710129598
0.57112.2258765145461.66621647354669
0.58112.5569810563571.71016537789485
0.59112.8983844777111.7649826117931
0.6113.2516406770771.82718130095032
0.61113.6175543440831.89112023729687
0.62113.9959592876801.95012933334803
0.63114.3856512732411.99768408436163
0.64114.7844902897912.02914716010942
0.65115.1896473062902.04145178997801
0.66115.5979363747972.03462354838228
0.67116.0061564777422.00997538826339
0.68116.4113760027101.97093341412028
0.69116.8111247658821.92088219502923
0.7117.2035032101321.8631699928894
0.71117.5872582502451.80055170208345
0.72117.9618921056841.73563523690843
0.73118.3278529277631.67187149008298
0.74118.6868051596081.61430816680075
0.75119.0419087068191.57019284034170
0.76119.3979752946901.54822881695657
0.77119.7613466583401.55692015182177
0.78120.1393734299721.60105280565858
0.79120.5394693731311.67919563670537
0.8120.9678540960951.78212976267771
0.81121.4282388929351.89390335640971
0.82121.9208037365461.99540763224676
0.83122.4418113519692.06774886383001
0.84122.9840809428012.09704783156996
0.85123.5383102724742.07732097630859
0.86124.0949452660902.01214717708188
0.87124.6460468504511.91361985885030
0.88125.1865144910131.79825923028733
0.89125.7141983857771.68136009635390
0.9126.2288874462911.57071782717221
0.91126.7307476468881.46405804668931
0.92127.219147896431.35310619854562
0.93127.6925488286181.23182662497054
0.94128.1493000034961.10228369092547
0.95128.5888409758860.971279713353208
0.96129.0141394973640.839135446320667
0.97129.4364289850990.708653396746479
0.98129.8721592741450.638691290352981
0.99130.3016748261340.729664555922533

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 92.7515289248163 & 3.08640528769207 \tabularnewline
0.02 & 94.3490433803817 & 2.02972635044677 \tabularnewline
0.03 & 95.6017807236588 & 1.27212061990743 \tabularnewline
0.04 & 96.4040946278448 & 0.860085051321878 \tabularnewline
0.05 & 96.9032235331578 & 0.667937622506312 \tabularnewline
0.06 & 97.243625277947 & 0.592154968317179 \tabularnewline
0.07 & 97.510928526253 & 0.583225941810971 \tabularnewline
0.08 & 97.7496693972515 & 0.621592407073007 \tabularnewline
0.09 & 97.9837497675861 & 0.695118368779659 \tabularnewline
0.1 & 98.2266524724183 & 0.790277235349132 \tabularnewline
0.11 & 98.4852811333074 & 0.89202321054661 \tabularnewline
0.12 & 98.7615439920984 & 0.986598883955582 \tabularnewline
0.13 & 99.053648285376 & 1.06443942213087 \tabularnewline
0.14 & 99.357642041091 & 1.12249618693110 \tabularnewline
0.15 & 99.6690537218593 & 1.16323233497905 \tabularnewline
0.16 & 99.9842573087462 & 1.19430019536560 \tabularnewline
0.17 & 100.301247552132 & 1.22429397027843 \tabularnewline
0.18 & 100.619712056563 & 1.26025731839266 \tabularnewline
0.19 & 100.940515769455 & 1.30466883086245 \tabularnewline
0.2 & 101.264877448424 & 1.35512942319352 \tabularnewline
0.21 & 101.593567961458 & 1.40562226035190 \tabularnewline
0.22 & 101.926396742374 & 1.44935153735305 \tabularnewline
0.23 & 102.262114088893 & 1.48071403745564 \tabularnewline
0.24 & 102.598700315691 & 1.49759224614887 \tabularnewline
