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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_harrell_davies.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationMon, 20 Oct 2008 13:10:42 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/20/t122452995345bcwj8k63x5ueg.htm/, Retrieved Sun, 19 May 2024 13:04:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17927, Retrieved Sun, 19 May 2024 13:04:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsQuantiles
Estimated Impact136

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Harrell-Davis Quantiles] [Q7 95% confidence...] [2007-10-20 15:02:46] [b731da8b544846036771bbf9bf2f34ce]
-   PD  [Harrell-Davis Quantiles] [Q7 Quantiles Tota...] [2008-10-19 19:50:40] [cf9c64468d04c2c4dd548cc66b4e3677]
F   PD      [Harrell-Davis Quantiles] [Task 2 nieuwe tij...] [2008-10-20 19:10:42] [e4cb5a8878d0401c2e8d19a1768b515b] [Current]
Feedback Forum
2008-10-24 09:44:07 [Kim Wester] [reply] 
Bij een betrouwbaarheid van 95% bevinden de waarden zich inderdaad tussen de 87,458 en 121,408. Voor de specifieke data geldt:

2007/03 118,8 valt binnen 87,458 en 121,408.
2007/06 117,2 valt binnen 87,458 en 121,408.
2007/10 122,4 valt NIET binnen 87,458 en 121,408.
2008/04 117,3 valt binnen 87,458 en 121,408.

De kans dat deze 122,4 toch voorkomt is miniem.

Overigens zijn 2007/03, 2007/06 en 2008/04 geen outliers want ze vallen binnen de 87,458 en 121,408.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100,7
109,9
114,6
85,4
100,5
114,8
116,5
112,9
102
106
105,3
118,8
106,1
109,3
117,2
92,5
104,2
112,5
122,4
113,3
100
110,7
112,8
109,8
117,3
109,1
115,9
95,7

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' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17927&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17927&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17927&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' @ 72.249.127.135






Harrell-Davis Quantiles
quantilesvaluestandard error
0.02587.45807732472065.98492752778309
0.03588.61866993728625.56222770007391
0.04589.8517146435515.16323760635567
0.05591.09034097296734.81127234111037
0.06592.28627244900714.50980452183225
0.07593.40943475689714.24832199324267
0.08594.44465561620444.01101274295052
0.09595.38744889598313.78432328060463
0.10596.2401343280333.56025543581017
0.11597.00885771372423.33748270574066
0.12597.70159585746613.11983226437528
0.13598.32697344450552.91434327331831
0.14598.8936354167612.72928284815573
0.15599.40993922409252.57214341026484
0.16599.88379724536592.44822794626808
0.175100.3225710953982.35964634910230
0.185100.7329761900152.30503685218476
0.195101.1209906735762.28010983875248
0.205101.4917796312472.27833653209663
0.215101.8496488456602.29267974537966
0.225102.1980380513502.31634443331657
0.235102.5395564203852.34349696473691
0.245102.876056029362.36973245542995
0.255103.2087339916262.39187501308408
0.265103.5382513538812.40815022281849
0.275103.8648565975292.41764742820949
0.285104.1885031153032.42053053330516
0.295104.5089526806532.41714878567848
0.305104.8258600439772.40836301180470
0.315105.1388368416062.39507451108103
0.325105.4474956064342.37812086266659
