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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationSat, 05 Oct 2013 14:37:15 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Oct/05/t1380998594k0zlslpabxpcjbz.htm/, Retrieved Thu, 02 May 2024 15:21:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=213366, Retrieved Thu, 02 May 2024 15:21:30 +0000
QR Codes:

Original text written by user:the computation allows me to estimate a confidence interval for the mean of the wine sales data
IsPrivate?No (this computation is public)
User-defined keywordsquantiles, wine sales, time series, workshop
Estimated Impact111

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] [Quantiles of Wine...] [2013-10-05 18:37:15] [9df62e693988eb4e1e1444ece0578579] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1954
2302
3054
2414
2226
2725
2589
3470
2400
3180
4009
3924
2072
2434
2956
2828
2687
2629
3150
4119
3030
3055
3821
4001
2529
2472
3134
2789
2758
2993
3282
3437
2804
3076
3782
3889
2271
2452
3084
2522
2769
3438
2839
3746
2632
2851
3871
3618
2389
2344
2678
2492
2858
2246
2800
3869
3007
3023
3907
4209

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ yule.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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=213366&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=213366&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=213366&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ yule.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.011987.05207326484117.29988279466
0.022038.63970610597117.708831192855
0.032095.26282197972112.059908242465
0.042147.4201674238199.5412011829797
0.052191.2477346523184.752659702047
0.062226.7238678434572.7884291596779
0.072255.55707183465.8892223758813
0.082279.7741822093463.2344344351711
0.092301.0279290882662.727023536805
0.12320.3992576847262.6377514135995
0.112338.4707254767562.0969535291253
0.122355.5015262927960.9329579991859
0.132371.599082565359.3877447828677
0.142386.8397917747857.883997197837
0.152401.3313690506656.8492175851615
0.162415.2294608373156.5900510590706
0.172428.7268254758757.2602199363997
0.182442.0310151926858.85995489368
0.192455.341264202261.2710639875198
0.22468.830143133564.3213977607668
0.212482.6317564324867.805475133216
0.222496.8360761551271.5027832205918
0.232511.488122845375.2027444503755
0.242526.5906271902378.7085676644062
0.252542.1090698524681.8427364172146
0.262557.9782860612684.4669487905069
0.272574.1099986831586.4832302524536
0.282590.400710369787.8315673486822
0.292606.7394138613488.4971500155503
0.32623.0146448122788.5045739187276
0.312639.1205395749187.9009986622484
0.322654.9617564157386.7555482933608
0.332670.4573208727985.151584967002
0.342685.5436026548183.1855977169796
0.352700.1766775312680.9612468411627
0.362714.334261314478.6012616788769
0.372728.0172486122576.2363260334596
0.382741.2506974674274.016445248661
0.392754.0839334135972.0999670570569
0.42766.5893570989870.6461491565349
0.412778.8595628779469.80075174204
0.422791.0025199995169.6746647393343
0.432803.1348155891770.326580431336
