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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 computationMon, 27 Oct 2008 17:58:43 -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/28/t1225152007ngk2nxpmeeidirr.htm/, Retrieved Sun, 19 May 2024 20:59:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19715, Retrieved Sun, 19 May 2024 20:59:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact196

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] [Q5 Distributions] [2007-10-22 09:17:45] [b731da8b544846036771bbf9bf2f34ce]
F   PD    [Harrell-Davis Quantiles] [Q5] [2008-10-27 23:58:43] [1d70db93c36870279a28f714be132c6e] [Current]
Feedback Forum
2008-11-03 10:14:14 [Chi-Kwong Man] [reply] 
Uitleg is correct. Er zijn 2 methodes om dit te berekenen.
1: in bijvoorbeeld excel het gemiddelde aftrekken van de originele waarden van de tijdreeks en plakken + berekenen.
2: R-code aanpassen door de lijn x <- x-gemiddelde in te voegen (dan moet je achteraf geen berekening meer moeten maken).
2008-11-03 17:58:46 [339a57d8a4d5d113e4804fc423e4a59e] [reply] 
De student heeft de juiste berekening gemaakt om deze vraag op te lossen. Hij heeft het gemiddelde van de waarden getrokken en bekomt zo de grenzen van de random component. Men kan ook de R-code veranderen door volgende lijn in te voegen: 'x = x-gemiddelde(getal)'.
2008-11-03 19:17:02 [Stijn Loomans] [reply] 
De student heeft hier de juiste uitkomst bekomen en goede conclusie getrokken.
De student had ook nog de andere methode kunnen gebruiken maar de deze was natuurlijk ook juist.
De R-code te gaan aanpassen door x <- x-gemiddelde in te voegen. Zodat je de berekening hierna niet meer moet doen.
2008-11-03 21:35:11 [Bonifer Spillemaeckers] [reply] 
De bovenstaande feedbacks zijn correct. Het is inderdaad zo dat er 2 manieren zijn om deze vraag op een goede manier te beantwoorden. We kunnen handmatig het gemiddelde aftrekken van onze interval-grenzen. Maar men kan dit ook doen door in de R-code een extra regel toe te voegen, nl. x <- x-gemiddelde.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.989130435
0.919087137
0.925417076
0.925612053
1.066666667
0.851108765
1.030693069
0.989031079
0.913000978
0.792723264
0.978170478
0.987513007
0.909433962
0.883608147
0.82745098
0.8252149
1.023255814
0.815418024
1.026192703
0.914742451
0.807276303
0.739130435
0.98973306
0.972164948
0.853889943
0.856864654
0.775739042
0.789473684
0.931350114
0.73971079
0.885245902
0.842435094
0.818458418
0.72755418
0.923238696
0.922680412
0.883762201
0.818270165
0.771047228
0.825852783
0.924485126
0.755165289
0.874671341
0.815956482
0.799807507
0.712598425
0.832980973
0.910323253
0.869149952
0.779182879
0.750254842
0.75856014
0.920889988
0.743991641
0.816254417
0.769593957
0.784007353
0.683284457
0.850505051
0.900695134
0.868398268

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=19715&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=19715&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19715&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
