FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationWed, 22 Feb 2012 16:49:21 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Feb/22/t1329947462vhsm2xe703ecro4.htm/, Retrieved Mon, 06 May 2024 22:32:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=163228, Retrieved Mon, 06 May 2024 22:32:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDG20114(1)
Estimated Impact75

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] [decielen traingin...] [2012-02-22 21:49:21] [f6a7b86b75cb82ac7a5a766dce297b13] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
162,32
162,76
163,39
162,58
162,66
162,66
162,66
162,89
163,03
162,38
162,44
162,51
162,51
162,42
162,07
161,45
162,22
162,21
162,21
162,21
162,41
163,96
163,79
163,86
163,86
164,39
164,74
164,27
165,2
165,42
165,42
165,5
165,71
165,74
165,29
164,88
164,88
164,57
164,53
165,03
165,92
165,92
165,92
165,92
166,12
166,34
165,48
165,61
165,61
165,94
165,88
166,23
166,32
166,43
166,43
166,2
166,21
168,02
168,68
168,65

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=163228&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=163228&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=163228&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 time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01161.5813372529940.510400548785571
0.02161.7603854165120.374217447446221
0.03161.9256029442140.248415740913165
0.04162.0485419495270.156174585390144
0.05162.1294908333210.0995062237119826
0.06162.1807133199720.0720741654419936
0.07162.2149507874730.0656431888686784
0.08162.2412417385520.0702238577867167
0.09162.2647664283020.0782352867220159
0.1162.2879466547130.0857858343179238
0.11162.3115703279880.0910161600332538
0.12162.3356197552140.0941005512397602
0.13162.3598035961290.0953098338654067
0.14162.3838583642830.0961740397629653
0.15162.4076853736060.0974012151762785
0.16162.4313813111980.100083361101456
0.17162.4552120314240.104590828085869
0.18162.4795676830250.111473614022014
0.19162.504923301810.120769151791633
0.2162.5318150946040.133018624393696
0.21162.5608314569940.148457483159881
0.22162.5926108651570.167548427497405
0.23162.6278364276620.19112726395109
0.24162.6672183669810.219082041100067
0.25162.7114597677050.251125610771153
0.26162.7612061428050.287240009727335
0.27162.8169843646350.326065679247373
0.28162.8791401636590.366505950560353
0.29162.9477849703990.406624718547283
0.3163.0227620862310.444901498158772
0.31163.1036392346260.479802824990449
0.32163.1897301277170.509373646578207
0.33163.2801427437820.532962395034937
0.34163.3738475931870.549741059352956
0.35163.4697562448260.560027793959699
0.36163.5667993322540.564054798218334
0.37163.6639942382270.562605559852691
0.38163.7604952965080.556799580630404
0.39163.8556229472730.547639927676734
0.4163.9488719976750.536271196773309
0.41164.0399022087530.523576631706126
0.42164.1285163404290.510228992124912
0.43164.2146313637070.496743676195084
0.44164.2982479520390.483368334728245
0.45164.3794219914810.470550443819496
0.46164.4582402022280.457987993768357
0.47164.534800500370.445938889660429
0.48164.6091967550850.433983302218865
0.49164.6815072181350.422620486822104
