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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, 12 Aug 2013 12:15:37 -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/Aug/12/t1376324170ah5vuzrpxzhkp93.htm/, Retrieved Sat, 27 Apr 2024 17:38:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=211055, Retrieved Sat, 27 Apr 2024 17:38:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsStefanie Gubbi
Estimated Impact119

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] [Tijdreeks 1 - Sta...] [2013-08-12 16:15:37] [3958f9c0a64aeec6b83979b094ee8a96] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
196.09
192.64
189.19
182.29
252.11
248.66
196.09
161.18
164.62
164.62
168.08
175.35
154.27
133.16
115.88
115.88
182.29
189.19
136.61
77.14
108.60
108.60
133.16
147.34
143.89
108.60
126.26
119.33
178.80
164.62
108.60
66.75
105.15
115.88
126.26
140.07
112.05
87.87
98.25
101.70
192.64
192.64
140.07
133.16
154.27
143.89
171.90
206.82
213.75
164.62
150.79
136.61
231.38
238.31
220.65
238.31
234.83
206.82
238.31
273.23
287.40
245.21
217.20
238.31
329.25
357.26
350.36
364.16
360.71
325.80
385.28
399.45
420.19
357.26
332.70
360.71
427.46
486.94
472.76
472.76
479.70
455.47
518.44
518.44
507.71
448.20
458.93
465.86
511.50
570.98
528.79
549.90
532.24
521.88
602.47
584.81
560.25
525.34
560.25
577.91
598.99
627.00
598.99
616.28
595.20
591.75
679.23
686.51
658.50
609.37
651.22
668.85
689.96
721.42
689.96
714.52
703.80
665.40
745.98
745.98

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 9 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211055&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211055&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211055&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 time9 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0174.305623614502710.831202712286
0.0284.826109304500911.1714537837566
0.0393.62735402767869.46855114449859
0.0499.88654460760857.10431334544555
0.05104.0930358890745.2673392743989
0.06106.994975167174.31251599824459
0.07109.2505708658724.24854014373719
0.08111.3295512570734.83420133726271
0.09113.5112312916725.73162445273933
0.1115.9175230464236.68970711347124
0.11118.5598078334767.54095031132422
0.12121.3825764275128.16253470183795
0.13124.2971848473668.48553358418586
0.14127.2101012919598.52433086967127
0.15130.0483133251748.38170226770366
0.16132.777191552548.20943605444787
0.17135.4046455007288.1487449376244
0.18137.9710286408018.27966759014306
0.19140.5306458608228.60418032459114
0.2143.1329668389769.06410612038509
0.21145.8096663226979.57233258715722
0.22148.56996336929110.0462316856915
0.23151.40359194757710.4284651407306
0.24154.28883010754910.6994511003384
0.25157.20220995569710.8789372787088
0.26160.12662920927911.0125558171302
0.27163.05553208437311.1522396213786
0.28165.99245540826311.3342641764258
0.29168.94704979090911.568512140196
0.3171.92997731430911.8386094265171
0.31174.94930145417512.119988396184
0.32178.0100475433912.3983107345803
0.33181.11698508818712.6828507728712
0.34184.27912499441713.0100486632336
0.35187.51361720791513.4326100188331
0.36190.84698891382513.9995637692022
0.37194.31283191885614.7368900409675