0.010.6903574823081820.0257493744938832
0.020.7006851289064970.021734532514729
0.030.7112036616821370.0181409407214812
0.040.720238984384720.0152701505942662
0.050.7274408814134870.0130169628370724
0.060.7330999213570140.0113755336274530
0.070.7376593354487540.0104102672587416
0.080.741512738453780.0100957980377989
0.090.744955141615840.0102701844619835
0.10.7481864285820470.0107193845356072
0.110.7513279103163620.0112601657760742
0.120.7544418052122760.0117752995862039
0.130.757550632499920.0122043778163178
0.140.760654299486320.0125298799458765
0.150.7637433053434060.0127639590477691
0.160.7668075494625120.012937217037477
0.170.7698411096453410.0130890257027324
0.180.772843795481730.0132543391742880
0.190.7758203960370540.0134562040704081
0.20.778778507182080.0137014134900641
0.210.781725742453370.0139761760838112
0.220.784667022737090.014254906668871
0.230.7876024948688150.0145009100196785
0.240.7905264451849560.0146742460172555
0.250.793427366340790.0147425838993809
0.260.7962891303806530.0146806157352704
0.270.7990930449262890.0144813558459163
0.280.8018204433897070.0141518828509622
0.290.8044553968438990.0137166291746623
0.30.8069871382093710.0132144865802642
0.310.8094118534720780.0126954985073174
0.320.8117336061086860.0122127590106538
0.330.8139642994700860.0118197530780406
0.340.8161227239319740.0115605302029674
0.350.8182328586074670.0114653295564385
0.360.8203216841359230.0115477666075857
0.370.822416804494980.0118008984086779
0.380.8245441716815950.0122015373336842
0.390.826726164489670.0127161972913673
0.40.828980202980720.0133047190084541
0.410.8313179966309320.0139270942039374
0.420.8337454388138560.0145468382768111
0.430.8362630834732790.0151326313986313
0.440.8388670792909960.0156627183912659
0.450.8415503975219250.0161249314936152
0.460.8443041744497640.0165157734928721
0.470.847118997713240.0168385143727890
0.480.8499859941259850.0171040905359246
0.490.8528976188598050.0173246160284153
0.50.8558480939932980.0175143229302128
0.510.8588334903013120.0176871470530748
0.520.861851483358480.0178499332357475
0.530.864900840362480.0180101805121891
0.540.8679807081071460.0181670326317408
0.550.871089778798590.0183152217343903
0.560.8742254136022550.0184445154323164
0.570.87738280749570.0185417822082271
0.580.8805542837879860.0185853019135757
0.590.8837288096407720.0185546256675338
0.60.8868918197174030.0184274237550889
0.610.8900254182823880.0181815126038245
0.620.893108998147960.0178003184355686
0.630.8961202704309170.0172750557804465
0.640.8990366504007640.0166064564640451
0.650.901836903877350.0158060406733841
0.660.9045029377773640.0148957772281856
0.670.907021624760360.0139084949432564
0.680.909386583594680.0128841617006653
0.690.911599880774640.0118732217969068
0.70.9136736522367340.0109276070046339
0.710.9156316395187150.0101118222886584
0.720.9175105695819820.0094955906524746
0.730.9193611741667920.00916083841819465
0.740.921248460770140.00919703433683982
0.750.9232506625810740.00968438506916855
0.760.9254561883433430.0106742913471305
0.770.9279579609765650.0121649595096515