0.5164.7517860344840.411366813578179
0.51164.8200576685420.400011419192807
0.52164.8863145355480.388315018540493
0.53164.9505183808590.376236431994461
0.54165.0126058643910.363480925082574
0.55165.0724983667830.350066251455449
0.56165.1301153361820.335891878947528
0.57165.1853897174280.32100845278249
0.58165.2382833564370.305714798650685
0.59165.2887999366890.290375747283514
0.6165.3369931015070.27533459127162
0.61165.3829679752190.261103322305887
0.62165.426875254180.247695930946406
0.63165.4688982524310.235792966736251
0.64165.509234562210.225191826516449
0.65165.5480751129480.215976712982127
0.66165.5855841799810.207794418234614
0.67165.6218841366570.200383380935977
0.68165.6570483458670.193247369923269
0.69165.6911045090290.186218832568136
0.7165.7240490897330.178796512908028
0.71165.755871285240.170916270162957
0.72165.7865827502130.162854008047782
0.73165.8162473316780.154866733519161
0.74165.8450039788860.147385197892598
0.75165.8730762445550.141196034640983
0.76165.9007637115160.136964657112534
0.77165.9284142315150.134801913981276
0.78165.9563805635150.134872100312152
0.79165.98496992410.13677994276019
0.8166.014398975150.139366198727713
0.81166.0447689557030.142154993620606
0.82166.0760758626630.143957076372165
0.83166.1082698199380.144258217241897
0.84166.1413780973760.143186548622634
0.85166.1757095045850.141440137031082
0.86166.2121630556860.140902331716597
0.87166.252663054550.145091770786224
0.88166.3007182085370.15990899214323
0.89166.3620278360320.193771697634347
0.9166.4449124415040.256201090896707
0.91166.5601425081650.354080947505947
0.92166.7195679217450.487586832537584
0.93166.9330016763320.645149349017006
0.94167.2033340341360.798121495140864
0.95167.5209885904050.90140420110835
0.96167.8603321776280.904156503953242
0.97168.181626137060.773110314268737
0.98168.4411296458980.522130930120125
0.99168.607941531520.230545771861486

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 161.581337252994 & 0.510400548785571 \tabularnewline
0.02 & 161.760385416512 & 0.374217447446221 \tabularnewline
0.03 & 161.925602944214 & 0.248415740913165 \tabularnewline
0.04 & 162.048541949527 & 0.156174585390144 \tabularnewline
0.05 & 162.129490833321 & 0.0995062237119826 \tabularnewline
0.06 & 162.180713319972 & 0.0720741654419936 \tabularnewline
0.07 & 162.214950787473 & 0.0656431888686784 \tabularnewline
0.08 & 162.241241738552 & 0.0702238577867167 \tabularnewline
0.09 & 162.264766428302 & 0.0782352867220159 \tabularnewline
0.1 & 162.287946654713 & 0.0857858343179238 \tabularnewline
0.11 & 162.311570327988 & 0.0910161600332538 \tabularnewline
0.12 & 162.335619755214 & 0.0941005512397602 \tabularnewline
0.13 & 162.359803596129 & 0.0953098338654067 \tabularnewline
0.14 & 162.383858364283 & 0.0961740397629653 \tabularnewline
0.15 & 162.407685373606 & 0.0974012151762785 \tabularnewline
0.16 & 162.431381311198 & 0.100083361101456 \tabularnewline
0.17 & 162.455212031424 & 0.104590828085869 \tabularnewline
0.18 & 162.479567683025 & 0.111473614022014 \tabularnewline
0.19 & 162.50492330181 & 0.120769151791633 \tabularnewline
0.2 & 162.531815094604 & 0.133018624393696 \tabularnewline
