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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, 08 Aug 2016 14:17:28 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Aug/08/t1470663103z2gztgi9avbbaou.htm/, Retrieved Mon, 29 Apr 2024 09:21:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296093, Retrieved Mon, 29 Apr 2024 09:21:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact157

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] [Braadoven Omzet -...] [2016-08-08 13:17:28] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7175
7048.75
6922.5
6670
9225
9098.75
7175
5897.5
6023.75
6023.75
6150
6416.25
5645
4872.5
4240
4240
6670
6922.5
4998.75
2822.5
3973.75
3973.75
4872.5
5391.25
5265
3973.75
4620
4366.25
6542.5
6023.75
3973.75
2442.5
3847.5
4240
4620
5125
4100
3215
3595
3721.25
7048.75
7048.75
5125
4872.5
5645
5265
6290
7567.5
7821.25
6023.75
5517.5
4998.75
8466.25
8720
8073.75
8720
8592.5
7567.5
8720
9997.5
10516.25
8972.5
7947.5
8720
12047.5
13072.5
12820
13325
13198.75
11921.25
14097.5
14616.25
15375
13072.5
12173.75
13198.75
15641.25
17817.5
17298.75
17298.75
17552.5
16666.25
18970
18970
18577.5
16400
16792.5
17046.25
18716.25
20892.5
19348.75
20121.25
19475
19096.25
22045
21398.75
20500
19222.5
20500
21146.25
21917.5
22942.5
21917.5
22550
21778.75
21652.5
24853.75
25120
24095
22297.5
23828.75
24473.75
25246.25
26397.5
25246.25
26145
25752.5
24347.5
27296.25
27296.25

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'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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296093&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296093&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296093&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'George Udny Yule' @ yule.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.012718.87683583865396.223788986606
0.023103.76368669835408.778673050717
0.033425.80942784541346.515506403099
0.043654.86580803277259.999128671196
0.053808.80695401058192.756706544085
0.063915.00028931361157.79603931449
0.073997.53277411963155.438942943397
0.084073.596949331176.869262345135
0.094153.41823123016209.712628294851
0.14241.46199877254244.786894023948
0.114338.14737654132275.950430161629
0.124441.4430624614298.713116053623
0.134548.10268946126310.534764007003
0.144654.69980410475311.947992406044
0.154758.55935200172306.70311802088
0.164858.41267237918300.378314595413
0.174954.54994910182298.142644805555
0.185048.45026801559302.927482994859
0.195142.10384813196314.824000051452
0.25237.32346900772331.668738273522
0.215335.26947665068350.28950666717
0.225436.27900568549367.634848579388
0.235539.97493648518381.631635418808
0.245645.56024118627391.544486620505
0.255752.17388684824398.107678917326
0.265859.18813299611402.985656826186
0.275966.36180929729408.067593702215
0.286073.82381288371414.705469532076
0.296181.92747771194423.250354636596
0.36291.06373733126433.118407546721
0.316401.52883624917443.417664171193
0.326513.50803803701453.589747772775
0.336627.17724021111464.004268392737
0.346742.86738164883475.988074175875
0.356861.20696842434491.464458949782
0.366983.16734727611512.221556929565
0.377109.97809797164539.215708794095
