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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 computationTue, 20 Aug 2013 21:03:02 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Aug/20/t13770470168k3556c6vihyi15.htm/, Retrieved Sat, 27 Apr 2024 10:41:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=211274, Retrieved Sat, 27 Apr 2024 10:41:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsRaedts Mathias
Estimated Impact97

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] [Tijdreeks B - Stap 7] [2013-08-21 01:03:02] [e2e43c39163d7563005e2a800525cced] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
910
910
970
950
980
860
920
950
900
950
950
940
860
810
870
960
970
860
850
910
970
980
970
1000
910
740
810
1050
920
830
880
910
880
960
900
1110
870
720
780
970
1020
830
820
920
840
920
920
1150
820
760
760
960
1010
790
820
880
820
870
870
1230
760
810
850
990
940
850
860
860
780
880
850
1220
850
800
840
1090
810
870
810
860
800
870
860
1220
820
860
750
1020
780
830
860
850
820
790
1020
1230
760
880
760
1090
840
900
930
820
780
870
990
1270

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'Herman Ole Andreas Wold' @ wold.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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211274&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211274&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211274&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'Herman Ole Andreas Wold' @ wold.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01730.20184453331915.6735348968479
0.02742.59701816431711.5471077214367
0.03751.4411900274338.3468178737607
0.04757.0466104478556.37341688222687
0.05761.0242874889156.56717443480649
0.06764.6329759180118.22522883909749
0.07768.5067773860619.94155314161171
0.08772.74530979582311.0290160647413
0.09777.18381221638611.517847215239
0.1781.63925442559911.7470163378831
0.11786.01036246698711.9360250151848
0.12790.25662147190412.0497163314208
0.13794.34406321028711.9370000932939
0.14798.21899998180711.5056684149206
0.15801.81833027902710.7868292407
0.16805.0947358785639.90624143117923
0.17808.0347306808229.01639216123736
0.18810.6614352060448.244037955826
0.19813.0260912214537.66521885185989
0.2815.1962817626787.31711486019615
0.21817.2462703137247.22326691737297
0.22819.2504244364457.39249307152953
0.23821.2779243588287.81369782068718
0.24823.3869392213448.43453241595076
0.25825.6181707325929.16554410913701
0.26827.9893835363639.89734808087804
0.27830.49306051166410.5198597319334
0.28833.09848400480310.9467218063928
0.29835.75800216653111.1285725898822
0.3838.4158568992211.0560045937065
0.31841.01730727465610.755511542169
0.32843.51600052302210.2792240039632
0.33845.8783776040299.68925486973243
0.34848.0849463041169.04635992213425
0.35850.129126455198.39971428905078
0.36852.0148181176287.78522905072813
0.37853.753798707897.22801168636147
0.38855.3636362353936.74683290353989
0.39856.8662556669076.36050309345451
0.4858.2868779666686.08631059341652
0.41859.6529365219585.93826074039912
0.42860.9927662117455.92150499134456
0.43862.3342010334426.02749961881934
