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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationMon, 09 Feb 2015 13:43:57 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Feb/09/t1423489532jo09juqdunzyefa.htm/, Retrieved Sat, 18 May 2024 07:09:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=276890, Retrieved Sat, 18 May 2024 07:09:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact65

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] [] [2015-02-09 13:43:57] [679411f6187277139d0a9a0a87b165a8] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
96,01
96,39
97,16
97,46
97,6
97,02
96,95
97,23
98
98,04
97,76
96,99
97,44
98
98,84
98,98
98,92
98,63
98,52
98,97
99,74
99,68
99,45
98,97
98,68
99,06
99,84
100,3
100,38
100,02
99,83
100,36
100,74
100,49
100,33
99,96
100,08
100,54
101,63
102,12
102,19
101,77
101,29
101,47
102,07
102,11
102,26
101,83
102,11
102,8
103,82
104,2
104,57
104,38
104,54
104,74
105,19
104,95
104,57
103,81
104,08
104,81
105,86
106,1
106,24
105,87
104,74
105,03
105,59
105,69
105,58
104,96
104,93
105,68
106,93
107,29
107,25
106,74
106,44
106,6
107,26
107,35
107,22
106,99
107
107,74
109,02
109,54
109,71
109,18
109,23
109,38
110,17
110,15
110,01
109,54
109,52
110,35
111,61
112,06
111,9
111,36
112,09
112,24
112,7
113,36
112,9
112,74
112,77
113,66
114,87
114,97
115
114,57
115,54
115,39
115,46
115,13
114,56
114,62

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=276890&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=276890&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=276890&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 time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0196.29078630165880.399156303237045
0.0296.65143505360210.335751652702446
0.0396.91128337817170.236897800829866
0.0497.08363322856050.216040362897854
0.0597.22369184917020.247855764604369
0.0697.36268525460080.290243192073705
0.0797.50979123311230.332138666889447
0.0897.66566223049070.372121551661265
0.0997.82882661165590.407723502245206
0.197.99679635049110.434807677761501
0.1198.16600023970440.449210411703064
0.1298.33222806642570.449200593079359
0.1398.4917026088650.43748383887036
0.1498.64227961336940.421477354516654
0.1598.78412241502420.409713093887138
0.1698.91944218898070.408745578666697
0.1799.05141148878250.41845712060677
0.1899.18280749934920.434450059426321
0.1999.31503701939680.449761258018703
0.299.44792620974480.458884235483641
0.2199.58024102861320.46014898634445
0.2299.71059018268280.456121217623607
0.2399.83828064654160.451583120160242
0.2499.9638178417020.451953252927843
0.25100.0889476284740.462677353134552
0.26100.2163091232680.485620502420175
0.27100.3488552726490.521034208061761
0.28100.4892157521140.565936432096829
0.29100.6391607780770.614830868979458
0.3100.7992954377470.662910222751619
0.31100.9690678324750.705073641379552
0.32101.1470999675980.739142549575835
0.33101.331753960860.76535675354807
0.34101.5217577085180.787555948578058
0.35101.7166738867120.811010202090551
0.36101.9170312741270.84030208361046
0.37102.124044491440.878250864073883
0.38102.3389917466690.922516242524449
0.39102.5624465077120.967793786730722
0.4102.7936193856061.00544572217816