0.442815.3732707296271.7365666317935
0.452827.8255650751873.8208491403408
0.462840.5807837962576.4124301253004
0.472853.7009788955979.2863739633862
0.482867.2148726743982.189011858343
0.492881.1147017428784.8548481362017
0.52895.3569086208487.0431327201148
0.512909.8669660696688.5502971807124
0.522924.5481238882789.2603150331429
0.532939.2933731978889.1325198366608
0.542953.9995071138488.2287066163332
0.552968.5818848723186.7114396730653
0.562982.9884182516884.8173002987964
0.572997.2113988593182.8824357247585
0.583011.2960419850281.2725572998742
0.593025.3449809161480.3851092380354
0.63039.5183386398380.6091268738016
0.613054.0293735766782.2742464138759
0.623069.1360065543485.6374292476174
0.633085.1287796354490.8279185778692
0.643102.3159879291197.8583523915925
0.653121.00688461404106.616956135629
0.663141.49399679508116.877075513645
0.673164.03568903622128.31804636481
0.683188.84012827211140.551274518596
0.693216.05168242441153.129541081027
0.73245.74048902669165.582606739457
0.713277.89547787652177.440071652301
0.723312.42061867276188.252333484781
0.733349.1337552926197.603347266558
0.743387.76726946176205.122672478449
0.753427.97011913982210.464111462969
0.763469.31151504483213.315073019386
0.773511.28744311409213.394744148553
0.783553.3320619935210.471945095474
0.793594.83629670837204.404998980089
0.83635.17540593879195.196108658561
0.813673.7458619405183.042523733438
0.823710.00980452991168.370464390694
0.833743.54312037601151.834001758557
0.843774.08143359959134.286933198038
0.853801.5574096408116.711726555612
0.863826.12295768014100.137778233895
0.873848.1512086173285.5528062207405
0.883868.2157326281573.813093968701
0.893887.0488733057565.540679902322
0.93905.4877746713360.9549514007787
0.913924.4246023778159.7221622932491
0.923944.7819338166961.0739297755141
0.933967.5260170980164.2281719953315
0.943993.6978296643168.8185957190205
0.954024.3756599232674.7834841295518
0.964060.3859428068681.4624073321076
0.974101.4975985985786.8754664554129
0.984144.9621711193289.0229391842482
0.994184.0524042629788.6993275629301

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 1987.05207326484 & 117.29988279466 \tabularnewline
0.02 & 2038.63970610597 & 117.708831192855 \tabularnewline
0.03 & 2095.26282197972 & 112.059908242465 \tabularnewline
0.04 & 2147.42016742381 & 99.5412011829797 \tabularnewline
0.05 & 2191.24773465231 & 84.752659702047 \tabularnewline
0.06 & 2226.72386784345 & 72.7884291596779 \tabularnewline
0.07 & 2255.557071834 & 65.8892223758813 \tabularnewline
0.08 & 2279.77418220934 & 63.2344344351711 \tabularnewline
0.09 & 2301.02792908826 & 62.727023536805 \tabularnewline
0.1 & 2320.39925768472 & 62.6377514135995 \tabularnewline
0.11 & 2338.47072547675 & 62.0969535291253 \tabularnewline
0.12 & 2355.50152629279 & 60.9329579991859 \tabularnewline
0.13 & 2371.5990825653 & 59.3877447828677 \tabularnewline
0.14 & 2386.83979177478 & 57.883997197837 \tabularnewline
0.15 & 2401.33136905066 & 56.8492175851615 \tabularnewline
0.16 & 2415.22946083731 & 56.5900510590706 \tabularnewline
0.17 & 2428.72682547587 & 57.2602199363997 \tabularnewline