0.44863.7034825395776.24364578952839
0.45865.1249007981646.55482964911543
0.46866.6213295577196.95595499774671
0.47868.2153958404247.45182180082546
0.48869.9306440808598.0555089028517
0.49871.7919020938468.77977186239218
0.5873.8242168271839.62585643299141
0.51876.05016051304910.5738228863215
0.52878.4858717654411.5815647666927
0.53881.13671120604812.5843263996382
0.54883.99371696293913.5050201003553
0.55887.0320412702414.2612875885067
0.56890.21221364976414.7880694724274
0.57893.48447019753515.046730404936
0.58896.79564835777115.0369987679381
0.59900.09745665867914.8003689947749
0.6903.35447571908114.4148302366071
0.61906.55016316200113.9864753121896
0.62909.68945738914213.6248721942503
0.63912.79723564163813.4249835185856
0.64915.91273652843513.4445105895408
0.65919.08093040720413.6889957162102
0.66922.34253782376714.1101271231795
0.67925.724795999614.6179427069167
0.68929.2350220049115.1014306288542
0.69932.85845099099315.454942228744
0.7936.56080624986715.5985553813153
0.71940.29484122141915.4946408298976
0.72944.00909444558715.1513816744515
0.73947.65673029856914.6140102441462
0.74951.20278676085313.9520036897233
0.75954.62920633013713.2436491534987
0.76957.93811748218512.5679083326292
0.77961.15431288763812.0067054546669
0.78964.32741091505211.6484567533032
0.79967.53306399882611.5895386315997
0.8970.87161108396811.9161704879624
0.81974.46271777707612.6764398453946
0.82978.43634561981713.8584094115897
0.83982.92352514556515.3946919091276
0.84988.05349643893917.2054137144672
0.85993.96443576400319.257345261108
0.861000.830536641321.632278822156
0.871008.8980050612624.5504828375092
0.881018.511566506128.2901332517035
0.891030.1126554813432.9933924146669
0.91044.2078294553838.5276312776145
0.911061.3234768301244.5710875228132
0.921081.9340944540950.8052373015244
0.931106.2601853699256.6764373804872
0.941133.7999351741760.4674661131348
0.951162.7298806211758.9167730611898
0.961189.9187013739849.3207014875698
0.971212.6600649945833.5684303340044
0.981232.0092860295420.9014489948179
0.991252.5929480920325.9221541576499

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 730.201844533319 & 15.6735348968479 \tabularnewline
0.02 & 742.597018164317 & 11.5471077214367 \tabularnewline
0.03 & 751.441190027433 & 8.3468178737607 \tabularnewline
0.04 & 757.046610447855 & 6.37341688222687 \tabularnewline
0.05 & 761.024287488915 & 6.56717443480649 \tabularnewline
0.06 & 764.632975918011 & 8.22522883909749 \tabularnewline
0.07 & 768.506777386061 & 9.94155314161171 \tabularnewline
0.08 & 772.745309795823 & 11.0290160647413 \tabularnewline
0.09 & 777.183812216386 & 11.517847215239 \tabularnewline
0.1 & 781.639254425599 & 11.7470163378831 \tabularnewline
0.11 & 786.010362466987 & 11.9360250151848 \tabularnewline
0.12 & 790.256621471904 & 12.0497163314208 \tabularnewline
0.13 & 794.344063210287 & 11.9370000932939 \tabularnewline
0.14 & 798.218999981807 & 11.5056684149206 \tabularnewline
0.15 & 801.818330279027 & 10.7868292407 \tabularnewline
0.16 & 805.094735878563 & 9.90624143117923 \tabularnewline
0.17 & 808.034730680822 & 9.01639216123736 \tabularnewline
0.18 & 810.661435206044 & 8.244037955826 \tabularnewline
