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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 computationWed, 14 Aug 2013 09:28:37 -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/14/t1376486958x4ltfme6vszdogr.htm/, Retrieved Sun, 05 May 2024 00:33:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=211094, Retrieved Sun, 05 May 2024 00:33:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact190

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Stap 2/2] [2013-08-14 13:02:24] [1cfd0014ba435dd2b8f9632cac0a7144]
- RMP   [Harrell-Davis Quantiles] [Stap 6 / 2] [2013-08-14 13:20:36] [9b490dd2ab715f1b5bf65aa31d98df3d]
- R P       [Harrell-Davis Quantiles] [Stap 7/2] [2013-08-14 13:28:37] [38a0db91cd47487c7649642dcb33e029] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10320
11400
9360
10080
10080
10800
10320
9720
10440
11160
9480
11160
9840
11160
8760
10320
9600
10680
10200
10680
10200
12480
8880
11280
9480
11040
9240
9360
9240
10680
10680
10320
9960
12240
8880
11280
9360
10320
9840
9120
9360
10800
9840
11760
9960
11160
9240
11520
9000
10200
10200
9840
8760
11520
9120
11280
10560
10680
9960
10200
10200
10320
9600
10080
9120
10920
7800
11880
9360
10920
9840
9360
10680
9720
9960
10680
9120
10320
8040
11280
8880
11040
9600
9600
11040
9720
9480
10200
9360
10800
8520
11520
9120
11040
8880
9600
10440
8880
8520
10800
8880
10560
8400
12480
10560
10800
9840
8880

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211094&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]2 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=211094&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211094&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 time2 seconds
R Server'George Udny Yule' @ yule.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.017960.97417984623266.786595073661
0.028192.37729579617266.718358838385
0.038390.57802761896222.419686315845
0.048536.6586054515185.851148906787
0.058644.20906877407161.482108710055
0.068725.59335804806134.922597324916
0.078786.88363136003105.626052089395
0.088832.2122686045681.407888261282
0.098866.5587405554169.5464556778687
0.18895.4795066309272.0644177505178
0.118923.7124965454384.1925075725966
0.128954.1619661362499.0331926260424
0.138987.72325014971111.471014000218
0.149023.79226069953119.015882791758
0.159061.06885200626121.664164830905
0.169098.26603205621120.972061364436
0.179134.49648781628118.765419913984
0.189169.32122350893116.179903645335
0.199202.59958565824113.442326474684
0.29234.31581395539110.329842102682
0.219264.49327384679106.775361955796
0.229293.20998577145103.199762258902
0.239320.66026525864100.455290371718
0.249347.193147787799.4627978686061
0.259373.28765927283100.779574458709
0.269399.46879574122104.339629716248
0.279426.19987516005109.486839072666
0.289453.79441894484115.270417920812
0.299482.3765504395120.83125683649
0.39511.89478091656125.54895234955
0.319542.17306497321129.149225878722
0.329572.97358234275131.617698863766
0.339604.04916238508133.079969809708
0.349635.17492646992133.689150692749
0.359666.16131652639133.578458793345
0.369696.858168447132.808816070842
0.379727.15954607504131.560879525177
0.389757.01336462746130.066680554746
0.399786.43253596176128.688278138807
0.49815.49964855633127.820950580952
0.419844.35732843481127.764944485236