0.387242.93791984214572.061543081226
0.397383.19678587969609.272615411437
0.47531.60855512761648.833784810245
0.417688.73956790953689.307713775936
0.427855.069718768730.737094338609
0.438031.35121974176775.395448915882
0.448219.01831745611827.763518967297
0.458420.49359859052893.612673391169
0.468639.23470862842978.26851924619
0.478879.419607294271084.29152120346
0.489145.271583689051209.73975829823
0.499440.150316221291347.72682235328
0.59765.64114166041487.2439120423
0.5110120.91866326991615.48007331444
0.5210502.61538943251720.69903077559
0.5310905.29331175221794.95842869192
0.5411322.43241044681836.14824622293
0.5511747.67614714741848.48894745007
0.5612175.9748553841841.16731213696
0.5712604.28635502841825.66042262042
0.5813031.63053958281812.01236459091
0.5913458.50713156991805.62738016329
0.613885.89813435241805.87982908425
0.6114314.21045886821806.86836468914
0.6214742.51938696911800.04082794727
0.6315168.34872676111777.65209156802
0.6415588.01869083461735.32065996279
0.6515997.38959921611673.17925508269
0.6616392.70868694911595.49364008606
0.6716771.27273896521508.95365157765
0.6817131.73923693291420.34381778683
0.6917474.09032523681335.14832772693
0.717799.39238440261256.73752436872
0.7118109.53406228581187.14169571661
0.7218407.05537574981128.00840862762
0.7318695.04905317181081.31282211668
0.7418977.00709640951048.84576346541
0.7519256.47295398821030.65708559897
0.7619536.45984872381023.82505785378
0.7719818.75862306731022.0140812571
0.7820103.3950821031017.02480554284
0.7920388.53081956691001.2276276166
0.820671.0085350815970.391371952028
0.8120947.5523427945925.527692821702
0.8221216.398065464873.850493614406
0.8321478.8955632832827.968101664496
0.8421740.4462017959803.28733384295
0.8522010.1080918981812.121128050155
0.8622298.4660645822856.133311373977
0.8722614.024690585921.535713891019
0.8822959.3016714821982.364241531033
0.8923328.4645993641010.40259432552
0.923708.1052215936987.162636767972
0.9124081.4142822393911.969760328968
0.9224434.4192049991802.221045244839
0.9324762.2243706394686.864351291748
0.9425073.3292294335598.632523066836
0.9525390.210734791563.2024508433
0.9625745.2316572364580.024715809868
0.9726170.0897887382624.809304418377
0.9826660.1779195984638.924101915484
0.9927099.210172136420.897359649751
127296.25NA

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 2718.87683583865 & 396.223788986606 \tabularnewline
0.02 & 3103.76368669835 & 408.778673050717 \tabularnewline
0.03 & 3425.80942784541 & 346.515506403099 \tabularnewline
0.04 & 3654.86580803277 & 259.999128671196 \tabularnewline
0.05 & 3808.80695401058 & 192.756706544085 \tabularnewline
0.06 & 3915.00028931361 & 157.79603931449 \tabularnewline
0.07 & 3997.53277411963 & 155.438942943397 \tabularnewline
0.08 & 4073.596949331 & 176.869262345135 \tabularnewline
0.09 & 4153.41823123016 & 209.712628294851 \tabularnewline
0.1 & 4241.46199877254 & 244.786894023948 \tabularnewline
0.11 & 4338.14737654132 & 275.950430161629 \tabularnewline
0.12 & 4441.4430624614 & 298.713116053623 \tabularnewline
0.13 & 4548.10268946126 & 310.534764007003 \tabularnewline
0.14 & 4654.69980410475 & 311.947992406044 \tabularnewline
0.15 & 4758.55935200172 & 306.70311802088 \tabularnewline