0.18 & 2442.03101519268 & 58.85995489368 \tabularnewline
0.19 & 2455.3412642022 & 61.2710639875198 \tabularnewline
0.2 & 2468.8301431335 & 64.3213977607668 \tabularnewline
0.21 & 2482.63175643248 & 67.805475133216 \tabularnewline
0.22 & 2496.83607615512 & 71.5027832205918 \tabularnewline
0.23 & 2511.4881228453 & 75.2027444503755 \tabularnewline
0.24 & 2526.59062719023 & 78.7085676644062 \tabularnewline
0.25 & 2542.10906985246 & 81.8427364172146 \tabularnewline
0.26 & 2557.97828606126 & 84.4669487905069 \tabularnewline
0.27 & 2574.10999868315 & 86.4832302524536 \tabularnewline
0.28 & 2590.4007103697 & 87.8315673486822 \tabularnewline
0.29 & 2606.73941386134 & 88.4971500155503 \tabularnewline
0.3 & 2623.01464481227 & 88.5045739187276 \tabularnewline
0.31 & 2639.12053957491 & 87.9009986622484 \tabularnewline
0.32 & 2654.96175641573 & 86.7555482933608 \tabularnewline
0.33 & 2670.45732087279 & 85.151584967002 \tabularnewline
0.34 & 2685.54360265481 & 83.1855977169796 \tabularnewline
0.35 & 2700.17667753126 & 80.9612468411627 \tabularnewline
0.36 & 2714.3342613144 & 78.6012616788769 \tabularnewline
0.37 & 2728.01724861225 & 76.2363260334596 \tabularnewline
0.38 & 2741.25069746742 & 74.016445248661 \tabularnewline
0.39 & 2754.08393341359 & 72.0999670570569 \tabularnewline
0.4 & 2766.58935709898 & 70.6461491565349 \tabularnewline
0.41 & 2778.85956287794 & 69.80075174204 \tabularnewline
0.42 & 2791.00251999951 & 69.6746647393343 \tabularnewline
0.43 & 2803.13481558917 & 70.326580431336 \tabularnewline
0.44 & 2815.37327072962 & 71.7365666317935 \tabularnewline
0.45 & 2827.82556507518 & 73.8208491403408 \tabularnewline
0.46 & 2840.58078379625 & 76.4124301253004 \tabularnewline
0.47 & 2853.70097889559 & 79.2863739633862 \tabularnewline
0.48 & 2867.21487267439 & 82.189011858343 \tabularnewline
0.49 & 2881.11470174287 & 84.8548481362017 \tabularnewline
0.5 & 2895.35690862084 & 87.0431327201148 \tabularnewline
0.51 & 2909.86696606966 & 88.5502971807124 \tabularnewline
0.52 & 2924.54812388827 & 89.2603150331429 \tabularnewline
0.53 & 2939.29337319788 & 89.1325198366608 \tabularnewline
0.54 & 2953.99950711384 & 88.2287066163332 \tabularnewline
0.55 & 2968.58188487231 & 86.7114396730653 \tabularnewline
0.56 & 2982.98841825168 & 84.8173002987964 \tabularnewline
0.57 & 2997.21139885931 & 82.8824357247585 \tabularnewline
0.58 & 3011.29604198502 & 81.2725572998742 \tabularnewline
0.59 & 3025.34498091614 & 80.3851092380354 \tabularnewline
0.6 & 3039.51833863983 & 80.6091268738016 \tabularnewline
0.61 & 3054.02937357667 & 82.2742464138759 \tabularnewline
0.62 & 3069.13600655434 & 85.6374292476174 \tabularnewline
0.63 & 3085.12877963544 & 90.8279185778692 \tabularnewline
0.64 & 3102.31598792911 & 97.8583523915925 \tabularnewline
0.65 & 3121.00688461404 & 106.616956135629 \tabularnewline
0.66 & 3141.49399679508 & 116.877075513645 \tabularnewline
0.67 & 3164.03568903622 & 128.31804636481 \tabularnewline
0.68 & 3188.84012827211 & 140.551274518596 \tabularnewline
0.69 & 3216.05168242441 & 153.129541081027 \tabularnewline
0.7 & 3245.74048902669 & 165.582606739457 \tabularnewline