0.429873.18106214009128.639008861912
0.439902.13802772382130.292869896735
0.449931.34136031533132.325420983148
0.459960.81197829313134.16088338607
0.469990.45879327547135.202953691962
0.4710020.0834854413134.941936875469
0.4810049.4096834406133.090829341185
0.4910078.1302939085129.629361960307
0.510105.9625738221124.811731145574
0.5110132.6993768393119.10478635905
0.5210158.2469865631113.175659692459
0.5310182.6442566215107.680880075963
0.5410206.0628025735103.277051677251
0.5510228.7918655967100.438179808128
0.5610251.212834225899.5530704664759
0.5710273.7671112358100.783740909156
0.5810296.9182930447104.178253196252
0.5910321.1076091854109.529108535011
0.610346.7021483535116.393948343796
0.6110373.9391179662124.039802319637
0.6210402.8749013394131.47810810488
0.6310433.3522022614137.649519080536
0.6410464.9991460406141.566601258737
0.6510497.2692231253142.525369868128
0.6610529.5211265178140.278582817394
0.6710561.1258502455135.117568326802
0.6810591.5790961255127.842776143055
0.6910620.5938009744119.623362616767
0.710648.152040308111.7824715996
0.7110674.5062886024105.541796855787
0.7210700.1330214088101.805712435271
0.7310725.6520266665100.988665159151
0.7410751.7291310771102.984412451328
0.7510778.9782646751107.281026803655
0.7610807.8741590715113.076159542337
0.7710838.6838531862119.376516972092
0.7810871.425611741125.085265732129
0.7910905.8655944711129.195873476039
0.810941.5605264704130.973653268876
0.8110977.9451559985130.137843252351
0.8211014.4486663109126.939955223327
0.8311050.6126485505122.076091252571
0.8411086.184065503116.459819379324
0.8511121.1728448662111.057475170593
0.8611155.8864427816106.726027053225
0.8711190.9631394217104.308234639638
0.8811227.404734512104.705201862767
0.8911266.5708230003108.771451568873
0.911310.1056120906116.734486491147
0.9111359.8997515191127.846060956921
0.9211418.3956312542141.538371831827
0.9311489.5424236484160.129417265198
0.9411580.1389624736189.590123171005
0.9511700.1378456075234.259690537364
0.9611859.1505580472287.229302938197
0.9712055.9284260927320.955978636857
0.9812262.0705242851285.273798074749
0.9912418.5911150036147.551901307613

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 7960.97417984623 & 266.786595073661 \tabularnewline
0.02 & 8192.37729579617 & 266.718358838385 \tabularnewline
0.03 & 8390.57802761896 & 222.419686315845 \tabularnewline
0.04 & 8536.6586054515 & 185.851148906787 \tabularnewline
0.05 & 8644.20906877407 & 161.482108710055 \tabularnewline
0.06 & 8725.59335804806 & 134.922597324916 \tabularnewline
0.07 & 8786.88363136003 & 105.626052089395 \tabularnewline
0.08 & 8832.21226860456 & 81.407888261282 \tabularnewline
0.09 & 8866.55874055541 & 69.5464556778687 \tabularnewline
0.1 & 8895.47950663092 & 72.0644177505178 \tabularnewline
0.11 & 8923.71249654543 & 84.1925075725966 \tabularnewline
0.12 & 8954.16196613624 & 99.0331926260424 \tabularnewline
0.13 & 8987.72325014971 & 111.471014000218 \tabularnewline
0.14 & 9023.79226069953 & 119.015882791758 \tabularnewline
0.15 & 9061.06885200626 & 121.664164830905 \tabularnewline
0.16 & 9098.26603205621 & 120.972061364436 \tabularnewline
0.17 & 9134.49648781628 & 118.765419913984 \tabularnewline
0.18 & 9169.32122350893 & 116.179903645335 \tabularnewline
0.19 & 9202.59958565824 & 113.442326474684 \tabularnewline
0.2 & 9234.31581395539 & 110.329842102682 \tabularnewline