0.16 & 4858.41267237918 & 300.378314595413 \tabularnewline
0.17 & 4954.54994910182 & 298.142644805555 \tabularnewline
0.18 & 5048.45026801559 & 302.927482994859 \tabularnewline
0.19 & 5142.10384813196 & 314.824000051452 \tabularnewline
0.2 & 5237.32346900772 & 331.668738273522 \tabularnewline
0.21 & 5335.26947665068 & 350.28950666717 \tabularnewline
0.22 & 5436.27900568549 & 367.634848579388 \tabularnewline
0.23 & 5539.97493648518 & 381.631635418808 \tabularnewline
0.24 & 5645.56024118627 & 391.544486620505 \tabularnewline
0.25 & 5752.17388684824 & 398.107678917326 \tabularnewline
0.26 & 5859.18813299611 & 402.985656826186 \tabularnewline
0.27 & 5966.36180929729 & 408.067593702215 \tabularnewline
0.28 & 6073.82381288371 & 414.705469532076 \tabularnewline
0.29 & 6181.92747771194 & 423.250354636596 \tabularnewline
0.3 & 6291.06373733126 & 433.118407546721 \tabularnewline
0.31 & 6401.52883624917 & 443.417664171193 \tabularnewline
0.32 & 6513.50803803701 & 453.589747772775 \tabularnewline
0.33 & 6627.17724021111 & 464.004268392737 \tabularnewline
0.34 & 6742.86738164883 & 475.988074175875 \tabularnewline
0.35 & 6861.20696842434 & 491.464458949782 \tabularnewline
0.36 & 6983.16734727611 & 512.221556929565 \tabularnewline
0.37 & 7109.97809797164 & 539.215708794095 \tabularnewline
0.38 & 7242.93791984214 & 572.061543081226 \tabularnewline
0.39 & 7383.19678587969 & 609.272615411437 \tabularnewline
0.4 & 7531.60855512761 & 648.833784810245 \tabularnewline
0.41 & 7688.73956790953 & 689.307713775936 \tabularnewline
0.42 & 7855.069718768 & 730.737094338609 \tabularnewline
0.43 & 8031.35121974176 & 775.395448915882 \tabularnewline
0.44 & 8219.01831745611 & 827.763518967297 \tabularnewline
0.45 & 8420.49359859052 & 893.612673391169 \tabularnewline
0.46 & 8639.23470862842 & 978.26851924619 \tabularnewline
0.47 & 8879.41960729427 & 1084.29152120346 \tabularnewline
0.48 & 9145.27158368905 & 1209.73975829823 \tabularnewline
0.49 & 9440.15031622129 & 1347.72682235328 \tabularnewline
0.5 & 9765.6411416604 & 1487.2439120423 \tabularnewline
0.51 & 10120.9186632699 & 1615.48007331444 \tabularnewline
0.52 & 10502.6153894325 & 1720.69903077559 \tabularnewline
0.53 & 10905.2933117522 & 1794.95842869192 \tabularnewline
0.54 & 11322.4324104468 & 1836.14824622293 \tabularnewline
0.55 & 11747.6761471474 & 1848.48894745007 \tabularnewline
0.56 & 12175.974855384 & 1841.16731213696 \tabularnewline
0.57 & 12604.2863550284 & 1825.66042262042 \tabularnewline
0.58 & 13031.6305395828 & 1812.01236459091 \tabularnewline
0.59 & 13458.5071315699 & 1805.62738016329 \tabularnewline
0.6 & 13885.8981343524 & 1805.87982908425 \tabularnewline
0.61 & 14314.2104588682 & 1806.86836468914 \tabularnewline
0.62 & 14742.5193869691 & 1800.04082794727 \tabularnewline
0.63 & 15168.3487267611 & 1777.65209156802 \tabularnewline
0.64 & 15588.0186908346 & 1735.32065996279 \tabularnewline
0.65 & 15997.3895992161 & 1673.17925508269 \tabularnewline
0.66 & 16392.7086869491 & 1595.49364008606 \tabularnewline
0.67 & 16771.2727389652 & 1508.95365157765 \tabularnewline
0.68 & 17131.7392369329 & 1420.34381778683 \tabularnewline
0.69 & 17474.0903252368 & 1335.14832772693 \tabularnewline
