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Description of Statistical Computation

Author's title

Harrel-Davis percentielen gemiddelde conumptieprijs blue jeans - Raf Pleysi...

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationSun, 02 Mar 2008 08:08:31 -0700
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/Mar/02/t1204470562npairfcqsj30ari.htm/, Retrieved Mon, 06 May 2024 20:32:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=9561, Retrieved Mon, 06 May 2024 20:32:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact165

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] [Harrel-Davis perc...] [2008-03-02 15:08:31] [6461440fa2a8ea0ebac8d11789a457eb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
48,04
48,06
48,04
48,09
48,12
48,16
48,16
48,16
48,08
48,13
48,16
48,15
48,15
48,15
48,27
48,47
48,51
48,53
48,53
48,53
48,68
48,64
48,67
48,66
48,66
48,67
48,71
48,96
49,01
49,04
49,04
49,04
49,06
49,13
49,19
49,26
49,26
49,26
49,29
49,43
49,43
49,45
49,45
49,46
49,57
49,68
49,71
49,7
49,7
49,8
49,84
50,09
50,2
50,16
50,16
50,29
50,36
51,02
51,03
51,04

Tables (Output of Computation)





Summary of compuational 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 compuational 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=9561&T=0

[TABLE]
[ROW][C]Summary of compuational 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=9561&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=9561&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 compuational 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
0.0148.04165773458720.0052930278546921
0.0248.04558904555040.0123299095986165
0.0348.05187713285070.0186398735877364
0.0448.06004245015340.0232674568495438
0.0548.0693906735290.0263351074434789
0.0648.07928491824920.0282935598119616
0.0748.08925134570750.0293768094800573
0.0848.09897127167590.0296544542158363
0.0948.10824195342990.0291951261392497
0.148.1169541392630.0282347496012743
0.1148.12509486763070.0271892319088986
0.1248.13276318293040.0267241579754858
0.1348.14018312665020.0276619678349142
0.1448.14770333285280.0308431844153915
0.1548.1557787424670.036805618440911
0.1648.16493459414840.0458314320306110
0.1748.17571594736560.0576755347685583
0.1848.18862830627180.0718777596353545
0.1948.20407680696850.0877065172292464
0.248.22231263398820.104169850553952
0.2148.24339525021080.120254010725292
0.2248.26717722071350.134721033999505
0.2348.29331495589080.146645963463509
0.2448.32130425174620.155271316366601
0.2548.35053512194440.160275697500749
0.2648.38035719288360.161587391714803
0.2748.41014563661200.159651813861407
0.2848.43935844763780.155060365816746
0.2948.46757843437030.148620620881153
0.348.4945367754240.141246434103999
0.3148.52011843244710.133814423491528
0.3248.54435232460260.127097006673656
0.3348.56739053375920.121705621292915
0.3448.58948093029040.118135887161811
0.3548.61093683950370.116711792210392
0.3648.63210623155070.117514621560220
0.3748.65334191079850.120564735592366
0.3848.67497362218420.125545539545716
0.3948.69728295055190.132144356224200
0.448.72048220453740.139660047163159
0.4148.74469885231320.147628311843853
0.4248.76996720152530.155195932703331
0.4348.79622867799390.161903205389958