0.21 & 9264.49327384679 & 106.775361955796 \tabularnewline
0.22 & 9293.20998577145 & 103.199762258902 \tabularnewline
0.23 & 9320.66026525864 & 100.455290371718 \tabularnewline
0.24 & 9347.1931477877 & 99.4627978686061 \tabularnewline
0.25 & 9373.28765927283 & 100.779574458709 \tabularnewline
0.26 & 9399.46879574122 & 104.339629716248 \tabularnewline
0.27 & 9426.19987516005 & 109.486839072666 \tabularnewline
0.28 & 9453.79441894484 & 115.270417920812 \tabularnewline
0.29 & 9482.3765504395 & 120.83125683649 \tabularnewline
0.3 & 9511.89478091656 & 125.54895234955 \tabularnewline
0.31 & 9542.17306497321 & 129.149225878722 \tabularnewline
0.32 & 9572.97358234275 & 131.617698863766 \tabularnewline
0.33 & 9604.04916238508 & 133.079969809708 \tabularnewline
0.34 & 9635.17492646992 & 133.689150692749 \tabularnewline
0.35 & 9666.16131652639 & 133.578458793345 \tabularnewline
0.36 & 9696.858168447 & 132.808816070842 \tabularnewline
0.37 & 9727.15954607504 & 131.560879525177 \tabularnewline
0.38 & 9757.01336462746 & 130.066680554746 \tabularnewline
0.39 & 9786.43253596176 & 128.688278138807 \tabularnewline
0.4 & 9815.49964855633 & 127.820950580952 \tabularnewline
0.41 & 9844.35732843481 & 127.764944485236 \tabularnewline
0.42 & 9873.18106214009 & 128.639008861912 \tabularnewline
0.43 & 9902.13802772382 & 130.292869896735 \tabularnewline
0.44 & 9931.34136031533 & 132.325420983148 \tabularnewline
0.45 & 9960.81197829313 & 134.16088338607 \tabularnewline
0.46 & 9990.45879327547 & 135.202953691962 \tabularnewline
0.47 & 10020.0834854413 & 134.941936875469 \tabularnewline
0.48 & 10049.4096834406 & 133.090829341185 \tabularnewline
0.49 & 10078.1302939085 & 129.629361960307 \tabularnewline
0.5 & 10105.9625738221 & 124.811731145574 \tabularnewline
0.51 & 10132.6993768393 & 119.10478635905 \tabularnewline
0.52 & 10158.2469865631 & 113.175659692459 \tabularnewline
0.53 & 10182.6442566215 & 107.680880075963 \tabularnewline
0.54 & 10206.0628025735 & 103.277051677251 \tabularnewline
0.55 & 10228.7918655967 & 100.438179808128 \tabularnewline
0.56 & 10251.2128342258 & 99.5530704664759 \tabularnewline
0.57 & 10273.7671112358 & 100.783740909156 \tabularnewline
0.58 & 10296.9182930447 & 104.178253196252 \tabularnewline
0.59 & 10321.1076091854 & 109.529108535011 \tabularnewline
0.6 & 10346.7021483535 & 116.393948343796 \tabularnewline
0.61 & 10373.9391179662 & 124.039802319637 \tabularnewline
0.62 & 10402.8749013394 & 131.47810810488 \tabularnewline
0.63 & 10433.3522022614 & 137.649519080536 \tabularnewline
0.64 & 10464.9991460406 & 141.566601258737 \tabularnewline
0.65 & 10497.2692231253 & 142.525369868128 \tabularnewline
0.66 & 10529.5211265178 & 140.278582817394 \tabularnewline
0.67 & 10561.1258502455 & 135.117568326802 \tabularnewline
0.68 & 10591.5790961255 & 127.842776143055 \tabularnewline
0.69 & 10620.5938009744 & 119.623362616767 \tabularnewline
0.7 & 10648.152040308 & 111.7824715996 \tabularnewline
0.71 & 10674.5062886024 & 105.541796855787 \tabularnewline
0.72 & 10700.1330214088 & 101.805712435271 \tabularnewline
0.73 & 10725.6520266665 & 100.988665159151 \tabularnewline
0.74 & 10751.7291310771 & 102.984412451328 \tabularnewline
0.75 & 10778.9782646751 & 107.281026803655 \tabularnewline
0.76 & 10807.8741590715 & 113.076159542337 \tabularnewline