0.19 & 813.026091221453 & 7.66521885185989 \tabularnewline
0.2 & 815.196281762678 & 7.31711486019615 \tabularnewline
0.21 & 817.246270313724 & 7.22326691737297 \tabularnewline
0.22 & 819.250424436445 & 7.39249307152953 \tabularnewline
0.23 & 821.277924358828 & 7.81369782068718 \tabularnewline
0.24 & 823.386939221344 & 8.43453241595076 \tabularnewline
0.25 & 825.618170732592 & 9.16554410913701 \tabularnewline
0.26 & 827.989383536363 & 9.89734808087804 \tabularnewline
0.27 & 830.493060511664 & 10.5198597319334 \tabularnewline
0.28 & 833.098484004803 & 10.9467218063928 \tabularnewline
0.29 & 835.758002166531 & 11.1285725898822 \tabularnewline
0.3 & 838.41585689922 & 11.0560045937065 \tabularnewline
0.31 & 841.017307274656 & 10.755511542169 \tabularnewline
0.32 & 843.516000523022 & 10.2792240039632 \tabularnewline
0.33 & 845.878377604029 & 9.68925486973243 \tabularnewline
0.34 & 848.084946304116 & 9.04635992213425 \tabularnewline
0.35 & 850.12912645519 & 8.39971428905078 \tabularnewline
0.36 & 852.014818117628 & 7.78522905072813 \tabularnewline
0.37 & 853.75379870789 & 7.22801168636147 \tabularnewline
0.38 & 855.363636235393 & 6.74683290353989 \tabularnewline
0.39 & 856.866255666907 & 6.36050309345451 \tabularnewline
0.4 & 858.286877966668 & 6.08631059341652 \tabularnewline
0.41 & 859.652936521958 & 5.93826074039912 \tabularnewline
0.42 & 860.992766211745 & 5.92150499134456 \tabularnewline
0.43 & 862.334201033442 & 6.02749961881934 \tabularnewline
0.44 & 863.703482539577 & 6.24364578952839 \tabularnewline
0.45 & 865.124900798164 & 6.55482964911543 \tabularnewline
0.46 & 866.621329557719 & 6.95595499774671 \tabularnewline
0.47 & 868.215395840424 & 7.45182180082546 \tabularnewline
0.48 & 869.930644080859 & 8.0555089028517 \tabularnewline
0.49 & 871.791902093846 & 8.77977186239218 \tabularnewline
0.5 & 873.824216827183 & 9.62585643299141 \tabularnewline
0.51 & 876.050160513049 & 10.5738228863215 \tabularnewline
0.52 & 878.48587176544 & 11.5815647666927 \tabularnewline
0.53 & 881.136711206048 & 12.5843263996382 \tabularnewline
0.54 & 883.993716962939 & 13.5050201003553 \tabularnewline
0.55 & 887.03204127024 & 14.2612875885067 \tabularnewline
0.56 & 890.212213649764 & 14.7880694724274 \tabularnewline
0.57 & 893.484470197535 & 15.046730404936 \tabularnewline
0.58 & 896.795648357771 & 15.0369987679381 \tabularnewline
0.59 & 900.097456658679 & 14.8003689947749 \tabularnewline
0.6 & 903.354475719081 & 14.4148302366071 \tabularnewline
0.61 & 906.550163162001 & 13.9864753121896 \tabularnewline
0.62 & 909.689457389142 & 13.6248721942503 \tabularnewline
0.63 & 912.797235641638 & 13.4249835185856 \tabularnewline
0.64 & 915.912736528435 & 13.4445105895408 \tabularnewline
0.65 & 919.080930407204 & 13.6889957162102 \tabularnewline
0.66 & 922.342537823767 & 14.1101271231795 \tabularnewline
0.67 & 925.7247959996 & 14.6179427069167 \tabularnewline
0.68 & 929.23502200491 & 15.1014306288542 \tabularnewline
0.69 & 932.858450990993 & 15.454942228744 \tabularnewline
0.7 & 936.560806249867 & 15.5985553813153 \tabularnewline
0.71 & 940.294841221419 & 15.4946408298976 \tabularnewline