0.335105.7514765940862.35788213863721
0.345106.0504612957182.33490776343051
0.355106.3441769215892.30927688225447
0.365106.6323959157892.28083035116282
0.375106.9149338619092.24962593318816
0.385107.1916481470272.21537300603362
0.395107.4624386518802.17832702128380
0.405107.7272506935522.1385874488729
0.415107.9860795938822.09657257842796
0.425108.2389756692342.05293783159589
0.435108.4860481754992.00864993376555
0.445108.7274667915011.96453212428767
0.455108.9634595405361.92167220948208
0.465109.1943065605661.88102714284639
0.475109.4203297476381.84328062313611
0.485109.6418789180861.80890527165509
0.495109.8593156732521.77821126614787
0.505110.0729965326361.75105650017546
0.515110.2832570785971.72687242114143
0.525110.4903988075131.70508173254932
0.535110.6946801174481.68481035669177
0.545110.8963124163691.66521728968408
0.555111.0954617645971.64551295275279
0.565111.2922558407581.62506898745843
0.575111.4867954171351.60331901938951
0.585111.6791690186201.58030412493708
0.595111.8694690775171.55606694677203
0.605112.0578077231431.53105230876545
0.615112.2443303762111.50577538193736
0.625112.4292255450271.48108618328162
0.635112.6127296126981.45780997879842
0.645112.7951259136631.43669633475028
0.655112.9767379649441.41835537845918
0.665113.1579172810421.40326826174848
0.675113.3390267060941.39146932943131
0.685113.5204206002641.38292767458357
0.695113.7024234964421.37715206746349
0.705113.8853089959671.37349077768351
0.715114.0692807174841.37109714127318
0.725114.2544570868071.36896059824780
0.735114.440861703311.36609674709036
0.745114.6284209863631.36144135725383
0.755114.8169708312921.35413236819186
0.765115.0062741081771.34326110814682
0.775115.1960510139811.32821156491732
0.785115.3860245052051.30852026845853
0.795115.5759832283181.28401083264954
0.805115.7658644236461.25494351056347
0.815115.9558590460081.22198198880204
0.825116.1465405736051.18641958931757
0.835116.3390172660351.15027771738731
0.845116.5351043451281.11653801519246
0.855116.7375067462761.08915644977511
0.865116.9499934220231.07332910279288
0.875117.1775292258501.07526256434325
0.885117.4263091689561.10170062536894
0.895117.7036130213351.15923929928478
0.905118.0173701999211.25338676869746
0.915118.3753062616431.38789724819286
0.925118.7835521610581.56455705347431
0.935119.2446632673811.78282687093812
0.945119.7551478011132.03899425366970
0.955120.3028642946922.32480721133482
0.965120.8650007914502.62617368473183
0.975121.4077143979642.92247528221839

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.025 & 87.4580773247206 & 5.98492752778309 \tabularnewline
0.035 & 88.6186699372862 & 5.56222770007391 \tabularnewline
0.045 & 89.851714643551 & 5.16323760635567 \tabularnewline
0.055 & 91.0903409729673 & 4.81127234111037 \tabularnewline
0.065 & 92.2862724490071 & 4.50980452183225 \tabularnewline
0.075 & 93.4094347568971 & 4.24832199324267 \tabularnewline
0.085 & 94.4446556162044 & 4.01101274295052 \tabularnewline
0.095 & 95.3874488959831 & 3.78432328060463 \tabularnewline
0.105 & 96.240134328033 & 3.56025543581017 \tabularnewline
0.115 & 97.0088577137242 & 3.33748270574066 \tabularnewline
0.125 & 97.7015958574661 & 3.11983226437528 \tabularnewline