0.4448.82334121419340.167166794778003
0.4548.85109704635950.170640442347469
0.4648.87924691055340.172166970785764
0.4748.90752754677250.171807953796022
0.4848.9356888461770.169729076041257
0.4948.96351706691370.166370153019186
0.548.99085129197980.162171146341858
0.5149.01759154232490.157581930299100
0.5249.04369841360360.1530523885573
0.5349.06918546400210.148898505729216
0.5449.09410657657380.145311686396380
0.5549.11854099317810.142383214687374
0.5649.14257864516630.140096697102179
0.5749.16630789051960.138330240881576
0.5849.18980699170310.136917921773375
0.5949.21313983669130.135753242318178
0.649.23635568300540.13475510605597
0.6149.25949218197890.133833982647740
0.6249.28258062886720.132928961828841
0.6349.30565224069140.132065428998032
0.6449.32874423403170.131324032557427
0.6549.35190453647230.130761236476772
0.6649.37519414596340.130487380770609
0.6749.39868651662790.130579014260492
0.6849.42246395236170.131148747731573
0.6949.44661181384380.132180424399354
0.749.47121225087920.133660350828534
0.7149.49633988959490.135390044408979
0.7249.52206208230340.137289545798934
0.7349.54844564799810.139188139863212
0.7449.57557035275140.141058876960053
0.7549.60354687462260.143081469147822
0.7649.63253422259860.145513607802889
0.7749.66274942700130.148765448345842
0.7849.69446183913230.153347548603578
0.7949.72796647308130.159506334184579
0.849.76353588463940.167057018534382
0.8149.80135767289140.175530676571435
0.8249.84147339147420.183837669186454
0.8349.8837422004430.190694317674096
0.8449.92785628211670.194905114615957
0.8549.97343233231090.195637720367272
0.8650.02019228721680.192918735044503
0.8750.06822520901440.187980156064933
0.8850.11828924155710.183600825821565
0.8950.17206670319910.184113797517421
0.950.23223071412730.194652579092855
0.9150.30213747678640.218943957546727
0.9250.38497087313110.256099421677848
0.9350.48230720896290.298589828943922
0.9450.5923931586790.332308535626227
0.9550.70888322910330.339674291105377
0.9650.82109466188520.306631601563360
0.9750.91655538424130.232501501301978
0.9850.98544047033560.136428376047274
0.9951.02483352595390.0519220720186393

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 48.0416577345872 & 0.0052930278546921 \tabularnewline
0.02 & 48.0455890455504 & 0.0123299095986165 \tabularnewline
0.03 & 48.0518771328507 & 0.0186398735877364 \tabularnewline
0.04 & 48.0600424501534 & 0.0232674568495438 \tabularnewline
0.05 & 48.069390673529 & 0.0263351074434789 \tabularnewline
0.06 & 48.0792849182492 & 0.0282935598119616 \tabularnewline
0.07 & 48.0892513457075 & 0.0293768094800573 \tabularnewline
0.08 & 48.0989712716759 & 0.0296544542158363 \tabularnewline
0.09 & 48.1082419534299 & 0.0291951261392497 \tabularnewline
0.1 & 48.116954139263 & 0.0282347496012743 \tabularnewline
0.11 & 48.1250948676307 & 0.0271892319088986 \tabularnewline
0.12 & 48.1327631829304 & 0.0267241579754858 \tabularnewline
0.13 & 48.1401831266502 & 0.0276619678349142 \tabularnewline
0.14 & 48.1477033328528 & 0.0308431844153915 \tabularnewline
0.15 & 48.155778742467 & 0.036805618440911 \tabularnewline
0.16 & 48.1649345941484 & 0.0458314320306110 \tabularnewline
0.17 & 48.1757159473656 & 0.0576755347685583 \tabularnewline