0.72 & 944.009094445587 & 15.1513816744515 \tabularnewline
0.73 & 947.656730298569 & 14.6140102441462 \tabularnewline
0.74 & 951.202786760853 & 13.9520036897233 \tabularnewline
0.75 & 954.629206330137 & 13.2436491534987 \tabularnewline
0.76 & 957.938117482185 & 12.5679083326292 \tabularnewline
0.77 & 961.154312887638 & 12.0067054546669 \tabularnewline
0.78 & 964.327410915052 & 11.6484567533032 \tabularnewline
0.79 & 967.533063998826 & 11.5895386315997 \tabularnewline
0.8 & 970.871611083968 & 11.9161704879624 \tabularnewline
0.81 & 974.462717777076 & 12.6764398453946 \tabularnewline
0.82 & 978.436345619817 & 13.8584094115897 \tabularnewline
0.83 & 982.923525145565 & 15.3946919091276 \tabularnewline
0.84 & 988.053496438939 & 17.2054137144672 \tabularnewline
0.85 & 993.964435764003 & 19.257345261108 \tabularnewline
0.86 & 1000.8305366413 & 21.632278822156 \tabularnewline
0.87 & 1008.89800506126 & 24.5504828375092 \tabularnewline
0.88 & 1018.5115665061 & 28.2901332517035 \tabularnewline
0.89 & 1030.11265548134 & 32.9933924146669 \tabularnewline
0.9 & 1044.20782945538 & 38.5276312776145 \tabularnewline
0.91 & 1061.32347683012 & 44.5710875228132 \tabularnewline
0.92 & 1081.93409445409 & 50.8052373015244 \tabularnewline
0.93 & 1106.26018536992 & 56.6764373804872 \tabularnewline
0.94 & 1133.79993517417 & 60.4674661131348 \tabularnewline
0.95 & 1162.72988062117 & 58.9167730611898 \tabularnewline
0.96 & 1189.91870137398 & 49.3207014875698 \tabularnewline
0.97 & 1212.66006499458 & 33.5684303340044 \tabularnewline
0.98 & 1232.00928602954 & 20.9014489948179 \tabularnewline
0.99 & 1252.59294809203 & 25.9221541576499 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211274&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]730.201844533319[/C][C]15.6735348968479[/C][/ROW]
[ROW][C]0.02[/C][C]742.597018164317[/C][C]11.5471077214367[/C][/ROW]
[ROW][C]0.03[/C][C]751.441190027433[/C][C]8.3468178737607[/C][/ROW]
[ROW][C]0.04[/C][C]757.046610447855[/C][C]6.37341688222687[/C][/ROW]
[ROW][C]0.05[/C][C]761.024287488915[/C][C]6.56717443480649[/C][/ROW]
[ROW][C]0.06[/C][C]764.632975918011[/C][C]8.22522883909749[/C][/ROW]
[ROW][C]0.07[/C][C]768.506777386061[/C][C]9.94155314161171[/C][/ROW]
[ROW][C]0.08[/C][C]772.745309795823[/C][C]11.0290160647413[/C][/ROW]
[ROW][C]0.09[/C][C]777.183812216386[/C][C]11.517847215239[/C][/ROW]
[ROW][C]0.1[/C][C]781.639254425599[/C][C]11.7470163378831[/C][/ROW]
[ROW][C]0.11[/C][C]786.010362466987[/C][C]11.9360250151848[/C][/ROW]
[ROW][C]0.12[/C][C]790.256621471904[/C][C]12.0497163314208[/C][/ROW]
[ROW][C]0.13[/C][C]794.344063210287[/C][C]11.9370000932939[/C][/ROW]
[ROW][C]0.14[/C][C]798.218999981807[/C][C]11.5056684149206[/C][/ROW]
[ROW][C]0.15[/C][C]801.818330279027[/C][C]10.7868292407[/C][/ROW]
[ROW][C]0.16[/C][C]805.094735878563[/C][C]9.90624143117923[/C][/ROW]
[ROW][C]0.17[/C][C]808.034730680822[/C][C]9.01639216123736[/C][/ROW]
[ROW][C]0.18[/C][C]810.661435206044[/C][C]8.244037955826[/C][/ROW]
[ROW][C]0.19[/C][C]813.026091221453[/C][C]7.66521885185989[/C][/ROW]
[ROW][C]0.2[/C][C]815.196281762678[/C][C]7.31711486019615[/C][/ROW]
[ROW][C]0.21[/C][C]817.246270313724[/C][C]7.22326691737297[/C][/ROW]