0.71 & 3277.89547787652 & 177.440071652301 \tabularnewline
0.72 & 3312.42061867276 & 188.252333484781 \tabularnewline
0.73 & 3349.1337552926 & 197.603347266558 \tabularnewline
0.74 & 3387.76726946176 & 205.122672478449 \tabularnewline
0.75 & 3427.97011913982 & 210.464111462969 \tabularnewline
0.76 & 3469.31151504483 & 213.315073019386 \tabularnewline
0.77 & 3511.28744311409 & 213.394744148553 \tabularnewline
0.78 & 3553.3320619935 & 210.471945095474 \tabularnewline
0.79 & 3594.83629670837 & 204.404998980089 \tabularnewline
0.8 & 3635.17540593879 & 195.196108658561 \tabularnewline
0.81 & 3673.7458619405 & 183.042523733438 \tabularnewline
0.82 & 3710.00980452991 & 168.370464390694 \tabularnewline
0.83 & 3743.54312037601 & 151.834001758557 \tabularnewline
0.84 & 3774.08143359959 & 134.286933198038 \tabularnewline
0.85 & 3801.5574096408 & 116.711726555612 \tabularnewline
0.86 & 3826.12295768014 & 100.137778233895 \tabularnewline
0.87 & 3848.15120861732 & 85.5528062207405 \tabularnewline
0.88 & 3868.21573262815 & 73.813093968701 \tabularnewline
0.89 & 3887.04887330575 & 65.540679902322 \tabularnewline
0.9 & 3905.48777467133 & 60.9549514007787 \tabularnewline
0.91 & 3924.42460237781 & 59.7221622932491 \tabularnewline
0.92 & 3944.78193381669 & 61.0739297755141 \tabularnewline
0.93 & 3967.52601709801 & 64.2281719953315 \tabularnewline
0.94 & 3993.69782966431 & 68.8185957190205 \tabularnewline
0.95 & 4024.37565992326 & 74.7834841295518 \tabularnewline
0.96 & 4060.38594280686 & 81.4624073321076 \tabularnewline
0.97 & 4101.49759859857 & 86.8754664554129 \tabularnewline
0.98 & 4144.96217111932 & 89.0229391842482 \tabularnewline
0.99 & 4184.05240426297 & 88.6993275629301 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=213366&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]1987.05207326484[/C][C]117.29988279466[/C][/ROW]
[ROW][C]0.02[/C][C]2038.63970610597[/C][C]117.708831192855[/C][/ROW]
[ROW][C]0.03[/C][C]2095.26282197972[/C][C]112.059908242465[/C][/ROW]
[ROW][C]0.04[/C][C]2147.42016742381[/C][C]99.5412011829797[/C][/ROW]
[ROW][C]0.05[/C][C]2191.24773465231[/C][C]84.752659702047[/C][/ROW]
[ROW][C]0.06[/C][C]2226.72386784345[/C][C]72.7884291596779[/C][/ROW]
[ROW][C]0.07[/C][C]2255.557071834[/C][C]65.8892223758813[/C][/ROW]
[ROW][C]0.08[/C][C]2279.77418220934[/C][C]63.2344344351711[/C][/ROW]
[ROW][C]0.09[/C][C]2301.02792908826[/C][C]62.727023536805[/C][/ROW]
[ROW][C]0.1[/C][C]2320.39925768472[/C][C]62.6377514135995[/C][/ROW]
[ROW][C]0.11[/C][C]2338.47072547675[/C][C]62.0969535291253[/C][/ROW]
[ROW][C]0.12[/C][C]2355.50152629279[/C][C]60.9329579991859[/C][/ROW]
[ROW][C]0.13[/C][C]2371.5990825653[/C][C]59.3877447828677[/C][/ROW]
[ROW][C]0.14[/C][C]2386.83979177478[/C][C]57.883997197837[/C][/ROW]
[ROW][C]0.15[/C][C]2401.33136905066[/C][C]56.8492175851615[/C][/ROW]
[ROW][C]0.16[/C][C]2415.22946083731[/C][C]56.5900510590706[/C][/ROW]
[ROW][C]0.17[/C][C]2428.72682547587[/C][C]57.2602199363997[/C][/ROW]
[ROW][C]0.18[/C][C]2442.03101519268[/C][C]58.85995489368[/C][/ROW]
[ROW][C]0.19[/C][C]2455.3412642022[/C][C]61.2710639875198[/C][/ROW]
