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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 17:27:13 -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/t1225150071o9b71y1i8no6dno.htm/, Retrieved Sun, 19 May 2024 20:25:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19710, Retrieved Sun, 19 May 2024 20:25:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact190

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] [] [2008-10-27 23:27:13] [e0f4dc76ea1a8276fe566258b977cec4] [Current]
Feedback Forum
2008-10-31 13:54:02 [Stijn Van de Velde] [reply] 
De student van vorig jaar heeft deze oefening inderdaad goed gemaakt.

Er zijn 2 manieren om dit te berekenen.
1) in bijvoorbeeld excel het gemiddelde aftrekken van de originele waarden van de tijdreeks en plakken + berekenen.
2) de originele waarde plakken en een stuk in de R-code aanpassen naar: x<-x-'gemiddelde' (wel het getal invullen en niet het woord.)
De software berekend dit dan automatisch.

De gevonden uitkomsten zijn eigenlijk de grenzen waarbinnen de zogenaamde random component zich bevind.
  2008-11-02 19:33:20 [Stijn Van de Velde] [reply] 
opmerking: 'gemiddelde' moet eigenlijk zijn 'constante', want je kan daar ook de mediaan voor gebruiken.
2008-11-01 11:18:22 [2df1bcd103d52957f4a39bd4617794c8] [reply] 
Unverified author, niet opgeslagen onder eigen inlog...

Student lost de oefening correct op en trekt een juist besluit.
2008-11-03 09:27:58 [256f97d8b7c07ed49f142eff724c6520] [reply] 
Dit is juist uitgevoerd. Je had de stapgrootte 0,005 kunnen plaatsen, maar dit gaf hetzelfde resultaat.
2008-11-03 09:29:18 [Bas van Keken] [reply] 
Een kleine toevoegingen is dat de percentielen kunnen worden vermeld waar de gegevens van zijn ontleend.

Post a new message

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19710&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19710&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19710&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Harrell-Davis Quantiles
quantilesvaluestandard error
0.010.6903574823081830.0257493744938832
0.020.7006851289064970.021734532514729
0.030.7112036616821370.0181409407214812
0.040.720238984384720.0152701505942662
0.050.7274408814134870.0130169628370724
0.060.7330999213570140.0113755336274530
0.070.7376593354487550.0104102672587416
0.080.741512738453780.0100957980377989
0.090.744955141615840.0102701844619835
0.10.7481864285820480.0107193845356072
0.110.7513279103163630.0112601657760742
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
0.20.7787785071820790.0137014134900641
0.210.781725742453370.0139761760838112
0.220.7846670227370890.014254906668871
0.230.7876024948688150.0145009100196785
0.240.7905264451849560.0146742460172555
0.250.793427366340790.0147425838993809
0.260.7962891303806530.0146806157352704
0.270.7990930449262890.0144813558459163
0.280.8018204433897080.0141518828509622
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
0.420.8337454388138570.0145468382768111
0.430.8362630834732790.0151326313986313
0.440.8388670792909960.0156627183912659
0.450.8415503975219250.0161249314936152
0.460.8443041744497640.0165157734928721
0.470.8471189977132410.0168385143727890
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
0.820.9472384824089770.0229581518854807
0.830.952456777322720.0243101462873557
0.840.9579318286391690.024886670194248
0.850.9635167295233330.0246046329518060
0.860.9690727846392930.0235246397989794
0.870.9745011651072760.0218629790162297
0.880.9797697824405530.0199805985887911
0.890.984925246383570.0183298783311204
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 & 0.690357482308183 & 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 & 0.737659335448755 & 0.0104102672587416 \tabularnewline
0.08 & 0.74151273845378 & 0.0100957980377989 \tabularnewline
0.09 & 0.74495514161584 & 0.0102701844619835 \tabularnewline
0.1 & 0.748186428582048 & 0.0107193845356072 \tabularnewline
0.11 & 0.751327910316363 & 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 & 0.778778507182079 & 0.0137014134900641 \tabularnewline
0.21 & 0.78172574245337 & 0.0139761760838112 \tabularnewline
0.22 & 0.784667022737089 & 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 & 0.801820443389708 & 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 & 0.833745438813857 & 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 & 0.847118997713241 & 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 & 0.947238482408977 & 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 & 0.979769782440553 & 0.0199805985887911 \tabularnewline
0.89 & 0.98492524638357 & 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=19710&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]0.690357482308183[/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]0.737659335448755[/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]0.748186428582048[/C][C]0.0107193845356072[/C][/ROW]
[ROW][C]0.11[/C][C]0.751327910316363[/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]0.778778507182079[/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]0.784667022737089[/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]0.801820443389708[/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]0.833745438813857[/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]0.847118997713241[/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]0.947238482408977[/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]0.979769782440553[/C][C]0.0199805985887911[/C][/ROW]
[ROW][C]0.89[/C][C]0.98492524638357[/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=19710&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19710&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
0.010.6903574823081830.0257493744938832
0.020.7006851289064970.021734532514729
0.030.7112036616821370.0181409407214812
0.040.720238984384720.0152701505942662
0.050.7274408814134870.0130169628370724
0.060.7330999213570140.0113755336274530
0.070.7376593354487550.0104102672587416
0.080.741512738453780.0100957980377989
0.090.744955141615840.0102701844619835
0.10.7481864285820480.0107193845356072
0.110.7513279103163630.0112601657760742
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
0.20.7787785071820790.0137014134900641
0.210.781725742453370.0139761760838112
0.220.7846670227370890.014254906668871
0.230.7876024948688150.0145009100196785
0.240.7905264451849560.0146742460172555
0.250.793427366340790.0147425838993809
0.260.7962891303806530.0146806157352704
0.270.7990930449262890.0144813558459163
0.280.8018204433897080.0141518828509622
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
0.420.8337454388138570.0145468382768111
0.430.8362630834732790.0151326313986313
0.440.8388670792909960.0156627183912659
0.450.8415503975219250.0161249314936152
0.460.8443041744497640.0165157734928721
0.470.8471189977132410.0168385143727890
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
0.820.9472384824089770.0229581518854807
0.830.952456777322720.0243101462873557
0.840.9579318286391690.024886670194248
0.850.9635167295233330.0246046329518060
0.860.9690727846392930.0235246397989794
0.870.9745011651072760.0218629790162297
0.880.9797697824405530.0199805985887911
0.890.984925246383570.0183298783311204
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')