0.18 & 48.1886283062718 & 0.0718777596353545 \tabularnewline
0.19 & 48.2040768069685 & 0.0877065172292464 \tabularnewline
0.2 & 48.2223126339882 & 0.104169850553952 \tabularnewline
0.21 & 48.2433952502108 & 0.120254010725292 \tabularnewline
0.22 & 48.2671772207135 & 0.134721033999505 \tabularnewline
0.23 & 48.2933149558908 & 0.146645963463509 \tabularnewline
0.24 & 48.3213042517462 & 0.155271316366601 \tabularnewline
0.25 & 48.3505351219444 & 0.160275697500749 \tabularnewline
0.26 & 48.3803571928836 & 0.161587391714803 \tabularnewline
0.27 & 48.4101456366120 & 0.159651813861407 \tabularnewline
0.28 & 48.4393584476378 & 0.155060365816746 \tabularnewline
0.29 & 48.4675784343703 & 0.148620620881153 \tabularnewline
0.3 & 48.494536775424 & 0.141246434103999 \tabularnewline
0.31 & 48.5201184324471 & 0.133814423491528 \tabularnewline
0.32 & 48.5443523246026 & 0.127097006673656 \tabularnewline
0.33 & 48.5673905337592 & 0.121705621292915 \tabularnewline
0.34 & 48.5894809302904 & 0.118135887161811 \tabularnewline
0.35 & 48.6109368395037 & 0.116711792210392 \tabularnewline
0.36 & 48.6321062315507 & 0.117514621560220 \tabularnewline
0.37 & 48.6533419107985 & 0.120564735592366 \tabularnewline
0.38 & 48.6749736221842 & 0.125545539545716 \tabularnewline
0.39 & 48.6972829505519 & 0.132144356224200 \tabularnewline
0.4 & 48.7204822045374 & 0.139660047163159 \tabularnewline
0.41 & 48.7446988523132 & 0.147628311843853 \tabularnewline
0.42 & 48.7699672015253 & 0.155195932703331 \tabularnewline
0.43 & 48.7962286779939 & 0.161903205389958 \tabularnewline
0.44 & 48.8233412141934 & 0.167166794778003 \tabularnewline
0.45 & 48.8510970463595 & 0.170640442347469 \tabularnewline
0.46 & 48.8792469105534 & 0.172166970785764 \tabularnewline
0.47 & 48.9075275467725 & 0.171807953796022 \tabularnewline
0.48 & 48.935688846177 & 0.169729076041257 \tabularnewline
0.49 & 48.9635170669137 & 0.166370153019186 \tabularnewline
0.5 & 48.9908512919798 & 0.162171146341858 \tabularnewline
0.51 & 49.0175915423249 & 0.157581930299100 \tabularnewline
0.52 & 49.0436984136036 & 0.1530523885573 \tabularnewline
0.53 & 49.0691854640021 & 0.148898505729216 \tabularnewline
0.54 & 49.0941065765738 & 0.145311686396380 \tabularnewline
0.55 & 49.1185409931781 & 0.142383214687374 \tabularnewline
0.56 & 49.1425786451663 & 0.140096697102179 \tabularnewline
0.57 & 49.1663078905196 & 0.138330240881576 \tabularnewline
0.58 & 49.1898069917031 & 0.136917921773375 \tabularnewline
0.59 & 49.2131398366913 & 0.135753242318178 \tabularnewline
0.6 & 49.2363556830054 & 0.13475510605597 \tabularnewline
0.61 & 49.2594921819789 & 0.133833982647740 \tabularnewline
0.62 & 49.2825806288672 & 0.132928961828841 \tabularnewline
0.63 & 49.3056522406914 & 0.132065428998032 \tabularnewline
0.64 & 49.3287442340317 & 0.131324032557427 \tabularnewline
0.65 & 49.3519045364723 & 0.130761236476772 \tabularnewline
0.66 & 49.3751941459634 & 0.130487380770609 \tabularnewline
0.67 & 49.3986865166279 & 0.130579014260492 \tabularnewline
0.68 & 49.4224639523617 & 0.131148747731573 \tabularnewline
0.69 & 49.4466118138438 & 0.132180424399354 \tabularnewline
0.7 & 49.4712122508792 & 0.133660350828534 \tabularnewline