0.77 & 10838.6838531862 & 119.376516972092 \tabularnewline
0.78 & 10871.425611741 & 125.085265732129 \tabularnewline
0.79 & 10905.8655944711 & 129.195873476039 \tabularnewline
0.8 & 10941.5605264704 & 130.973653268876 \tabularnewline
0.81 & 10977.9451559985 & 130.137843252351 \tabularnewline
0.82 & 11014.4486663109 & 126.939955223327 \tabularnewline
0.83 & 11050.6126485505 & 122.076091252571 \tabularnewline
0.84 & 11086.184065503 & 116.459819379324 \tabularnewline
0.85 & 11121.1728448662 & 111.057475170593 \tabularnewline
0.86 & 11155.8864427816 & 106.726027053225 \tabularnewline
0.87 & 11190.9631394217 & 104.308234639638 \tabularnewline
0.88 & 11227.404734512 & 104.705201862767 \tabularnewline
0.89 & 11266.5708230003 & 108.771451568873 \tabularnewline
0.9 & 11310.1056120906 & 116.734486491147 \tabularnewline
0.91 & 11359.8997515191 & 127.846060956921 \tabularnewline
0.92 & 11418.3956312542 & 141.538371831827 \tabularnewline
0.93 & 11489.5424236484 & 160.129417265198 \tabularnewline
0.94 & 11580.1389624736 & 189.590123171005 \tabularnewline
0.95 & 11700.1378456075 & 234.259690537364 \tabularnewline
0.96 & 11859.1505580472 & 287.229302938197 \tabularnewline
0.97 & 12055.9284260927 & 320.955978636857 \tabularnewline
0.98 & 12262.0705242851 & 285.273798074749 \tabularnewline
0.99 & 12418.5911150036 & 147.551901307613 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211094&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]7960.97417984623[/C][C]266.786595073661[/C][/ROW]
[ROW][C]0.02[/C][C]8192.37729579617[/C][C]266.718358838385[/C][/ROW]
[ROW][C]0.03[/C][C]8390.57802761896[/C][C]222.419686315845[/C][/ROW]
[ROW][C]0.04[/C][C]8536.6586054515[/C][C]185.851148906787[/C][/ROW]
[ROW][C]0.05[/C][C]8644.20906877407[/C][C]161.482108710055[/C][/ROW]
[ROW][C]0.06[/C][C]8725.59335804806[/C][C]134.922597324916[/C][/ROW]
[ROW][C]0.07[/C][C]8786.88363136003[/C][C]105.626052089395[/C][/ROW]
[ROW][C]0.08[/C][C]8832.21226860456[/C][C]81.407888261282[/C][/ROW]
[ROW][C]0.09[/C][C]8866.55874055541[/C][C]69.5464556778687[/C][/ROW]
[ROW][C]0.1[/C][C]8895.47950663092[/C][C]72.0644177505178[/C][/ROW]
[ROW][C]0.11[/C][C]8923.71249654543[/C][C]84.1925075725966[/C][/ROW]
[ROW][C]0.12[/C][C]8954.16196613624[/C][C]99.0331926260424[/C][/ROW]
[ROW][C]0.13[/C][C]8987.72325014971[/C][C]111.471014000218[/C][/ROW]
[ROW][C]0.14[/C][C]9023.79226069953[/C][C]119.015882791758[/C][/ROW]
[ROW][C]0.15[/C][C]9061.06885200626[/C][C]121.664164830905[/C][/ROW]
[ROW][C]0.16[/C][C]9098.26603205621[/C][C]120.972061364436[/C][/ROW]
[ROW][C]0.17[/C][C]9134.49648781628[/C][C]118.765419913984[/C][/ROW]
[ROW][C]0.18[/C][C]9169.32122350893[/C][C]116.179903645335[/C][/ROW]
[ROW][C]0.19[/C][C]9202.59958565824[/C][C]113.442326474684[/C][/ROW]
[ROW][C]0.2[/C][C]9234.31581395539[/C][C]110.329842102682[/C][/ROW]
[ROW][C]0.21[/C][C]9264.49327384679[/C][C]106.775361955796[/C][/ROW]
[ROW][C]0.22[/C][C]9293.20998577145[/C][C]103.199762258902[/C][/ROW]
[ROW][C]0.23[/C][C]9320.66026525864[/C][C]100.455290371718[/C][/ROW]
[ROW][C]0.24[/C][C]9347.1931477877[/C][C]99.4627978686061[/C][/ROW]
[ROW][C]0.25[/C][C]9373.28765927283[/C][C]100.779574458709[/C][/ROW]
[ROW][C]0.26[/C][C]9399.46879574122[/C][C]104.339629716248[/C][/ROW]
[ROW][C]0.27[/C][C]9426.19987516005[/C][C]109.486839072666[/C][/ROW]
[ROW][C]0.28[/C][C]9453.79441894484[/C][C]115.270417920812[/C][/ROW]