0.25 & 102.933891146171 & 1.50103228172252 \tabularnewline
0.26 & 103.265734711201 & 1.49509592366059 \tabularnewline
0.27 & 103.592994623850 & 1.48563938533259 \tabularnewline
0.28 & 103.915287694974 & 1.47776261286888 \tabularnewline
0.29 & 104.232942323507 & 1.47478323041976 \tabularnewline
0.3 & 104.546651453012 & 1.47690522134481 \tabularnewline
0.31 & 104.857047877036 & 1.48175707311005 \tabularnewline
0.32 & 105.164339251024 & 1.48499690344007 \tabularnewline
0.33 & 105.468109351613 & 1.48183557563193 \tabularnewline
0.34 & 105.767335354403 & 1.46892095742490 \tabularnewline
0.35 & 106.060607280704 & 1.44452473061678 \tabularnewline
0.36 & 106.346483128725 & 1.40988404664635 \tabularnewline
0.37 & 106.623883679234 & 1.36833406228273 \tabularnewline
0.38 & 106.892428825583 & 1.32538154279382 \tabularnewline
0.39 & 107.152639203151 & 1.28731004841309 \tabularnewline
0.4 & 107.405964102705 & 1.25954154858745 \tabularnewline
0.41 & 107.654638048717 & 1.24680331754857 \tabularnewline
0.42 & 107.901403782838 & 1.25092188501175 \tabularnewline
0.43 & 108.149161763348 & 1.27162339270103 \tabularnewline
0.44 & 108.400613109530 & 1.30598628691964 \tabularnewline
0.45 & 108.657955755881 & 1.34993140837904 \tabularnewline
0.46 & 108.922676840092 & 1.39848435132797 \tabularnewline
0.47 & 109.195463487482 & 1.44685306082138 \tabularnewline
0.48 & 109.476234020817 & 1.49108646396612 \tabularnewline
0.49 & 109.764275371696 & 1.52783293139274 \tabularnewline
0.5 & 110.058461241119 & 1.55595561879263 \tabularnewline
0.51 & 110.357518872833 & 1.57536874006998 \tabularnewline
0.52 & 110.660308898525 & 1.58760062297502 \tabularnewline
0.53 & 110.966081489099 & 1.59553201969881 \tabularnewline
0.54 & 111.274672791557 & 1.60321539041704 \tabularnewline
0.55 & 111.586609260581 & 1.61495426083765 \tabularnewline
0.56 & 111.903095649490 & 1.63502710129598 \tabularnewline
0.57 & 112.225876514546 & 1.66621647354669 \tabularnewline
0.58 & 112.556981056357 & 1.71016537789485 \tabularnewline
0.59 & 112.898384477711 & 1.7649826117931 \tabularnewline
0.6 & 113.251640677077 & 1.82718130095032 \tabularnewline
0.61 & 113.617554344083 & 1.89112023729687 \tabularnewline
0.62 & 113.995959287680 & 1.95012933334803 \tabularnewline
0.63 & 114.385651273241 & 1.99768408436163 \tabularnewline
0.64 & 114.784490289791 & 2.02914716010942 \tabularnewline
0.65 & 115.189647306290 & 2.04145178997801 \tabularnewline
0.66 & 115.597936374797 & 2.03462354838228 \tabularnewline
0.67 & 116.006156477742 & 2.00997538826339 \tabularnewline
0.68 & 116.411376002710 & 1.97093341412028 \tabularnewline
0.69 & 116.811124765882 & 1.92088219502923 \tabularnewline
0.7 & 117.203503210132 & 1.8631699928894 \tabularnewline
0.71 & 117.587258250245 & 1.80055170208345 \tabularnewline
0.72 & 117.961892105684 & 1.73563523690843 \tabularnewline
0.73 & 118.327852927763 & 1.67187149008298 \tabularnewline
0.74 & 118.686805159608 & 1.61430816680075 \tabularnewline
0.75 & 119.041908706819 & 1.57019284034170 \tabularnewline