0.21 & 162.560831456994 & 0.148457483159881 \tabularnewline
0.22 & 162.592610865157 & 0.167548427497405 \tabularnewline
0.23 & 162.627836427662 & 0.19112726395109 \tabularnewline
0.24 & 162.667218366981 & 0.219082041100067 \tabularnewline
0.25 & 162.711459767705 & 0.251125610771153 \tabularnewline
0.26 & 162.761206142805 & 0.287240009727335 \tabularnewline
0.27 & 162.816984364635 & 0.326065679247373 \tabularnewline
0.28 & 162.879140163659 & 0.366505950560353 \tabularnewline
0.29 & 162.947784970399 & 0.406624718547283 \tabularnewline
0.3 & 163.022762086231 & 0.444901498158772 \tabularnewline
0.31 & 163.103639234626 & 0.479802824990449 \tabularnewline
0.32 & 163.189730127717 & 0.509373646578207 \tabularnewline
0.33 & 163.280142743782 & 0.532962395034937 \tabularnewline
0.34 & 163.373847593187 & 0.549741059352956 \tabularnewline
0.35 & 163.469756244826 & 0.560027793959699 \tabularnewline
0.36 & 163.566799332254 & 0.564054798218334 \tabularnewline
0.37 & 163.663994238227 & 0.562605559852691 \tabularnewline
0.38 & 163.760495296508 & 0.556799580630404 \tabularnewline
0.39 & 163.855622947273 & 0.547639927676734 \tabularnewline
0.4 & 163.948871997675 & 0.536271196773309 \tabularnewline
0.41 & 164.039902208753 & 0.523576631706126 \tabularnewline
0.42 & 164.128516340429 & 0.510228992124912 \tabularnewline
0.43 & 164.214631363707 & 0.496743676195084 \tabularnewline
0.44 & 164.298247952039 & 0.483368334728245 \tabularnewline
0.45 & 164.379421991481 & 0.470550443819496 \tabularnewline
0.46 & 164.458240202228 & 0.457987993768357 \tabularnewline
0.47 & 164.53480050037 & 0.445938889660429 \tabularnewline
0.48 & 164.609196755085 & 0.433983302218865 \tabularnewline
0.49 & 164.681507218135 & 0.422620486822104 \tabularnewline
0.5 & 164.751786034484 & 0.411366813578179 \tabularnewline
0.51 & 164.820057668542 & 0.400011419192807 \tabularnewline
0.52 & 164.886314535548 & 0.388315018540493 \tabularnewline
0.53 & 164.950518380859 & 0.376236431994461 \tabularnewline
0.54 & 165.012605864391 & 0.363480925082574 \tabularnewline
0.55 & 165.072498366783 & 0.350066251455449 \tabularnewline
0.56 & 165.130115336182 & 0.335891878947528 \tabularnewline
0.57 & 165.185389717428 & 0.32100845278249 \tabularnewline
0.58 & 165.238283356437 & 0.305714798650685 \tabularnewline
0.59 & 165.288799936689 & 0.290375747283514 \tabularnewline
0.6 & 165.336993101507 & 0.27533459127162 \tabularnewline
0.61 & 165.382967975219 & 0.261103322305887 \tabularnewline
0.62 & 165.42687525418 & 0.247695930946406 \tabularnewline
0.63 & 165.468898252431 & 0.235792966736251 \tabularnewline
0.64 & 165.50923456221 & 0.225191826516449 \tabularnewline
0.65 & 165.548075112948 & 0.215976712982127 \tabularnewline
0.66 & 165.585584179981 & 0.207794418234614 \tabularnewline
0.67 & 165.621884136657 & 0.200383380935977 \tabularnewline
0.68 & 165.657048345867 & 0.193247369923269 \tabularnewline
0.69 & 165.691104509029 & 0.186218832568136 \tabularnewline
0.7 & 165.724049089733 & 0.178796512908028 \tabularnewline
0.71 & 165.75587128524 & 0.170916270162957 \tabularnewline
0.72 & 165.786582750213 & 0.162854008047782 \tabularnewline
