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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 13:48:40 -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/27/t1225136962kwg2swke0kqfqkz.htm/, Retrieved Sun, 19 May 2024 12:55:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19507, Retrieved Sun, 19 May 2024 12:55:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Harrell-Davis Quantiles] [Q 5] [2008-10-25 13:18:34] [4300be8b33fd3dcdacd2aa9800ceba23]
F   P     [Harrell-Davis Quantiles] [Q5] [2008-10-27 19:48:40] [541f63fa3157af9df10fc4d202b2a90b] [Current]
Feedback Forum
2008-11-01 20:49:32 [Tom Ardies] [reply] 
Je hebt het rekenkundig gemiddelde afgetrokken van de quartielen. Hierdoor bekom je het verwachtte betrouwbaarheidsinterval.
2008-11-04 07:28:19 [Nilay Erdogdu] [reply] 
stepsize veranderen naar 0.005 daarna gemiddelde nemen en aftrekken van de data. in de R code aanpassen: x<-x- gemiddelde. Vervolgens op compute klikken.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.9891304348
0.9190871369
0.9254170756
0.9256120527
1.0666666667
0.8511087645
1.0306930693
0.9890310786
0.9130009775
0.7927232635
0.9781704782
0.9875130073
0.9094339623
0.8836081474
0.8274509804
0.8252148997
1.0232558140
0.8154180239
1.0261927035
0.9147424512
0.8072763029
0.7391304348
0.9897330595
0.9721649485
0.8538899431
0.8568646543
0.7757390418
0.7894736842
0.9313501144
0.7397107898
0.8852459016
0.8424350940
0.8184584178
0.7275541796
0.9232386961
0.9226804124
0.8837622005
0.8182701652
0.7710472279
0.8258527828
0.9244851259
0.7551652893
0.8746713409
0.8159564823
0.7998075072
0.7125984252
0.8329809725
0.9103232534
0.8691499522
0.7791828794
0.7502548420
0.7585601405
0.9208899876
0.7439916405
0.8162544170
0.7695939566
0.7840073529
0.6832844575
0.8505050505
0.9006951341
0.8683982684

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19507&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19507&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19507&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'George Udny Yule' @ 72.249.76.132






Harrell-Davis Quantiles
quantilesvaluestandard error
0.010.6903574827147760.0257493744938832
0.020.700685129167420.021734532514729
0.030.7112036617888870.0181409407214812
0.040.7202389843621290.0152701505942662
0.050.7274408813012880.0130169628370724
0.060.7330999211955620.0113755336274530
0.070.7376593352715910.0104102672587416
0.080.7415127382853370.0100957980377989
0.090.7449551414717470.0102701844619835
0.10.7481864284703220.0107193845356072
0.110.7513279102387620.0112601657760742
0.120.7544418051657710.0117752995862039
0.130.7575506324783360.0122043778163178
0.140.7606542994820610.0125298799458765
0.150.7637433053490180.0127639590477691
0.160.7668075494718250.012937217037477
0.170.7698411096540330.0130890257027324
0.180.7728437954873660.0132543391742880
0.190.7758203960387350.0134562040704081
0.20.7787785071799270.0137014134900641