0.76 & 119.397975294690 & 1.54822881695657 \tabularnewline
0.77 & 119.761346658340 & 1.55692015182177 \tabularnewline
0.78 & 120.139373429972 & 1.60105280565858 \tabularnewline
0.79 & 120.539469373131 & 1.67919563670537 \tabularnewline
0.8 & 120.967854096095 & 1.78212976267771 \tabularnewline
0.81 & 121.428238892935 & 1.89390335640971 \tabularnewline
0.82 & 121.920803736546 & 1.99540763224676 \tabularnewline
0.83 & 122.441811351969 & 2.06774886383001 \tabularnewline
0.84 & 122.984080942801 & 2.09704783156996 \tabularnewline
0.85 & 123.538310272474 & 2.07732097630859 \tabularnewline
0.86 & 124.094945266090 & 2.01214717708188 \tabularnewline
0.87 & 124.646046850451 & 1.91361985885030 \tabularnewline
0.88 & 125.186514491013 & 1.79825923028733 \tabularnewline
0.89 & 125.714198385777 & 1.68136009635390 \tabularnewline
0.9 & 126.228887446291 & 1.57071782717221 \tabularnewline
0.91 & 126.730747646888 & 1.46405804668931 \tabularnewline
0.92 & 127.21914789643 & 1.35310619854562 \tabularnewline
0.93 & 127.692548828618 & 1.23182662497054 \tabularnewline
0.94 & 128.149300003496 & 1.10228369092547 \tabularnewline
0.95 & 128.588840975886 & 0.971279713353208 \tabularnewline
0.96 & 129.014139497364 & 0.839135446320667 \tabularnewline
0.97 & 129.436428985099 & 0.708653396746479 \tabularnewline
0.98 & 129.872159274145 & 0.638691290352981 \tabularnewline
0.99 & 130.301674826134 & 0.729664555922533 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5058&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]92.7515289248163[/C][C]3.08640528769207[/C][/ROW]
[ROW][C]0.02[/C][C]94.3490433803817[/C][C]2.02972635044677[/C][/ROW]
[ROW][C]0.03[/C][C]95.6017807236588[/C][C]1.27212061990743[/C][/ROW]
[ROW][C]0.04[/C][C]96.4040946278448[/C][C]0.860085051321878[/C][/ROW]
[ROW][C]0.05[/C][C]96.9032235331578[/C][C]0.667937622506312[/C][/ROW]
[ROW][C]0.06[/C][C]97.243625277947[/C][C]0.592154968317179[/C][/ROW]
[ROW][C]0.07[/C][C]97.510928526253[/C][C]0.583225941810971[/C][/ROW]
[ROW][C]0.08[/C][C]97.7496693972515[/C][C]0.621592407073007[/C][/ROW]
[ROW][C]0.09[/C][C]97.9837497675861[/C][C]0.695118368779659[/C][/ROW]
[ROW][C]0.1[/C][C]98.2266524724183[/C][C]0.790277235349132[/C][/ROW]
[ROW][C]0.11[/C][C]98.4852811333074[/C][C]0.89202321054661[/C][/ROW]
[ROW][C]0.12[/C][C]98.7615439920984[/C][C]0.986598883955582[/C][/ROW]
[ROW][C]0.13[/C][C]99.053648285376[/C][C]1.06443942213087[/C][/ROW]
[ROW][C]0.14[/C][C]99.357642041091[/C][C]1.12249618693110[/C][/ROW]
[ROW][C]0.15[/C][C]99.6690537218593[/C][C]1.16323233497905[/C][/ROW]
[ROW][C]0.16[/C][C]99.9842573087462[/C][C]1.19430019536560[/C][/ROW]
[ROW][C]0.17[/C][C]100.301247552132[/C][C]1.22429397027843[/C][/ROW]
[ROW][C]0.18[/C][C]100.619712056563[/C][C]1.26025731839266[/C][/ROW]
[ROW][C]0.19[/C][C]100.940515769455[/C][C]1.30466883086245[/C][/ROW]
[ROW][C]0.2[/C][C]101.264877448424[/C][C]1.35512942319352[/C][/ROW]
[ROW][C]0.21[/C][C]101.593567961458[/C][C]1.40562226035190[/C][/ROW]
[ROW][C]0.22[/C][C]101.926396742374[/C][C]1.44935153735305[/C][/ROW]
[ROW][C]0.23[/C][C]102.262114088893[/C][C]1.48071403745564[/C][/ROW]