0.73 & 165.816247331678 & 0.154866733519161 \tabularnewline
0.74 & 165.845003978886 & 0.147385197892598 \tabularnewline
0.75 & 165.873076244555 & 0.141196034640983 \tabularnewline
0.76 & 165.900763711516 & 0.136964657112534 \tabularnewline
0.77 & 165.928414231515 & 0.134801913981276 \tabularnewline
0.78 & 165.956380563515 & 0.134872100312152 \tabularnewline
0.79 & 165.9849699241 & 0.13677994276019 \tabularnewline
0.8 & 166.01439897515 & 0.139366198727713 \tabularnewline
0.81 & 166.044768955703 & 0.142154993620606 \tabularnewline
0.82 & 166.076075862663 & 0.143957076372165 \tabularnewline
0.83 & 166.108269819938 & 0.144258217241897 \tabularnewline
0.84 & 166.141378097376 & 0.143186548622634 \tabularnewline
0.85 & 166.175709504585 & 0.141440137031082 \tabularnewline
0.86 & 166.212163055686 & 0.140902331716597 \tabularnewline
0.87 & 166.25266305455 & 0.145091770786224 \tabularnewline
0.88 & 166.300718208537 & 0.15990899214323 \tabularnewline
0.89 & 166.362027836032 & 0.193771697634347 \tabularnewline
0.9 & 166.444912441504 & 0.256201090896707 \tabularnewline
0.91 & 166.560142508165 & 0.354080947505947 \tabularnewline
0.92 & 166.719567921745 & 0.487586832537584 \tabularnewline
0.93 & 166.933001676332 & 0.645149349017006 \tabularnewline
0.94 & 167.203334034136 & 0.798121495140864 \tabularnewline
0.95 & 167.520988590405 & 0.90140420110835 \tabularnewline
0.96 & 167.860332177628 & 0.904156503953242 \tabularnewline
0.97 & 168.18162613706 & 0.773110314268737 \tabularnewline
0.98 & 168.441129645898 & 0.522130930120125 \tabularnewline
0.99 & 168.60794153152 & 0.230545771861486 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=163228&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]161.581337252994[/C][C]0.510400548785571[/C][/ROW]
[ROW][C]0.02[/C][C]161.760385416512[/C][C]0.374217447446221[/C][/ROW]
[ROW][C]0.03[/C][C]161.925602944214[/C][C]0.248415740913165[/C][/ROW]
[ROW][C]0.04[/C][C]162.048541949527[/C][C]0.156174585390144[/C][/ROW]
[ROW][C]0.05[/C][C]162.129490833321[/C][C]0.0995062237119826[/C][/ROW]
[ROW][C]0.06[/C][C]162.180713319972[/C][C]0.0720741654419936[/C][/ROW]
[ROW][C]0.07[/C][C]162.214950787473[/C][C]0.0656431888686784[/C][/ROW]
[ROW][C]0.08[/C][C]162.241241738552[/C][C]0.0702238577867167[/C][/ROW]
[ROW][C]0.09[/C][C]162.264766428302[/C][C]0.0782352867220159[/C][/ROW]
[ROW][C]0.1[/C][C]162.287946654713[/C][C]0.0857858343179238[/C][/ROW]
[ROW][C]0.11[/C][C]162.311570327988[/C][C]0.0910161600332538[/C][/ROW]
[ROW][C]0.12[/C][C]162.335619755214[/C][C]0.0941005512397602[/C][/ROW]
[ROW][C]0.13[/C][C]162.359803596129[/C][C]0.0953098338654067[/C][/ROW]
[ROW][C]0.14[/C][C]162.383858364283[/C][C]0.0961740397629653[/C][/ROW]
[ROW][C]0.15[/C][C]162.407685373606[/C][C]0.0974012151762785[/C][/ROW]
[ROW][C]0.16[/C][C]162.431381311198[/C][C]0.100083361101456[/C][/ROW]
[ROW][C]0.17[/C][C]162.455212031424[/C][C]0.104590828085869[/C][/ROW]
[ROW][C]0.18[/C][C]162.479567683025[/C][C]0.111473614022014[/C][/ROW]
[ROW][C]0.19[/C][C]162.50492330181[/C][C]0.120769151791633[/C][/ROW]
[ROW][C]0.2[/C][C]162.531815094604[/C][C]0.133018624393696[/C][/ROW]
[ROW][C]0.21[/C][C]162.560831456994[/C][C]0.148457483159881[/C][/ROW]