[ROW][C]0.22[/C][C]819.250424436445[/C][C]7.39249307152953[/C][/ROW]
[ROW][C]0.23[/C][C]821.277924358828[/C][C]7.81369782068718[/C][/ROW]
[ROW][C]0.24[/C][C]823.386939221344[/C][C]8.43453241595076[/C][/ROW]
[ROW][C]0.25[/C][C]825.618170732592[/C][C]9.16554410913701[/C][/ROW]
[ROW][C]0.26[/C][C]827.989383536363[/C][C]9.89734808087804[/C][/ROW]
[ROW][C]0.27[/C][C]830.493060511664[/C][C]10.5198597319334[/C][/ROW]
[ROW][C]0.28[/C][C]833.098484004803[/C][C]10.9467218063928[/C][/ROW]
[ROW][C]0.29[/C][C]835.758002166531[/C][C]11.1285725898822[/C][/ROW]
[ROW][C]0.3[/C][C]838.41585689922[/C][C]11.0560045937065[/C][/ROW]
[ROW][C]0.31[/C][C]841.017307274656[/C][C]10.755511542169[/C][/ROW]
[ROW][C]0.32[/C][C]843.516000523022[/C][C]10.2792240039632[/C][/ROW]
[ROW][C]0.33[/C][C]845.878377604029[/C][C]9.68925486973243[/C][/ROW]
[ROW][C]0.34[/C][C]848.084946304116[/C][C]9.04635992213425[/C][/ROW]
[ROW][C]0.35[/C][C]850.12912645519[/C][C]8.39971428905078[/C][/ROW]
[ROW][C]0.36[/C][C]852.014818117628[/C][C]7.78522905072813[/C][/ROW]
[ROW][C]0.37[/C][C]853.75379870789[/C][C]7.22801168636147[/C][/ROW]
[ROW][C]0.38[/C][C]855.363636235393[/C][C]6.74683290353989[/C][/ROW]
[ROW][C]0.39[/C][C]856.866255666907[/C][C]6.36050309345451[/C][/ROW]
[ROW][C]0.4[/C][C]858.286877966668[/C][C]6.08631059341652[/C][/ROW]
[ROW][C]0.41[/C][C]859.652936521958[/C][C]5.93826074039912[/C][/ROW]
[ROW][C]0.42[/C][C]860.992766211745[/C][C]5.92150499134456[/C][/ROW]
[ROW][C]0.43[/C][C]862.334201033442[/C][C]6.02749961881934[/C][/ROW]
[ROW][C]0.44[/C][C]863.703482539577[/C][C]6.24364578952839[/C][/ROW]
[ROW][C]0.45[/C][C]865.124900798164[/C][C]6.55482964911543[/C][/ROW]
[ROW][C]0.46[/C][C]866.621329557719[/C][C]6.95595499774671[/C][/ROW]
[ROW][C]0.47[/C][C]868.215395840424[/C][C]7.45182180082546[/C][/ROW]
[ROW][C]0.48[/C][C]869.930644080859[/C][C]8.0555089028517[/C][/ROW]
[ROW][C]0.49[/C][C]871.791902093846[/C][C]8.77977186239218[/C][/ROW]
[ROW][C]0.5[/C][C]873.824216827183[/C][C]9.62585643299141[/C][/ROW]
[ROW][C]0.51[/C][C]876.050160513049[/C][C]10.5738228863215[/C][/ROW]
[ROW][C]0.52[/C][C]878.48587176544[/C][C]11.5815647666927[/C][/ROW]
[ROW][C]0.53[/C][C]881.136711206048[/C][C]12.5843263996382[/C][/ROW]
[ROW][C]0.54[/C][C]883.993716962939[/C][C]13.5050201003553[/C][/ROW]
[ROW][C]0.55[/C][C]887.03204127024[/C][C]14.2612875885067[/C][/ROW]
[ROW][C]0.56[/C][C]890.212213649764[/C][C]14.7880694724274[/C][/ROW]
[ROW][C]0.57[/C][C]893.484470197535[/C][C]15.046730404936[/C][/ROW]
[ROW][C]0.58[/C][C]896.795648357771[/C][C]15.0369987679381[/C][/ROW]
[ROW][C]0.59[/C][C]900.097456658679[/C][C]14.8003689947749[/C][/ROW]
[ROW][C]0.6[/C][C]903.354475719081[/C][C]14.4148302366071[/C][/ROW]
[ROW][C]0.61[/C][C]906.550163162001[/C][C]13.9864753121896[/C][/ROW]
[ROW][C]0.62[/C][C]909.689457389142[/C][C]13.6248721942503[/C][/ROW]
[ROW][C]0.63[/C][C]912.797235641638[/C][C]13.4249835185856[/C][/ROW]
[ROW][C]0.64[/C][C]915.912736528435[/C][C]13.4445105895408[/C][/ROW]
[ROW][C]0.65[/C][C]919.080930407204[/C][C]13.6889957162102[/C][/ROW]
[ROW][C]0.66[/C][C]922.342537823767[/C][C]14.1101271231795[/C][/ROW]
[ROW][C]0.67[/C][C]925.7247959996[/C][C]14.6179427069167[/C][/ROW]