0.7 & 17799.3923844026 & 1256.73752436872 \tabularnewline
0.71 & 18109.5340622858 & 1187.14169571661 \tabularnewline
0.72 & 18407.0553757498 & 1128.00840862762 \tabularnewline
0.73 & 18695.0490531718 & 1081.31282211668 \tabularnewline
0.74 & 18977.0070964095 & 1048.84576346541 \tabularnewline
0.75 & 19256.4729539882 & 1030.65708559897 \tabularnewline
0.76 & 19536.4598487238 & 1023.82505785378 \tabularnewline
0.77 & 19818.7586230673 & 1022.0140812571 \tabularnewline
0.78 & 20103.395082103 & 1017.02480554284 \tabularnewline
0.79 & 20388.5308195669 & 1001.2276276166 \tabularnewline
0.8 & 20671.0085350815 & 970.391371952028 \tabularnewline
0.81 & 20947.5523427945 & 925.527692821702 \tabularnewline
0.82 & 21216.398065464 & 873.850493614406 \tabularnewline
0.83 & 21478.8955632832 & 827.968101664496 \tabularnewline
0.84 & 21740.4462017959 & 803.28733384295 \tabularnewline
0.85 & 22010.1080918981 & 812.121128050155 \tabularnewline
0.86 & 22298.4660645822 & 856.133311373977 \tabularnewline
0.87 & 22614.024690585 & 921.535713891019 \tabularnewline
0.88 & 22959.3016714821 & 982.364241531033 \tabularnewline
0.89 & 23328.464599364 & 1010.40259432552 \tabularnewline
0.9 & 23708.1052215936 & 987.162636767972 \tabularnewline
0.91 & 24081.4142822393 & 911.969760328968 \tabularnewline
0.92 & 24434.4192049991 & 802.221045244839 \tabularnewline
0.93 & 24762.2243706394 & 686.864351291748 \tabularnewline
0.94 & 25073.3292294335 & 598.632523066836 \tabularnewline
0.95 & 25390.210734791 & 563.2024508433 \tabularnewline
0.96 & 25745.2316572364 & 580.024715809868 \tabularnewline
0.97 & 26170.0897887382 & 624.809304418377 \tabularnewline
0.98 & 26660.1779195984 & 638.924101915484 \tabularnewline
0.99 & 27099.210172136 & 420.897359649751 \tabularnewline
1 & 27296.25 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296093&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]2718.87683583865[/C][C]396.223788986606[/C][/ROW]
[ROW][C]0.02[/C][C]3103.76368669835[/C][C]408.778673050717[/C][/ROW]
[ROW][C]0.03[/C][C]3425.80942784541[/C][C]346.515506403099[/C][/ROW]
[ROW][C]0.04[/C][C]3654.86580803277[/C][C]259.999128671196[/C][/ROW]
[ROW][C]0.05[/C][C]3808.80695401058[/C][C]192.756706544085[/C][/ROW]
[ROW][C]0.06[/C][C]3915.00028931361[/C][C]157.79603931449[/C][/ROW]
[ROW][C]0.07[/C][C]3997.53277411963[/C][C]155.438942943397[/C][/ROW]
[ROW][C]0.08[/C][C]4073.596949331[/C][C]176.869262345135[/C][/ROW]
[ROW][C]0.09[/C][C]4153.41823123016[/C][C]209.712628294851[/C][/ROW]
[ROW][C]0.1[/C][C]4241.46199877254[/C][C]244.786894023948[/C][/ROW]
[ROW][C]0.11[/C][C]4338.14737654132[/C][C]275.950430161629[/C][/ROW]
[ROW][C]0.12[/C][C]4441.4430624614[/C][C]298.713116053623[/C][/ROW]
[ROW][C]0.13[/C][C]4548.10268946126[/C][C]310.534764007003[/C][/ROW]
[ROW][C]0.14[/C][C]4654.69980410475[/C][C]311.947992406044[/C][/ROW]
[ROW][C]0.15[/C][C]4758.55935200172[/C][C]306.70311802088[/C][/ROW]
[ROW][C]0.16[/C][C]4858.41267237918[/C][C]300.378314595413[/C][/ROW]
[ROW][C]0.17[/C][C]4954.54994910182[/C][C]298.142644805555[/C][/ROW]
[ROW][C]0.18[/C][C]5048.45026801559[/C][C]302.927482994859[/C][/ROW]
[ROW][C]0.19[/C][C]5142.10384813196[/C][C]314.824000051452[/C][/ROW]
[ROW][C]0.2[/C][C]5237.32346900772[/C][C]331.668738273522[/C][/ROW]