0.135 & 98.3269734445055 & 2.91434327331831 \tabularnewline
0.145 & 98.893635416761 & 2.72928284815573 \tabularnewline
0.155 & 99.4099392240925 & 2.57214341026484 \tabularnewline
0.165 & 99.8837972453659 & 2.44822794626808 \tabularnewline
0.175 & 100.322571095398 & 2.35964634910230 \tabularnewline
0.185 & 100.732976190015 & 2.30503685218476 \tabularnewline
0.195 & 101.120990673576 & 2.28010983875248 \tabularnewline
0.205 & 101.491779631247 & 2.27833653209663 \tabularnewline
0.215 & 101.849648845660 & 2.29267974537966 \tabularnewline
0.225 & 102.198038051350 & 2.31634443331657 \tabularnewline
0.235 & 102.539556420385 & 2.34349696473691 \tabularnewline
0.245 & 102.87605602936 & 2.36973245542995 \tabularnewline
0.255 & 103.208733991626 & 2.39187501308408 \tabularnewline
0.265 & 103.538251353881 & 2.40815022281849 \tabularnewline
0.275 & 103.864856597529 & 2.41764742820949 \tabularnewline
0.285 & 104.188503115303 & 2.42053053330516 \tabularnewline
0.295 & 104.508952680653 & 2.41714878567848 \tabularnewline
0.305 & 104.825860043977 & 2.40836301180470 \tabularnewline
0.315 & 105.138836841606 & 2.39507451108103 \tabularnewline
0.325 & 105.447495606434 & 2.37812086266659 \tabularnewline
0.335 & 105.751476594086 & 2.35788213863721 \tabularnewline
0.345 & 106.050461295718 & 2.33490776343051 \tabularnewline
0.355 & 106.344176921589 & 2.30927688225447 \tabularnewline
0.365 & 106.632395915789 & 2.28083035116282 \tabularnewline
0.375 & 106.914933861909 & 2.24962593318816 \tabularnewline
0.385 & 107.191648147027 & 2.21537300603362 \tabularnewline
0.395 & 107.462438651880 & 2.17832702128380 \tabularnewline
0.405 & 107.727250693552 & 2.1385874488729 \tabularnewline
0.415 & 107.986079593882 & 2.09657257842796 \tabularnewline
0.425 & 108.238975669234 & 2.05293783159589 \tabularnewline
0.435 & 108.486048175499 & 2.00864993376555 \tabularnewline
0.445 & 108.727466791501 & 1.96453212428767 \tabularnewline
0.455 & 108.963459540536 & 1.92167220948208 \tabularnewline
0.465 & 109.194306560566 & 1.88102714284639 \tabularnewline
0.475 & 109.420329747638 & 1.84328062313611 \tabularnewline
0.485 & 109.641878918086 & 1.80890527165509 \tabularnewline
0.495 & 109.859315673252 & 1.77821126614787 \tabularnewline
0.505 & 110.072996532636 & 1.75105650017546 \tabularnewline
0.515 & 110.283257078597 & 1.72687242114143 \tabularnewline
0.525 & 110.490398807513 & 1.70508173254932 \tabularnewline
0.535 & 110.694680117448 & 1.68481035669177 \tabularnewline
0.545 & 110.896312416369 & 1.66521728968408 \tabularnewline
0.555 & 111.095461764597 & 1.64551295275279 \tabularnewline
0.565 & 111.292255840758 & 1.62506898745843 \tabularnewline
0.575 & 111.486795417135 & 1.60331901938951 \tabularnewline
0.585 & 111.679169018620 & 1.58030412493708 \tabularnewline
0.595 & 111.869469077517 & 1.55606694677203 \tabularnewline
0.605 & 112.057807723143 & 1.53105230876545 \tabularnewline
0.615 & 112.244330376211 & 1.50577538193736 \tabularnewline
0.625 & 112.429225545027 & 1.48108618328162 \tabularnewline
0.635 & 112.612729612698 & 1.45780997879842 \tabularnewline
0.645 & 112.795125913663 & 1.43669633475028 \tabularnewline
0.655 & 112.976737964944 & 1.41835537845918 \tabularnewline
0.665 & 113.157917281042 & 1.40326826174848 \tabularnewline
