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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 computationSun, 19 Oct 2008 09:39:19 -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/19/t1224430857155lchpqbc2mefo.htm/, Retrieved Tue, 10 Feb 2026 22:59:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=16920, Retrieved Tue, 10 Feb 2026 22:59:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact322

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]
F   PD    [Harrell-Davis Quantiles] [Task 1 Q7 ] [2008-10-19 15:39:19] [8a1195ff8db4df756ce44b463a631c76] [Current]
Feedback Forum
2008-10-27 07:33:58 [Siem Van Opstal] [reply] 
De student maakte een juiste berekening en trekt de correcte conclusie

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
110.40
96.40
101.90
106.20
81.00
94.70
101.00
109.40
102.30
90.70
96.20
96.10
106.00
103.10
102.00
104.70
86.00
92.10
106.90
112.60
101.70
92.00
97.40
97.00
105.40
102.70
98.10
104.50
87.40
89.90
109.80
111.70
98.60
96.90
95.10
97.00
112.70
102.90
97.40
111.40
87.40
96.80
114.10
110.30
103.90
101.60
94.60
95.90
104.70
102.80
98.10
113.90
80.90
95.70
113.20
105.90
108.80
102.30
99.00
100.70
115.50

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=16920&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=16920&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16920&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'Gwilym Jenkins' @ 72.249.127.135






Harrell-Davis Quantiles
quantilesvaluestandard error
0.02582.51854424450952.65031685408418
0.03583.69125852637863.01413985255907
0.04584.92361970972472.93596649036505
0.05586.08755429790432.6936963961831
0.06587.12909436170152.49249930409674
0.07588.0496093624642.3960718287685
0.08588.8748710009992.37389542960224
0.09589.63210395751522.37564007114971
0.10590.3398815531962.36782613118765
0.11591.00716494726382.33653818665573
0.12591.63621469032472.27825576099546
0.13592.22588187215932.19390493138701
0.14592.77392665935822.08554606078295
0.15593.27830390759811.95621198871686
0.16593.73778435344351.81076118759724
0.17594.15223822629561.65542121082470
0.18594.52274259069621.49763447905667
0.19594.85155643408571.34465414883054
0.20595.14197154741261.20287140013514
0.21595.39806130523461.07690904084579
0.22595.62437362785260.969457020685035
0.23595.82562507732010.881486736492672
0.24596.00644531404240.812620096099038
0.25596.1712013673350.761839247147076
0.26596.32390856815180.727663454547889
0.27596.46821650168860.708924556839398
0.28596.60744709287930.705014380561172
0.29596.7446579619580.715338796277648
0.30596.88270584077220.73997776350069
0.31597.024290050240.77899327932338
0.32597.17196299131520.83194274466424
0.33597.3281019755310.898336228058859
0.34597.49484366575830.976408672263835
0.35597.67398841082241.06414566618482
0.36597.86688654829421.15842502315543
0.37598.07432211720531.25532153866152
0.38598.29641116912921.35066025954350
0.39598.5325317700831.43938150927995
0.40598.78130064822081.51700073697618
0.41599.0406072020611.57892778289308
0.42599.30770945649591.62151485068268
0.43599.5793891305791.64226842250390
