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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 10:54:35 -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/t1225126520bxtwyf0r332i35k.htm/, Retrieved Sun, 19 May 2024 13:09:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19256, Retrieved Sun, 19 May 2024 13:09:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact159

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 16:54:35] [2ba2a74112fb2c960057a572bf2825d3] [Current]
- RMP       [Central Tendency] [Q6] [2008-10-30 16:40:21] [491a70d26f8c977398d8a0c1c87d3dd4]
- R         [Harrell-Davis Quantiles] [Q5] [2008-10-30 17:32:24] [491a70d26f8c977398d8a0c1c87d3dd4]
- R P       [Harrell-Davis Quantiles] [Q5] [2008-10-30 20:43:25] [491a70d26f8c977398d8a0c1c87d3dd4]
Feedback Forum
2008-11-03 10:48:21 [Dorien Peeters] [reply] 
je had hier 2 manieren om te werken:met Harrel-Davis
: of de R-code vervangen door x-gem en Harrel -davis berekenen (kijken naar 2.5% en 97.5%(0.1802)
De student heeft gewerkt met de 1e manier, namelijk door de Harrel-Davis quantiles te berekenen.Je werkt inderdaad met 95% betrouwbaarheid zoals de student zegt.(95% kans dat tussen 0.70 en 1.04 ligt). je neemt de stepsize van 0.005.
Dit is niet een random component->de gemiddelde voorspelling nog aftrekken van de grenzen.
2008-11-03 17:43:52 [Liese Tormans] [reply] 
Ik heb de derde parameter niet aangepast nl de stepsize had ik op 0,005 moeten zetten. Dit was nodig om van elke staart 2,5% te laten vallen.

Mijn conclusie was wel correct dat het gevonden interval klopt, omdat ik enkel de random component wou hebben, ik heb daarom van de minima en maxima het gemiddelde afgetrokken (ik had ook de mediaan als constante factor kunnen aftrekken dit is afhankelijk of ik rekening wou houden met outliers.)

Rekening houden met outliers: gemiddelde
Geen rekening houden met outliers: mediaan


Ik had deze opgaven nog op een tweede manier kunnen oplossen, deze manier heb ik niet in mijn opgave besproken.

Manier 2:
Ik had de R-code kunnen veranderen door bovenaan x door ‘x <- x –gemiddelde’ toe te voegen

Het voordeel van deze methode is dat ik achteraf geen berekeningen meer moet gaan uitvoeren zoals bij de eerste methode.

Voorbeeld
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Oct/30/t1225399456st3ltl0ddcluo2o.htm , Retrieved Thu, 30 Oct 2008 20:44:19 +0000
2008-11-03 21:56:32 [2b91075c702c6e89854c34747e80ec72] [reply] 
Je hebt dit goed opgelost a.d.h.v. de Harrel-Davis Quantiles, enkel had je inderdaad de stepsize van de derde parameter moeten veranderen naar 0,005 maar dit had je zelf eerder al vermeld.

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'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=19256&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=19256&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19256&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
0.010.6903574823081820.0257493744938832
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=19256&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=19256&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19256&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')