[ROW][C]0.21[/C][C]5335.26947665068[/C][C]350.28950666717[/C][/ROW]
[ROW][C]0.22[/C][C]5436.27900568549[/C][C]367.634848579388[/C][/ROW]
[ROW][C]0.23[/C][C]5539.97493648518[/C][C]381.631635418808[/C][/ROW]
[ROW][C]0.24[/C][C]5645.56024118627[/C][C]391.544486620505[/C][/ROW]
[ROW][C]0.25[/C][C]5752.17388684824[/C][C]398.107678917326[/C][/ROW]
[ROW][C]0.26[/C][C]5859.18813299611[/C][C]402.985656826186[/C][/ROW]
[ROW][C]0.27[/C][C]5966.36180929729[/C][C]408.067593702215[/C][/ROW]
[ROW][C]0.28[/C][C]6073.82381288371[/C][C]414.705469532076[/C][/ROW]
[ROW][C]0.29[/C][C]6181.92747771194[/C][C]423.250354636596[/C][/ROW]
[ROW][C]0.3[/C][C]6291.06373733126[/C][C]433.118407546721[/C][/ROW]
[ROW][C]0.31[/C][C]6401.52883624917[/C][C]443.417664171193[/C][/ROW]
[ROW][C]0.32[/C][C]6513.50803803701[/C][C]453.589747772775[/C][/ROW]
[ROW][C]0.33[/C][C]6627.17724021111[/C][C]464.004268392737[/C][/ROW]
[ROW][C]0.34[/C][C]6742.86738164883[/C][C]475.988074175875[/C][/ROW]
[ROW][C]0.35[/C][C]6861.20696842434[/C][C]491.464458949782[/C][/ROW]
[ROW][C]0.36[/C][C]6983.16734727611[/C][C]512.221556929565[/C][/ROW]
[ROW][C]0.37[/C][C]7109.97809797164[/C][C]539.215708794095[/C][/ROW]
[ROW][C]0.38[/C][C]7242.93791984214[/C][C]572.061543081226[/C][/ROW]
[ROW][C]0.39[/C][C]7383.19678587969[/C][C]609.272615411437[/C][/ROW]
[ROW][C]0.4[/C][C]7531.60855512761[/C][C]648.833784810245[/C][/ROW]
[ROW][C]0.41[/C][C]7688.73956790953[/C][C]689.307713775936[/C][/ROW]
[ROW][C]0.42[/C][C]7855.069718768[/C][C]730.737094338609[/C][/ROW]
[ROW][C]0.43[/C][C]8031.35121974176[/C][C]775.395448915882[/C][/ROW]
[ROW][C]0.44[/C][C]8219.01831745611[/C][C]827.763518967297[/C][/ROW]
[ROW][C]0.45[/C][C]8420.49359859052[/C][C]893.612673391169[/C][/ROW]
[ROW][C]0.46[/C][C]8639.23470862842[/C][C]978.26851924619[/C][/ROW]
[ROW][C]0.47[/C][C]8879.41960729427[/C][C]1084.29152120346[/C][/ROW]
[ROW][C]0.48[/C][C]9145.27158368905[/C][C]1209.73975829823[/C][/ROW]
[ROW][C]0.49[/C][C]9440.15031622129[/C][C]1347.72682235328[/C][/ROW]
[ROW][C]0.5[/C][C]9765.6411416604[/C][C]1487.2439120423[/C][/ROW]
[ROW][C]0.51[/C][C]10120.9186632699[/C][C]1615.48007331444[/C][/ROW]
[ROW][C]0.52[/C][C]10502.6153894325[/C][C]1720.69903077559[/C][/ROW]
[ROW][C]0.53[/C][C]10905.2933117522[/C][C]1794.95842869192[/C][/ROW]
[ROW][C]0.54[/C][C]11322.4324104468[/C][C]1836.14824622293[/C][/ROW]
[ROW][C]0.55[/C][C]11747.6761471474[/C][C]1848.48894745007[/C][/ROW]
[ROW][C]0.56[/C][C]12175.974855384[/C][C]1841.16731213696[/C][/ROW]
[ROW][C]0.57[/C][C]12604.2863550284[/C][C]1825.66042262042[/C][/ROW]
[ROW][C]0.58[/C][C]13031.6305395828[/C][C]1812.01236459091[/C][/ROW]
[ROW][C]0.59[/C][C]13458.5071315699[/C][C]1805.62738016329[/C][/ROW]
[ROW][C]0.6[/C][C]13885.8981343524[/C][C]1805.87982908425[/C][/ROW]
[ROW][C]0.61[/C][C]14314.2104588682[/C][C]1806.86836468914[/C][/ROW]
[ROW][C]0.62[/C][C]14742.5193869691[/C][C]1800.04082794727[/C][/ROW]
[ROW][C]0.63[/C][C]15168.3487267611[/C][C]1777.65209156802[/C][/ROW]
[ROW][C]0.64[/C][C]15588.0186908346[/C][C]1735.32065996279[/C][/ROW]
[ROW][C]0.65[/C][C]15997.3895992161[/C][C]1673.17925508269[/C][/ROW]
[ROW][C]0.66[/C][C]16392.7086869491[/C][C]1595.49364008606[/C][/ROW]