[ROW][C]0.68[/C][C]929.23502200491[/C][C]15.1014306288542[/C][/ROW]
[ROW][C]0.69[/C][C]932.858450990993[/C][C]15.454942228744[/C][/ROW]
[ROW][C]0.7[/C][C]936.560806249867[/C][C]15.5985553813153[/C][/ROW]
[ROW][C]0.71[/C][C]940.294841221419[/C][C]15.4946408298976[/C][/ROW]
[ROW][C]0.72[/C][C]944.009094445587[/C][C]15.1513816744515[/C][/ROW]
[ROW][C]0.73[/C][C]947.656730298569[/C][C]14.6140102441462[/C][/ROW]
[ROW][C]0.74[/C][C]951.202786760853[/C][C]13.9520036897233[/C][/ROW]
[ROW][C]0.75[/C][C]954.629206330137[/C][C]13.2436491534987[/C][/ROW]
[ROW][C]0.76[/C][C]957.938117482185[/C][C]12.5679083326292[/C][/ROW]
[ROW][C]0.77[/C][C]961.154312887638[/C][C]12.0067054546669[/C][/ROW]
[ROW][C]0.78[/C][C]964.327410915052[/C][C]11.6484567533032[/C][/ROW]
[ROW][C]0.79[/C][C]967.533063998826[/C][C]11.5895386315997[/C][/ROW]
[ROW][C]0.8[/C][C]970.871611083968[/C][C]11.9161704879624[/C][/ROW]
[ROW][C]0.81[/C][C]974.462717777076[/C][C]12.6764398453946[/C][/ROW]
[ROW][C]0.82[/C][C]978.436345619817[/C][C]13.8584094115897[/C][/ROW]
[ROW][C]0.83[/C][C]982.923525145565[/C][C]15.3946919091276[/C][/ROW]
[ROW][C]0.84[/C][C]988.053496438939[/C][C]17.2054137144672[/C][/ROW]
[ROW][C]0.85[/C][C]993.964435764003[/C][C]19.257345261108[/C][/ROW]
[ROW][C]0.86[/C][C]1000.8305366413[/C][C]21.632278822156[/C][/ROW]
[ROW][C]0.87[/C][C]1008.89800506126[/C][C]24.5504828375092[/C][/ROW]
[ROW][C]0.88[/C][C]1018.5115665061[/C][C]28.2901332517035[/C][/ROW]
[ROW][C]0.89[/C][C]1030.11265548134[/C][C]32.9933924146669[/C][/ROW]
[ROW][C]0.9[/C][C]1044.20782945538[/C][C]38.5276312776145[/C][/ROW]
[ROW][C]0.91[/C][C]1061.32347683012[/C][C]44.5710875228132[/C][/ROW]
[ROW][C]0.92[/C][C]1081.93409445409[/C][C]50.8052373015244[/C][/ROW]
[ROW][C]0.93[/C][C]1106.26018536992[/C][C]56.6764373804872[/C][/ROW]
[ROW][C]0.94[/C][C]1133.79993517417[/C][C]60.4674661131348[/C][/ROW]
[ROW][C]0.95[/C][C]1162.72988062117[/C][C]58.9167730611898[/C][/ROW]
[ROW][C]0.96[/C][C]1189.91870137398[/C][C]49.3207014875698[/C][/ROW]
[ROW][C]0.97[/C][C]1212.66006499458[/C][C]33.5684303340044[/C][/ROW]
[ROW][C]0.98[/C][C]1232.00928602954[/C][C]20.9014489948179[/C][/ROW]
[ROW][C]0.99[/C][C]1252.59294809203[/C][C]25.9221541576499[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211274&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211274&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
0.01730.20184453331915.6735348968479
0.02742.59701816431711.5471077214367
0.03751.4411900274338.3468178737607
0.04757.0466104478556.37341688222687
0.05761.0242874889156.56717443480649
0.06764.6329759180118.22522883909749
0.07768.5067773860619.94155314161171
0.08772.74530979582311.0290160647413
0.09777.18381221638611.517847215239
0.1781.63925442559911.7470163378831
0.11786.01036246698711.9360250151848
0.12790.25662147190412.0497163314208
0.13794.34406321028711.9370000932939
0.14798.21899998180711.5056684149206
0.15801.81833027902710.7868292407
0.16805.0947358785639.90624143117923
0.17808.0347306808229.01639216123736
0.18810.6614352060448.244037955826
0.19813.0260912214537.66521885185989
0.2815.1962817626787.31711486019615
0.21817.2462703137247.22326691737297