0.38197.94663327836315.6344327349093
0.39201.77982059511416.6506423739953
0.4205.8357332177217.7316325993287
0.41210.12985678645918.8372176879491
0.42214.67531833699719.9694111344391
0.43219.49269089387721.1896714244213
0.44224.62119014158822.6208265264213
0.45230.12704423080624.420608431035
0.46236.10476856630426.734110791057
0.47242.6685616448329.6319787401808
0.48249.93385588233433.0610747234228
0.49257.99247532444636.8314608917246
0.5266.88774563880940.6447270146314
0.51276.59710303670944.1496275813776
0.52287.02850654020947.0254603751978
0.53298.03332875162249.0545870644978
0.54309.43337362432750.1806468836568
0.55321.05491649442150.5173401394793
0.56332.75995232058550.317823143705
0.57344.46534192027249.8945020701877
0.58356.14430213182749.5209612281996
0.59367.81049203815749.3469843357406
0.6379.49075011836949.3536385143132
0.61391.1961974742449.3804044472302
0.62402.90156337466749.1936279734569
0.63414.53917813212848.5824363842284
0.64426.00848062987347.4246046124683
0.65437.19634229611945.7268717612143
0.66448.00020791229143.6048987057148
0.67458.34620286178341.2390765186451
0.68468.1976350508338.8177057686523
0.69477.55400981050936.4891267942082
0.7486.44446017489334.3464009351129
0.71494.92058928257832.4443223001628
0.72503.05180183525230.828191105584
0.73510.92260940980129.5514485959266
0.74518.6284379800828.6642923717995
0.75526.26612239572528.1669673572519
0.76533.91800976762127.9802836282129
0.77541.63304326520527.9311407362091
0.78549.4119311341427.7940642143088
0.79557.20443502796627.3622092696423
0.8564.92427124789426.5194295992202
0.81572.48191289745925.294086366143
0.82579.82914520080423.8818023937803
0.83587.00285922331322.6274888239899
0.84594.15067669048721.9527817186029
0.85601.52016372252622.194066083303
0.86609.40061518152723.3966739096392
0.87618.02446866499325.1841868720933
0.88627.46052853986526.8468274644679
0.89637.54937683127127.6132733405979
0.9647.92454554307526.9781750240891
0.91658.12663871518624.9231833403443
0.92667.77382677345221.9235852590765
0.93676.73237471694918.7712100231274
0.94685.23457719902216.3601007297673
0.95693.89457247127615.3916376860621
0.96703.59651306995215.8506160803028
0.97715.2064358459417.0736676544702
0.98728.59858908998417.4591704945479
0.99740.5956203518511.501526635672

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 74.3056236145027 & 10.831202712286 \tabularnewline
0.02 & 84.8261093045009 & 11.1714537837566 \tabularnewline
0.03 & 93.6273540276786 & 9.46855114449859 \tabularnewline
0.04 & 99.8865446076085 & 7.10431334544555 \tabularnewline
0.05 & 104.093035889074 & 5.2673392743989 \tabularnewline
0.06 & 106.99497516717 & 4.31251599824459 \tabularnewline
0.07 & 109.250570865872 & 4.24854014373719 \tabularnewline
0.08 & 111.329551257073 & 4.83420133726271 \tabularnewline
0.09 & 113.511231291672 & 5.73162445273933 \tabularnewline
0.1 & 115.917523046423 & 6.68970711347124 \tabularnewline
0.11 & 118.559807833476 & 7.54095031132422 \tabularnewline
0.12 & 121.382576427512 & 8.16253470183795 \tabularnewline
0.13 & 124.297184847366 & 8.48553358418586 \tabularnewline
0.14 & 127.210101291959 & 8.52433086967127 \tabularnewline
0.15 & 130.048313325174 & 8.38170226770366 \tabularnewline