0.780.9308448613948550.0140954137567437
0.790.934190619123560.0163422947029298
0.80.938041365031490.0187253547553665
0.810.9424040217808930.0210153504000639
0.820.9472384824089780.0229581518854807
0.830.952456777322720.0243101462873557
0.840.9579318286391690.024886670194248
0.850.9635167295233330.0246046329518060
0.860.9690727846392930.0235246397989794
0.870.9745011651072760.0218629790162297
0.880.9797697824405520.0199805985887911
0.890.9849252463835710.0183298783311204
0.90.9900814596140850.0173304254644116
0.910.9953835692027580.0171531920939682
0.921.000959599044210.0175490373660681
0.931.006889460926540.0179383444747054
0.941.013231741173920.0177538738190025
0.951.020129917136740.0168765909408637
0.961.027939333519310.0161209786732948
0.971.037167521194920.0174324825582754
0.981.047920937174680.0223196274919401
0.991.058853123692230.0295050170940449

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 0.690357482308182 & 0.0257493744938832 \tabularnewline
0.02 & 0.700685128906497 & 0.021734532514729 \tabularnewline
0.03 & 0.711203661682137 & 0.0181409407214812 \tabularnewline
0.04 & 0.72023898438472 & 0.0152701505942662 \tabularnewline
0.05 & 0.727440881413487 & 0.0130169628370724 \tabularnewline
0.06 & 0.733099921357014 & 0.0113755336274530 \tabularnewline
0.07 & 0.737659335448754 & 0.0104102672587416 \tabularnewline
0.08 & 0.74151273845378 & 0.0100957980377989 \tabularnewline
0.09 & 0.74495514161584 & 0.0102701844619835 \tabularnewline
0.1 & 0.748186428582047 & 0.0107193845356072 \tabularnewline
0.11 & 0.751327910316362 & 0.0112601657760742 \tabularnewline
0.12 & 0.754441805212276 & 0.0117752995862039 \tabularnewline
0.13 & 0.75755063249992 & 0.0122043778163178 \tabularnewline
0.14 & 0.76065429948632 & 0.0125298799458765 \tabularnewline
0.15 & 0.763743305343406 & 0.0127639590477691 \tabularnewline
0.16 & 0.766807549462512 & 0.012937217037477 \tabularnewline
0.17 & 0.769841109645341 & 0.0130890257027324 \tabularnewline
0.18 & 0.77284379548173 & 0.0132543391742880 \tabularnewline
0.19 & 0.775820396037054 & 0.0134562040704081 \tabularnewline
0.2 & 0.77877850718208 & 0.0137014134900641 \tabularnewline
0.21 & 0.78172574245337 & 0.0139761760838112 \tabularnewline
0.22 & 0.78466702273709 & 0.014254906668871 \tabularnewline
0.23 & 0.787602494868815 & 0.0145009100196785 \tabularnewline
0.24 & 0.790526445184956 & 0.0146742460172555 \tabularnewline
0.25 & 0.79342736634079 & 0.0147425838993809 \tabularnewline
0.26 & 0.796289130380653 & 0.0146806157352704 \tabularnewline
0.27 & 0.799093044926289 & 0.0144813558459163 \tabularnewline
0.28 & 0.801820443389707 & 0.0141518828509622 \tabularnewline
0.29 & 0.804455396843899 & 0.0137166291746623 \tabularnewline
0.3 & 0.806987138209371 & 0.0132144865802642 \tabularnewline
0.31 & 0.809411853472078 & 0.0126954985073174 \tabularnewline
0.32 & 0.811733606108686 & 0.0122127590106538 \tabularnewline
0.33 & 0.813964299470086 & 0.0118197530780406 \tabularnewline
0.34 & 0.816122723931974 & 0.0115605302029674 \tabularnewline
0.35 & 0.818232858607467 & 0.0114653295564385 \tabularnewline