0.41103.0300372944731.02711209501668
0.42103.2676792650741.02628319380987
0.43103.5015427997761.00042259672337
0.44103.7264843297660.951172345084637
0.45103.9381058436610.883821649729066
0.46104.1334652332160.806328142864145
0.47104.3114588331190.728055605282221
0.48104.4728285127950.656878323001139
0.49104.6198448551130.5992115201506
0.5104.7557843815590.5584232838961
0.51104.8843414262580.535098398104587
0.52105.0090988908380.527305549194704
0.53105.1331407090550.531318743221858
0.54105.2588384890080.543714481771018
0.55105.3877992116390.560391342772372
0.56105.5209298997620.578893757173735
0.57105.6585644390170.597241233762763
0.58105.8006077970940.613687494844368
0.59105.9466781285860.627586545865625
0.6106.0962559310430.638684012575593
0.61106.2488665553480.647069918803304
0.62106.4043154989770.654160617903777
0.63106.5629617384450.662628910643819
0.64106.7259632717460.67685372564056
0.65106.8953844705030.70103240724841
0.66107.0740460842710.73871181211258
0.67107.2650481922080.790742799484965
0.68107.471005111770.852575720277025
0.69107.6931696622190.916506350335288
0.7107.9307355256510.971929682985506
0.71108.1806271467761.00833420193224
0.72108.4379781015471.01931687333051
0.73108.6972759565871.00433259154929
0.74108.9538884540870.969918905623472
0.75109.2054898596920.928405730418813
0.76109.4528702839020.894482177448331
0.77109.6997685023210.880565072028015
0.78109.9516788768530.891756016951447
0.79110.2139459547460.92337707923758
0.8110.4897533947830.96246424678658
0.81110.778725765380.992612880960105
0.82111.0767255300050.999828818164278
0.83111.3770558910210.97737702062363
0.84111.6727863585240.928293767064873
0.85111.9594811073450.865125483817754
0.86112.2373761024830.806294840814197
0.87112.5120526431380.770316330075664
0.88112.7928784990250.767485857766081
0.89113.0890482933030.792347196225135
0.9113.4041707349750.820756753718741
0.91113.7318448717910.819131397480408
0.92114.055426302270.762004278197944
0.93114.3537205083550.648109683162622
0.94114.6107126560830.503992685194233
0.95114.824103347950.370652314535769
0.96115.00657319250.28229417872722
0.97115.1755627363080.239366506519617
0.98115.3353059284380.193816282372924
0.99115.4681039010140.117480271901807

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 96.2907863016588 & 0.399156303237045 \tabularnewline
0.02 & 96.6514350536021 & 0.335751652702446 \tabularnewline
0.03 & 96.9112833781717 & 0.236897800829866 \tabularnewline
0.04 & 97.0836332285605 & 0.216040362897854 \tabularnewline
0.05 & 97.2236918491702 & 0.247855764604369 \tabularnewline
0.06 & 97.3626852546008 & 0.290243192073705 \tabularnewline
0.07 & 97.5097912331123 & 0.332138666889447 \tabularnewline
0.08 & 97.6656622304907 & 0.372121551661265 \tabularnewline
0.09 & 97.8288266116559 & 0.407723502245206 \tabularnewline
0.1 & 97.9967963504911 & 0.434807677761501 \tabularnewline
0.11 & 98.1660002397044 & 0.449210411703064 \tabularnewline
0.12 & 98.3322280664257 & 0.449200593079359 \tabularnewline
0.13 & 98.491702608865 & 0.43748383887036 \tabularnewline
0.14 & 98.6422796133694 & 0.421477354516654 \tabularnewline
0.15 & 98.7841224150242 & 0.409713093887138 \tabularnewline