0.71 & 49.4963398895949 & 0.135390044408979 \tabularnewline
0.72 & 49.5220620823034 & 0.137289545798934 \tabularnewline
0.73 & 49.5484456479981 & 0.139188139863212 \tabularnewline
0.74 & 49.5755703527514 & 0.141058876960053 \tabularnewline
0.75 & 49.6035468746226 & 0.143081469147822 \tabularnewline
0.76 & 49.6325342225986 & 0.145513607802889 \tabularnewline
0.77 & 49.6627494270013 & 0.148765448345842 \tabularnewline
0.78 & 49.6944618391323 & 0.153347548603578 \tabularnewline
0.79 & 49.7279664730813 & 0.159506334184579 \tabularnewline
0.8 & 49.7635358846394 & 0.167057018534382 \tabularnewline
0.81 & 49.8013576728914 & 0.175530676571435 \tabularnewline
0.82 & 49.8414733914742 & 0.183837669186454 \tabularnewline
0.83 & 49.883742200443 & 0.190694317674096 \tabularnewline
0.84 & 49.9278562821167 & 0.194905114615957 \tabularnewline
0.85 & 49.9734323323109 & 0.195637720367272 \tabularnewline
0.86 & 50.0201922872168 & 0.192918735044503 \tabularnewline
0.87 & 50.0682252090144 & 0.187980156064933 \tabularnewline
0.88 & 50.1182892415571 & 0.183600825821565 \tabularnewline
0.89 & 50.1720667031991 & 0.184113797517421 \tabularnewline
0.9 & 50.2322307141273 & 0.194652579092855 \tabularnewline
0.91 & 50.3021374767864 & 0.218943957546727 \tabularnewline
0.92 & 50.3849708731311 & 0.256099421677848 \tabularnewline
0.93 & 50.4823072089629 & 0.298589828943922 \tabularnewline
0.94 & 50.592393158679 & 0.332308535626227 \tabularnewline
0.95 & 50.7088832291033 & 0.339674291105377 \tabularnewline
0.96 & 50.8210946618852 & 0.306631601563360 \tabularnewline
0.97 & 50.9165553842413 & 0.232501501301978 \tabularnewline
0.98 & 50.9854404703356 & 0.136428376047274 \tabularnewline
0.99 & 51.0248335259539 & 0.0519220720186393 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=9561&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]48.0416577345872[/C][C]0.0052930278546921[/C][/ROW]
[ROW][C]0.02[/C][C]48.0455890455504[/C][C]0.0123299095986165[/C][/ROW]
[ROW][C]0.03[/C][C]48.0518771328507[/C][C]0.0186398735877364[/C][/ROW]
[ROW][C]0.04[/C][C]48.0600424501534[/C][C]0.0232674568495438[/C][/ROW]
[ROW][C]0.05[/C][C]48.069390673529[/C][C]0.0263351074434789[/C][/ROW]
[ROW][C]0.06[/C][C]48.0792849182492[/C][C]0.0282935598119616[/C][/ROW]
[ROW][C]0.07[/C][C]48.0892513457075[/C][C]0.0293768094800573[/C][/ROW]
[ROW][C]0.08[/C][C]48.0989712716759[/C][C]0.0296544542158363[/C][/ROW]
[ROW][C]0.09[/C][C]48.1082419534299[/C][C]0.0291951261392497[/C][/ROW]
[ROW][C]0.1[/C][C]48.116954139263[/C][C]0.0282347496012743[/C][/ROW]
[ROW][C]0.11[/C][C]48.1250948676307[/C][C]0.0271892319088986[/C][/ROW]
[ROW][C]0.12[/C][C]48.1327631829304[/C][C]0.0267241579754858[/C][/ROW]
[ROW][C]0.13[/C][C]48.1401831266502[/C][C]0.0276619678349142[/C][/ROW]
[ROW][C]0.14[/C][C]48.1477033328528[/C][C]0.0308431844153915[/C][/ROW]
[ROW][C]0.15[/C][C]48.155778742467[/C][C]0.036805618440911[/C][/ROW]
[ROW][C]0.16[/C][C]48.1649345941484[/C][C]0.0458314320306110[/C][/ROW]
[ROW][C]0.17[/C][C]48.1757159473656[/C][C]0.0576755347685583[/C][/ROW]
[ROW][C]0.18[/C][C]48.1886283062718[/C][C]0.0718777596353545[/C][/ROW]
[ROW][C]0.19[/C][C]48.2040768069685[/C][C]0.0877065172292464[/C][/ROW]
[ROW][C]0.2[/C][C]48.2223126339882[/C][C]0.104169850553952[/C][/ROW]