0.16 & 132.77719155254 & 8.20943605444787 \tabularnewline
0.17 & 135.404645500728 & 8.1487449376244 \tabularnewline
0.18 & 137.971028640801 & 8.27966759014306 \tabularnewline
0.19 & 140.530645860822 & 8.60418032459114 \tabularnewline
0.2 & 143.132966838976 & 9.06410612038509 \tabularnewline
0.21 & 145.809666322697 & 9.57233258715722 \tabularnewline
0.22 & 148.569963369291 & 10.0462316856915 \tabularnewline
0.23 & 151.403591947577 & 10.4284651407306 \tabularnewline
0.24 & 154.288830107549 & 10.6994511003384 \tabularnewline
0.25 & 157.202209955697 & 10.8789372787088 \tabularnewline
0.26 & 160.126629209279 & 11.0125558171302 \tabularnewline
0.27 & 163.055532084373 & 11.1522396213786 \tabularnewline
0.28 & 165.992455408263 & 11.3342641764258 \tabularnewline
0.29 & 168.947049790909 & 11.568512140196 \tabularnewline
0.3 & 171.929977314309 & 11.8386094265171 \tabularnewline
0.31 & 174.949301454175 & 12.119988396184 \tabularnewline
0.32 & 178.01004754339 & 12.3983107345803 \tabularnewline
0.33 & 181.116985088187 & 12.6828507728712 \tabularnewline
0.34 & 184.279124994417 & 13.0100486632336 \tabularnewline
0.35 & 187.513617207915 & 13.4326100188331 \tabularnewline
0.36 & 190.846988913825 & 13.9995637692022 \tabularnewline
0.37 & 194.312831918856 & 14.7368900409675 \tabularnewline
0.38 & 197.946633278363 & 15.6344327349093 \tabularnewline
0.39 & 201.779820595114 & 16.6506423739953 \tabularnewline
0.4 & 205.83573321772 & 17.7316325993287 \tabularnewline
0.41 & 210.129856786459 & 18.8372176879491 \tabularnewline
0.42 & 214.675318336997 & 19.9694111344391 \tabularnewline
0.43 & 219.492690893877 & 21.1896714244213 \tabularnewline
0.44 & 224.621190141588 & 22.6208265264213 \tabularnewline
0.45 & 230.127044230806 & 24.420608431035 \tabularnewline
0.46 & 236.104768566304 & 26.734110791057 \tabularnewline
0.47 & 242.66856164483 & 29.6319787401808 \tabularnewline
0.48 & 249.933855882334 & 33.0610747234228 \tabularnewline
0.49 & 257.992475324446 & 36.8314608917246 \tabularnewline
0.5 & 266.887745638809 & 40.6447270146314 \tabularnewline
0.51 & 276.597103036709 & 44.1496275813776 \tabularnewline
0.52 & 287.028506540209 & 47.0254603751978 \tabularnewline
0.53 & 298.033328751622 & 49.0545870644978 \tabularnewline
0.54 & 309.433373624327 & 50.1806468836568 \tabularnewline
0.55 & 321.054916494421 & 50.5173401394793 \tabularnewline
0.56 & 332.759952320585 & 50.317823143705 \tabularnewline
0.57 & 344.465341920272 & 49.8945020701877 \tabularnewline
0.58 & 356.144302131827 & 49.5209612281996 \tabularnewline
0.59 & 367.810492038157 & 49.3469843357406 \tabularnewline
0.6 & 379.490750118369 & 49.3536385143132 \tabularnewline
0.61 & 391.19619747424 & 49.3804044472302 \tabularnewline
0.62 & 402.901563374667 & 49.1936279734569 \tabularnewline
0.63 & 414.539178132128 & 48.5824363842284 \tabularnewline
0.64 & 426.008480629873 & 47.4246046124683 \tabularnewline
0.65 & 437.196342296119 & 45.7268717612143 \tabularnewline
0.66 & 448.000207912291 & 43.6048987057148 \tabularnewline
0.67 & 458.346202861783 & 41.2390765186451 \tabularnewline
0.68 & 468.19763505083 & 38.8177057686523 \tabularnewline
0.69 & 477.554009810509 & 36.4891267942082 \tabularnewline