0.675 & 113.339026706094 & 1.39146932943131 \tabularnewline
0.685 & 113.520420600264 & 1.38292767458357 \tabularnewline
0.695 & 113.702423496442 & 1.37715206746349 \tabularnewline
0.705 & 113.885308995967 & 1.37349077768351 \tabularnewline
0.715 & 114.069280717484 & 1.37109714127318 \tabularnewline
0.725 & 114.254457086807 & 1.36896059824780 \tabularnewline
0.735 & 114.44086170331 & 1.36609674709036 \tabularnewline
0.745 & 114.628420986363 & 1.36144135725383 \tabularnewline
0.755 & 114.816970831292 & 1.35413236819186 \tabularnewline
0.765 & 115.006274108177 & 1.34326110814682 \tabularnewline
0.775 & 115.196051013981 & 1.32821156491732 \tabularnewline
0.785 & 115.386024505205 & 1.30852026845853 \tabularnewline
0.795 & 115.575983228318 & 1.28401083264954 \tabularnewline
0.805 & 115.765864423646 & 1.25494351056347 \tabularnewline
0.815 & 115.955859046008 & 1.22198198880204 \tabularnewline
0.825 & 116.146540573605 & 1.18641958931757 \tabularnewline
0.835 & 116.339017266035 & 1.15027771738731 \tabularnewline
0.845 & 116.535104345128 & 1.11653801519246 \tabularnewline
0.855 & 116.737506746276 & 1.08915644977511 \tabularnewline
0.865 & 116.949993422023 & 1.07332910279288 \tabularnewline
0.875 & 117.177529225850 & 1.07526256434325 \tabularnewline
0.885 & 117.426309168956 & 1.10170062536894 \tabularnewline
0.895 & 117.703613021335 & 1.15923929928478 \tabularnewline
0.905 & 118.017370199921 & 1.25338676869746 \tabularnewline
0.915 & 118.375306261643 & 1.38789724819286 \tabularnewline
0.925 & 118.783552161058 & 1.56455705347431 \tabularnewline
0.935 & 119.244663267381 & 1.78282687093812 \tabularnewline
0.945 & 119.755147801113 & 2.03899425366970 \tabularnewline
0.955 & 120.302864294692 & 2.32480721133482 \tabularnewline
0.965 & 120.865000791450 & 2.62617368473183 \tabularnewline
0.975 & 121.407714397964 & 2.92247528221839 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17927&T=1

[TABLE]
[ROW][C]Harrell-Davis Quantiles[/C][/ROW]
[ROW][C]quantiles[/C][C]value[/C][C]standard error[/C][/ROW]
[ROW][C]0.025[/C][C]87.4580773247206[/C][C]5.98492752778309[/C][/ROW]
[ROW][C]0.035[/C][C]88.6186699372862[/C][C]5.56222770007391[/C][/ROW]
[ROW][C]0.045[/C][C]89.851714643551[/C][C]5.16323760635567[/C][/ROW]
[ROW][C]0.055[/C][C]91.0903409729673[/C][C]4.81127234111037[/C][/ROW]
[ROW][C]0.065[/C][C]92.2862724490071[/C][C]4.50980452183225[/C][/ROW]
[ROW][C]0.075[/C][C]93.4094347568971[/C][C]4.24832199324267[/C][/ROW]
[ROW][C]0.085[/C][C]94.4446556162044[/C][C]4.01101274295052[/C][/ROW]
[ROW][C]0.095[/C][C]95.3874488959831[/C][C]3.78432328060463[/C][/ROW]
[ROW][C]0.105[/C][C]96.240134328033[/C][C]3.56025543581017[/C][/ROW]
[ROW][C]0.115[/C][C]97.0088577137242[/C][C]3.33748270574066[/C][/ROW]
[ROW][C]0.125[/C][C]97.7015958574661[/C][C]3.11983226437528[/C][/ROW]
[ROW][C]0.135[/C][C]98.3269734445055[/C][C]2.91434327331831[/C][/ROW]
[ROW][C]0.145[/C][C]98.893635416761[/C][C]2.72928284815573[/C][/ROW]
[ROW][C]0.155[/C][C]99.4099392240925[/C][C]2.57214341026484[/C][/ROW]
[ROW][C]0.165[/C][C]99.8837972453659[/C][C]2.44822794626808[/C][/ROW]
[ROW][C]0.175[/C][C]100.322571095398[/C][C]2.35964634910230[/C][/ROW]