0.44599.85215522812971.63993340158923
0.455100.1224786882811.61493749360811
0.465100.3870358469491.56920358530886
0.475100.6429366818231.50609060858048
0.485100.8879154289531.43005860227547
0.495101.1204658999471.34625214812251
0.505101.3399108211941.26012103237568
0.515101.5464024893041.17690756486508
0.525101.7408596296531.10157661182926
0.535101.9248514255031.03800390021050
0.545102.1004435840110.989328433480531
0.555102.2700229059640.956875063604355
0.565102.4361164936760.941056956755126
0.575102.6012201177530.940875767585206
0.585102.7676480545330.954343746863882
0.595102.9374143999630.978860775754133
0.605103.1121536441861.01092225485789
0.615103.2930860188341.04769828113348
0.625103.4810304667021.08636133241370
0.635103.6764646676811.12453341671024
0.645103.8796271825941.16087001052786
0.655104.0906515409271.19492751152629
0.665104.3097164519491.22730745927895
0.675104.5371910671341.25960133901638
0.685104.7737504654871.29417486750808
0.695105.0204355627171.33366265502076
0.705105.2786347657971.38066153308199
0.715105.5499729389431.43672308187635
0.725105.8361069463281.50208268536314
0.735106.1384452979711.57456578211717
0.745106.4578296830051.65029477507345
0.755106.7942340890111.72309179878512
0.765107.1465472003591.78586919163292
0.775107.5125003574721.83152873758077
0.785107.8887831184321.85396575362142
0.795108.2713521052061.84967936212432
0.805108.6558925287941.81831734359677
0.815109.038347001921.76283387918991
0.825109.4153973196491.68937027964361
0.835109.7847848890601.60562925278192
0.845110.1453910738551.51925872673878
0.855110.4970656115561.43607697988861
0.865110.8402721217741.35865921728910
0.875111.1756861579981.28621657348218
0.885111.5039016974631.21582135566334
0.895111.8253570803311.14437288907870
0.905112.1404966899961.07068357066230
0.915112.4501117663640.996142631629173
0.925112.7558711866860.923668212240974
0.935113.0613225964220.855468592950953
0.945113.3738493379450.792527322581515
0.955113.7072590733590.742093997217997
0.965114.0814533612670.734645104706135
0.975114.5105322687190.827041312988908

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.025 & 82.5185442445095 & 2.65031685408418 \tabularnewline
0.035 & 83.6912585263786 & 3.01413985255907 \tabularnewline
0.045 & 84.9236197097247 & 2.93596649036505 \tabularnewline
0.055 & 86.0875542979043 & 2.6936963961831 \tabularnewline
0.065 & 87.1290943617015 & 2.49249930409674 \tabularnewline
0.075 & 88.049609362464 & 2.3960718287685 \tabularnewline
0.085 & 88.874871000999 & 2.37389542960224 \tabularnewline
0.095 & 89.6321039575152 & 2.37564007114971 \tabularnewline
0.105 & 90.339881553196 & 2.36782613118765 \tabularnewline
0.115 & 91.0071649472638 & 2.33653818665573 \tabularnewline
0.125 & 91.6362146903247 & 2.27825576099546 \tabularnewline
0.135 & 92.2258818721593 & 2.19390493138701 \tabularnewline
0.145 & 92.7739266593582 & 2.08554606078295 \tabularnewline
0.155 & 93.2783039075981 & 1.95621198871686 \tabularnewline
0.165 & 93.7377843534435 & 1.81076118759724 \tabularnewline
0.175 & 94.1522382262956 & 1.65542121082470 \tabularnewline