[ROW][C]0.2[/C][C]2468.8301431335[/C][C]64.3213977607668[/C][/ROW]
[ROW][C]0.21[/C][C]2482.63175643248[/C][C]67.805475133216[/C][/ROW]
[ROW][C]0.22[/C][C]2496.83607615512[/C][C]71.5027832205918[/C][/ROW]
[ROW][C]0.23[/C][C]2511.4881228453[/C][C]75.2027444503755[/C][/ROW]
[ROW][C]0.24[/C][C]2526.59062719023[/C][C]78.7085676644062[/C][/ROW]
[ROW][C]0.25[/C][C]2542.10906985246[/C][C]81.8427364172146[/C][/ROW]
[ROW][C]0.26[/C][C]2557.97828606126[/C][C]84.4669487905069[/C][/ROW]
[ROW][C]0.27[/C][C]2574.10999868315[/C][C]86.4832302524536[/C][/ROW]
[ROW][C]0.28[/C][C]2590.4007103697[/C][C]87.8315673486822[/C][/ROW]
[ROW][C]0.29[/C][C]2606.73941386134[/C][C]88.4971500155503[/C][/ROW]
[ROW][C]0.3[/C][C]2623.01464481227[/C][C]88.5045739187276[/C][/ROW]
[ROW][C]0.31[/C][C]2639.12053957491[/C][C]87.9009986622484[/C][/ROW]
[ROW][C]0.32[/C][C]2654.96175641573[/C][C]86.7555482933608[/C][/ROW]
[ROW][C]0.33[/C][C]2670.45732087279[/C][C]85.151584967002[/C][/ROW]
[ROW][C]0.34[/C][C]2685.54360265481[/C][C]83.1855977169796[/C][/ROW]
[ROW][C]0.35[/C][C]2700.17667753126[/C][C]80.9612468411627[/C][/ROW]
[ROW][C]0.36[/C][C]2714.3342613144[/C][C]78.6012616788769[/C][/ROW]
[ROW][C]0.37[/C][C]2728.01724861225[/C][C]76.2363260334596[/C][/ROW]
[ROW][C]0.38[/C][C]2741.25069746742[/C][C]74.016445248661[/C][/ROW]
[ROW][C]0.39[/C][C]2754.08393341359[/C][C]72.0999670570569[/C][/ROW]
[ROW][C]0.4[/C][C]2766.58935709898[/C][C]70.6461491565349[/C][/ROW]
[ROW][C]0.41[/C][C]2778.85956287794[/C][C]69.80075174204[/C][/ROW]
[ROW][C]0.42[/C][C]2791.00251999951[/C][C]69.6746647393343[/C][/ROW]
[ROW][C]0.43[/C][C]2803.13481558917[/C][C]70.326580431336[/C][/ROW]
[ROW][C]0.44[/C][C]2815.37327072962[/C][C]71.7365666317935[/C][/ROW]
[ROW][C]0.45[/C][C]2827.82556507518[/C][C]73.8208491403408[/C][/ROW]
[ROW][C]0.46[/C][C]2840.58078379625[/C][C]76.4124301253004[/C][/ROW]
[ROW][C]0.47[/C][C]2853.70097889559[/C][C]79.2863739633862[/C][/ROW]
[ROW][C]0.48[/C][C]2867.21487267439[/C][C]82.189011858343[/C][/ROW]
[ROW][C]0.49[/C][C]2881.11470174287[/C][C]84.8548481362017[/C][/ROW]
[ROW][C]0.5[/C][C]2895.35690862084[/C][C]87.0431327201148[/C][/ROW]
[ROW][C]0.51[/C][C]2909.86696606966[/C][C]88.5502971807124[/C][/ROW]
[ROW][C]0.52[/C][C]2924.54812388827[/C][C]89.2603150331429[/C][/ROW]
[ROW][C]0.53[/C][C]2939.29337319788[/C][C]89.1325198366608[/C][/ROW]
[ROW][C]0.54[/C][C]2953.99950711384[/C][C]88.2287066163332[/C][/ROW]
[ROW][C]0.55[/C][C]2968.58188487231[/C][C]86.7114396730653[/C][/ROW]
[ROW][C]0.56[/C][C]2982.98841825168[/C][C]84.8173002987964[/C][/ROW]
[ROW][C]0.57[/C][C]2997.21139885931[/C][C]82.8824357247585[/C][/ROW]
[ROW][C]0.58[/C][C]3011.29604198502[/C][C]81.2725572998742[/C][/ROW]
[ROW][C]0.59[/C][C]3025.34498091614[/C][C]80.3851092380354[/C][/ROW]
[ROW][C]0.6[/C][C]3039.51833863983[/C][C]80.6091268738016[/C][/ROW]
[ROW][C]0.61[/C][C]3054.02937357667[/C][C]82.2742464138759[/C][/ROW]
[ROW][C]0.62[/C][C]3069.13600655434[/C][C]85.6374292476174[/C][/ROW]
[ROW][C]0.63[/C][C]3085.12877963544[/C][C]90.8279185778692[/C][/ROW]
[ROW][C]0.64[/C][C]3102.31598792911[/C][C]97.8583523915925[/C][/ROW]
[ROW][C]0.65[/C][C]3121.00688461404[/C][C]106.616956135629[/C][/ROW]