0.7 & 486.444460174893 & 34.3464009351129 \tabularnewline
0.71 & 494.920589282578 & 32.4443223001628 \tabularnewline
0.72 & 503.051801835252 & 30.828191105584 \tabularnewline
0.73 & 510.922609409801 & 29.5514485959266 \tabularnewline
0.74 & 518.62843798008 & 28.6642923717995 \tabularnewline
0.75 & 526.266122395725 & 28.1669673572519 \tabularnewline
0.76 & 533.918009767621 & 27.9802836282129 \tabularnewline
0.77 & 541.633043265205 & 27.9311407362091 \tabularnewline
0.78 & 549.41193113414 & 27.7940642143088 \tabularnewline
0.79 & 557.204435027966 & 27.3622092696423 \tabularnewline
0.8 & 564.924271247894 & 26.5194295992202 \tabularnewline
0.81 & 572.481912897459 & 25.294086366143 \tabularnewline
0.82 & 579.829145200804 & 23.8818023937803 \tabularnewline
0.83 & 587.002859223313 & 22.6274888239899 \tabularnewline
0.84 & 594.150676690487 & 21.9527817186029 \tabularnewline
0.85 & 601.520163722526 & 22.194066083303 \tabularnewline
0.86 & 609.400615181527 & 23.3966739096392 \tabularnewline
0.87 & 618.024468664993 & 25.1841868720933 \tabularnewline
0.88 & 627.460528539865 & 26.8468274644679 \tabularnewline
0.89 & 637.549376831271 & 27.6132733405979 \tabularnewline
0.9 & 647.924545543075 & 26.9781750240891 \tabularnewline
0.91 & 658.126638715186 & 24.9231833403443 \tabularnewline
0.92 & 667.773826773452 & 21.9235852590765 \tabularnewline
0.93 & 676.732374716949 & 18.7712100231274 \tabularnewline
0.94 & 685.234577199022 & 16.3601007297673 \tabularnewline
0.95 & 693.894572471276 & 15.3916376860621 \tabularnewline
0.96 & 703.596513069952 & 15.8506160803028 \tabularnewline
0.97 & 715.20643584594 & 17.0736676544702 \tabularnewline
0.98 & 728.598589089984 & 17.4591704945479 \tabularnewline
0.99 & 740.59562035185 & 11.501526635672 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211055&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]74.3056236145027[/C][C]10.831202712286[/C][/ROW]
[ROW][C]0.02[/C][C]84.8261093045009[/C][C]11.1714537837566[/C][/ROW]
[ROW][C]0.03[/C][C]93.6273540276786[/C][C]9.46855114449859[/C][/ROW]
[ROW][C]0.04[/C][C]99.8865446076085[/C][C]7.10431334544555[/C][/ROW]
[ROW][C]0.05[/C][C]104.093035889074[/C][C]5.2673392743989[/C][/ROW]
[ROW][C]0.06[/C][C]106.99497516717[/C][C]4.31251599824459[/C][/ROW]
[ROW][C]0.07[/C][C]109.250570865872[/C][C]4.24854014373719[/C][/ROW]
[ROW][C]0.08[/C][C]111.329551257073[/C][C]4.83420133726271[/C][/ROW]
[ROW][C]0.09[/C][C]113.511231291672[/C][C]5.73162445273933[/C][/ROW]
[ROW][C]0.1[/C][C]115.917523046423[/C][C]6.68970711347124[/C][/ROW]
[ROW][C]0.11[/C][C]118.559807833476[/C][C]7.54095031132422[/C][/ROW]
[ROW][C]0.12[/C][C]121.382576427512[/C][C]8.16253470183795[/C][/ROW]
[ROW][C]0.13[/C][C]124.297184847366[/C][C]8.48553358418586[/C][/ROW]
[ROW][C]0.14[/C][C]127.210101291959[/C][C]8.52433086967127[/C][/ROW]
[ROW][C]0.15[/C][C]130.048313325174[/C][C]8.38170226770366[/C][/ROW]
[ROW][C]0.16[/C][C]132.77719155254[/C][C]8.20943605444787[/C][/ROW]
[ROW][C]0.17[/C][C]135.404645500728[/C][C]8.1487449376244[/C][/ROW]
[ROW][C]0.18[/C][C]137.971028640801[/C][C]8.27966759014306[/C][/ROW]
[ROW][C]0.19[/C][C]140.530645860822[/C][C]8.60418032459114[/C][/ROW]