0.36 & 0.820321684135923 & 0.0115477666075857 \tabularnewline
0.37 & 0.82241680449498 & 0.0118008984086779 \tabularnewline
0.38 & 0.824544171681595 & 0.0122015373336842 \tabularnewline
0.39 & 0.82672616448967 & 0.0127161972913673 \tabularnewline
0.4 & 0.82898020298072 & 0.0133047190084541 \tabularnewline
0.41 & 0.831317996630932 & 0.0139270942039374 \tabularnewline
0.42 & 0.833745438813856 & 0.0145468382768111 \tabularnewline
0.43 & 0.836263083473279 & 0.0151326313986313 \tabularnewline
0.44 & 0.838867079290996 & 0.0156627183912659 \tabularnewline
0.45 & 0.841550397521925 & 0.0161249314936152 \tabularnewline
0.46 & 0.844304174449764 & 0.0165157734928721 \tabularnewline
0.47 & 0.84711899771324 & 0.0168385143727890 \tabularnewline
0.48 & 0.849985994125985 & 0.0171040905359246 \tabularnewline
0.49 & 0.852897618859805 & 0.0173246160284153 \tabularnewline
0.5 & 0.855848093993298 & 0.0175143229302128 \tabularnewline
0.51 & 0.858833490301312 & 0.0176871470530748 \tabularnewline
0.52 & 0.86185148335848 & 0.0178499332357475 \tabularnewline
0.53 & 0.86490084036248 & 0.0180101805121891 \tabularnewline
0.54 & 0.867980708107146 & 0.0181670326317408 \tabularnewline
0.55 & 0.87108977879859 & 0.0183152217343903 \tabularnewline
0.56 & 0.874225413602255 & 0.0184445154323164 \tabularnewline
0.57 & 0.8773828074957 & 0.0185417822082271 \tabularnewline
0.58 & 0.880554283787986 & 0.0185853019135757 \tabularnewline
0.59 & 0.883728809640772 & 0.0185546256675338 \tabularnewline
0.6 & 0.886891819717403 & 0.0184274237550889 \tabularnewline
0.61 & 0.890025418282388 & 0.0181815126038245 \tabularnewline
0.62 & 0.89310899814796 & 0.0178003184355686 \tabularnewline
0.63 & 0.896120270430917 & 0.0172750557804465 \tabularnewline
0.64 & 0.899036650400764 & 0.0166064564640451 \tabularnewline
0.65 & 0.90183690387735 & 0.0158060406733841 \tabularnewline
0.66 & 0.904502937777364 & 0.0148957772281856 \tabularnewline
0.67 & 0.90702162476036 & 0.0139084949432564 \tabularnewline
0.68 & 0.90938658359468 & 0.0128841617006653 \tabularnewline
0.69 & 0.91159988077464 & 0.0118732217969068 \tabularnewline
0.7 & 0.913673652236734 & 0.0109276070046339 \tabularnewline
0.71 & 0.915631639518715 & 0.0101118222886584 \tabularnewline
0.72 & 0.917510569581982 & 0.0094955906524746 \tabularnewline
0.73 & 0.919361174166792 & 0.00916083841819465 \tabularnewline
0.74 & 0.92124846077014 & 0.00919703433683982 \tabularnewline
0.75 & 0.923250662581074 & 0.00968438506916855 \tabularnewline
0.76 & 0.925456188343343 & 0.0106742913471305 \tabularnewline
0.77 & 0.927957960976565 & 0.0121649595096515 \tabularnewline
0.78 & 0.930844861394855 & 0.0140954137567437 \tabularnewline
0.79 & 0.93419061912356 & 0.0163422947029298 \tabularnewline
0.8 & 0.93804136503149 & 0.0187253547553665 \tabularnewline
0.81 & 0.942404021780893 & 0.0210153504000639 \tabularnewline
0.82 & 0.947238482408978 & 0.0229581518854807 \tabularnewline
0.83 & 0.95245677732272 & 0.0243101462873557 \tabularnewline
0.84 & 0.957931828639169 & 0.024886670194248 \tabularnewline