[ROW][C]0.24[/C][C]102.598700315691[/C][C]1.49759224614887[/C][/ROW]
[ROW][C]0.25[/C][C]102.933891146171[/C][C]1.50103228172252[/C][/ROW]
[ROW][C]0.26[/C][C]103.265734711201[/C][C]1.49509592366059[/C][/ROW]
[ROW][C]0.27[/C][C]103.592994623850[/C][C]1.48563938533259[/C][/ROW]
[ROW][C]0.28[/C][C]103.915287694974[/C][C]1.47776261286888[/C][/ROW]
[ROW][C]0.29[/C][C]104.232942323507[/C][C]1.47478323041976[/C][/ROW]
[ROW][C]0.3[/C][C]104.546651453012[/C][C]1.47690522134481[/C][/ROW]
[ROW][C]0.31[/C][C]104.857047877036[/C][C]1.48175707311005[/C][/ROW]
[ROW][C]0.32[/C][C]105.164339251024[/C][C]1.48499690344007[/C][/ROW]
[ROW][C]0.33[/C][C]105.468109351613[/C][C]1.48183557563193[/C][/ROW]
[ROW][C]0.34[/C][C]105.767335354403[/C][C]1.46892095742490[/C][/ROW]
[ROW][C]0.35[/C][C]106.060607280704[/C][C]1.44452473061678[/C][/ROW]
[ROW][C]0.36[/C][C]106.346483128725[/C][C]1.40988404664635[/C][/ROW]
[ROW][C]0.37[/C][C]106.623883679234[/C][C]1.36833406228273[/C][/ROW]
[ROW][C]0.38[/C][C]106.892428825583[/C][C]1.32538154279382[/C][/ROW]
[ROW][C]0.39[/C][C]107.152639203151[/C][C]1.28731004841309[/C][/ROW]
[ROW][C]0.4[/C][C]107.405964102705[/C][C]1.25954154858745[/C][/ROW]
[ROW][C]0.41[/C][C]107.654638048717[/C][C]1.24680331754857[/C][/ROW]
[ROW][C]0.42[/C][C]107.901403782838[/C][C]1.25092188501175[/C][/ROW]
[ROW][C]0.43[/C][C]108.149161763348[/C][C]1.27162339270103[/C][/ROW]
[ROW][C]0.44[/C][C]108.400613109530[/C][C]1.30598628691964[/C][/ROW]
[ROW][C]0.45[/C][C]108.657955755881[/C][C]1.34993140837904[/C][/ROW]
[ROW][C]0.46[/C][C]108.922676840092[/C][C]1.39848435132797[/C][/ROW]
[ROW][C]0.47[/C][C]109.195463487482[/C][C]1.44685306082138[/C][/ROW]
[ROW][C]0.48[/C][C]109.476234020817[/C][C]1.49108646396612[/C][/ROW]
[ROW][C]0.49[/C][C]109.764275371696[/C][C]1.52783293139274[/C][/ROW]
[ROW][C]0.5[/C][C]110.058461241119[/C][C]1.55595561879263[/C][/ROW]
[ROW][C]0.51[/C][C]110.357518872833[/C][C]1.57536874006998[/C][/ROW]
[ROW][C]0.52[/C][C]110.660308898525[/C][C]1.58760062297502[/C][/ROW]
[ROW][C]0.53[/C][C]110.966081489099[/C][C]1.59553201969881[/C][/ROW]
[ROW][C]0.54[/C][C]111.274672791557[/C][C]1.60321539041704[/C][/ROW]
[ROW][C]0.55[/C][C]111.586609260581[/C][C]1.61495426083765[/C][/ROW]
[ROW][C]0.56[/C][C]111.903095649490[/C][C]1.63502710129598[/C][/ROW]
[ROW][C]0.57[/C][C]112.225876514546[/C][C]1.66621647354669[/C][/ROW]
[ROW][C]0.58[/C][C]112.556981056357[/C][C]1.71016537789485[/C][/ROW]
[ROW][C]0.59[/C][C]112.898384477711[/C][C]1.7649826117931[/C][/ROW]
[ROW][C]0.6[/C][C]113.251640677077[/C][C]1.82718130095032[/C][/ROW]
[ROW][C]0.61[/C][C]113.617554344083[/C][C]1.89112023729687[/C][/ROW]
[ROW][C]0.62[/C][C]113.995959287680[/C][C]1.95012933334803[/C][/ROW]
[ROW][C]0.63[/C][C]114.385651273241[/C][C]1.99768408436163[/C][/ROW]
[ROW][C]0.64[/C][C]114.784490289791[/C][C]2.02914716010942[/C][/ROW]
[ROW][C]0.65[/C][C]115.189647306290[/C][C]2.04145178997801[/C][/ROW]
[ROW][C]0.66[/C][C]115.597936374797[/C][C]2.03462354838228[/C][/ROW]
[ROW][C]0.67[/C][C]116.006156477742[/C][C]2.00997538826339[/C][/ROW]