0.185 & 94.5227425906962 & 1.49763447905667 \tabularnewline
0.195 & 94.8515564340857 & 1.34465414883054 \tabularnewline
0.205 & 95.1419715474126 & 1.20287140013514 \tabularnewline
0.215 & 95.3980613052346 & 1.07690904084579 \tabularnewline
0.225 & 95.6243736278526 & 0.969457020685035 \tabularnewline
0.235 & 95.8256250773201 & 0.881486736492672 \tabularnewline
0.245 & 96.0064453140424 & 0.812620096099038 \tabularnewline
0.255 & 96.171201367335 & 0.761839247147076 \tabularnewline
0.265 & 96.3239085681518 & 0.727663454547889 \tabularnewline
0.275 & 96.4682165016886 & 0.708924556839398 \tabularnewline
0.285 & 96.6074470928793 & 0.705014380561172 \tabularnewline
0.295 & 96.744657961958 & 0.715338796277648 \tabularnewline
0.305 & 96.8827058407722 & 0.73997776350069 \tabularnewline
0.315 & 97.02429005024 & 0.77899327932338 \tabularnewline
0.325 & 97.1719629913152 & 0.83194274466424 \tabularnewline
0.335 & 97.328101975531 & 0.898336228058859 \tabularnewline
0.345 & 97.4948436657583 & 0.976408672263835 \tabularnewline
0.355 & 97.6739884108224 & 1.06414566618482 \tabularnewline
0.365 & 97.8668865482942 & 1.15842502315543 \tabularnewline
0.375 & 98.0743221172053 & 1.25532153866152 \tabularnewline
0.385 & 98.2964111691292 & 1.35066025954350 \tabularnewline
0.395 & 98.532531770083 & 1.43938150927995 \tabularnewline
0.405 & 98.7813006482208 & 1.51700073697618 \tabularnewline
0.415 & 99.040607202061 & 1.57892778289308 \tabularnewline
0.425 & 99.3077094564959 & 1.62151485068268 \tabularnewline
0.435 & 99.579389130579 & 1.64226842250390 \tabularnewline
0.445 & 99.8521552281297 & 1.63993340158923 \tabularnewline
0.455 & 100.122478688281 & 1.61493749360811 \tabularnewline
0.465 & 100.387035846949 & 1.56920358530886 \tabularnewline
0.475 & 100.642936681823 & 1.50609060858048 \tabularnewline
0.485 & 100.887915428953 & 1.43005860227547 \tabularnewline
0.495 & 101.120465899947 & 1.34625214812251 \tabularnewline
0.505 & 101.339910821194 & 1.26012103237568 \tabularnewline
0.515 & 101.546402489304 & 1.17690756486508 \tabularnewline
0.525 & 101.740859629653 & 1.10157661182926 \tabularnewline
0.535 & 101.924851425503 & 1.03800390021050 \tabularnewline
0.545 & 102.100443584011 & 0.989328433480531 \tabularnewline
0.555 & 102.270022905964 & 0.956875063604355 \tabularnewline
0.565 & 102.436116493676 & 0.941056956755126 \tabularnewline
0.575 & 102.601220117753 & 0.940875767585206 \tabularnewline
0.585 & 102.767648054533 & 0.954343746863882 \tabularnewline
0.595 & 102.937414399963 & 0.978860775754133 \tabularnewline
0.605 & 103.112153644186 & 1.01092225485789 \tabularnewline
0.615 & 103.293086018834 & 1.04769828113348 \tabularnewline
0.625 & 103.481030466702 & 1.08636133241370 \tabularnewline
0.635 & 103.676464667681 & 1.12453341671024 \tabularnewline
0.645 & 103.879627182594 & 1.16087001052786 \tabularnewline
0.655 & 104.090651540927 & 1.19492751152629 \tabularnewline
0.665 & 104.309716451949 & 1.22730745927895 \tabularnewline
0.675 & 104.537191067134 & 1.25960133901638 \tabularnewline
0.685 & 104.773750465487 & 1.29417486750808 \tabularnewline
0.695 & 105.020435562717 & 1.33366265502076 \tabularnewline