[ROW][C]0.67[/C][C]16771.2727389652[/C][C]1508.95365157765[/C][/ROW]
[ROW][C]0.68[/C][C]17131.7392369329[/C][C]1420.34381778683[/C][/ROW]
[ROW][C]0.69[/C][C]17474.0903252368[/C][C]1335.14832772693[/C][/ROW]
[ROW][C]0.7[/C][C]17799.3923844026[/C][C]1256.73752436872[/C][/ROW]
[ROW][C]0.71[/C][C]18109.5340622858[/C][C]1187.14169571661[/C][/ROW]
[ROW][C]0.72[/C][C]18407.0553757498[/C][C]1128.00840862762[/C][/ROW]
[ROW][C]0.73[/C][C]18695.0490531718[/C][C]1081.31282211668[/C][/ROW]
[ROW][C]0.74[/C][C]18977.0070964095[/C][C]1048.84576346541[/C][/ROW]
[ROW][C]0.75[/C][C]19256.4729539882[/C][C]1030.65708559897[/C][/ROW]
[ROW][C]0.76[/C][C]19536.4598487238[/C][C]1023.82505785378[/C][/ROW]
[ROW][C]0.77[/C][C]19818.7586230673[/C][C]1022.0140812571[/C][/ROW]
[ROW][C]0.78[/C][C]20103.395082103[/C][C]1017.02480554284[/C][/ROW]
[ROW][C]0.79[/C][C]20388.5308195669[/C][C]1001.2276276166[/C][/ROW]
[ROW][C]0.8[/C][C]20671.0085350815[/C][C]970.391371952028[/C][/ROW]
[ROW][C]0.81[/C][C]20947.5523427945[/C][C]925.527692821702[/C][/ROW]
[ROW][C]0.82[/C][C]21216.398065464[/C][C]873.850493614406[/C][/ROW]
[ROW][C]0.83[/C][C]21478.8955632832[/C][C]827.968101664496[/C][/ROW]
[ROW][C]0.84[/C][C]21740.4462017959[/C][C]803.28733384295[/C][/ROW]
[ROW][C]0.85[/C][C]22010.1080918981[/C][C]812.121128050155[/C][/ROW]
[ROW][C]0.86[/C][C]22298.4660645822[/C][C]856.133311373977[/C][/ROW]
[ROW][C]0.87[/C][C]22614.024690585[/C][C]921.535713891019[/C][/ROW]
[ROW][C]0.88[/C][C]22959.3016714821[/C][C]982.364241531033[/C][/ROW]
[ROW][C]0.89[/C][C]23328.464599364[/C][C]1010.40259432552[/C][/ROW]
[ROW][C]0.9[/C][C]23708.1052215936[/C][C]987.162636767972[/C][/ROW]
[ROW][C]0.91[/C][C]24081.4142822393[/C][C]911.969760328968[/C][/ROW]
[ROW][C]0.92[/C][C]24434.4192049991[/C][C]802.221045244839[/C][/ROW]
[ROW][C]0.93[/C][C]24762.2243706394[/C][C]686.864351291748[/C][/ROW]
[ROW][C]0.94[/C][C]25073.3292294335[/C][C]598.632523066836[/C][/ROW]
[ROW][C]0.95[/C][C]25390.210734791[/C][C]563.2024508433[/C][/ROW]
[ROW][C]0.96[/C][C]25745.2316572364[/C][C]580.024715809868[/C][/ROW]
[ROW][C]0.97[/C][C]26170.0897887382[/C][C]624.809304418377[/C][/ROW]
[ROW][C]0.98[/C][C]26660.1779195984[/C][C]638.924101915484[/C][/ROW]
[ROW][C]0.99[/C][C]27099.210172136[/C][C]420.897359649751[/C][/ROW]
[ROW][C]1[/C][C]27296.25[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296093&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296093&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
0.012718.87683583865396.223788986606
0.023103.76368669835408.778673050717
0.033425.80942784541346.515506403099
0.043654.86580803277259.999128671196
0.053808.80695401058192.756706544085
0.063915.00028931361157.79603931449
0.073997.53277411963155.438942943397
0.084073.596949331176.869262345135
0.094153.41823123016209.712628294851
0.14241.46199877254244.786894023948
0.114338.14737654132275.950430161629
0.124441.4430624614298.713116053623
0.134548.10268946126310.534764007003
0.144654.69980410475311.947992406044
0.154758.55935200172306.70311802088
0.164858.41267237918300.378314595413
0.174954.54994910182298.142644805555
0.185048.45026801559302.927482994859
0.195142.10384813196314.824000051452
0.25237.32346900772331.668738273522