0.210.7817257424480380.0139761760838112
0.220.7846670227293940.014254906668871
0.230.787602494859530.0145009100196785
0.240.7905264451747280.0146742460172555
0.250.793427366330130.0147425838993809
0.260.7962891303699270.0146806157352704
0.270.7990930449156880.0144813558459163
0.280.8018204433791970.0141518828509622
0.290.8044553968331480.0137166291746623
0.30.8069871381977040.0132144865802642
0.310.809411853458460.0126954985073174
0.320.811733606091770.0122127590106538
0.330.8139642994483080.0118197530780406
0.340.81612272390370.0115605302029674
0.350.818232858571160.0114653295564385
0.360.8203216840903190.0115477666075857
0.370.8224168044392430.0118008984086779
0.380.8245441716154450.0122015373336842
0.390.826726164413470.0127161972913673
0.40.828980202895510.0133047190084541
0.410.8313179965384260.0139270942039374
0.420.8337454387163690.0145468382768111
0.430.8362630833736180.0151326313986313
0.440.8388670791922960.0156627183912659
0.450.841550397427440.0161249314936152
0.460.8443041743626370.0165157734928721
0.470.8471189976362540.0168385143727890
0.480.849985994061330.0171040905359246
0.490.8528976188088980.0173246160284153
0.50.8558480939566570.0175143229302128
0.510.8588334902785350.0176871470530748
0.520.8618514833483050.0178499332357475
0.530.8649008403629530.0180101805121891
0.540.8679807081158470.0181670326317408
0.550.8710897788129070.0183152217343903
0.560.874225413619650.0184445154323164
0.570.8773828075139420.0185417822082271
0.580.8805542838053150.0185853019135757
0.590.8837288096559690.0185546256675338
0.60.8868918197297790.0184274237550889
0.610.8900254182916940.0181815126038245
0.620.8931089981542590.0178003184355686
0.630.8961202704344240.0172750557804465
0.640.8990366504017180.0166064564640451
0.650.9018369038759160.0158060377358362
0.660.9045029377735810.0148957772281856
0.670.9070216247541430.0139084949432564
0.680.9093865835858630.0128841617006653
0.690.9115998807630440.0118732217969068
0.70.9136736522222550.0109276070046339
0.710.9156316395014270.0101118222886584
0.720.9175105695622530.0094955906524746
0.730.9193611741454070.00916083841819465
0.740.9212484607484150.00919703433683982
0.750.9232506625609540.00968438506916855
0.760.9254561883274020.0106742913471305
0.770.927957960967890.0121649595096515
0.780.9308448613967480.0140954115679621
0.790.934190619139020.0163422947029298
0.80.9380413650625380.0187253547553665
0.810.9424040218277960.0210153504000639
0.820.9472384824695650.0229581518854807
0.830.9524567773919770.0243101462873557
0.840.9579318287093380.024886670194248
0.850.9635167295846660.0246046329518060
0.860.9690727846815370.0235246397989794
0.870.9745011651217780.0218629790162297
0.880.9797697824227140.0199805985887911
0.890.984925246335180.0183298783311204
0.90.9900814595448570.0173304254644116
0.910.995383569130270.0171531920939682
0.921.000959598991420.0175490373660681
0.931.00688946091630.0179383444747054
0.941.013231741220420.0177538738190025