0.705 & 105.278634765797 & 1.38066153308199 \tabularnewline
0.715 & 105.549972938943 & 1.43672308187635 \tabularnewline
0.725 & 105.836106946328 & 1.50208268536314 \tabularnewline
0.735 & 106.138445297971 & 1.57456578211717 \tabularnewline
0.745 & 106.457829683005 & 1.65029477507345 \tabularnewline
0.755 & 106.794234089011 & 1.72309179878512 \tabularnewline
0.765 & 107.146547200359 & 1.78586919163292 \tabularnewline
0.775 & 107.512500357472 & 1.83152873758077 \tabularnewline
0.785 & 107.888783118432 & 1.85396575362142 \tabularnewline
0.795 & 108.271352105206 & 1.84967936212432 \tabularnewline
0.805 & 108.655892528794 & 1.81831734359677 \tabularnewline
0.815 & 109.03834700192 & 1.76283387918991 \tabularnewline
0.825 & 109.415397319649 & 1.68937027964361 \tabularnewline
0.835 & 109.784784889060 & 1.60562925278192 \tabularnewline
0.845 & 110.145391073855 & 1.51925872673878 \tabularnewline
0.855 & 110.497065611556 & 1.43607697988861 \tabularnewline
0.865 & 110.840272121774 & 1.35865921728910 \tabularnewline
0.875 & 111.175686157998 & 1.28621657348218 \tabularnewline
0.885 & 111.503901697463 & 1.21582135566334 \tabularnewline
0.895 & 111.825357080331 & 1.14437288907870 \tabularnewline
0.905 & 112.140496689996 & 1.07068357066230 \tabularnewline
0.915 & 112.450111766364 & 0.996142631629173 \tabularnewline
0.925 & 112.755871186686 & 0.923668212240974 \tabularnewline
0.935 & 113.061322596422 & 0.855468592950953 \tabularnewline
0.945 & 113.373849337945 & 0.792527322581515 \tabularnewline
0.955 & 113.707259073359 & 0.742093997217997 \tabularnewline
0.965 & 114.081453361267 & 0.734645104706135 \tabularnewline
0.975 & 114.510532268719 & 0.827041312988908 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=16920&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]82.5185442445095[/C][C]2.65031685408418[/C][/ROW]
[ROW][C]0.035[/C][C]83.6912585263786[/C][C]3.01413985255907[/C][/ROW]
[ROW][C]0.045[/C][C]84.9236197097247[/C][C]2.93596649036505[/C][/ROW]
[ROW][C]0.055[/C][C]86.0875542979043[/C][C]2.6936963961831[/C][/ROW]
[ROW][C]0.065[/C][C]87.1290943617015[/C][C]2.49249930409674[/C][/ROW]
[ROW][C]0.075[/C][C]88.049609362464[/C][C]2.3960718287685[/C][/ROW]
[ROW][C]0.085[/C][C]88.874871000999[/C][C]2.37389542960224[/C][/ROW]
[ROW][C]0.095[/C][C]89.6321039575152[/C][C]2.37564007114971[/C][/ROW]
[ROW][C]0.105[/C][C]90.339881553196[/C][C]2.36782613118765[/C][/ROW]
[ROW][C]0.115[/C][C]91.0071649472638[/C][C]2.33653818665573[/C][/ROW]
[ROW][C]0.125[/C][C]91.6362146903247[/C][C]2.27825576099546[/C][/ROW]
[ROW][C]0.135[/C][C]92.2258818721593[/C][C]2.19390493138701[/C][/ROW]
[ROW][C]0.145[/C][C]92.7739266593582[/C][C]2.08554606078295[/C][/ROW]
[ROW][C]0.155[/C][C]93.2783039075981[/C][C]1.95621198871686[/C][/ROW]
[ROW][C]0.165[/C][C]93.7377843534435[/C][C]1.81076118759724[/C][/ROW]
[ROW][C]0.175[/C][C]94.1522382262956[/C][C]1.65542121082470[/C][/ROW]
[ROW][C]0.185[/C][C]94.5227425906962[/C][C]1.49763447905667[/C][/ROW]
[ROW][C]0.195[/C][C]94.8515564340857[/C][C]1.34465414883054[/C][/ROW]
[ROW][C]0.205[/C][C]95.1419715474126[/C][C]1.20287140013514[/C][/ROW]