[ROW][C]0.68[/C][C]116.411376002710[/C][C]1.97093341412028[/C][/ROW]
[ROW][C]0.69[/C][C]116.811124765882[/C][C]1.92088219502923[/C][/ROW]
[ROW][C]0.7[/C][C]117.203503210132[/C][C]1.8631699928894[/C][/ROW]
[ROW][C]0.71[/C][C]117.587258250245[/C][C]1.80055170208345[/C][/ROW]
[ROW][C]0.72[/C][C]117.961892105684[/C][C]1.73563523690843[/C][/ROW]
[ROW][C]0.73[/C][C]118.327852927763[/C][C]1.67187149008298[/C][/ROW]
[ROW][C]0.74[/C][C]118.686805159608[/C][C]1.61430816680075[/C][/ROW]
[ROW][C]0.75[/C][C]119.041908706819[/C][C]1.57019284034170[/C][/ROW]
[ROW][C]0.76[/C][C]119.397975294690[/C][C]1.54822881695657[/C][/ROW]
[ROW][C]0.77[/C][C]119.761346658340[/C][C]1.55692015182177[/C][/ROW]
[ROW][C]0.78[/C][C]120.139373429972[/C][C]1.60105280565858[/C][/ROW]
[ROW][C]0.79[/C][C]120.539469373131[/C][C]1.67919563670537[/C][/ROW]
[ROW][C]0.8[/C][C]120.967854096095[/C][C]1.78212976267771[/C][/ROW]
[ROW][C]0.81[/C][C]121.428238892935[/C][C]1.89390335640971[/C][/ROW]
[ROW][C]0.82[/C][C]121.920803736546[/C][C]1.99540763224676[/C][/ROW]
[ROW][C]0.83[/C][C]122.441811351969[/C][C]2.06774886383001[/C][/ROW]
[ROW][C]0.84[/C][C]122.984080942801[/C][C]2.09704783156996[/C][/ROW]
[ROW][C]0.85[/C][C]123.538310272474[/C][C]2.07732097630859[/C][/ROW]
[ROW][C]0.86[/C][C]124.094945266090[/C][C]2.01214717708188[/C][/ROW]
[ROW][C]0.87[/C][C]124.646046850451[/C][C]1.91361985885030[/C][/ROW]
[ROW][C]0.88[/C][C]125.186514491013[/C][C]1.79825923028733[/C][/ROW]
[ROW][C]0.89[/C][C]125.714198385777[/C][C]1.68136009635390[/C][/ROW]
[ROW][C]0.9[/C][C]126.228887446291[/C][C]1.57071782717221[/C][/ROW]
[ROW][C]0.91[/C][C]126.730747646888[/C][C]1.46405804668931[/C][/ROW]
[ROW][C]0.92[/C][C]127.21914789643[/C][C]1.35310619854562[/C][/ROW]
[ROW][C]0.93[/C][C]127.692548828618[/C][C]1.23182662497054[/C][/ROW]
[ROW][C]0.94[/C][C]128.149300003496[/C][C]1.10228369092547[/C][/ROW]
[ROW][C]0.95[/C][C]128.588840975886[/C][C]0.971279713353208[/C][/ROW]
[ROW][C]0.96[/C][C]129.014139497364[/C][C]0.839135446320667[/C][/ROW]
[ROW][C]0.97[/C][C]129.436428985099[/C][C]0.708653396746479[/C][/ROW]
[ROW][C]0.98[/C][C]129.872159274145[/C][C]0.638691290352981[/C][/ROW]
[ROW][C]0.99[/C][C]130.301674826134[/C][C]0.729664555922533[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5058&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5058&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
0.0192.75152892481633.08640528769207
0.0294.34904338038172.02972635044677
0.0395.60178072365881.27212061990743
0.0496.40409462784480.860085051321878
0.0596.90322353315780.667937622506312
0.0697.2436252779470.592154968317179
0.0797.5109285262530.583225941810971
0.0897.74966939725150.621592407073007
0.0997.98374976758610.695118368779659
0.198.22665247241830.790277235349132
0.1198.48528113330740.89202321054661
0.1298.76154399209840.986598883955582
0.1399.0536482853761.06443942213087
0.1499.3576420410911.12249618693110
0.1599.66905372185931.16323233497905
0.1699.98425730874621.19430019536560
0.17100.3012475521321.22429397027843
0.18100.6197120565631.26025731839266