0.951.020129917235370.0168765909408637
0.961.027939333638250.0161209786732948
0.971.037167521275100.0174324825582754
0.981.047920937146610.0223196274919401
0.991.058853123514070.0295050170940449

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 0.690357482714776 & 0.0257493744938832 \tabularnewline
0.02 & 0.70068512916742 & 0.021734532514729 \tabularnewline
0.03 & 0.711203661788887 & 0.0181409407214812 \tabularnewline
0.04 & 0.720238984362129 & 0.0152701505942662 \tabularnewline
0.05 & 0.727440881301288 & 0.0130169628370724 \tabularnewline
0.06 & 0.733099921195562 & 0.0113755336274530 \tabularnewline
0.07 & 0.737659335271591 & 0.0104102672587416 \tabularnewline
0.08 & 0.741512738285337 & 0.0100957980377989 \tabularnewline
0.09 & 0.744955141471747 & 0.0102701844619835 \tabularnewline
0.1 & 0.748186428470322 & 0.0107193845356072 \tabularnewline
0.11 & 0.751327910238762 & 0.0112601657760742 \tabularnewline
0.12 & 0.754441805165771 & 0.0117752995862039 \tabularnewline
0.13 & 0.757550632478336 & 0.0122043778163178 \tabularnewline
0.14 & 0.760654299482061 & 0.0125298799458765 \tabularnewline
0.15 & 0.763743305349018 & 0.0127639590477691 \tabularnewline
0.16 & 0.766807549471825 & 0.012937217037477 \tabularnewline
0.17 & 0.769841109654033 & 0.0130890257027324 \tabularnewline
0.18 & 0.772843795487366 & 0.0132543391742880 \tabularnewline
0.19 & 0.775820396038735 & 0.0134562040704081 \tabularnewline
0.2 & 0.778778507179927 & 0.0137014134900641 \tabularnewline
0.21 & 0.781725742448038 & 0.0139761760838112 \tabularnewline
0.22 & 0.784667022729394 & 0.014254906668871 \tabularnewline
0.23 & 0.78760249485953 & 0.0145009100196785 \tabularnewline
0.24 & 0.790526445174728 & 0.0146742460172555 \tabularnewline
0.25 & 0.79342736633013 & 0.0147425838993809 \tabularnewline
0.26 & 0.796289130369927 & 0.0146806157352704 \tabularnewline
0.27 & 0.799093044915688 & 0.0144813558459163 \tabularnewline
0.28 & 0.801820443379197 & 0.0141518828509622 \tabularnewline
0.29 & 0.804455396833148 & 0.0137166291746623 \tabularnewline
0.3 & 0.806987138197704 & 0.0132144865802642 \tabularnewline
0.31 & 0.80941185345846 & 0.0126954985073174 \tabularnewline
0.32 & 0.81173360609177 & 0.0122127590106538 \tabularnewline
0.33 & 0.813964299448308 & 0.0118197530780406 \tabularnewline
0.34 & 0.8161227239037 & 0.0115605302029674 \tabularnewline
0.35 & 0.81823285857116 & 0.0114653295564385 \tabularnewline
0.36 & 0.820321684090319 & 0.0115477666075857 \tabularnewline
0.37 & 0.822416804439243 & 0.0118008984086779 \tabularnewline
0.38 & 0.824544171615445 & 0.0122015373336842 \tabularnewline
0.39 & 0.82672616441347 & 0.0127161972913673 \tabularnewline
0.4 & 0.82898020289551 & 0.0133047190084541 \tabularnewline
0.41 & 0.831317996538426 & 0.0139270942039374 \tabularnewline
0.42 & 0.833745438716369 & 0.0145468382768111 \tabularnewline
0.43 & 0.836263083373618 & 0.0151326313986313 \tabularnewline
0.44 & 0.838867079192296 & 0.0156627183912659 \tabularnewline