[ROW][C]0.22[/C][C]162.592610865157[/C][C]0.167548427497405[/C][/ROW]
[ROW][C]0.23[/C][C]162.627836427662[/C][C]0.19112726395109[/C][/ROW]
[ROW][C]0.24[/C][C]162.667218366981[/C][C]0.219082041100067[/C][/ROW]
[ROW][C]0.25[/C][C]162.711459767705[/C][C]0.251125610771153[/C][/ROW]
[ROW][C]0.26[/C][C]162.761206142805[/C][C]0.287240009727335[/C][/ROW]
[ROW][C]0.27[/C][C]162.816984364635[/C][C]0.326065679247373[/C][/ROW]
[ROW][C]0.28[/C][C]162.879140163659[/C][C]0.366505950560353[/C][/ROW]
[ROW][C]0.29[/C][C]162.947784970399[/C][C]0.406624718547283[/C][/ROW]
[ROW][C]0.3[/C][C]163.022762086231[/C][C]0.444901498158772[/C][/ROW]
[ROW][C]0.31[/C][C]163.103639234626[/C][C]0.479802824990449[/C][/ROW]
[ROW][C]0.32[/C][C]163.189730127717[/C][C]0.509373646578207[/C][/ROW]
[ROW][C]0.33[/C][C]163.280142743782[/C][C]0.532962395034937[/C][/ROW]
[ROW][C]0.34[/C][C]163.373847593187[/C][C]0.549741059352956[/C][/ROW]
[ROW][C]0.35[/C][C]163.469756244826[/C][C]0.560027793959699[/C][/ROW]
[ROW][C]0.36[/C][C]163.566799332254[/C][C]0.564054798218334[/C][/ROW]
[ROW][C]0.37[/C][C]163.663994238227[/C][C]0.562605559852691[/C][/ROW]
[ROW][C]0.38[/C][C]163.760495296508[/C][C]0.556799580630404[/C][/ROW]
[ROW][C]0.39[/C][C]163.855622947273[/C][C]0.547639927676734[/C][/ROW]
[ROW][C]0.4[/C][C]163.948871997675[/C][C]0.536271196773309[/C][/ROW]
[ROW][C]0.41[/C][C]164.039902208753[/C][C]0.523576631706126[/C][/ROW]
[ROW][C]0.42[/C][C]164.128516340429[/C][C]0.510228992124912[/C][/ROW]
[ROW][C]0.43[/C][C]164.214631363707[/C][C]0.496743676195084[/C][/ROW]
[ROW][C]0.44[/C][C]164.298247952039[/C][C]0.483368334728245[/C][/ROW]
[ROW][C]0.45[/C][C]164.379421991481[/C][C]0.470550443819496[/C][/ROW]
[ROW][C]0.46[/C][C]164.458240202228[/C][C]0.457987993768357[/C][/ROW]
[ROW][C]0.47[/C][C]164.53480050037[/C][C]0.445938889660429[/C][/ROW]
[ROW][C]0.48[/C][C]164.609196755085[/C][C]0.433983302218865[/C][/ROW]
[ROW][C]0.49[/C][C]164.681507218135[/C][C]0.422620486822104[/C][/ROW]
[ROW][C]0.5[/C][C]164.751786034484[/C][C]0.411366813578179[/C][/ROW]
[ROW][C]0.51[/C][C]164.820057668542[/C][C]0.400011419192807[/C][/ROW]
[ROW][C]0.52[/C][C]164.886314535548[/C][C]0.388315018540493[/C][/ROW]
[ROW][C]0.53[/C][C]164.950518380859[/C][C]0.376236431994461[/C][/ROW]
[ROW][C]0.54[/C][C]165.012605864391[/C][C]0.363480925082574[/C][/ROW]
[ROW][C]0.55[/C][C]165.072498366783[/C][C]0.350066251455449[/C][/ROW]
[ROW][C]0.56[/C][C]165.130115336182[/C][C]0.335891878947528[/C][/ROW]
[ROW][C]0.57[/C][C]165.185389717428[/C][C]0.32100845278249[/C][/ROW]
[ROW][C]0.58[/C][C]165.238283356437[/C][C]0.305714798650685[/C][/ROW]
[ROW][C]0.59[/C][C]165.288799936689[/C][C]0.290375747283514[/C][/ROW]
[ROW][C]0.6[/C][C]165.336993101507[/C][C]0.27533459127162[/C][/ROW]
[ROW][C]0.61[/C][C]165.382967975219[/C][C]0.261103322305887[/C][/ROW]
[ROW][C]0.62[/C][C]165.42687525418[/C][C]0.247695930946406[/C][/ROW]
[ROW][C]0.63[/C][C]165.468898252431[/C][C]0.235792966736251[/C][/ROW]
[ROW][C]0.64[/C][C]165.50923456221[/C][C]0.225191826516449[/C][/ROW]
[ROW][C]0.65[/C][C]165.548075112948[/C][C]0.215976712982127[/C][/ROW]
[ROW][C]0.66[/C][C]165.585584179981[/C][C]0.207794418234614[/C][/ROW]