[ROW][C]0.185[/C][C]100.732976190015[/C][C]2.30503685218476[/C][/ROW]
[ROW][C]0.195[/C][C]101.120990673576[/C][C]2.28010983875248[/C][/ROW]
[ROW][C]0.205[/C][C]101.491779631247[/C][C]2.27833653209663[/C][/ROW]
[ROW][C]0.215[/C][C]101.849648845660[/C][C]2.29267974537966[/C][/ROW]
[ROW][C]0.225[/C][C]102.198038051350[/C][C]2.31634443331657[/C][/ROW]
[ROW][C]0.235[/C][C]102.539556420385[/C][C]2.34349696473691[/C][/ROW]
[ROW][C]0.245[/C][C]102.87605602936[/C][C]2.36973245542995[/C][/ROW]
[ROW][C]0.255[/C][C]103.208733991626[/C][C]2.39187501308408[/C][/ROW]
[ROW][C]0.265[/C][C]103.538251353881[/C][C]2.40815022281849[/C][/ROW]
[ROW][C]0.275[/C][C]103.864856597529[/C][C]2.41764742820949[/C][/ROW]
[ROW][C]0.285[/C][C]104.188503115303[/C][C]2.42053053330516[/C][/ROW]
[ROW][C]0.295[/C][C]104.508952680653[/C][C]2.41714878567848[/C][/ROW]
[ROW][C]0.305[/C][C]104.825860043977[/C][C]2.40836301180470[/C][/ROW]
[ROW][C]0.315[/C][C]105.138836841606[/C][C]2.39507451108103[/C][/ROW]
[ROW][C]0.325[/C][C]105.447495606434[/C][C]2.37812086266659[/C][/ROW]
[ROW][C]0.335[/C][C]105.751476594086[/C][C]2.35788213863721[/C][/ROW]
[ROW][C]0.345[/C][C]106.050461295718[/C][C]2.33490776343051[/C][/ROW]
[ROW][C]0.355[/C][C]106.344176921589[/C][C]2.30927688225447[/C][/ROW]
[ROW][C]0.365[/C][C]106.632395915789[/C][C]2.28083035116282[/C][/ROW]
[ROW][C]0.375[/C][C]106.914933861909[/C][C]2.24962593318816[/C][/ROW]
[ROW][C]0.385[/C][C]107.191648147027[/C][C]2.21537300603362[/C][/ROW]
[ROW][C]0.395[/C][C]107.462438651880[/C][C]2.17832702128380[/C][/ROW]
[ROW][C]0.405[/C][C]107.727250693552[/C][C]2.1385874488729[/C][/ROW]
[ROW][C]0.415[/C][C]107.986079593882[/C][C]2.09657257842796[/C][/ROW]
[ROW][C]0.425[/C][C]108.238975669234[/C][C]2.05293783159589[/C][/ROW]
[ROW][C]0.435[/C][C]108.486048175499[/C][C]2.00864993376555[/C][/ROW]
[ROW][C]0.445[/C][C]108.727466791501[/C][C]1.96453212428767[/C][/ROW]
[ROW][C]0.455[/C][C]108.963459540536[/C][C]1.92167220948208[/C][/ROW]
[ROW][C]0.465[/C][C]109.194306560566[/C][C]1.88102714284639[/C][/ROW]
[ROW][C]0.475[/C][C]109.420329747638[/C][C]1.84328062313611[/C][/ROW]
[ROW][C]0.485[/C][C]109.641878918086[/C][C]1.80890527165509[/C][/ROW]
[ROW][C]0.495[/C][C]109.859315673252[/C][C]1.77821126614787[/C][/ROW]
[ROW][C]0.505[/C][C]110.072996532636[/C][C]1.75105650017546[/C][/ROW]
[ROW][C]0.515[/C][C]110.283257078597[/C][C]1.72687242114143[/C][/ROW]
[ROW][C]0.525[/C][C]110.490398807513[/C][C]1.70508173254932[/C][/ROW]
[ROW][C]0.535[/C][C]110.694680117448[/C][C]1.68481035669177[/C][/ROW]
[ROW][C]0.545[/C][C]110.896312416369[/C][C]1.66521728968408[/C][/ROW]
[ROW][C]0.555[/C][C]111.095461764597[/C][C]1.64551295275279[/C][/ROW]
[ROW][C]0.565[/C][C]111.292255840758[/C][C]1.62506898745843[/C][/ROW]
[ROW][C]0.575[/C][C]111.486795417135[/C][C]1.60331901938951[/C][/ROW]
[ROW][C]0.585[/C][C]111.679169018620[/C][C]1.58030412493708[/C][/ROW]
[ROW][C]0.595[/C][C]111.869469077517[/C][C]1.55606694677203[/C][/ROW]
[ROW][C]0.605[/C][C]112.057807723143[/C][C]1.53105230876545[/C][/ROW]
[ROW][C]0.615[/C][C]112.244330376211[/C][C]1.50577538193736[/C][/ROW]
[ROW][C]0.625[/C][C]112.429225545027[/C][C]1.48108618328162[/C][/ROW]
[ROW][C]0.635[/C][C]112.612729612698[/C][C]1.45780997879842[/C][/ROW]