[ROW][C]0.21[/C][C]48.2433952502108[/C][C]0.120254010725292[/C][/ROW]
[ROW][C]0.22[/C][C]48.2671772207135[/C][C]0.134721033999505[/C][/ROW]
[ROW][C]0.23[/C][C]48.2933149558908[/C][C]0.146645963463509[/C][/ROW]
[ROW][C]0.24[/C][C]48.3213042517462[/C][C]0.155271316366601[/C][/ROW]
[ROW][C]0.25[/C][C]48.3505351219444[/C][C]0.160275697500749[/C][/ROW]
[ROW][C]0.26[/C][C]48.3803571928836[/C][C]0.161587391714803[/C][/ROW]
[ROW][C]0.27[/C][C]48.4101456366120[/C][C]0.159651813861407[/C][/ROW]
[ROW][C]0.28[/C][C]48.4393584476378[/C][C]0.155060365816746[/C][/ROW]
[ROW][C]0.29[/C][C]48.4675784343703[/C][C]0.148620620881153[/C][/ROW]
[ROW][C]0.3[/C][C]48.494536775424[/C][C]0.141246434103999[/C][/ROW]
[ROW][C]0.31[/C][C]48.5201184324471[/C][C]0.133814423491528[/C][/ROW]
[ROW][C]0.32[/C][C]48.5443523246026[/C][C]0.127097006673656[/C][/ROW]
[ROW][C]0.33[/C][C]48.5673905337592[/C][C]0.121705621292915[/C][/ROW]
[ROW][C]0.34[/C][C]48.5894809302904[/C][C]0.118135887161811[/C][/ROW]
[ROW][C]0.35[/C][C]48.6109368395037[/C][C]0.116711792210392[/C][/ROW]
[ROW][C]0.36[/C][C]48.6321062315507[/C][C]0.117514621560220[/C][/ROW]
[ROW][C]0.37[/C][C]48.6533419107985[/C][C]0.120564735592366[/C][/ROW]
[ROW][C]0.38[/C][C]48.6749736221842[/C][C]0.125545539545716[/C][/ROW]
[ROW][C]0.39[/C][C]48.6972829505519[/C][C]0.132144356224200[/C][/ROW]
[ROW][C]0.4[/C][C]48.7204822045374[/C][C]0.139660047163159[/C][/ROW]
[ROW][C]0.41[/C][C]48.7446988523132[/C][C]0.147628311843853[/C][/ROW]
[ROW][C]0.42[/C][C]48.7699672015253[/C][C]0.155195932703331[/C][/ROW]
[ROW][C]0.43[/C][C]48.7962286779939[/C][C]0.161903205389958[/C][/ROW]
[ROW][C]0.44[/C][C]48.8233412141934[/C][C]0.167166794778003[/C][/ROW]
[ROW][C]0.45[/C][C]48.8510970463595[/C][C]0.170640442347469[/C][/ROW]
[ROW][C]0.46[/C][C]48.8792469105534[/C][C]0.172166970785764[/C][/ROW]
[ROW][C]0.47[/C][C]48.9075275467725[/C][C]0.171807953796022[/C][/ROW]
[ROW][C]0.48[/C][C]48.935688846177[/C][C]0.169729076041257[/C][/ROW]
[ROW][C]0.49[/C][C]48.9635170669137[/C][C]0.166370153019186[/C][/ROW]
[ROW][C]0.5[/C][C]48.9908512919798[/C][C]0.162171146341858[/C][/ROW]
[ROW][C]0.51[/C][C]49.0175915423249[/C][C]0.157581930299100[/C][/ROW]
[ROW][C]0.52[/C][C]49.0436984136036[/C][C]0.1530523885573[/C][/ROW]
[ROW][C]0.53[/C][C]49.0691854640021[/C][C]0.148898505729216[/C][/ROW]
[ROW][C]0.54[/C][C]49.0941065765738[/C][C]0.145311686396380[/C][/ROW]
[ROW][C]0.55[/C][C]49.1185409931781[/C][C]0.142383214687374[/C][/ROW]
[ROW][C]0.56[/C][C]49.1425786451663[/C][C]0.140096697102179[/C][/ROW]
[ROW][C]0.57[/C][C]49.1663078905196[/C][C]0.138330240881576[/C][/ROW]
[ROW][C]0.58[/C][C]49.1898069917031[/C][C]0.136917921773375[/C][/ROW]
[ROW][C]0.59[/C][C]49.2131398366913[/C][C]0.135753242318178[/C][/ROW]
[ROW][C]0.6[/C][C]49.2363556830054[/C][C]0.13475510605597[/C][/ROW]
[ROW][C]0.61[/C][C]49.2594921819789[/C][C]0.133833982647740[/C][/ROW]
[ROW][C]0.62[/C][C]49.2825806288672[/C][C]0.132928961828841[/C][/ROW]
[ROW][C]0.63[/C][C]49.3056522406914[/C][C]0.132065428998032[/C][/ROW]
[ROW][C]0.64[/C][C]49.3287442340317[/C][C]0.131324032557427[/C][/ROW]
[ROW][C]0.65[/C][C]49.3519045364723[/C][C]0.130761236476772[/C][/ROW]
[ROW][C]0.66[/C][C]49.3751941459634[/C][C]0.130487380770609[/C][/ROW]