0.45 & 0.84155039742744 & 0.0161249314936152 \tabularnewline
0.46 & 0.844304174362637 & 0.0165157734928721 \tabularnewline
0.47 & 0.847118997636254 & 0.0168385143727890 \tabularnewline
0.48 & 0.84998599406133 & 0.0171040905359246 \tabularnewline
0.49 & 0.852897618808898 & 0.0173246160284153 \tabularnewline
0.5 & 0.855848093956657 & 0.0175143229302128 \tabularnewline
0.51 & 0.858833490278535 & 0.0176871470530748 \tabularnewline
0.52 & 0.861851483348305 & 0.0178499332357475 \tabularnewline
0.53 & 0.864900840362953 & 0.0180101805121891 \tabularnewline
0.54 & 0.867980708115847 & 0.0181670326317408 \tabularnewline
0.55 & 0.871089778812907 & 0.0183152217343903 \tabularnewline
0.56 & 0.87422541361965 & 0.0184445154323164 \tabularnewline
0.57 & 0.877382807513942 & 0.0185417822082271 \tabularnewline
0.58 & 0.880554283805315 & 0.0185853019135757 \tabularnewline
0.59 & 0.883728809655969 & 0.0185546256675338 \tabularnewline
0.6 & 0.886891819729779 & 0.0184274237550889 \tabularnewline
0.61 & 0.890025418291694 & 0.0181815126038245 \tabularnewline
0.62 & 0.893108998154259 & 0.0178003184355686 \tabularnewline
0.63 & 0.896120270434424 & 0.0172750557804465 \tabularnewline
0.64 & 0.899036650401718 & 0.0166064564640451 \tabularnewline
0.65 & 0.901836903875916 & 0.0158060377358362 \tabularnewline
0.66 & 0.904502937773581 & 0.0148957772281856 \tabularnewline
0.67 & 0.907021624754143 & 0.0139084949432564 \tabularnewline
0.68 & 0.909386583585863 & 0.0128841617006653 \tabularnewline
0.69 & 0.911599880763044 & 0.0118732217969068 \tabularnewline
0.7 & 0.913673652222255 & 0.0109276070046339 \tabularnewline
0.71 & 0.915631639501427 & 0.0101118222886584 \tabularnewline
0.72 & 0.917510569562253 & 0.0094955906524746 \tabularnewline
0.73 & 0.919361174145407 & 0.00916083841819465 \tabularnewline
0.74 & 0.921248460748415 & 0.00919703433683982 \tabularnewline
0.75 & 0.923250662560954 & 0.00968438506916855 \tabularnewline
0.76 & 0.925456188327402 & 0.0106742913471305 \tabularnewline
0.77 & 0.92795796096789 & 0.0121649595096515 \tabularnewline
0.78 & 0.930844861396748 & 0.0140954115679621 \tabularnewline
0.79 & 0.93419061913902 & 0.0163422947029298 \tabularnewline
0.8 & 0.938041365062538 & 0.0187253547553665 \tabularnewline
0.81 & 0.942404021827796 & 0.0210153504000639 \tabularnewline
0.82 & 0.947238482469565 & 0.0229581518854807 \tabularnewline
0.83 & 0.952456777391977 & 0.0243101462873557 \tabularnewline
0.84 & 0.957931828709338 & 0.024886670194248 \tabularnewline
0.85 & 0.963516729584666 & 0.0246046329518060 \tabularnewline
0.86 & 0.969072784681537 & 0.0235246397989794 \tabularnewline
0.87 & 0.974501165121778 & 0.0218629790162297 \tabularnewline
0.88 & 0.979769782422714 & 0.0199805985887911 \tabularnewline
0.89 & 0.98492524633518 & 0.0183298783311204 \tabularnewline
0.9 & 0.990081459544857 & 0.0173304254644116 \tabularnewline
0.91 & 0.99538356913027 & 0.0171531920939682 \tabularnewline
0.92 & 1.00095959899142 & 0.0175490373660681 \tabularnewline