[ROW][C]0.67[/C][C]165.621884136657[/C][C]0.200383380935977[/C][/ROW]
[ROW][C]0.68[/C][C]165.657048345867[/C][C]0.193247369923269[/C][/ROW]
[ROW][C]0.69[/C][C]165.691104509029[/C][C]0.186218832568136[/C][/ROW]
[ROW][C]0.7[/C][C]165.724049089733[/C][C]0.178796512908028[/C][/ROW]
[ROW][C]0.71[/C][C]165.75587128524[/C][C]0.170916270162957[/C][/ROW]
[ROW][C]0.72[/C][C]165.786582750213[/C][C]0.162854008047782[/C][/ROW]
[ROW][C]0.73[/C][C]165.816247331678[/C][C]0.154866733519161[/C][/ROW]
[ROW][C]0.74[/C][C]165.845003978886[/C][C]0.147385197892598[/C][/ROW]
[ROW][C]0.75[/C][C]165.873076244555[/C][C]0.141196034640983[/C][/ROW]
[ROW][C]0.76[/C][C]165.900763711516[/C][C]0.136964657112534[/C][/ROW]
[ROW][C]0.77[/C][C]165.928414231515[/C][C]0.134801913981276[/C][/ROW]
[ROW][C]0.78[/C][C]165.956380563515[/C][C]0.134872100312152[/C][/ROW]
[ROW][C]0.79[/C][C]165.9849699241[/C][C]0.13677994276019[/C][/ROW]
[ROW][C]0.8[/C][C]166.01439897515[/C][C]0.139366198727713[/C][/ROW]
[ROW][C]0.81[/C][C]166.044768955703[/C][C]0.142154993620606[/C][/ROW]
[ROW][C]0.82[/C][C]166.076075862663[/C][C]0.143957076372165[/C][/ROW]
[ROW][C]0.83[/C][C]166.108269819938[/C][C]0.144258217241897[/C][/ROW]
[ROW][C]0.84[/C][C]166.141378097376[/C][C]0.143186548622634[/C][/ROW]
[ROW][C]0.85[/C][C]166.175709504585[/C][C]0.141440137031082[/C][/ROW]
[ROW][C]0.86[/C][C]166.212163055686[/C][C]0.140902331716597[/C][/ROW]
[ROW][C]0.87[/C][C]166.25266305455[/C][C]0.145091770786224[/C][/ROW]
[ROW][C]0.88[/C][C]166.300718208537[/C][C]0.15990899214323[/C][/ROW]
[ROW][C]0.89[/C][C]166.362027836032[/C][C]0.193771697634347[/C][/ROW]
[ROW][C]0.9[/C][C]166.444912441504[/C][C]0.256201090896707[/C][/ROW]
[ROW][C]0.91[/C][C]166.560142508165[/C][C]0.354080947505947[/C][/ROW]
[ROW][C]0.92[/C][C]166.719567921745[/C][C]0.487586832537584[/C][/ROW]
[ROW][C]0.93[/C][C]166.933001676332[/C][C]0.645149349017006[/C][/ROW]
[ROW][C]0.94[/C][C]167.203334034136[/C][C]0.798121495140864[/C][/ROW]
[ROW][C]0.95[/C][C]167.520988590405[/C][C]0.90140420110835[/C][/ROW]
[ROW][C]0.96[/C][C]167.860332177628[/C][C]0.904156503953242[/C][/ROW]
[ROW][C]0.97[/C][C]168.18162613706[/C][C]0.773110314268737[/C][/ROW]
[ROW][C]0.98[/C][C]168.441129645898[/C][C]0.522130930120125[/C][/ROW]
[ROW][C]0.99[/C][C]168.60794153152[/C][C]0.230545771861486[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=163228&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=163228&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
0.01161.5813372529940.510400548785571
0.02161.7603854165120.374217447446221
0.03161.9256029442140.248415740913165
0.04162.0485419495270.156174585390144
0.05162.1294908333210.0995062237119826
0.06162.1807133199720.0720741654419936
0.07162.2149507874730.0656431888686784
0.08162.2412417385520.0702238577867167
0.09162.2647664283020.0782352867220159
0.1162.2879466547130.0857858343179238
0.11162.3115703279880.0910161600332538
0.12162.3356197552140.0941005512397602
0.13162.3598035961290.0953098338654067
0.14162.3838583642830.0961740397629653
0.15162.4076853736060.0974012151762785
0.16162.4313813111980.100083361101456
0.17162.4552120314240.104590828085869