[ROW][C]0.215[/C][C]95.3980613052346[/C][C]1.07690904084579[/C][/ROW]
[ROW][C]0.225[/C][C]95.6243736278526[/C][C]0.969457020685035[/C][/ROW]
[ROW][C]0.235[/C][C]95.8256250773201[/C][C]0.881486736492672[/C][/ROW]
[ROW][C]0.245[/C][C]96.0064453140424[/C][C]0.812620096099038[/C][/ROW]
[ROW][C]0.255[/C][C]96.171201367335[/C][C]0.761839247147076[/C][/ROW]
[ROW][C]0.265[/C][C]96.3239085681518[/C][C]0.727663454547889[/C][/ROW]
[ROW][C]0.275[/C][C]96.4682165016886[/C][C]0.708924556839398[/C][/ROW]
[ROW][C]0.285[/C][C]96.6074470928793[/C][C]0.705014380561172[/C][/ROW]
[ROW][C]0.295[/C][C]96.744657961958[/C][C]0.715338796277648[/C][/ROW]
[ROW][C]0.305[/C][C]96.8827058407722[/C][C]0.73997776350069[/C][/ROW]
[ROW][C]0.315[/C][C]97.02429005024[/C][C]0.77899327932338[/C][/ROW]
[ROW][C]0.325[/C][C]97.1719629913152[/C][C]0.83194274466424[/C][/ROW]
[ROW][C]0.335[/C][C]97.328101975531[/C][C]0.898336228058859[/C][/ROW]
[ROW][C]0.345[/C][C]97.4948436657583[/C][C]0.976408672263835[/C][/ROW]
[ROW][C]0.355[/C][C]97.6739884108224[/C][C]1.06414566618482[/C][/ROW]
[ROW][C]0.365[/C][C]97.8668865482942[/C][C]1.15842502315543[/C][/ROW]
[ROW][C]0.375[/C][C]98.0743221172053[/C][C]1.25532153866152[/C][/ROW]
[ROW][C]0.385[/C][C]98.2964111691292[/C][C]1.35066025954350[/C][/ROW]
[ROW][C]0.395[/C][C]98.532531770083[/C][C]1.43938150927995[/C][/ROW]
[ROW][C]0.405[/C][C]98.7813006482208[/C][C]1.51700073697618[/C][/ROW]
[ROW][C]0.415[/C][C]99.040607202061[/C][C]1.57892778289308[/C][/ROW]
[ROW][C]0.425[/C][C]99.3077094564959[/C][C]1.62151485068268[/C][/ROW]
[ROW][C]0.435[/C][C]99.579389130579[/C][C]1.64226842250390[/C][/ROW]
[ROW][C]0.445[/C][C]99.8521552281297[/C][C]1.63993340158923[/C][/ROW]
[ROW][C]0.455[/C][C]100.122478688281[/C][C]1.61493749360811[/C][/ROW]
[ROW][C]0.465[/C][C]100.387035846949[/C][C]1.56920358530886[/C][/ROW]
[ROW][C]0.475[/C][C]100.642936681823[/C][C]1.50609060858048[/C][/ROW]
[ROW][C]0.485[/C][C]100.887915428953[/C][C]1.43005860227547[/C][/ROW]
[ROW][C]0.495[/C][C]101.120465899947[/C][C]1.34625214812251[/C][/ROW]
[ROW][C]0.505[/C][C]101.339910821194[/C][C]1.26012103237568[/C][/ROW]
[ROW][C]0.515[/C][C]101.546402489304[/C][C]1.17690756486508[/C][/ROW]
[ROW][C]0.525[/C][C]101.740859629653[/C][C]1.10157661182926[/C][/ROW]
[ROW][C]0.535[/C][C]101.924851425503[/C][C]1.03800390021050[/C][/ROW]
[ROW][C]0.545[/C][C]102.100443584011[/C][C]0.989328433480531[/C][/ROW]
[ROW][C]0.555[/C][C]102.270022905964[/C][C]0.956875063604355[/C][/ROW]
[ROW][C]0.565[/C][C]102.436116493676[/C][C]0.941056956755126[/C][/ROW]
[ROW][C]0.575[/C][C]102.601220117753[/C][C]0.940875767585206[/C][/ROW]
[ROW][C]0.585[/C][C]102.767648054533[/C][C]0.954343746863882[/C][/ROW]
[ROW][C]0.595[/C][C]102.937414399963[/C][C]0.978860775754133[/C][/ROW]
[ROW][C]0.605[/C][C]103.112153644186[/C][C]1.01092225485789[/C][/ROW]
[ROW][C]0.615[/C][C]103.293086018834[/C][C]1.04769828113348[/C][/ROW]
[ROW][C]0.625[/C][C]103.481030466702[/C][C]1.08636133241370[/C][/ROW]
[ROW][C]0.635[/C][C]103.676464667681[/C][C]1.12453341671024[/C][/ROW]
[ROW][C]0.645[/C][C]103.879627182594[/C][C]1.16087001052786[/C][/ROW]