0.93 & 1.0068894609163 & 0.0179383444747054 \tabularnewline
0.94 & 1.01323174122042 & 0.0177538738190025 \tabularnewline
0.95 & 1.02012991723537 & 0.0168765909408637 \tabularnewline
0.96 & 1.02793933363825 & 0.0161209786732948 \tabularnewline
0.97 & 1.03716752127510 & 0.0174324825582754 \tabularnewline
0.98 & 1.04792093714661 & 0.0223196274919401 \tabularnewline
0.99 & 1.05885312351407 & 0.0295050170940449 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19507&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]0.690357482714776[/C][C]0.0257493744938832[/C][/ROW]
[ROW][C]0.02[/C][C]0.70068512916742[/C][C]0.021734532514729[/C][/ROW]
[ROW][C]0.03[/C][C]0.711203661788887[/C][C]0.0181409407214812[/C][/ROW]
[ROW][C]0.04[/C][C]0.720238984362129[/C][C]0.0152701505942662[/C][/ROW]
[ROW][C]0.05[/C][C]0.727440881301288[/C][C]0.0130169628370724[/C][/ROW]
[ROW][C]0.06[/C][C]0.733099921195562[/C][C]0.0113755336274530[/C][/ROW]
[ROW][C]0.07[/C][C]0.737659335271591[/C][C]0.0104102672587416[/C][/ROW]
[ROW][C]0.08[/C][C]0.741512738285337[/C][C]0.0100957980377989[/C][/ROW]
[ROW][C]0.09[/C][C]0.744955141471747[/C][C]0.0102701844619835[/C][/ROW]
[ROW][C]0.1[/C][C]0.748186428470322[/C][C]0.0107193845356072[/C][/ROW]
[ROW][C]0.11[/C][C]0.751327910238762[/C][C]0.0112601657760742[/C][/ROW]
[ROW][C]0.12[/C][C]0.754441805165771[/C][C]0.0117752995862039[/C][/ROW]
[ROW][C]0.13[/C][C]0.757550632478336[/C][C]0.0122043778163178[/C][/ROW]
[ROW][C]0.14[/C][C]0.760654299482061[/C][C]0.0125298799458765[/C][/ROW]
[ROW][C]0.15[/C][C]0.763743305349018[/C][C]0.0127639590477691[/C][/ROW]
[ROW][C]0.16[/C][C]0.766807549471825[/C][C]0.012937217037477[/C][/ROW]
[ROW][C]0.17[/C][C]0.769841109654033[/C][C]0.0130890257027324[/C][/ROW]
[ROW][C]0.18[/C][C]0.772843795487366[/C][C]0.0132543391742880[/C][/ROW]
[ROW][C]0.19[/C][C]0.775820396038735[/C][C]0.0134562040704081[/C][/ROW]
[ROW][C]0.2[/C][C]0.778778507179927[/C][C]0.0137014134900641[/C][/ROW]
[ROW][C]0.21[/C][C]0.781725742448038[/C][C]0.0139761760838112[/C][/ROW]
[ROW][C]0.22[/C][C]0.784667022729394[/C][C]0.014254906668871[/C][/ROW]
[ROW][C]0.23[/C][C]0.78760249485953[/C][C]0.0145009100196785[/C][/ROW]
[ROW][C]0.24[/C][C]0.790526445174728[/C][C]0.0146742460172555[/C][/ROW]
[ROW][C]0.25[/C][C]0.79342736633013[/C][C]0.0147425838993809[/C][/ROW]
[ROW][C]0.26[/C][C]0.796289130369927[/C][C]0.0146806157352704[/C][/ROW]
[ROW][C]0.27[/C][C]0.799093044915688[/C][C]0.0144813558459163[/C][/ROW]
[ROW][C]0.28[/C][C]0.801820443379197[/C][C]0.0141518828509622[/C][/ROW]
[ROW][C]0.29[/C][C]0.804455396833148[/C][C]0.0137166291746623[/C][/ROW]
[ROW][C]0.3[/C][C]0.806987138197704[/C][C]0.0132144865802642[/C][/ROW]
[ROW][C]0.31[/C][C]0.80941185345846[/C][C]0.0126954985073174[/C][/ROW]
[ROW][C]0.32[/C][C]0.81173360609177[/C][C]0.0122127590106538[/C][/ROW]
[ROW][C]0.33[/C][C]0.813964299448308[/C][C]0.0118197530780406[/C][/ROW]
[ROW][C]0.34[/C][C]0.8161227239037[/C][C]0.0115605302029674[/C][/ROW]