[ROW][C]0.645[/C][C]112.795125913663[/C][C]1.43669633475028[/C][/ROW]
[ROW][C]0.655[/C][C]112.976737964944[/C][C]1.41835537845918[/C][/ROW]
[ROW][C]0.665[/C][C]113.157917281042[/C][C]1.40326826174848[/C][/ROW]
[ROW][C]0.675[/C][C]113.339026706094[/C][C]1.39146932943131[/C][/ROW]
[ROW][C]0.685[/C][C]113.520420600264[/C][C]1.38292767458357[/C][/ROW]
[ROW][C]0.695[/C][C]113.702423496442[/C][C]1.37715206746349[/C][/ROW]
[ROW][C]0.705[/C][C]113.885308995967[/C][C]1.37349077768351[/C][/ROW]
[ROW][C]0.715[/C][C]114.069280717484[/C][C]1.37109714127318[/C][/ROW]
[ROW][C]0.725[/C][C]114.254457086807[/C][C]1.36896059824780[/C][/ROW]
[ROW][C]0.735[/C][C]114.44086170331[/C][C]1.36609674709036[/C][/ROW]
[ROW][C]0.745[/C][C]114.628420986363[/C][C]1.36144135725383[/C][/ROW]
[ROW][C]0.755[/C][C]114.816970831292[/C][C]1.35413236819186[/C][/ROW]
[ROW][C]0.765[/C][C]115.006274108177[/C][C]1.34326110814682[/C][/ROW]
[ROW][C]0.775[/C][C]115.196051013981[/C][C]1.32821156491732[/C][/ROW]
[ROW][C]0.785[/C][C]115.386024505205[/C][C]1.30852026845853[/C][/ROW]
[ROW][C]0.795[/C][C]115.575983228318[/C][C]1.28401083264954[/C][/ROW]
[ROW][C]0.805[/C][C]115.765864423646[/C][C]1.25494351056347[/C][/ROW]
[ROW][C]0.815[/C][C]115.955859046008[/C][C]1.22198198880204[/C][/ROW]
[ROW][C]0.825[/C][C]116.146540573605[/C][C]1.18641958931757[/C][/ROW]
[ROW][C]0.835[/C][C]116.339017266035[/C][C]1.15027771738731[/C][/ROW]
[ROW][C]0.845[/C][C]116.535104345128[/C][C]1.11653801519246[/C][/ROW]
[ROW][C]0.855[/C][C]116.737506746276[/C][C]1.08915644977511[/C][/ROW]
[ROW][C]0.865[/C][C]116.949993422023[/C][C]1.07332910279288[/C][/ROW]
[ROW][C]0.875[/C][C]117.177529225850[/C][C]1.07526256434325[/C][/ROW]
[ROW][C]0.885[/C][C]117.426309168956[/C][C]1.10170062536894[/C][/ROW]
[ROW][C]0.895[/C][C]117.703613021335[/C][C]1.15923929928478[/C][/ROW]
[ROW][C]0.905[/C][C]118.017370199921[/C][C]1.25338676869746[/C][/ROW]
[ROW][C]0.915[/C][C]118.375306261643[/C][C]1.38789724819286[/C][/ROW]
[ROW][C]0.925[/C][C]118.783552161058[/C][C]1.56455705347431[/C][/ROW]
[ROW][C]0.935[/C][C]119.244663267381[/C][C]1.78282687093812[/C][/ROW]
[ROW][C]0.945[/C][C]119.755147801113[/C][C]2.03899425366970[/C][/ROW]
[ROW][C]0.955[/C][C]120.302864294692[/C][C]2.32480721133482[/C][/ROW]
[ROW][C]0.965[/C][C]120.865000791450[/C][C]2.62617368473183[/C][/ROW]
[ROW][C]0.975[/C][C]121.407714397964[/C][C]2.92247528221839[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17927&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17927&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
0.02587.45807732472065.98492752778309
0.03588.61866993728625.56222770007391
0.04589.8517146435515.16323760635567
0.05591.09034097296734.81127234111037
0.06592.28627244900714.50980452183225
0.07593.40943475689714.24832199324267
0.08594.44465561620444.01101274295052
0.09595.38744889598313.78432328060463
0.10596.2401343280333.56025543581017
0.11597.00885771372423.33748270574066
0.12597.70159585746613.11983226437528
0.13598.32697344450552.91434327331831
0.14598.8936354167612.72928284815573
0.15599.40993922409252.57214341026484
0.16599.88379724536592.44822794626808
0.175100.3225710953982.35964634910230
0.185100.7329761900152.30503685218476