0.16 & 98.9194421889807 & 0.408745578666697 \tabularnewline
0.17 & 99.0514114887825 & 0.41845712060677 \tabularnewline
0.18 & 99.1828074993492 & 0.434450059426321 \tabularnewline
0.19 & 99.3150370193968 & 0.449761258018703 \tabularnewline
0.2 & 99.4479262097448 & 0.458884235483641 \tabularnewline
0.21 & 99.5802410286132 & 0.46014898634445 \tabularnewline
0.22 & 99.7105901826828 & 0.456121217623607 \tabularnewline
0.23 & 99.8382806465416 & 0.451583120160242 \tabularnewline
0.24 & 99.963817841702 & 0.451953252927843 \tabularnewline
0.25 & 100.088947628474 & 0.462677353134552 \tabularnewline
0.26 & 100.216309123268 & 0.485620502420175 \tabularnewline
0.27 & 100.348855272649 & 0.521034208061761 \tabularnewline
0.28 & 100.489215752114 & 0.565936432096829 \tabularnewline
0.29 & 100.639160778077 & 0.614830868979458 \tabularnewline
0.3 & 100.799295437747 & 0.662910222751619 \tabularnewline
0.31 & 100.969067832475 & 0.705073641379552 \tabularnewline
0.32 & 101.147099967598 & 0.739142549575835 \tabularnewline
0.33 & 101.33175396086 & 0.76535675354807 \tabularnewline
0.34 & 101.521757708518 & 0.787555948578058 \tabularnewline
0.35 & 101.716673886712 & 0.811010202090551 \tabularnewline
0.36 & 101.917031274127 & 0.84030208361046 \tabularnewline
0.37 & 102.12404449144 & 0.878250864073883 \tabularnewline
0.38 & 102.338991746669 & 0.922516242524449 \tabularnewline
0.39 & 102.562446507712 & 0.967793786730722 \tabularnewline
0.4 & 102.793619385606 & 1.00544572217816 \tabularnewline
0.41 & 103.030037294473 & 1.02711209501668 \tabularnewline
0.42 & 103.267679265074 & 1.02628319380987 \tabularnewline
0.43 & 103.501542799776 & 1.00042259672337 \tabularnewline
0.44 & 103.726484329766 & 0.951172345084637 \tabularnewline
0.45 & 103.938105843661 & 0.883821649729066 \tabularnewline
0.46 & 104.133465233216 & 0.806328142864145 \tabularnewline
0.47 & 104.311458833119 & 0.728055605282221 \tabularnewline
0.48 & 104.472828512795 & 0.656878323001139 \tabularnewline
0.49 & 104.619844855113 & 0.5992115201506 \tabularnewline
0.5 & 104.755784381559 & 0.5584232838961 \tabularnewline
0.51 & 104.884341426258 & 0.535098398104587 \tabularnewline
0.52 & 105.009098890838 & 0.527305549194704 \tabularnewline
0.53 & 105.133140709055 & 0.531318743221858 \tabularnewline
0.54 & 105.258838489008 & 0.543714481771018 \tabularnewline
0.55 & 105.387799211639 & 0.560391342772372 \tabularnewline
0.56 & 105.520929899762 & 0.578893757173735 \tabularnewline
0.57 & 105.658564439017 & 0.597241233762763 \tabularnewline
0.58 & 105.800607797094 & 0.613687494844368 \tabularnewline
0.59 & 105.946678128586 & 0.627586545865625 \tabularnewline
0.6 & 106.096255931043 & 0.638684012575593 \tabularnewline
0.61 & 106.248866555348 & 0.647069918803304 \tabularnewline
0.62 & 106.404315498977 & 0.654160617903777 \tabularnewline
0.63 & 106.562961738445 & 0.662628910643819 \tabularnewline
0.64 & 106.725963271746 & 0.67685372564056 \tabularnewline
0.65 & 106.895384470503 & 0.70103240724841 \tabularnewline
0.66 & 107.074046084271 & 0.73871181211258 \tabularnewline
0.67 & 107.265048192208 & 0.790742799484965 \tabularnewline
0.68 & 107.47100511177 & 0.852575720277025 \tabularnewline
0.69 & 107.693169662219 & 0.916506350335288 \tabularnewline