[ROW][C]0.67[/C][C]49.3986865166279[/C][C]0.130579014260492[/C][/ROW]
[ROW][C]0.68[/C][C]49.4224639523617[/C][C]0.131148747731573[/C][/ROW]
[ROW][C]0.69[/C][C]49.4466118138438[/C][C]0.132180424399354[/C][/ROW]
[ROW][C]0.7[/C][C]49.4712122508792[/C][C]0.133660350828534[/C][/ROW]
[ROW][C]0.71[/C][C]49.4963398895949[/C][C]0.135390044408979[/C][/ROW]
[ROW][C]0.72[/C][C]49.5220620823034[/C][C]0.137289545798934[/C][/ROW]
[ROW][C]0.73[/C][C]49.5484456479981[/C][C]0.139188139863212[/C][/ROW]
[ROW][C]0.74[/C][C]49.5755703527514[/C][C]0.141058876960053[/C][/ROW]
[ROW][C]0.75[/C][C]49.6035468746226[/C][C]0.143081469147822[/C][/ROW]
[ROW][C]0.76[/C][C]49.6325342225986[/C][C]0.145513607802889[/C][/ROW]
[ROW][C]0.77[/C][C]49.6627494270013[/C][C]0.148765448345842[/C][/ROW]
[ROW][C]0.78[/C][C]49.6944618391323[/C][C]0.153347548603578[/C][/ROW]
[ROW][C]0.79[/C][C]49.7279664730813[/C][C]0.159506334184579[/C][/ROW]
[ROW][C]0.8[/C][C]49.7635358846394[/C][C]0.167057018534382[/C][/ROW]
[ROW][C]0.81[/C][C]49.8013576728914[/C][C]0.175530676571435[/C][/ROW]
[ROW][C]0.82[/C][C]49.8414733914742[/C][C]0.183837669186454[/C][/ROW]
[ROW][C]0.83[/C][C]49.883742200443[/C][C]0.190694317674096[/C][/ROW]
[ROW][C]0.84[/C][C]49.9278562821167[/C][C]0.194905114615957[/C][/ROW]
[ROW][C]0.85[/C][C]49.9734323323109[/C][C]0.195637720367272[/C][/ROW]
[ROW][C]0.86[/C][C]50.0201922872168[/C][C]0.192918735044503[/C][/ROW]
[ROW][C]0.87[/C][C]50.0682252090144[/C][C]0.187980156064933[/C][/ROW]
[ROW][C]0.88[/C][C]50.1182892415571[/C][C]0.183600825821565[/C][/ROW]
[ROW][C]0.89[/C][C]50.1720667031991[/C][C]0.184113797517421[/C][/ROW]
[ROW][C]0.9[/C][C]50.2322307141273[/C][C]0.194652579092855[/C][/ROW]
[ROW][C]0.91[/C][C]50.3021374767864[/C][C]0.218943957546727[/C][/ROW]
[ROW][C]0.92[/C][C]50.3849708731311[/C][C]0.256099421677848[/C][/ROW]
[ROW][C]0.93[/C][C]50.4823072089629[/C][C]0.298589828943922[/C][/ROW]
[ROW][C]0.94[/C][C]50.592393158679[/C][C]0.332308535626227[/C][/ROW]
[ROW][C]0.95[/C][C]50.7088832291033[/C][C]0.339674291105377[/C][/ROW]
[ROW][C]0.96[/C][C]50.8210946618852[/C][C]0.306631601563360[/C][/ROW]
[ROW][C]0.97[/C][C]50.9165553842413[/C][C]0.232501501301978[/C][/ROW]
[ROW][C]0.98[/C][C]50.9854404703356[/C][C]0.136428376047274[/C][/ROW]
[ROW][C]0.99[/C][C]51.0248335259539[/C][C]0.0519220720186393[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=9561&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=9561&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
0.0148.04165773458720.0052930278546921
0.0248.04558904555040.0123299095986165
0.0348.05187713285070.0186398735877364
0.0448.06004245015340.0232674568495438
0.0548.0693906735290.0263351074434789
0.0648.07928491824920.0282935598119616
0.0748.08925134570750.0293768094800573
0.0848.09897127167590.0296544542158363
0.0948.10824195342990.0291951261392497
0.148.1169541392630.0282347496012743
0.1148.12509486763070.0271892319088986
0.1248.13276318293040.0267241579754858
0.1348.14018312665020.0276619678349142
0.1448.14770333285280.0308431844153915
0.1548.1557787424670.036805618440911
0.1648.16493459414840.0458314320306110
0.1748.17571594736560.0576755347685583
0.1848.18862830627180.0718777596353545