[ROW][C]0.2[/C][C]143.132966838976[/C][C]9.06410612038509[/C][/ROW]
[ROW][C]0.21[/C][C]145.809666322697[/C][C]9.57233258715722[/C][/ROW]
[ROW][C]0.22[/C][C]148.569963369291[/C][C]10.0462316856915[/C][/ROW]
[ROW][C]0.23[/C][C]151.403591947577[/C][C]10.4284651407306[/C][/ROW]
[ROW][C]0.24[/C][C]154.288830107549[/C][C]10.6994511003384[/C][/ROW]
[ROW][C]0.25[/C][C]157.202209955697[/C][C]10.8789372787088[/C][/ROW]
[ROW][C]0.26[/C][C]160.126629209279[/C][C]11.0125558171302[/C][/ROW]
[ROW][C]0.27[/C][C]163.055532084373[/C][C]11.1522396213786[/C][/ROW]
[ROW][C]0.28[/C][C]165.992455408263[/C][C]11.3342641764258[/C][/ROW]
[ROW][C]0.29[/C][C]168.947049790909[/C][C]11.568512140196[/C][/ROW]
[ROW][C]0.3[/C][C]171.929977314309[/C][C]11.8386094265171[/C][/ROW]
[ROW][C]0.31[/C][C]174.949301454175[/C][C]12.119988396184[/C][/ROW]
[ROW][C]0.32[/C][C]178.01004754339[/C][C]12.3983107345803[/C][/ROW]
[ROW][C]0.33[/C][C]181.116985088187[/C][C]12.6828507728712[/C][/ROW]
[ROW][C]0.34[/C][C]184.279124994417[/C][C]13.0100486632336[/C][/ROW]
[ROW][C]0.35[/C][C]187.513617207915[/C][C]13.4326100188331[/C][/ROW]
[ROW][C]0.36[/C][C]190.846988913825[/C][C]13.9995637692022[/C][/ROW]
[ROW][C]0.37[/C][C]194.312831918856[/C][C]14.7368900409675[/C][/ROW]
[ROW][C]0.38[/C][C]197.946633278363[/C][C]15.6344327349093[/C][/ROW]
[ROW][C]0.39[/C][C]201.779820595114[/C][C]16.6506423739953[/C][/ROW]
[ROW][C]0.4[/C][C]205.83573321772[/C][C]17.7316325993287[/C][/ROW]
[ROW][C]0.41[/C][C]210.129856786459[/C][C]18.8372176879491[/C][/ROW]
[ROW][C]0.42[/C][C]214.675318336997[/C][C]19.9694111344391[/C][/ROW]
[ROW][C]0.43[/C][C]219.492690893877[/C][C]21.1896714244213[/C][/ROW]
[ROW][C]0.44[/C][C]224.621190141588[/C][C]22.6208265264213[/C][/ROW]
[ROW][C]0.45[/C][C]230.127044230806[/C][C]24.420608431035[/C][/ROW]
[ROW][C]0.46[/C][C]236.104768566304[/C][C]26.734110791057[/C][/ROW]
[ROW][C]0.47[/C][C]242.66856164483[/C][C]29.6319787401808[/C][/ROW]
[ROW][C]0.48[/C][C]249.933855882334[/C][C]33.0610747234228[/C][/ROW]
[ROW][C]0.49[/C][C]257.992475324446[/C][C]36.8314608917246[/C][/ROW]
[ROW][C]0.5[/C][C]266.887745638809[/C][C]40.6447270146314[/C][/ROW]
[ROW][C]0.51[/C][C]276.597103036709[/C][C]44.1496275813776[/C][/ROW]
[ROW][C]0.52[/C][C]287.028506540209[/C][C]47.0254603751978[/C][/ROW]
[ROW][C]0.53[/C][C]298.033328751622[/C][C]49.0545870644978[/C][/ROW]
[ROW][C]0.54[/C][C]309.433373624327[/C][C]50.1806468836568[/C][/ROW]
[ROW][C]0.55[/C][C]321.054916494421[/C][C]50.5173401394793[/C][/ROW]
[ROW][C]0.56[/C][C]332.759952320585[/C][C]50.317823143705[/C][/ROW]
[ROW][C]0.57[/C][C]344.465341920272[/C][C]49.8945020701877[/C][/ROW]
[ROW][C]0.58[/C][C]356.144302131827[/C][C]49.5209612281996[/C][/ROW]
[ROW][C]0.59[/C][C]367.810492038157[/C][C]49.3469843357406[/C][/ROW]
[ROW][C]0.6[/C][C]379.490750118369[/C][C]49.3536385143132[/C][/ROW]
[ROW][C]0.61[/C][C]391.19619747424[/C][C]49.3804044472302[/C][/ROW]
[ROW][C]0.62[/C][C]402.901563374667[/C][C]49.1936279734569[/C][/ROW]
[ROW][C]0.63[/C][C]414.539178132128[/C][C]48.5824363842284[/C][/ROW]
[ROW][C]0.64[/C][C]426.008480629873[/C][C]47.4246046124683[/C][/ROW]
[ROW][C]0.65[/C][C]437.196342296119[/C][C]45.7268717612143[/C][/ROW]