[ROW][C]0.35[/C][C]0.81823285857116[/C][C]0.0114653295564385[/C][/ROW]
[ROW][C]0.36[/C][C]0.820321684090319[/C][C]0.0115477666075857[/C][/ROW]
[ROW][C]0.37[/C][C]0.822416804439243[/C][C]0.0118008984086779[/C][/ROW]
[ROW][C]0.38[/C][C]0.824544171615445[/C][C]0.0122015373336842[/C][/ROW]
[ROW][C]0.39[/C][C]0.82672616441347[/C][C]0.0127161972913673[/C][/ROW]
[ROW][C]0.4[/C][C]0.82898020289551[/C][C]0.0133047190084541[/C][/ROW]
[ROW][C]0.41[/C][C]0.831317996538426[/C][C]0.0139270942039374[/C][/ROW]
[ROW][C]0.42[/C][C]0.833745438716369[/C][C]0.0145468382768111[/C][/ROW]
[ROW][C]0.43[/C][C]0.836263083373618[/C][C]0.0151326313986313[/C][/ROW]
[ROW][C]0.44[/C][C]0.838867079192296[/C][C]0.0156627183912659[/C][/ROW]
[ROW][C]0.45[/C][C]0.84155039742744[/C][C]0.0161249314936152[/C][/ROW]
[ROW][C]0.46[/C][C]0.844304174362637[/C][C]0.0165157734928721[/C][/ROW]
[ROW][C]0.47[/C][C]0.847118997636254[/C][C]0.0168385143727890[/C][/ROW]
[ROW][C]0.48[/C][C]0.84998599406133[/C][C]0.0171040905359246[/C][/ROW]
[ROW][C]0.49[/C][C]0.852897618808898[/C][C]0.0173246160284153[/C][/ROW]
[ROW][C]0.5[/C][C]0.855848093956657[/C][C]0.0175143229302128[/C][/ROW]
[ROW][C]0.51[/C][C]0.858833490278535[/C][C]0.0176871470530748[/C][/ROW]
[ROW][C]0.52[/C][C]0.861851483348305[/C][C]0.0178499332357475[/C][/ROW]
[ROW][C]0.53[/C][C]0.864900840362953[/C][C]0.0180101805121891[/C][/ROW]
[ROW][C]0.54[/C][C]0.867980708115847[/C][C]0.0181670326317408[/C][/ROW]
[ROW][C]0.55[/C][C]0.871089778812907[/C][C]0.0183152217343903[/C][/ROW]
[ROW][C]0.56[/C][C]0.87422541361965[/C][C]0.0184445154323164[/C][/ROW]
[ROW][C]0.57[/C][C]0.877382807513942[/C][C]0.0185417822082271[/C][/ROW]
[ROW][C]0.58[/C][C]0.880554283805315[/C][C]0.0185853019135757[/C][/ROW]
[ROW][C]0.59[/C][C]0.883728809655969[/C][C]0.0185546256675338[/C][/ROW]
[ROW][C]0.6[/C][C]0.886891819729779[/C][C]0.0184274237550889[/C][/ROW]
[ROW][C]0.61[/C][C]0.890025418291694[/C][C]0.0181815126038245[/C][/ROW]
[ROW][C]0.62[/C][C]0.893108998154259[/C][C]0.0178003184355686[/C][/ROW]
[ROW][C]0.63[/C][C]0.896120270434424[/C][C]0.0172750557804465[/C][/ROW]
[ROW][C]0.64[/C][C]0.899036650401718[/C][C]0.0166064564640451[/C][/ROW]
[ROW][C]0.65[/C][C]0.901836903875916[/C][C]0.0158060377358362[/C][/ROW]
[ROW][C]0.66[/C][C]0.904502937773581[/C][C]0.0148957772281856[/C][/ROW]
[ROW][C]0.67[/C][C]0.907021624754143[/C][C]0.0139084949432564[/C][/ROW]
[ROW][C]0.68[/C][C]0.909386583585863[/C][C]0.0128841617006653[/C][/ROW]
[ROW][C]0.69[/C][C]0.911599880763044[/C][C]0.0118732217969068[/C][/ROW]
[ROW][C]0.7[/C][C]0.913673652222255[/C][C]0.0109276070046339[/C][/ROW]
[ROW][C]0.71[/C][C]0.915631639501427[/C][C]0.0101118222886584[/C][/ROW]
[ROW][C]0.72[/C][C]0.917510569562253[/C][C]0.0094955906524746[/C][/ROW]
[ROW][C]0.73[/C][C]0.919361174145407[/C][C]0.00916083841819465[/C][/ROW]
[ROW][C]0.74[/C][C]0.921248460748415[/C][C]0.00919703433683982[/C][/ROW]
[ROW][C]0.75[/C][C]0.923250662560954[/C][C]0.00968438506916855[/C][/ROW]
