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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, 27 Oct 2008 18:31:07 -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/t1225153900ub6pi79dcf1a1ua.htm/, Retrieved Sun, 19 May 2024 19:48:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19723, Retrieved Sun, 19 May 2024 19:48:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact214

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Explorative Data Analysis] [Investigating Dis...] [2007-10-21 18:26:46] [b9964c45117f7aac638ab9056d451faa]
F RMPD    [Harrell-Davis Quantiles] [Q4] [2008-10-28 00:31:07] [40845526110da2d5a5bf7b165da84e03] [Current]
Feedback Forum
2008-11-03 09:38:45 [a7e076854c32462fd499d2de3f6d4e86] [reply] 
Correct opgelost.
2008-11-03 20:40:16 [Nathalie Boden] [reply] 
2008-11-03 20:41:01 [Nathalie Boden] [reply] 
We zien hier dat de student de opdracht correct heeft opgelost. We zien hier een zeker seizonaal patroon maar dit is moeilijk te zien.
2008-11-03 20:43:09 [Nathalie Boden] [reply] 
De voorgaande commentaar was een antwoord op Q4 aangezien hier geen link bijgezet was. Bij q5 zien we dat de student de oplossing correct heeft beantwoord maar we kunnen ook een andere methode zien namelijk de r-code. Zo kunnen we de reeks manipuleren. We zetten in de r-code x<-x-.... gemiddelde Daarin kijken we naar 0.025 die een waarde van -015% aangeeft en naar 0.975 die een waarde aangeeft van 0.1802 aangeeft.
2008-11-03 21:51:50 [Kristof Francken] [reply] 
De student heeft gelijk, al kunnen wit ook oplossen door een andere methode. We kunnen namelijk de R-code aanpassen, X<-X-0,86… (0,86.. = gemiddelde). Hierbij moeten we dan kijken naar 0,025 en 0,975.

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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 time3 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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19723&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]3 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=19723&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19723&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 time3 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=19723&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=19723&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19723&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')