[ROW][C]0.655[/C][C]104.090651540927[/C][C]1.19492751152629[/C][/ROW]
[ROW][C]0.665[/C][C]104.309716451949[/C][C]1.22730745927895[/C][/ROW]
[ROW][C]0.675[/C][C]104.537191067134[/C][C]1.25960133901638[/C][/ROW]
[ROW][C]0.685[/C][C]104.773750465487[/C][C]1.29417486750808[/C][/ROW]
[ROW][C]0.695[/C][C]105.020435562717[/C][C]1.33366265502076[/C][/ROW]
[ROW][C]0.705[/C][C]105.278634765797[/C][C]1.38066153308199[/C][/ROW]
[ROW][C]0.715[/C][C]105.549972938943[/C][C]1.43672308187635[/C][/ROW]
[ROW][C]0.725[/C][C]105.836106946328[/C][C]1.50208268536314[/C][/ROW]
[ROW][C]0.735[/C][C]106.138445297971[/C][C]1.57456578211717[/C][/ROW]
[ROW][C]0.745[/C][C]106.457829683005[/C][C]1.65029477507345[/C][/ROW]
[ROW][C]0.755[/C][C]106.794234089011[/C][C]1.72309179878512[/C][/ROW]
[ROW][C]0.765[/C][C]107.146547200359[/C][C]1.78586919163292[/C][/ROW]
[ROW][C]0.775[/C][C]107.512500357472[/C][C]1.83152873758077[/C][/ROW]
[ROW][C]0.785[/C][C]107.888783118432[/C][C]1.85396575362142[/C][/ROW]
[ROW][C]0.795[/C][C]108.271352105206[/C][C]1.84967936212432[/C][/ROW]
[ROW][C]0.805[/C][C]108.655892528794[/C][C]1.81831734359677[/C][/ROW]
[ROW][C]0.815[/C][C]109.03834700192[/C][C]1.76283387918991[/C][/ROW]
[ROW][C]0.825[/C][C]109.415397319649[/C][C]1.68937027964361[/C][/ROW]
[ROW][C]0.835[/C][C]109.784784889060[/C][C]1.60562925278192[/C][/ROW]
[ROW][C]0.845[/C][C]110.145391073855[/C][C]1.51925872673878[/C][/ROW]
[ROW][C]0.855[/C][C]110.497065611556[/C][C]1.43607697988861[/C][/ROW]
[ROW][C]0.865[/C][C]110.840272121774[/C][C]1.35865921728910[/C][/ROW]
[ROW][C]0.875[/C][C]111.175686157998[/C][C]1.28621657348218[/C][/ROW]
[ROW][C]0.885[/C][C]111.503901697463[/C][C]1.21582135566334[/C][/ROW]
[ROW][C]0.895[/C][C]111.825357080331[/C][C]1.14437288907870[/C][/ROW]
[ROW][C]0.905[/C][C]112.140496689996[/C][C]1.07068357066230[/C][/ROW]
[ROW][C]0.915[/C][C]112.450111766364[/C][C]0.996142631629173[/C][/ROW]
[ROW][C]0.925[/C][C]112.755871186686[/C][C]0.923668212240974[/C][/ROW]
[ROW][C]0.935[/C][C]113.061322596422[/C][C]0.855468592950953[/C][/ROW]
[ROW][C]0.945[/C][C]113.373849337945[/C][C]0.792527322581515[/C][/ROW]
[ROW][C]0.955[/C][C]113.707259073359[/C][C]0.742093997217997[/C][/ROW]
[ROW][C]0.965[/C][C]114.081453361267[/C][C]0.734645104706135[/C][/ROW]
[ROW][C]0.975[/C][C]114.510532268719[/C][C]0.827041312988908[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=16920&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16920&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
0.02582.51854424450952.65031685408418
0.03583.69125852637863.01413985255907
0.04584.92361970972472.93596649036505
0.05586.08755429790432.6936963961831
0.06587.12909436170152.49249930409674
0.07588.0496093624642.3960718287685
0.08588.8748710009992.37389542960224
0.09589.63210395751522.37564007114971
0.10590.3398815531962.36782613118765
0.11591.00716494726382.33653818665573
0.12591.63621469032472.27825576099546
0.13592.22588187215932.19390493138701
0.14592.77392665935822.08554606078295
0.15593.27830390759811.95621198871686
0.16593.73778435344351.81076118759724
0.17594.15223822629561.65542121082470