[ROW][C]0.66[/C][C]448.000207912291[/C][C]43.6048987057148[/C][/ROW]
[ROW][C]0.67[/C][C]458.346202861783[/C][C]41.2390765186451[/C][/ROW]
[ROW][C]0.68[/C][C]468.19763505083[/C][C]38.8177057686523[/C][/ROW]
[ROW][C]0.69[/C][C]477.554009810509[/C][C]36.4891267942082[/C][/ROW]
[ROW][C]0.7[/C][C]486.444460174893[/C][C]34.3464009351129[/C][/ROW]
[ROW][C]0.71[/C][C]494.920589282578[/C][C]32.4443223001628[/C][/ROW]
[ROW][C]0.72[/C][C]503.051801835252[/C][C]30.828191105584[/C][/ROW]
[ROW][C]0.73[/C][C]510.922609409801[/C][C]29.5514485959266[/C][/ROW]
[ROW][C]0.74[/C][C]518.62843798008[/C][C]28.6642923717995[/C][/ROW]
[ROW][C]0.75[/C][C]526.266122395725[/C][C]28.1669673572519[/C][/ROW]
[ROW][C]0.76[/C][C]533.918009767621[/C][C]27.9802836282129[/C][/ROW]
[ROW][C]0.77[/C][C]541.633043265205[/C][C]27.9311407362091[/C][/ROW]
[ROW][C]0.78[/C][C]549.41193113414[/C][C]27.7940642143088[/C][/ROW]
[ROW][C]0.79[/C][C]557.204435027966[/C][C]27.3622092696423[/C][/ROW]
[ROW][C]0.8[/C][C]564.924271247894[/C][C]26.5194295992202[/C][/ROW]
[ROW][C]0.81[/C][C]572.481912897459[/C][C]25.294086366143[/C][/ROW]
[ROW][C]0.82[/C][C]579.829145200804[/C][C]23.8818023937803[/C][/ROW]
[ROW][C]0.83[/C][C]587.002859223313[/C][C]22.6274888239899[/C][/ROW]
[ROW][C]0.84[/C][C]594.150676690487[/C][C]21.9527817186029[/C][/ROW]
[ROW][C]0.85[/C][C]601.520163722526[/C][C]22.194066083303[/C][/ROW]
[ROW][C]0.86[/C][C]609.400615181527[/C][C]23.3966739096392[/C][/ROW]
[ROW][C]0.87[/C][C]618.024468664993[/C][C]25.1841868720933[/C][/ROW]
[ROW][C]0.88[/C][C]627.460528539865[/C][C]26.8468274644679[/C][/ROW]
[ROW][C]0.89[/C][C]637.549376831271[/C][C]27.6132733405979[/C][/ROW]
[ROW][C]0.9[/C][C]647.924545543075[/C][C]26.9781750240891[/C][/ROW]
[ROW][C]0.91[/C][C]658.126638715186[/C][C]24.9231833403443[/C][/ROW]
[ROW][C]0.92[/C][C]667.773826773452[/C][C]21.9235852590765[/C][/ROW]
[ROW][C]0.93[/C][C]676.732374716949[/C][C]18.7712100231274[/C][/ROW]
[ROW][C]0.94[/C][C]685.234577199022[/C][C]16.3601007297673[/C][/ROW]
[ROW][C]0.95[/C][C]693.894572471276[/C][C]15.3916376860621[/C][/ROW]
[ROW][C]0.96[/C][C]703.596513069952[/C][C]15.8506160803028[/C][/ROW]
[ROW][C]0.97[/C][C]715.20643584594[/C][C]17.0736676544702[/C][/ROW]
[ROW][C]0.98[/C][C]728.598589089984[/C][C]17.4591704945479[/C][/ROW]
[ROW][C]0.99[/C][C]740.59562035185[/C][C]11.501526635672[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211055&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211055&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
0.0174.305623614502710.831202712286
0.0284.826109304500911.1714537837566
0.0393.62735402767869.46855114449859
0.0499.88654460760857.10431334544555
0.05104.0930358890745.2673392743989
0.06106.994975167174.31251599824459
0.07109.2505708658724.24854014373719
0.08111.3295512570734.83420133726271
0.09113.5112312916725.73162445273933
0.1115.9175230464236.68970711347124
0.11118.5598078334767.54095031132422
0.12121.3825764275128.16253470183795
0.13124.2971848473668.48553358418586
0.14127.2101012919598.52433086967127
0.15130.0483133251748.38170226770366
0.16132.777191552548.20943605444787
0.17135.4046455007288.1487449376244
0.18137.9710286408018.27966759014306
0.19140.5306458608228.60418032459114