0.195101.1209906735762.28010983875248
0.205101.4917796312472.27833653209663
0.215101.8496488456602.29267974537966
0.225102.1980380513502.31634443331657
0.235102.5395564203852.34349696473691
0.245102.876056029362.36973245542995
0.255103.2087339916262.39187501308408
0.265103.5382513538812.40815022281849
0.275103.8648565975292.41764742820949
0.285104.1885031153032.42053053330516
0.295104.5089526806532.41714878567848
0.305104.8258600439772.40836301180470
0.315105.1388368416062.39507451108103
0.325105.4474956064342.37812086266659
0.335105.7514765940862.35788213863721
0.345106.0504612957182.33490776343051
0.355106.3441769215892.30927688225447
0.365106.6323959157892.28083035116282
0.375106.9149338619092.24962593318816
0.385107.1916481470272.21537300603362
0.395107.4624386518802.17832702128380
0.405107.7272506935522.1385874488729
0.415107.9860795938822.09657257842796
0.425108.2389756692342.05293783159589
0.435108.4860481754992.00864993376555
0.445108.7274667915011.96453212428767
0.455108.9634595405361.92167220948208
0.465109.1943065605661.88102714284639
0.475109.4203297476381.84328062313611
0.485109.6418789180861.80890527165509
0.495109.8593156732521.77821126614787
0.505110.0729965326361.75105650017546
0.515110.2832570785971.72687242114143
0.525110.4903988075131.70508173254932
0.535110.6946801174481.68481035669177
0.545110.8963124163691.66521728968408
0.555111.0954617645971.64551295275279
0.565111.2922558407581.62506898745843
0.575111.4867954171351.60331901938951
0.585111.6791690186201.58030412493708
0.595111.8694690775171.55606694677203
0.605112.0578077231431.53105230876545
0.615112.2443303762111.50577538193736
0.625112.4292255450271.48108618328162
0.635112.6127296126981.45780997879842
0.645112.7951259136631.43669633475028
0.655112.9767379649441.41835537845918
0.665113.1579172810421.40326826174848
0.675113.3390267060941.39146932943131
0.685113.5204206002641.38292767458357
0.695113.7024234964421.37715206746349
0.705113.8853089959671.37349077768351
0.715114.0692807174841.37109714127318
0.725114.2544570868071.36896059824780
0.735114.440861703311.36609674709036
0.745114.6284209863631.36144135725383
0.755114.8169708312921.35413236819186
0.765115.0062741081771.34326110814682
0.775115.1960510139811.32821156491732
0.785115.3860245052051.30852026845853
0.795115.5759832283181.28401083264954
0.805115.7658644236461.25494351056347
0.815115.9558590460081.22198198880204
0.825116.1465405736051.18641958931757
0.835116.3390172660351.15027771738731
0.845116.5351043451281.11653801519246
0.855116.7375067462761.08915644977511
0.865116.9499934220231.07332910279288
0.875117.1775292258501.07526256434325
0.885117.4263091689561.10170062536894
0.895117.7036130213351.15923929928478
0.905118.0173701999211.25338676869746
0.915118.3753062616431.38789724819286
0.925118.7835521610581.56455705347431
0.935119.2446632673811.78282687093812
0.945119.7551478011132.03899425366970
0.955120.3028642946922.32480721133482
0.965120.8650007914502.62617368473183
0.975121.4077143979642.92247528221839


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.025 ; par2 = 0.975 ; par3 = 0.01 ;
Parameters (R input):
par1 = 0.025 ; par2 = 0.975 ; 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')