[ROW][C]0.66[/C][C]3141.49399679508[/C][C]116.877075513645[/C][/ROW]
[ROW][C]0.67[/C][C]3164.03568903622[/C][C]128.31804636481[/C][/ROW]
[ROW][C]0.68[/C][C]3188.84012827211[/C][C]140.551274518596[/C][/ROW]
[ROW][C]0.69[/C][C]3216.05168242441[/C][C]153.129541081027[/C][/ROW]
[ROW][C]0.7[/C][C]3245.74048902669[/C][C]165.582606739457[/C][/ROW]
[ROW][C]0.71[/C][C]3277.89547787652[/C][C]177.440071652301[/C][/ROW]
[ROW][C]0.72[/C][C]3312.42061867276[/C][C]188.252333484781[/C][/ROW]
[ROW][C]0.73[/C][C]3349.1337552926[/C][C]197.603347266558[/C][/ROW]
[ROW][C]0.74[/C][C]3387.76726946176[/C][C]205.122672478449[/C][/ROW]
[ROW][C]0.75[/C][C]3427.97011913982[/C][C]210.464111462969[/C][/ROW]
[ROW][C]0.76[/C][C]3469.31151504483[/C][C]213.315073019386[/C][/ROW]
[ROW][C]0.77[/C][C]3511.28744311409[/C][C]213.394744148553[/C][/ROW]
[ROW][C]0.78[/C][C]3553.3320619935[/C][C]210.471945095474[/C][/ROW]
[ROW][C]0.79[/C][C]3594.83629670837[/C][C]204.404998980089[/C][/ROW]
[ROW][C]0.8[/C][C]3635.17540593879[/C][C]195.196108658561[/C][/ROW]
[ROW][C]0.81[/C][C]3673.7458619405[/C][C]183.042523733438[/C][/ROW]
[ROW][C]0.82[/C][C]3710.00980452991[/C][C]168.370464390694[/C][/ROW]
[ROW][C]0.83[/C][C]3743.54312037601[/C][C]151.834001758557[/C][/ROW]
[ROW][C]0.84[/C][C]3774.08143359959[/C][C]134.286933198038[/C][/ROW]
[ROW][C]0.85[/C][C]3801.5574096408[/C][C]116.711726555612[/C][/ROW]
[ROW][C]0.86[/C][C]3826.12295768014[/C][C]100.137778233895[/C][/ROW]
[ROW][C]0.87[/C][C]3848.15120861732[/C][C]85.5528062207405[/C][/ROW]
[ROW][C]0.88[/C][C]3868.21573262815[/C][C]73.813093968701[/C][/ROW]
[ROW][C]0.89[/C][C]3887.04887330575[/C][C]65.540679902322[/C][/ROW]
[ROW][C]0.9[/C][C]3905.48777467133[/C][C]60.9549514007787[/C][/ROW]
[ROW][C]0.91[/C][C]3924.42460237781[/C][C]59.7221622932491[/C][/ROW]
[ROW][C]0.92[/C][C]3944.78193381669[/C][C]61.0739297755141[/C][/ROW]
[ROW][C]0.93[/C][C]3967.52601709801[/C][C]64.2281719953315[/C][/ROW]
[ROW][C]0.94[/C][C]3993.69782966431[/C][C]68.8185957190205[/C][/ROW]
[ROW][C]0.95[/C][C]4024.37565992326[/C][C]74.7834841295518[/C][/ROW]
[ROW][C]0.96[/C][C]4060.38594280686[/C][C]81.4624073321076[/C][/ROW]
[ROW][C]0.97[/C][C]4101.49759859857[/C][C]86.8754664554129[/C][/ROW]
[ROW][C]0.98[/C][C]4144.96217111932[/C][C]89.0229391842482[/C][/ROW]
[ROW][C]0.99[/C][C]4184.05240426297[/C][C]88.6993275629301[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=213366&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=213366&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
0.011987.05207326484117.29988279466
0.022038.63970610597117.708831192855
0.032095.26282197972112.059908242465
0.042147.4201674238199.5412011829797
0.052191.2477346523184.752659702047
0.062226.7238678434572.7884291596779
0.072255.55707183465.8892223758813
0.082279.7741822093463.2344344351711
0.092301.0279290882662.727023536805
0.12320.3992576847262.6377514135995
0.112338.4707254767562.0969535291253
0.122355.5015262927960.9329579991859
0.132371.599082565359.3877447828677
0.142386.8397917747857.883997197837
0.152401.3313690506656.8492175851615
0.162415.2294608373156.5900510590706