0.18162.4795676830250.111473614022014
0.19162.504923301810.120769151791633
0.2162.5318150946040.133018624393696
0.21162.5608314569940.148457483159881
0.22162.5926108651570.167548427497405
0.23162.6278364276620.19112726395109
0.24162.6672183669810.219082041100067
0.25162.7114597677050.251125610771153
0.26162.7612061428050.287240009727335
0.27162.8169843646350.326065679247373
0.28162.8791401636590.366505950560353
0.29162.9477849703990.406624718547283
0.3163.0227620862310.444901498158772
0.31163.1036392346260.479802824990449
0.32163.1897301277170.509373646578207
0.33163.2801427437820.532962395034937
0.34163.3738475931870.549741059352956
0.35163.4697562448260.560027793959699
0.36163.5667993322540.564054798218334
0.37163.6639942382270.562605559852691
0.38163.7604952965080.556799580630404
0.39163.8556229472730.547639927676734
0.4163.9488719976750.536271196773309
0.41164.0399022087530.523576631706126
0.42164.1285163404290.510228992124912
0.43164.2146313637070.496743676195084
0.44164.2982479520390.483368334728245
0.45164.3794219914810.470550443819496
0.46164.4582402022280.457987993768357
0.47164.534800500370.445938889660429
0.48164.6091967550850.433983302218865
0.49164.6815072181350.422620486822104
0.5164.7517860344840.411366813578179
0.51164.8200576685420.400011419192807
0.52164.8863145355480.388315018540493
0.53164.9505183808590.376236431994461
0.54165.0126058643910.363480925082574
0.55165.0724983667830.350066251455449
0.56165.1301153361820.335891878947528
0.57165.1853897174280.32100845278249
0.58165.2382833564370.305714798650685
0.59165.2887999366890.290375747283514
0.6165.3369931015070.27533459127162
0.61165.3829679752190.261103322305887
0.62165.426875254180.247695930946406
0.63165.4688982524310.235792966736251
0.64165.509234562210.225191826516449
0.65165.5480751129480.215976712982127
0.66165.5855841799810.207794418234614
0.67165.6218841366570.200383380935977
0.68165.6570483458670.193247369923269
0.69165.6911045090290.186218832568136
0.7165.7240490897330.178796512908028
0.71165.755871285240.170916270162957
0.72165.7865827502130.162854008047782
0.73165.8162473316780.154866733519161
0.74165.8450039788860.147385197892598
0.75165.8730762445550.141196034640983
0.76165.9007637115160.136964657112534
0.77165.9284142315150.134801913981276
0.78165.9563805635150.134872100312152
0.79165.98496992410.13677994276019
0.8166.014398975150.139366198727713
0.81166.0447689557030.142154993620606
0.82166.0760758626630.143957076372165
0.83166.1082698199380.144258217241897
0.84166.1413780973760.143186548622634
0.85166.1757095045850.141440137031082
0.86166.2121630556860.140902331716597
0.87166.252663054550.145091770786224
0.88166.3007182085370.15990899214323
0.89166.3620278360320.193771697634347
0.9166.4449124415040.256201090896707
0.91166.5601425081650.354080947505947
0.92166.7195679217450.487586832537584
0.93166.9330016763320.645149349017006
0.94167.2033340341360.798121495140864
0.95167.5209885904050.90140420110835
0.96167.8603321776280.904156503953242
0.97168.181626137060.773110314268737
0.98168.4411296458980.522130930120125
0.99168.607941531520.230545771861486


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')