0.85 & 0.963516729523333 & 0.0246046329518060 \tabularnewline
0.86 & 0.969072784639293 & 0.0235246397989794 \tabularnewline
0.87 & 0.974501165107276 & 0.0218629790162297 \tabularnewline
0.88 & 0.979769782440552 & 0.0199805985887911 \tabularnewline
0.89 & 0.984925246383571 & 0.0183298783311204 \tabularnewline
0.9 & 0.990081459614085 & 0.0173304254644116 \tabularnewline
0.91 & 0.995383569202758 & 0.0171531920939682 \tabularnewline
0.92 & 1.00095959904421 & 0.0175490373660681 \tabularnewline
0.93 & 1.00688946092654 & 0.0179383444747054 \tabularnewline
0.94 & 1.01323174117392 & 0.0177538738190025 \tabularnewline
0.95 & 1.02012991713674 & 0.0168765909408637 \tabularnewline
0.96 & 1.02793933351931 & 0.0161209786732948 \tabularnewline
0.97 & 1.03716752119492 & 0.0174324825582754 \tabularnewline
0.98 & 1.04792093717468 & 0.0223196274919401 \tabularnewline
0.99 & 1.05885312369223 & 0.0295050170940449 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19715&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]0.690357482308182[/C][C]0.0257493744938832[/C][/ROW]
[ROW][C]0.02[/C][C]0.700685128906497[/C][C]0.021734532514729[/C][/ROW]
[ROW][C]0.03[/C][C]0.711203661682137[/C][C]0.0181409407214812[/C][/ROW]
[ROW][C]0.04[/C][C]0.72023898438472[/C][C]0.0152701505942662[/C][/ROW]
[ROW][C]0.05[/C][C]0.727440881413487[/C][C]0.0130169628370724[/C][/ROW]
[ROW][C]0.06[/C][C]0.733099921357014[/C][C]0.0113755336274530[/C][/ROW]
[ROW][C]0.07[/C][C]0.737659335448754[/C][C]0.0104102672587416[/C][/ROW]
[ROW][C]0.08[/C][C]0.74151273845378[/C][C]0.0100957980377989[/C][/ROW]
[ROW][C]0.09[/C][C]0.74495514161584[/C][C]0.0102701844619835[/C][/ROW]
[ROW][C]0.1[/C][C]0.748186428582047[/C][C]0.0107193845356072[/C][/ROW]
[ROW][C]0.11[/C][C]0.751327910316362[/C][C]0.0112601657760742[/C][/ROW]
[ROW][C]0.12[/C][C]0.754441805212276[/C][C]0.0117752995862039[/C][/ROW]
[ROW][C]0.13[/C][C]0.75755063249992[/C][C]0.0122043778163178[/C][/ROW]
[ROW][C]0.14[/C][C]0.76065429948632[/C][C]0.0125298799458765[/C][/ROW]
[ROW][C]0.15[/C][C]0.763743305343406[/C][C]0.0127639590477691[/C][/ROW]
[ROW][C]0.16[/C][C]0.766807549462512[/C][C]0.012937217037477[/C][/ROW]
[ROW][C]0.17[/C][C]0.769841109645341[/C][C]0.0130890257027324[/C][/ROW]
[ROW][C]0.18[/C][C]0.77284379548173[/C][C]0.0132543391742880[/C][/ROW]
[ROW][C]0.19[/C][C]0.775820396037054[/C][C]0.0134562040704081[/C][/ROW]
[ROW][C]0.2[/C][C]0.77877850718208[/C][C]0.0137014134900641[/C][/ROW]
[ROW][C]0.21[/C][C]0.78172574245337[/C][C]0.0139761760838112[/C][/ROW]
[ROW][C]0.22[/C][C]0.78466702273709[/C][C]0.014254906668871[/C][/ROW]
[ROW][C]0.23[/C][C]0.787602494868815[/C][C]0.0145009100196785[/C][/ROW]
[ROW][C]0.24[/C][C]0.790526445184956[/C][C]0.0146742460172555[/C][/ROW]
[ROW][C]0.25[/C][C]0.79342736634079[/C][C]0.0147425838993809[/C][/ROW]
[ROW][C]0.26[/C][C]0.796289130380653[/C][C]0.0146806157352704[/C][/ROW]
[ROW][C]0.27[/C][C]0.799093044926289[/C][C]0.0144813558459163[/C][/ROW]
[ROW][C]0.28[/C][C]0.801820443389707[/C][C]0.0141518828509622[/C][/ROW]
[ROW][C]0.29[/C][C]0.804455396843899[/C][C]0.0137166291746623[/C][/ROW]