0.1948.20407680696850.0877065172292464
0.248.22231263398820.104169850553952
0.2148.24339525021080.120254010725292
0.2248.26717722071350.134721033999505
0.2348.29331495589080.146645963463509
0.2448.32130425174620.155271316366601
0.2548.35053512194440.160275697500749
0.2648.38035719288360.161587391714803
0.2748.41014563661200.159651813861407
0.2848.43935844763780.155060365816746
0.2948.46757843437030.148620620881153
0.348.4945367754240.141246434103999
0.3148.52011843244710.133814423491528
0.3248.54435232460260.127097006673656
0.3348.56739053375920.121705621292915
0.3448.58948093029040.118135887161811
0.3548.61093683950370.116711792210392
0.3648.63210623155070.117514621560220
0.3748.65334191079850.120564735592366
0.3848.67497362218420.125545539545716
0.3948.69728295055190.132144356224200
0.448.72048220453740.139660047163159
0.4148.74469885231320.147628311843853
0.4248.76996720152530.155195932703331
0.4348.79622867799390.161903205389958
0.4448.82334121419340.167166794778003
0.4548.85109704635950.170640442347469
0.4648.87924691055340.172166970785764
0.4748.90752754677250.171807953796022
0.4848.9356888461770.169729076041257
0.4948.96351706691370.166370153019186
0.548.99085129197980.162171146341858
0.5149.01759154232490.157581930299100
0.5249.04369841360360.1530523885573
0.5349.06918546400210.148898505729216
0.5449.09410657657380.145311686396380
0.5549.11854099317810.142383214687374
0.5649.14257864516630.140096697102179
0.5749.16630789051960.138330240881576
0.5849.18980699170310.136917921773375
0.5949.21313983669130.135753242318178
0.649.23635568300540.13475510605597
0.6149.25949218197890.133833982647740
0.6249.28258062886720.132928961828841
0.6349.30565224069140.132065428998032
0.6449.32874423403170.131324032557427
0.6549.35190453647230.130761236476772
0.6649.37519414596340.130487380770609
0.6749.39868651662790.130579014260492
0.6849.42246395236170.131148747731573
0.6949.44661181384380.132180424399354
0.749.47121225087920.133660350828534
0.7149.49633988959490.135390044408979
0.7249.52206208230340.137289545798934
0.7349.54844564799810.139188139863212
0.7449.57557035275140.141058876960053
0.7549.60354687462260.143081469147822
0.7649.63253422259860.145513607802889
0.7749.66274942700130.148765448345842
0.7849.69446183913230.153347548603578
0.7949.72796647308130.159506334184579
0.849.76353588463940.167057018534382
0.8149.80135767289140.175530676571435
0.8249.84147339147420.183837669186454
0.8349.8837422004430.190694317674096
0.8449.92785628211670.194905114615957
0.8549.97343233231090.195637720367272
0.8650.02019228721680.192918735044503
0.8750.06822520901440.187980156064933
0.8850.11828924155710.183600825821565
0.8950.17206670319910.184113797517421
0.950.23223071412730.194652579092855
0.9150.30213747678640.218943957546727
0.9250.38497087313110.256099421677848
0.9350.48230720896290.298589828943922
0.9450.5923931586790.332308535626227
0.9550.70888322910330.339674291105377
0.9650.82109466188520.306631601563360
0.9750.91655538424130.232501501301978
0.9850.98544047033560.136428376047274
0.9951.02483352595390.0519220720186393


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.1 ; par2 = 0.9 ; par3 = 0.1 ;
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')