0.172428.7268254758757.2602199363997
0.182442.0310151926858.85995489368
0.192455.341264202261.2710639875198
0.22468.830143133564.3213977607668
0.212482.6317564324867.805475133216
0.222496.8360761551271.5027832205918
0.232511.488122845375.2027444503755
0.242526.5906271902378.7085676644062
0.252542.1090698524681.8427364172146
0.262557.9782860612684.4669487905069
0.272574.1099986831586.4832302524536
0.282590.400710369787.8315673486822
0.292606.7394138613488.4971500155503
0.32623.0146448122788.5045739187276
0.312639.1205395749187.9009986622484
0.322654.9617564157386.7555482933608
0.332670.4573208727985.151584967002
0.342685.5436026548183.1855977169796
0.352700.1766775312680.9612468411627
0.362714.334261314478.6012616788769
0.372728.0172486122576.2363260334596
0.382741.2506974674274.016445248661
0.392754.0839334135972.0999670570569
0.42766.5893570989870.6461491565349
0.412778.8595628779469.80075174204
0.422791.0025199995169.6746647393343
0.432803.1348155891770.326580431336
0.442815.3732707296271.7365666317935
0.452827.8255650751873.8208491403408
0.462840.5807837962576.4124301253004
0.472853.7009788955979.2863739633862
0.482867.2148726743982.189011858343
0.492881.1147017428784.8548481362017
0.52895.3569086208487.0431327201148
0.512909.8669660696688.5502971807124
0.522924.5481238882789.2603150331429
0.532939.2933731978889.1325198366608
0.542953.9995071138488.2287066163332
0.552968.5818848723186.7114396730653
0.562982.9884182516884.8173002987964
0.572997.2113988593182.8824357247585
0.583011.2960419850281.2725572998742
0.593025.3449809161480.3851092380354
0.63039.5183386398380.6091268738016
0.613054.0293735766782.2742464138759
0.623069.1360065543485.6374292476174
0.633085.1287796354490.8279185778692
0.643102.3159879291197.8583523915925
0.653121.00688461404106.616956135629
0.663141.49399679508116.877075513645
0.673164.03568903622128.31804636481
0.683188.84012827211140.551274518596
0.693216.05168242441153.129541081027
0.73245.74048902669165.582606739457
0.713277.89547787652177.440071652301
0.723312.42061867276188.252333484781
0.733349.1337552926197.603347266558
0.743387.76726946176205.122672478449
0.753427.97011913982210.464111462969
0.763469.31151504483213.315073019386
0.773511.28744311409213.394744148553
0.783553.3320619935210.471945095474
0.793594.83629670837204.404998980089
0.83635.17540593879195.196108658561
0.813673.7458619405183.042523733438
0.823710.00980452991168.370464390694
0.833743.54312037601151.834001758557
0.843774.08143359959134.286933198038
0.853801.5574096408116.711726555612
0.863826.12295768014100.137778233895
0.873848.1512086173285.5528062207405
0.883868.2157326281573.813093968701
0.893887.0488733057565.540679902322
0.93905.4877746713360.9549514007787
0.913924.4246023778159.7221622932491
0.923944.7819338166961.0739297755141
0.933967.5260170980164.2281719953315
0.943993.6978296643168.8185957190205
0.954024.3756599232674.7834841295518
0.964060.3859428068681.4624073321076
0.974101.4975985985786.8754664554129
0.984144.9621711193289.0229391842482
0.994184.0524042629788.6993275629301


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')