[ROW][C]0.3[/C][C]0.806987138209371[/C][C]0.0132144865802642[/C][/ROW]
[ROW][C]0.31[/C][C]0.809411853472078[/C][C]0.0126954985073174[/C][/ROW]
[ROW][C]0.32[/C][C]0.811733606108686[/C][C]0.0122127590106538[/C][/ROW]
[ROW][C]0.33[/C][C]0.813964299470086[/C][C]0.0118197530780406[/C][/ROW]
[ROW][C]0.34[/C][C]0.816122723931974[/C][C]0.0115605302029674[/C][/ROW]
[ROW][C]0.35[/C][C]0.818232858607467[/C][C]0.0114653295564385[/C][/ROW]
[ROW][C]0.36[/C][C]0.820321684135923[/C][C]0.0115477666075857[/C][/ROW]
[ROW][C]0.37[/C][C]0.82241680449498[/C][C]0.0118008984086779[/C][/ROW]
[ROW][C]0.38[/C][C]0.824544171681595[/C][C]0.0122015373336842[/C][/ROW]
[ROW][C]0.39[/C][C]0.82672616448967[/C][C]0.0127161972913673[/C][/ROW]
[ROW][C]0.4[/C][C]0.82898020298072[/C][C]0.0133047190084541[/C][/ROW]
[ROW][C]0.41[/C][C]0.831317996630932[/C][C]0.0139270942039374[/C][/ROW]
[ROW][C]0.42[/C][C]0.833745438813856[/C][C]0.0145468382768111[/C][/ROW]
[ROW][C]0.43[/C][C]0.836263083473279[/C][C]0.0151326313986313[/C][/ROW]
[ROW][C]0.44[/C][C]0.838867079290996[/C][C]0.0156627183912659[/C][/ROW]
[ROW][C]0.45[/C][C]0.841550397521925[/C][C]0.0161249314936152[/C][/ROW]
[ROW][C]0.46[/C][C]0.844304174449764[/C][C]0.0165157734928721[/C][/ROW]
[ROW][C]0.47[/C][C]0.84711899771324[/C][C]0.0168385143727890[/C][/ROW]
[ROW][C]0.48[/C][C]0.849985994125985[/C][C]0.0171040905359246[/C][/ROW]
[ROW][C]0.49[/C][C]0.852897618859805[/C][C]0.0173246160284153[/C][/ROW]
[ROW][C]0.5[/C][C]0.855848093993298[/C][C]0.0175143229302128[/C][/ROW]
[ROW][C]0.51[/C][C]0.858833490301312[/C][C]0.0176871470530748[/C][/ROW]
[ROW][C]0.52[/C][C]0.86185148335848[/C][C]0.0178499332357475[/C][/ROW]
[ROW][C]0.53[/C][C]0.86490084036248[/C][C]0.0180101805121891[/C][/ROW]
[ROW][C]0.54[/C][C]0.867980708107146[/C][C]0.0181670326317408[/C][/ROW]
[ROW][C]0.55[/C][C]0.87108977879859[/C][C]0.0183152217343903[/C][/ROW]
[ROW][C]0.56[/C][C]0.874225413602255[/C][C]0.0184445154323164[/C][/ROW]
[ROW][C]0.57[/C][C]0.8773828074957[/C][C]0.0185417822082271[/C][/ROW]
[ROW][C]0.58[/C][C]0.880554283787986[/C][C]0.0185853019135757[/C][/ROW]
[ROW][C]0.59[/C][C]0.883728809640772[/C][C]0.0185546256675338[/C][/ROW]
[ROW][C]0.6[/C][C]0.886891819717403[/C][C]0.0184274237550889[/C][/ROW]
[ROW][C]0.61[/C][C]0.890025418282388[/C][C]0.0181815126038245[/C][/ROW]
[ROW][C]0.62[/C][C]0.89310899814796[/C][C]0.0178003184355686[/C][/ROW]
[ROW][C]0.63[/C][C]0.896120270430917[/C][C]0.0172750557804465[/C][/ROW]
[ROW][C]0.64[/C][C]0.899036650400764[/C][C]0.0166064564640451[/C][/ROW]
[ROW][C]0.65[/C][C]0.90183690387735[/C][C]0.0158060406733841[/C][/ROW]
[ROW][C]0.66[/C][C]0.904502937777364[/C][C]0.0148957772281856[/C][/ROW]
[ROW][C]0.67[/C][C]0.90702162476036[/C][C]0.0139084949432564[/C][/ROW]
[ROW][C]0.68[/C][C]0.90938658359468[/C][C]0.0128841617006653[/C][/ROW]
[ROW][C]0.69[/C][C]0.91159988077464[/C][C]0.0118732217969068[/C][/ROW]
[ROW][C]0.7[/C][C]0.913673652236734[/C][C]0.0109276070046339[/C][/ROW]
[ROW][C]0.71[/C][C]0.915631639518715[/C][C]0.0101118222886584[/C][/ROW]
[ROW][C]0.72[/C][C]0.917510569581982[/C][C]0.0094955906524746[/C][/ROW]