0.7 & 107.930735525651 & 0.971929682985506 \tabularnewline
0.71 & 108.180627146776 & 1.00833420193224 \tabularnewline
0.72 & 108.437978101547 & 1.01931687333051 \tabularnewline
0.73 & 108.697275956587 & 1.00433259154929 \tabularnewline
0.74 & 108.953888454087 & 0.969918905623472 \tabularnewline
0.75 & 109.205489859692 & 0.928405730418813 \tabularnewline
0.76 & 109.452870283902 & 0.894482177448331 \tabularnewline
0.77 & 109.699768502321 & 0.880565072028015 \tabularnewline
0.78 & 109.951678876853 & 0.891756016951447 \tabularnewline
0.79 & 110.213945954746 & 0.92337707923758 \tabularnewline
0.8 & 110.489753394783 & 0.96246424678658 \tabularnewline
0.81 & 110.77872576538 & 0.992612880960105 \tabularnewline
0.82 & 111.076725530005 & 0.999828818164278 \tabularnewline
0.83 & 111.377055891021 & 0.97737702062363 \tabularnewline
0.84 & 111.672786358524 & 0.928293767064873 \tabularnewline
0.85 & 111.959481107345 & 0.865125483817754 \tabularnewline
0.86 & 112.237376102483 & 0.806294840814197 \tabularnewline
0.87 & 112.512052643138 & 0.770316330075664 \tabularnewline
0.88 & 112.792878499025 & 0.767485857766081 \tabularnewline
0.89 & 113.089048293303 & 0.792347196225135 \tabularnewline
0.9 & 113.404170734975 & 0.820756753718741 \tabularnewline
0.91 & 113.731844871791 & 0.819131397480408 \tabularnewline
0.92 & 114.05542630227 & 0.762004278197944 \tabularnewline
0.93 & 114.353720508355 & 0.648109683162622 \tabularnewline
0.94 & 114.610712656083 & 0.503992685194233 \tabularnewline
0.95 & 114.82410334795 & 0.370652314535769 \tabularnewline
0.96 & 115.0065731925 & 0.28229417872722 \tabularnewline
0.97 & 115.175562736308 & 0.239366506519617 \tabularnewline
0.98 & 115.335305928438 & 0.193816282372924 \tabularnewline
0.99 & 115.468103901014 & 0.117480271901807 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=276890&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]96.2907863016588[/C][C]0.399156303237045[/C][/ROW]
[ROW][C]0.02[/C][C]96.6514350536021[/C][C]0.335751652702446[/C][/ROW]
[ROW][C]0.03[/C][C]96.9112833781717[/C][C]0.236897800829866[/C][/ROW]
[ROW][C]0.04[/C][C]97.0836332285605[/C][C]0.216040362897854[/C][/ROW]
[ROW][C]0.05[/C][C]97.2236918491702[/C][C]0.247855764604369[/C][/ROW]
[ROW][C]0.06[/C][C]97.3626852546008[/C][C]0.290243192073705[/C][/ROW]
[ROW][C]0.07[/C][C]97.5097912331123[/C][C]0.332138666889447[/C][/ROW]
[ROW][C]0.08[/C][C]97.6656622304907[/C][C]0.372121551661265[/C][/ROW]
[ROW][C]0.09[/C][C]97.8288266116559[/C][C]0.407723502245206[/C][/ROW]
[ROW][C]0.1[/C][C]97.9967963504911[/C][C]0.434807677761501[/C][/ROW]
[ROW][C]0.11[/C][C]98.1660002397044[/C][C]0.449210411703064[/C][/ROW]
[ROW][C]0.12[/C][C]98.3322280664257[/C][C]0.449200593079359[/C][/ROW]
[ROW][C]0.13[/C][C]98.491702608865[/C][C]0.43748383887036[/C][/ROW]
[ROW][C]0.14[/C][C]98.6422796133694[/C][C]0.421477354516654[/C][/ROW]
[ROW][C]0.15[/C][C]98.7841224150242[/C][C]0.409713093887138[/C][/ROW]
[ROW][C]0.16[/C][C]98.9194421889807[/C][C]0.408745578666697[/C][/ROW]
[ROW][C]0.17[/C][C]99.0514114887825[/C][C]0.41845712060677[/C][/ROW]
[ROW][C]0.18[/C][C]99.1828074993492[/C][C]0.434450059426321[/C][/ROW]
[ROW][C]0.19[/C][C]99.3150370193968[/C][C]0.449761258018703[/C][/ROW]