0.19100.9405157694551.30466883086245
0.2101.2648774484241.35512942319352
0.21101.5935679614581.40562226035190
0.22101.9263967423741.44935153735305
0.23102.2621140888931.48071403745564
0.24102.5987003156911.49759224614887
0.25102.9338911461711.50103228172252
0.26103.2657347112011.49509592366059
0.27103.5929946238501.48563938533259
0.28103.9152876949741.47776261286888
0.29104.2329423235071.47478323041976
0.3104.5466514530121.47690522134481
0.31104.8570478770361.48175707311005
0.32105.1643392510241.48499690344007
0.33105.4681093516131.48183557563193
0.34105.7673353544031.46892095742490
0.35106.0606072807041.44452473061678
0.36106.3464831287251.40988404664635
0.37106.6238836792341.36833406228273
0.38106.8924288255831.32538154279382
0.39107.1526392031511.28731004841309
0.4107.4059641027051.25954154858745
0.41107.6546380487171.24680331754857
0.42107.9014037828381.25092188501175
0.43108.1491617633481.27162339270103
0.44108.4006131095301.30598628691964
0.45108.6579557558811.34993140837904
0.46108.9226768400921.39848435132797
0.47109.1954634874821.44685306082138
0.48109.4762340208171.49108646396612
0.49109.7642753716961.52783293139274
0.5110.0584612411191.55595561879263
0.51110.3575188728331.57536874006998
0.52110.6603088985251.58760062297502
0.53110.9660814890991.59553201969881
0.54111.2746727915571.60321539041704
0.55111.5866092605811.61495426083765
0.56111.9030956494901.63502710129598
0.57112.2258765145461.66621647354669
0.58112.5569810563571.71016537789485
0.59112.8983844777111.7649826117931
0.6113.2516406770771.82718130095032
0.61113.6175543440831.89112023729687
0.62113.9959592876801.95012933334803
0.63114.3856512732411.99768408436163
0.64114.7844902897912.02914716010942
0.65115.1896473062902.04145178997801
0.66115.5979363747972.03462354838228
0.67116.0061564777422.00997538826339
0.68116.4113760027101.97093341412028
0.69116.8111247658821.92088219502923
0.7117.2035032101321.8631699928894
0.71117.5872582502451.80055170208345
0.72117.9618921056841.73563523690843
0.73118.3278529277631.67187149008298
0.74118.6868051596081.61430816680075
0.75119.0419087068191.57019284034170
0.76119.3979752946901.54822881695657
0.77119.7613466583401.55692015182177
0.78120.1393734299721.60105280565858
0.79120.5394693731311.67919563670537
0.8120.9678540960951.78212976267771
0.81121.4282388929351.89390335640971
0.82121.9208037365461.99540763224676
0.83122.4418113519692.06774886383001
0.84122.9840809428012.09704783156996
0.85123.5383102724742.07732097630859
0.86124.0949452660902.01214717708188
0.87124.6460468504511.91361985885030
0.88125.1865144910131.79825923028733
0.89125.7141983857771.68136009635390
0.9126.2288874462911.57071782717221
0.91126.7307476468881.46405804668931
0.92127.219147896431.35310619854562
0.93127.6925488286181.23182662497054
0.94128.1493000034961.10228369092547
0.95128.5888409758860.971279713353208
0.96129.0141394973640.839135446320667
0.97129.4364289850990.708653396746479
0.98129.8721592741450.638691290352981
0.99130.3016748261340.729664555922533


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')