[ROW][C]0.73[/C][C]0.919361174166792[/C][C]0.00916083841819465[/C][/ROW]
[ROW][C]0.74[/C][C]0.92124846077014[/C][C]0.00919703433683982[/C][/ROW]
[ROW][C]0.75[/C][C]0.923250662581074[/C][C]0.00968438506916855[/C][/ROW]
[ROW][C]0.76[/C][C]0.925456188343343[/C][C]0.0106742913471305[/C][/ROW]
[ROW][C]0.77[/C][C]0.927957960976565[/C][C]0.0121649595096515[/C][/ROW]
[ROW][C]0.78[/C][C]0.930844861394855[/C][C]0.0140954137567437[/C][/ROW]
[ROW][C]0.79[/C][C]0.93419061912356[/C][C]0.0163422947029298[/C][/ROW]
[ROW][C]0.8[/C][C]0.93804136503149[/C][C]0.0187253547553665[/C][/ROW]
[ROW][C]0.81[/C][C]0.942404021780893[/C][C]0.0210153504000639[/C][/ROW]
[ROW][C]0.82[/C][C]0.947238482408978[/C][C]0.0229581518854807[/C][/ROW]
[ROW][C]0.83[/C][C]0.95245677732272[/C][C]0.0243101462873557[/C][/ROW]
[ROW][C]0.84[/C][C]0.957931828639169[/C][C]0.024886670194248[/C][/ROW]
[ROW][C]0.85[/C][C]0.963516729523333[/C][C]0.0246046329518060[/C][/ROW]
[ROW][C]0.86[/C][C]0.969072784639293[/C][C]0.0235246397989794[/C][/ROW]
[ROW][C]0.87[/C][C]0.974501165107276[/C][C]0.0218629790162297[/C][/ROW]
[ROW][C]0.88[/C][C]0.979769782440552[/C][C]0.0199805985887911[/C][/ROW]
[ROW][C]0.89[/C][C]0.984925246383571[/C][C]0.0183298783311204[/C][/ROW]
[ROW][C]0.9[/C][C]0.990081459614085[/C][C]0.0173304254644116[/C][/ROW]
[ROW][C]0.91[/C][C]0.995383569202758[/C][C]0.0171531920939682[/C][/ROW]
[ROW][C]0.92[/C][C]1.00095959904421[/C][C]0.0175490373660681[/C][/ROW]
[ROW][C]0.93[/C][C]1.00688946092654[/C][C]0.0179383444747054[/C][/ROW]
[ROW][C]0.94[/C][C]1.01323174117392[/C][C]0.0177538738190025[/C][/ROW]
[ROW][C]0.95[/C][C]1.02012991713674[/C][C]0.0168765909408637[/C][/ROW]
[ROW][C]0.96[/C][C]1.02793933351931[/C][C]0.0161209786732948[/C][/ROW]
[ROW][C]0.97[/C][C]1.03716752119492[/C][C]0.0174324825582754[/C][/ROW]
[ROW][C]0.98[/C][C]1.04792093717468[/C][C]0.0223196274919401[/C][/ROW]
[ROW][C]0.99[/C][C]1.05885312369223[/C][C]0.0295050170940449[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19715&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19715&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
0.010.6903574823081820.0257493744938832
0.020.7006851289064970.021734532514729
0.030.7112036616821370.0181409407214812
0.040.720238984384720.0152701505942662
0.050.7274408814134870.0130169628370724
0.060.7330999213570140.0113755336274530
0.070.7376593354487540.0104102672587416
0.080.741512738453780.0100957980377989
0.090.744955141615840.0102701844619835
0.10.7481864285820470.0107193845356072
0.110.7513279103163620.0112601657760742
0.120.7544418052122760.0117752995862039
0.130.757550632499920.0122043778163178
0.140.760654299486320.0125298799458765
0.150.7637433053434060.0127639590477691
0.160.7668075494625120.012937217037477
0.170.7698411096453410.0130890257027324
0.180.772843795481730.0132543391742880
0.190.7758203960370540.0134562040704081
0.20.778778507182080.0137014134900641
0.210.781725742453370.0139761760838112
0.220.784667022737090.014254906668871
0.230.7876024948688150.0145009100196785