[ROW][C]0.76[/C][C]0.925456188327402[/C][C]0.0106742913471305[/C][/ROW]
[ROW][C]0.77[/C][C]0.92795796096789[/C][C]0.0121649595096515[/C][/ROW]
[ROW][C]0.78[/C][C]0.930844861396748[/C][C]0.0140954115679621[/C][/ROW]
[ROW][C]0.79[/C][C]0.93419061913902[/C][C]0.0163422947029298[/C][/ROW]
[ROW][C]0.8[/C][C]0.938041365062538[/C][C]0.0187253547553665[/C][/ROW]
[ROW][C]0.81[/C][C]0.942404021827796[/C][C]0.0210153504000639[/C][/ROW]
[ROW][C]0.82[/C][C]0.947238482469565[/C][C]0.0229581518854807[/C][/ROW]
[ROW][C]0.83[/C][C]0.952456777391977[/C][C]0.0243101462873557[/C][/ROW]
[ROW][C]0.84[/C][C]0.957931828709338[/C][C]0.024886670194248[/C][/ROW]
[ROW][C]0.85[/C][C]0.963516729584666[/C][C]0.0246046329518060[/C][/ROW]
[ROW][C]0.86[/C][C]0.969072784681537[/C][C]0.0235246397989794[/C][/ROW]
[ROW][C]0.87[/C][C]0.974501165121778[/C][C]0.0218629790162297[/C][/ROW]
[ROW][C]0.88[/C][C]0.979769782422714[/C][C]0.0199805985887911[/C][/ROW]
[ROW][C]0.89[/C][C]0.98492524633518[/C][C]0.0183298783311204[/C][/ROW]
[ROW][C]0.9[/C][C]0.990081459544857[/C][C]0.0173304254644116[/C][/ROW]
[ROW][C]0.91[/C][C]0.99538356913027[/C][C]0.0171531920939682[/C][/ROW]
[ROW][C]0.92[/C][C]1.00095959899142[/C][C]0.0175490373660681[/C][/ROW]
[ROW][C]0.93[/C][C]1.0068894609163[/C][C]0.0179383444747054[/C][/ROW]
[ROW][C]0.94[/C][C]1.01323174122042[/C][C]0.0177538738190025[/C][/ROW]
[ROW][C]0.95[/C][C]1.02012991723537[/C][C]0.0168765909408637[/C][/ROW]
[ROW][C]0.96[/C][C]1.02793933363825[/C][C]0.0161209786732948[/C][/ROW]
[ROW][C]0.97[/C][C]1.03716752127510[/C][C]0.0174324825582754[/C][/ROW]
[ROW][C]0.98[/C][C]1.04792093714661[/C][C]0.0223196274919401[/C][/ROW]
[ROW][C]0.99[/C][C]1.05885312351407[/C][C]0.0295050170940449[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19507&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19507&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
0.010.6903574827147760.0257493744938832
0.020.700685129167420.021734532514729
0.030.7112036617888870.0181409407214812
0.040.7202389843621290.0152701505942662
0.050.7274408813012880.0130169628370724
0.060.7330999211955620.0113755336274530
0.070.7376593352715910.0104102672587416
0.080.7415127382853370.0100957980377989
0.090.7449551414717470.0102701844619835
0.10.7481864284703220.0107193845356072
0.110.7513279102387620.0112601657760742
0.120.7544418051657710.0117752995862039
0.130.7575506324783360.0122043778163178
0.140.7606542994820610.0125298799458765
0.150.7637433053490180.0127639590477691
0.160.7668075494718250.012937217037477
0.170.7698411096540330.0130890257027324
0.180.7728437954873660.0132543391742880
0.190.7758203960387350.0134562040704081
0.20.7787785071799270.0137014134900641
0.210.7817257424480380.0139761760838112
0.220.7846670227293940.014254906668871
0.230.787602494859530.0145009100196785
0.240.7905264451747280.0146742460172555
0.250.793427366330130.0147425838993809
0.260.7962891303699270.0146806157352704