0.2143.1329668389769.06410612038509
0.21145.8096663226979.57233258715722
0.22148.56996336929110.0462316856915
0.23151.40359194757710.4284651407306
0.24154.28883010754910.6994511003384
0.25157.20220995569710.8789372787088
0.26160.12662920927911.0125558171302
0.27163.05553208437311.1522396213786
0.28165.99245540826311.3342641764258
0.29168.94704979090911.568512140196
0.3171.92997731430911.8386094265171
0.31174.94930145417512.119988396184
0.32178.0100475433912.3983107345803
0.33181.11698508818712.6828507728712
0.34184.27912499441713.0100486632336
0.35187.51361720791513.4326100188331
0.36190.84698891382513.9995637692022
0.37194.31283191885614.7368900409675
0.38197.94663327836315.6344327349093
0.39201.77982059511416.6506423739953
0.4205.8357332177217.7316325993287
0.41210.12985678645918.8372176879491
0.42214.67531833699719.9694111344391
0.43219.49269089387721.1896714244213
0.44224.62119014158822.6208265264213
0.45230.12704423080624.420608431035
0.46236.10476856630426.734110791057
0.47242.6685616448329.6319787401808
0.48249.93385588233433.0610747234228
0.49257.99247532444636.8314608917246
0.5266.88774563880940.6447270146314
0.51276.59710303670944.1496275813776
0.52287.02850654020947.0254603751978
0.53298.03332875162249.0545870644978
0.54309.43337362432750.1806468836568
0.55321.05491649442150.5173401394793
0.56332.75995232058550.317823143705
0.57344.46534192027249.8945020701877
0.58356.14430213182749.5209612281996
0.59367.81049203815749.3469843357406
0.6379.49075011836949.3536385143132
0.61391.1961974742449.3804044472302
0.62402.90156337466749.1936279734569
0.63414.53917813212848.5824363842284
0.64426.00848062987347.4246046124683
0.65437.19634229611945.7268717612143
0.66448.00020791229143.6048987057148
0.67458.34620286178341.2390765186451
0.68468.1976350508338.8177057686523
0.69477.55400981050936.4891267942082
0.7486.44446017489334.3464009351129
0.71494.92058928257832.4443223001628
0.72503.05180183525230.828191105584
0.73510.92260940980129.5514485959266
0.74518.6284379800828.6642923717995
0.75526.26612239572528.1669673572519
0.76533.91800976762127.9802836282129
0.77541.63304326520527.9311407362091
0.78549.4119311341427.7940642143088
0.79557.20443502796627.3622092696423
0.8564.92427124789426.5194295992202
0.81572.48191289745925.294086366143
0.82579.82914520080423.8818023937803
0.83587.00285922331322.6274888239899
0.84594.15067669048721.9527817186029
0.85601.52016372252622.194066083303
0.86609.40061518152723.3966739096392
0.87618.02446866499325.1841868720933
0.88627.46052853986526.8468274644679
0.89637.54937683127127.6132733405979
0.9647.92454554307526.9781750240891
0.91658.12663871518624.9231833403443
0.92667.77382677345221.9235852590765
0.93676.73237471694918.7712100231274
0.94685.23457719902216.3601007297673
0.95693.89457247127615.3916376860621
0.96703.59651306995215.8506160803028
0.97715.2064358459417.0736676544702
0.98728.59858908998417.4591704945479
0.99740.5956203518511.501526635672


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Omzet UK Shipping (EUR) ; par2 = Niet gekend ; par3 = Deze reeks geeft de maandelijkse Shipping omzet (x1000) van de UK weer ; par4 = 12 ;
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')