0.240.7905264451849560.0146742460172555
0.250.793427366340790.0147425838993809
0.260.7962891303806530.0146806157352704
0.270.7990930449262890.0144813558459163
0.280.8018204433897070.0141518828509622
0.290.8044553968438990.0137166291746623
0.30.8069871382093710.0132144865802642
0.310.8094118534720780.0126954985073174
0.320.8117336061086860.0122127590106538
0.330.8139642994700860.0118197530780406
0.340.8161227239319740.0115605302029674
0.350.8182328586074670.0114653295564385
0.360.8203216841359230.0115477666075857
0.370.822416804494980.0118008984086779
0.380.8245441716815950.0122015373336842
0.390.826726164489670.0127161972913673
0.40.828980202980720.0133047190084541
0.410.8313179966309320.0139270942039374
0.420.8337454388138560.0145468382768111
0.430.8362630834732790.0151326313986313
0.440.8388670792909960.0156627183912659
0.450.8415503975219250.0161249314936152
0.460.8443041744497640.0165157734928721
0.470.847118997713240.0168385143727890
0.480.8499859941259850.0171040905359246
0.490.8528976188598050.0173246160284153
0.50.8558480939932980.0175143229302128
0.510.8588334903013120.0176871470530748
0.520.861851483358480.0178499332357475
0.530.864900840362480.0180101805121891
0.540.8679807081071460.0181670326317408
0.550.871089778798590.0183152217343903
0.560.8742254136022550.0184445154323164
0.570.87738280749570.0185417822082271
0.580.8805542837879860.0185853019135757
0.590.8837288096407720.0185546256675338
0.60.8868918197174030.0184274237550889
0.610.8900254182823880.0181815126038245
0.620.893108998147960.0178003184355686
0.630.8961202704309170.0172750557804465
0.640.8990366504007640.0166064564640451
0.650.901836903877350.0158060406733841
0.660.9045029377773640.0148957772281856
0.670.907021624760360.0139084949432564
0.680.909386583594680.0128841617006653
0.690.911599880774640.0118732217969068
0.70.9136736522367340.0109276070046339
0.710.9156316395187150.0101118222886584
0.720.9175105695819820.0094955906524746
0.730.9193611741667920.00916083841819465
0.740.921248460770140.00919703433683982
0.750.9232506625810740.00968438506916855
0.760.9254561883433430.0106742913471305
0.770.9279579609765650.0121649595096515
0.780.9308448613948550.0140954137567437
0.790.934190619123560.0163422947029298
0.80.938041365031490.0187253547553665
0.810.9424040217808930.0210153504000639
0.820.9472384824089780.0229581518854807
0.830.952456777322720.0243101462873557
0.840.9579318286391690.024886670194248
0.850.9635167295233330.0246046329518060
0.860.9690727846392930.0235246397989794
0.870.9745011651072760.0218629790162297
0.880.9797697824405520.0199805985887911
0.890.9849252463835710.0183298783311204
0.90.9900814596140850.0173304254644116
0.910.9953835692027580.0171531920939682
0.921.000959599044210.0175490373660681
0.931.006889460926540.0179383444747054
0.941.013231741173920.0177538738190025
0.951.020129917136740.0168765909408637
0.961.027939333519310.0161209786732948
0.971.037167521194920.0174324825582754
0.981.047920937174680.0223196274919401
0.991.058853123692230.0295050170940449


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')