0.270.7990930449156880.0144813558459163
0.280.8018204433791970.0141518828509622
0.290.8044553968331480.0137166291746623
0.30.8069871381977040.0132144865802642
0.310.809411853458460.0126954985073174
0.320.811733606091770.0122127590106538
0.330.8139642994483080.0118197530780406
0.340.81612272390370.0115605302029674
0.350.818232858571160.0114653295564385
0.360.8203216840903190.0115477666075857
0.370.8224168044392430.0118008984086779
0.380.8245441716154450.0122015373336842
0.390.826726164413470.0127161972913673
0.40.828980202895510.0133047190084541
0.410.8313179965384260.0139270942039374
0.420.8337454387163690.0145468382768111
0.430.8362630833736180.0151326313986313
0.440.8388670791922960.0156627183912659
0.450.841550397427440.0161249314936152
0.460.8443041743626370.0165157734928721
0.470.8471189976362540.0168385143727890
0.480.849985994061330.0171040905359246
0.490.8528976188088980.0173246160284153
0.50.8558480939566570.0175143229302128
0.510.8588334902785350.0176871470530748
0.520.8618514833483050.0178499332357475
0.530.8649008403629530.0180101805121891
0.540.8679807081158470.0181670326317408
0.550.8710897788129070.0183152217343903
0.560.874225413619650.0184445154323164
0.570.8773828075139420.0185417822082271
0.580.8805542838053150.0185853019135757
0.590.8837288096559690.0185546256675338
0.60.8868918197297790.0184274237550889
0.610.8900254182916940.0181815126038245
0.620.8931089981542590.0178003184355686
0.630.8961202704344240.0172750557804465
0.640.8990366504017180.0166064564640451
0.650.9018369038759160.0158060377358362
0.660.9045029377735810.0148957772281856
0.670.9070216247541430.0139084949432564
0.680.9093865835858630.0128841617006653
0.690.9115998807630440.0118732217969068
0.70.9136736522222550.0109276070046339
0.710.9156316395014270.0101118222886584
0.720.9175105695622530.0094955906524746
0.730.9193611741454070.00916083841819465
0.740.9212484607484150.00919703433683982
0.750.9232506625609540.00968438506916855
0.760.9254561883274020.0106742913471305
0.770.927957960967890.0121649595096515
0.780.9308448613967480.0140954115679621
0.790.934190619139020.0163422947029298
0.80.9380413650625380.0187253547553665
0.810.9424040218277960.0210153504000639
0.820.9472384824695650.0229581518854807
0.830.9524567773919770.0243101462873557
0.840.9579318287093380.024886670194248
0.850.9635167295846660.0246046329518060
0.860.9690727846815370.0235246397989794
0.870.9745011651217780.0218629790162297
0.880.9797697824227140.0199805985887911
0.890.984925246335180.0183298783311204
0.90.9900814595448570.0173304254644116
0.910.995383569130270.0171531920939682
0.921.000959598991420.0175490373660681
0.931.00688946091630.0179383444747054
0.941.013231741220420.0177538738190025
0.951.020129917235370.0168765909408637
0.961.027939333638250.0161209786732948
0.971.037167521275100.0174324825582754
0.981.047920937146610.0223196274919401
0.991.058853123514070.0295050170940449


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')