[ROW][C]0.2[/C][C]99.4479262097448[/C][C]0.458884235483641[/C][/ROW]
[ROW][C]0.21[/C][C]99.5802410286132[/C][C]0.46014898634445[/C][/ROW]
[ROW][C]0.22[/C][C]99.7105901826828[/C][C]0.456121217623607[/C][/ROW]
[ROW][C]0.23[/C][C]99.8382806465416[/C][C]0.451583120160242[/C][/ROW]
[ROW][C]0.24[/C][C]99.963817841702[/C][C]0.451953252927843[/C][/ROW]
[ROW][C]0.25[/C][C]100.088947628474[/C][C]0.462677353134552[/C][/ROW]
[ROW][C]0.26[/C][C]100.216309123268[/C][C]0.485620502420175[/C][/ROW]
[ROW][C]0.27[/C][C]100.348855272649[/C][C]0.521034208061761[/C][/ROW]
[ROW][C]0.28[/C][C]100.489215752114[/C][C]0.565936432096829[/C][/ROW]
[ROW][C]0.29[/C][C]100.639160778077[/C][C]0.614830868979458[/C][/ROW]
[ROW][C]0.3[/C][C]100.799295437747[/C][C]0.662910222751619[/C][/ROW]
[ROW][C]0.31[/C][C]100.969067832475[/C][C]0.705073641379552[/C][/ROW]
[ROW][C]0.32[/C][C]101.147099967598[/C][C]0.739142549575835[/C][/ROW]
[ROW][C]0.33[/C][C]101.33175396086[/C][C]0.76535675354807[/C][/ROW]
[ROW][C]0.34[/C][C]101.521757708518[/C][C]0.787555948578058[/C][/ROW]
[ROW][C]0.35[/C][C]101.716673886712[/C][C]0.811010202090551[/C][/ROW]
[ROW][C]0.36[/C][C]101.917031274127[/C][C]0.84030208361046[/C][/ROW]
[ROW][C]0.37[/C][C]102.12404449144[/C][C]0.878250864073883[/C][/ROW]
[ROW][C]0.38[/C][C]102.338991746669[/C][C]0.922516242524449[/C][/ROW]
[ROW][C]0.39[/C][C]102.562446507712[/C][C]0.967793786730722[/C][/ROW]
[ROW][C]0.4[/C][C]102.793619385606[/C][C]1.00544572217816[/C][/ROW]
[ROW][C]0.41[/C][C]103.030037294473[/C][C]1.02711209501668[/C][/ROW]
[ROW][C]0.42[/C][C]103.267679265074[/C][C]1.02628319380987[/C][/ROW]
[ROW][C]0.43[/C][C]103.501542799776[/C][C]1.00042259672337[/C][/ROW]
[ROW][C]0.44[/C][C]103.726484329766[/C][C]0.951172345084637[/C][/ROW]
[ROW][C]0.45[/C][C]103.938105843661[/C][C]0.883821649729066[/C][/ROW]
[ROW][C]0.46[/C][C]104.133465233216[/C][C]0.806328142864145[/C][/ROW]
[ROW][C]0.47[/C][C]104.311458833119[/C][C]0.728055605282221[/C][/ROW]
[ROW][C]0.48[/C][C]104.472828512795[/C][C]0.656878323001139[/C][/ROW]
[ROW][C]0.49[/C][C]104.619844855113[/C][C]0.5992115201506[/C][/ROW]
[ROW][C]0.5[/C][C]104.755784381559[/C][C]0.5584232838961[/C][/ROW]
[ROW][C]0.51[/C][C]104.884341426258[/C][C]0.535098398104587[/C][/ROW]
[ROW][C]0.52[/C][C]105.009098890838[/C][C]0.527305549194704[/C][/ROW]
[ROW][C]0.53[/C][C]105.133140709055[/C][C]0.531318743221858[/C][/ROW]
[ROW][C]0.54[/C][C]105.258838489008[/C][C]0.543714481771018[/C][/ROW]
[ROW][C]0.55[/C][C]105.387799211639[/C][C]0.560391342772372[/C][/ROW]
[ROW][C]0.56[/C][C]105.520929899762[/C][C]0.578893757173735[/C][/ROW]
[ROW][C]0.57[/C][C]105.658564439017[/C][C]0.597241233762763[/C][/ROW]
[ROW][C]0.58[/C][C]105.800607797094[/C][C]0.613687494844368[/C][/ROW]
[ROW][C]0.59[/C][C]105.946678128586[/C][C]0.627586545865625[/C][/ROW]
[ROW][C]0.6[/C][C]106.096255931043[/C][C]0.638684012575593[/C][/ROW]
[ROW][C]0.61[/C][C]106.248866555348[/C][C]0.647069918803304[/C][/ROW]
[ROW][C]0.62[/C][C]106.404315498977[/C][C]0.654160617903777[/C][/ROW]
[ROW][C]0.63[/C][C]106.562961738445[/C][C]0.662628910643819[/C][/ROW]
[ROW][C]0.64[/C][C]106.725963271746[/C][C]0.67685372564056[/C][/ROW]