0.215335.26947665068350.28950666717
0.225436.27900568549367.634848579388
0.235539.97493648518381.631635418808
0.245645.56024118627391.544486620505
0.255752.17388684824398.107678917326
0.265859.18813299611402.985656826186
0.275966.36180929729408.067593702215
0.286073.82381288371414.705469532076
0.296181.92747771194423.250354636596
0.36291.06373733126433.118407546721
0.316401.52883624917443.417664171193
0.326513.50803803701453.589747772775
0.336627.17724021111464.004268392737
0.346742.86738164883475.988074175875
0.356861.20696842434491.464458949782
0.366983.16734727611512.221556929565
0.377109.97809797164539.215708794095
0.387242.93791984214572.061543081226
0.397383.19678587969609.272615411437
0.47531.60855512761648.833784810245
0.417688.73956790953689.307713775936
0.427855.069718768730.737094338609
0.438031.35121974176775.395448915882
0.448219.01831745611827.763518967297
0.458420.49359859052893.612673391169
0.468639.23470862842978.26851924619
0.478879.419607294271084.29152120346
0.489145.271583689051209.73975829823
0.499440.150316221291347.72682235328
0.59765.64114166041487.2439120423
0.5110120.91866326991615.48007331444
0.5210502.61538943251720.69903077559
0.5310905.29331175221794.95842869192
0.5411322.43241044681836.14824622293
0.5511747.67614714741848.48894745007
0.5612175.9748553841841.16731213696
0.5712604.28635502841825.66042262042
0.5813031.63053958281812.01236459091
0.5913458.50713156991805.62738016329
0.613885.89813435241805.87982908425
0.6114314.21045886821806.86836468914
0.6214742.51938696911800.04082794727
0.6315168.34872676111777.65209156802
0.6415588.01869083461735.32065996279
0.6515997.38959921611673.17925508269
0.6616392.70868694911595.49364008606
0.6716771.27273896521508.95365157765
0.6817131.73923693291420.34381778683
0.6917474.09032523681335.14832772693
0.717799.39238440261256.73752436872
0.7118109.53406228581187.14169571661
0.7218407.05537574981128.00840862762
0.7318695.04905317181081.31282211668
0.7418977.00709640951048.84576346541
0.7519256.47295398821030.65708559897
0.7619536.45984872381023.82505785378
0.7719818.75862306731022.0140812571
0.7820103.3950821031017.02480554284
0.7920388.53081956691001.2276276166
0.820671.0085350815970.391371952028
0.8120947.5523427945925.527692821702
0.8221216.398065464873.850493614406
0.8321478.8955632832827.968101664496
0.8421740.4462017959803.28733384295
0.8522010.1080918981812.121128050155
0.8622298.4660645822856.133311373977
0.8722614.024690585921.535713891019
0.8822959.3016714821982.364241531033
0.8923328.4645993641010.40259432552
0.923708.1052215936987.162636767972
0.9124081.4142822393911.969760328968
0.9224434.4192049991802.221045244839
0.9324762.2243706394686.864351291748
0.9425073.3292294335598.632523066836
0.9525390.210734791563.2024508433
0.9625745.2316572364580.024715809868
0.9726170.0897887382624.809304418377
0.9826660.1779195984638.924101915484
0.9927099.210172136420.897359649751
127296.25NA


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.01 ; par2 = 1 ; par3 = 0.01 ;
Parameters (R input):
par1 = 0.01 ; par2 = 1 ; par3 = 0.01 ;
R code (references can be found in the software module):
par3 <- '0.01'
par2 <- '1'
par1 <- '0.01'
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')