0.18594.52274259069621.49763447905667
0.19594.85155643408571.34465414883054
0.20595.14197154741261.20287140013514
0.21595.39806130523461.07690904084579
0.22595.62437362785260.969457020685035
0.23595.82562507732010.881486736492672
0.24596.00644531404240.812620096099038
0.25596.1712013673350.761839247147076
0.26596.32390856815180.727663454547889
0.27596.46821650168860.708924556839398
0.28596.60744709287930.705014380561172
0.29596.7446579619580.715338796277648
0.30596.88270584077220.73997776350069
0.31597.024290050240.77899327932338
0.32597.17196299131520.83194274466424
0.33597.3281019755310.898336228058859
0.34597.49484366575830.976408672263835
0.35597.67398841082241.06414566618482
0.36597.86688654829421.15842502315543
0.37598.07432211720531.25532153866152
0.38598.29641116912921.35066025954350
0.39598.5325317700831.43938150927995
0.40598.78130064822081.51700073697618
0.41599.0406072020611.57892778289308
0.42599.30770945649591.62151485068268
0.43599.5793891305791.64226842250390
0.44599.85215522812971.63993340158923
0.455100.1224786882811.61493749360811
0.465100.3870358469491.56920358530886
0.475100.6429366818231.50609060858048
0.485100.8879154289531.43005860227547
0.495101.1204658999471.34625214812251
0.505101.3399108211941.26012103237568
0.515101.5464024893041.17690756486508
0.525101.7408596296531.10157661182926
0.535101.9248514255031.03800390021050
0.545102.1004435840110.989328433480531
0.555102.2700229059640.956875063604355
0.565102.4361164936760.941056956755126
0.575102.6012201177530.940875767585206
0.585102.7676480545330.954343746863882
0.595102.9374143999630.978860775754133
0.605103.1121536441861.01092225485789
0.615103.2930860188341.04769828113348
0.625103.4810304667021.08636133241370
0.635103.6764646676811.12453341671024
0.645103.8796271825941.16087001052786
0.655104.0906515409271.19492751152629
0.665104.3097164519491.22730745927895
0.675104.5371910671341.25960133901638
0.685104.7737504654871.29417486750808
0.695105.0204355627171.33366265502076
0.705105.2786347657971.38066153308199
0.715105.5499729389431.43672308187635
0.725105.8361069463281.50208268536314
0.735106.1384452979711.57456578211717
0.745106.4578296830051.65029477507345
0.755106.7942340890111.72309179878512
0.765107.1465472003591.78586919163292
0.775107.5125003574721.83152873758077
0.785107.8887831184321.85396575362142
0.795108.2713521052061.84967936212432
0.805108.6558925287941.81831734359677
0.815109.038347001921.76283387918991
0.825109.4153973196491.68937027964361
0.835109.7847848890601.60562925278192
0.845110.1453910738551.51925872673878
0.855110.4970656115561.43607697988861
0.865110.8402721217741.35865921728910
0.875111.1756861579981.28621657348218
0.885111.5039016974631.21582135566334
0.895111.8253570803311.14437288907870
0.905112.1404966899961.07068357066230
0.915112.4501117663640.996142631629173
0.925112.7558711866860.923668212240974
0.935113.0613225964220.855468592950953
0.945113.3738493379450.792527322581515
0.955113.7072590733590.742093997217997
0.965114.0814533612670.734645104706135
0.975114.5105322687190.827041312988908


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')