[ROW][C]0.65[/C][C]106.895384470503[/C][C]0.70103240724841[/C][/ROW]
[ROW][C]0.66[/C][C]107.074046084271[/C][C]0.73871181211258[/C][/ROW]
[ROW][C]0.67[/C][C]107.265048192208[/C][C]0.790742799484965[/C][/ROW]
[ROW][C]0.68[/C][C]107.47100511177[/C][C]0.852575720277025[/C][/ROW]
[ROW][C]0.69[/C][C]107.693169662219[/C][C]0.916506350335288[/C][/ROW]
[ROW][C]0.7[/C][C]107.930735525651[/C][C]0.971929682985506[/C][/ROW]
[ROW][C]0.71[/C][C]108.180627146776[/C][C]1.00833420193224[/C][/ROW]
[ROW][C]0.72[/C][C]108.437978101547[/C][C]1.01931687333051[/C][/ROW]
[ROW][C]0.73[/C][C]108.697275956587[/C][C]1.00433259154929[/C][/ROW]
[ROW][C]0.74[/C][C]108.953888454087[/C][C]0.969918905623472[/C][/ROW]
[ROW][C]0.75[/C][C]109.205489859692[/C][C]0.928405730418813[/C][/ROW]
[ROW][C]0.76[/C][C]109.452870283902[/C][C]0.894482177448331[/C][/ROW]
[ROW][C]0.77[/C][C]109.699768502321[/C][C]0.880565072028015[/C][/ROW]
[ROW][C]0.78[/C][C]109.951678876853[/C][C]0.891756016951447[/C][/ROW]
[ROW][C]0.79[/C][C]110.213945954746[/C][C]0.92337707923758[/C][/ROW]
[ROW][C]0.8[/C][C]110.489753394783[/C][C]0.96246424678658[/C][/ROW]
[ROW][C]0.81[/C][C]110.77872576538[/C][C]0.992612880960105[/C][/ROW]
[ROW][C]0.82[/C][C]111.076725530005[/C][C]0.999828818164278[/C][/ROW]
[ROW][C]0.83[/C][C]111.377055891021[/C][C]0.97737702062363[/C][/ROW]
[ROW][C]0.84[/C][C]111.672786358524[/C][C]0.928293767064873[/C][/ROW]
[ROW][C]0.85[/C][C]111.959481107345[/C][C]0.865125483817754[/C][/ROW]
[ROW][C]0.86[/C][C]112.237376102483[/C][C]0.806294840814197[/C][/ROW]
[ROW][C]0.87[/C][C]112.512052643138[/C][C]0.770316330075664[/C][/ROW]
[ROW][C]0.88[/C][C]112.792878499025[/C][C]0.767485857766081[/C][/ROW]
[ROW][C]0.89[/C][C]113.089048293303[/C][C]0.792347196225135[/C][/ROW]
[ROW][C]0.9[/C][C]113.404170734975[/C][C]0.820756753718741[/C][/ROW]
[ROW][C]0.91[/C][C]113.731844871791[/C][C]0.819131397480408[/C][/ROW]
[ROW][C]0.92[/C][C]114.05542630227[/C][C]0.762004278197944[/C][/ROW]
[ROW][C]0.93[/C][C]114.353720508355[/C][C]0.648109683162622[/C][/ROW]
[ROW][C]0.94[/C][C]114.610712656083[/C][C]0.503992685194233[/C][/ROW]
[ROW][C]0.95[/C][C]114.82410334795[/C][C]0.370652314535769[/C][/ROW]
[ROW][C]0.96[/C][C]115.0065731925[/C][C]0.28229417872722[/C][/ROW]
[ROW][C]0.97[/C][C]115.175562736308[/C][C]0.239366506519617[/C][/ROW]
[ROW][C]0.98[/C][C]115.335305928438[/C][C]0.193816282372924[/C][/ROW]
[ROW][C]0.99[/C][C]115.468103901014[/C][C]0.117480271901807[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=276890&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=276890&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
0.0196.29078630165880.399156303237045
0.0296.65143505360210.335751652702446
0.0396.91128337817170.236897800829866
0.0497.08363322856050.216040362897854
0.0597.22369184917020.247855764604369
0.0697.36268525460080.290243192073705
0.0797.50979123311230.332138666889447
0.0897.66566223049070.372121551661265
0.0997.82882661165590.407723502245206
0.197.99679635049110.434807677761501
0.1198.16600023970440.449210411703064
0.1298.33222806642570.449200593079359
0.1398.4917026088650.43748383887036
0.1498.64227961336940.421477354516654
0.1598.78412241502420.409713093887138
0.1698.91944218898070.408745578666697