0.22819.2504244364457.39249307152953
0.23821.2779243588287.81369782068718
0.24823.3869392213448.43453241595076
0.25825.6181707325929.16554410913701
0.26827.9893835363639.89734808087804
0.27830.49306051166410.5198597319334
0.28833.09848400480310.9467218063928
0.29835.75800216653111.1285725898822
0.3838.4158568992211.0560045937065
0.31841.01730727465610.755511542169
0.32843.51600052302210.2792240039632
0.33845.8783776040299.68925486973243
0.34848.0849463041169.04635992213425
0.35850.129126455198.39971428905078
0.36852.0148181176287.78522905072813
0.37853.753798707897.22801168636147
0.38855.3636362353936.74683290353989
0.39856.8662556669076.36050309345451
0.4858.2868779666686.08631059341652
0.41859.6529365219585.93826074039912
0.42860.9927662117455.92150499134456
0.43862.3342010334426.02749961881934
0.44863.7034825395776.24364578952839
0.45865.1249007981646.55482964911543
0.46866.6213295577196.95595499774671
0.47868.2153958404247.45182180082546
0.48869.9306440808598.0555089028517
0.49871.7919020938468.77977186239218
0.5873.8242168271839.62585643299141
0.51876.05016051304910.5738228863215
0.52878.4858717654411.5815647666927
0.53881.13671120604812.5843263996382
0.54883.99371696293913.5050201003553
0.55887.0320412702414.2612875885067
0.56890.21221364976414.7880694724274
0.57893.48447019753515.046730404936
0.58896.79564835777115.0369987679381
0.59900.09745665867914.8003689947749
0.6903.35447571908114.4148302366071
0.61906.55016316200113.9864753121896
0.62909.68945738914213.6248721942503
0.63912.79723564163813.4249835185856
0.64915.91273652843513.4445105895408
0.65919.08093040720413.6889957162102
0.66922.34253782376714.1101271231795
0.67925.724795999614.6179427069167
0.68929.2350220049115.1014306288542
0.69932.85845099099315.454942228744
0.7936.56080624986715.5985553813153
0.71940.29484122141915.4946408298976
0.72944.00909444558715.1513816744515
0.73947.65673029856914.6140102441462
0.74951.20278676085313.9520036897233
0.75954.62920633013713.2436491534987
0.76957.93811748218512.5679083326292
0.77961.15431288763812.0067054546669
0.78964.32741091505211.6484567533032
0.79967.53306399882611.5895386315997
0.8970.87161108396811.9161704879624
0.81974.46271777707612.6764398453946
0.82978.43634561981713.8584094115897
0.83982.92352514556515.3946919091276
0.84988.05349643893917.2054137144672
0.85993.96443576400319.257345261108
0.861000.830536641321.632278822156
0.871008.8980050612624.5504828375092
0.881018.511566506128.2901332517035
0.891030.1126554813432.9933924146669
0.91044.2078294553838.5276312776145
0.911061.3234768301244.5710875228132
0.921081.9340944540950.8052373015244
0.931106.2601853699256.6764373804872
0.941133.7999351741760.4674661131348
0.951162.7298806211758.9167730611898
0.961189.9187013739849.3207014875698
0.971212.6600649945833.5684303340044
0.981232.0092860295420.9014489948179
0.991252.5929480920325.9221541576499


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 22 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
R code (references can be found in the software module):
par3 <- '0.1'
par2 <- '0.9'
par1 <- '0.1'
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')