0.1799.05141148878250.41845712060677
0.1899.18280749934920.434450059426321
0.1999.31503701939680.449761258018703
0.299.44792620974480.458884235483641
0.2199.58024102861320.46014898634445
0.2299.71059018268280.456121217623607
0.2399.83828064654160.451583120160242
0.2499.9638178417020.451953252927843
0.25100.0889476284740.462677353134552
0.26100.2163091232680.485620502420175
0.27100.3488552726490.521034208061761
0.28100.4892157521140.565936432096829
0.29100.6391607780770.614830868979458
0.3100.7992954377470.662910222751619
0.31100.9690678324750.705073641379552
0.32101.1470999675980.739142549575835
0.33101.331753960860.76535675354807
0.34101.5217577085180.787555948578058
0.35101.7166738867120.811010202090551
0.36101.9170312741270.84030208361046
0.37102.124044491440.878250864073883
0.38102.3389917466690.922516242524449
0.39102.5624465077120.967793786730722
0.4102.7936193856061.00544572217816
0.41103.0300372944731.02711209501668
0.42103.2676792650741.02628319380987
0.43103.5015427997761.00042259672337
0.44103.7264843297660.951172345084637
0.45103.9381058436610.883821649729066
0.46104.1334652332160.806328142864145
0.47104.3114588331190.728055605282221
0.48104.4728285127950.656878323001139
0.49104.6198448551130.5992115201506
0.5104.7557843815590.5584232838961
0.51104.8843414262580.535098398104587
0.52105.0090988908380.527305549194704
0.53105.1331407090550.531318743221858
0.54105.2588384890080.543714481771018
0.55105.3877992116390.560391342772372
0.56105.5209298997620.578893757173735
0.57105.6585644390170.597241233762763
0.58105.8006077970940.613687494844368
0.59105.9466781285860.627586545865625
0.6106.0962559310430.638684012575593
0.61106.2488665553480.647069918803304
0.62106.4043154989770.654160617903777
0.63106.5629617384450.662628910643819
0.64106.7259632717460.67685372564056
0.65106.8953844705030.70103240724841
0.66107.0740460842710.73871181211258
0.67107.2650481922080.790742799484965
0.68107.471005111770.852575720277025
0.69107.6931696622190.916506350335288
0.7107.9307355256510.971929682985506
0.71108.1806271467761.00833420193224
0.72108.4379781015471.01931687333051
0.73108.6972759565871.00433259154929
0.74108.9538884540870.969918905623472
0.75109.2054898596920.928405730418813
0.76109.4528702839020.894482177448331
0.77109.6997685023210.880565072028015
0.78109.9516788768530.891756016951447
0.79110.2139459547460.92337707923758
0.8110.4897533947830.96246424678658
0.81110.778725765380.992612880960105
0.82111.0767255300050.999828818164278
0.83111.3770558910210.97737702062363
0.84111.6727863585240.928293767064873
0.85111.9594811073450.865125483817754
0.86112.2373761024830.806294840814197
0.87112.5120526431380.770316330075664
0.88112.7928784990250.767485857766081
0.89113.0890482933030.792347196225135
0.9113.4041707349750.820756753718741
0.91113.7318448717910.819131397480408
0.92114.055426302270.762004278197944
0.93114.3537205083550.648109683162622
0.94114.6107126560830.503992685194233
0.95114.824103347950.370652314535769
0.96115.00657319250.28229417872722
0.97115.1755627363080.239366506519617
0.98115.3353059284380.193816282372924
0.99115.4681039010140.117480271901807


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')