[ROW][C]0.29[/C][C]9482.3765504395[/C][C]120.83125683649[/C][/ROW]
[ROW][C]0.3[/C][C]9511.89478091656[/C][C]125.54895234955[/C][/ROW]
[ROW][C]0.31[/C][C]9542.17306497321[/C][C]129.149225878722[/C][/ROW]
[ROW][C]0.32[/C][C]9572.97358234275[/C][C]131.617698863766[/C][/ROW]
[ROW][C]0.33[/C][C]9604.04916238508[/C][C]133.079969809708[/C][/ROW]
[ROW][C]0.34[/C][C]9635.17492646992[/C][C]133.689150692749[/C][/ROW]
[ROW][C]0.35[/C][C]9666.16131652639[/C][C]133.578458793345[/C][/ROW]
[ROW][C]0.36[/C][C]9696.858168447[/C][C]132.808816070842[/C][/ROW]
[ROW][C]0.37[/C][C]9727.15954607504[/C][C]131.560879525177[/C][/ROW]
[ROW][C]0.38[/C][C]9757.01336462746[/C][C]130.066680554746[/C][/ROW]
[ROW][C]0.39[/C][C]9786.43253596176[/C][C]128.688278138807[/C][/ROW]
[ROW][C]0.4[/C][C]9815.49964855633[/C][C]127.820950580952[/C][/ROW]
[ROW][C]0.41[/C][C]9844.35732843481[/C][C]127.764944485236[/C][/ROW]
[ROW][C]0.42[/C][C]9873.18106214009[/C][C]128.639008861912[/C][/ROW]
[ROW][C]0.43[/C][C]9902.13802772382[/C][C]130.292869896735[/C][/ROW]
[ROW][C]0.44[/C][C]9931.34136031533[/C][C]132.325420983148[/C][/ROW]
[ROW][C]0.45[/C][C]9960.81197829313[/C][C]134.16088338607[/C][/ROW]
[ROW][C]0.46[/C][C]9990.45879327547[/C][C]135.202953691962[/C][/ROW]
[ROW][C]0.47[/C][C]10020.0834854413[/C][C]134.941936875469[/C][/ROW]
[ROW][C]0.48[/C][C]10049.4096834406[/C][C]133.090829341185[/C][/ROW]
[ROW][C]0.49[/C][C]10078.1302939085[/C][C]129.629361960307[/C][/ROW]
[ROW][C]0.5[/C][C]10105.9625738221[/C][C]124.811731145574[/C][/ROW]
[ROW][C]0.51[/C][C]10132.6993768393[/C][C]119.10478635905[/C][/ROW]
[ROW][C]0.52[/C][C]10158.2469865631[/C][C]113.175659692459[/C][/ROW]
[ROW][C]0.53[/C][C]10182.6442566215[/C][C]107.680880075963[/C][/ROW]
[ROW][C]0.54[/C][C]10206.0628025735[/C][C]103.277051677251[/C][/ROW]
[ROW][C]0.55[/C][C]10228.7918655967[/C][C]100.438179808128[/C][/ROW]
[ROW][C]0.56[/C][C]10251.2128342258[/C][C]99.5530704664759[/C][/ROW]
[ROW][C]0.57[/C][C]10273.7671112358[/C][C]100.783740909156[/C][/ROW]
[ROW][C]0.58[/C][C]10296.9182930447[/C][C]104.178253196252[/C][/ROW]
[ROW][C]0.59[/C][C]10321.1076091854[/C][C]109.529108535011[/C][/ROW]
[ROW][C]0.6[/C][C]10346.7021483535[/C][C]116.393948343796[/C][/ROW]
[ROW][C]0.61[/C][C]10373.9391179662[/C][C]124.039802319637[/C][/ROW]
[ROW][C]0.62[/C][C]10402.8749013394[/C][C]131.47810810488[/C][/ROW]
[ROW][C]0.63[/C][C]10433.3522022614[/C][C]137.649519080536[/C][/ROW]
[ROW][C]0.64[/C][C]10464.9991460406[/C][C]141.566601258737[/C][/ROW]
[ROW][C]0.65[/C][C]10497.2692231253[/C][C]142.525369868128[/C][/ROW]
[ROW][C]0.66[/C][C]10529.5211265178[/C][C]140.278582817394[/C][/ROW]
[ROW][C]0.67[/C][C]10561.1258502455[/C][C]135.117568326802[/C][/ROW]
[ROW][C]0.68[/C][C]10591.5790961255[/C][C]127.842776143055[/C][/ROW]
[ROW][C]0.69[/C][C]10620.5938009744[/C][C]119.623362616767[/C][/ROW]
[ROW][C]0.7[/C][C]10648.152040308[/C][C]111.7824715996[/C][/ROW]
[ROW][C]0.71[/C][C]10674.5062886024[/C][C]105.541796855787[/C][/ROW]
[ROW][C]0.72[/C][C]10700.1330214088[/C][C]101.805712435271[/C][/ROW]
[ROW][C]0.73[/C][C]10725.6520266665[/C][C]100.988665159151[/C][/ROW]
[ROW][C]0.74[/C][C]10751.7291310771[/C][C]102.984412451328[/C][/ROW]
[ROW][C]0.75[/C][C]10778.9782646751[/C][C]107.281026803655[/C][/ROW]
[ROW][C]0.76[/C][C]10807.8741590715[/C][C]113.076159542337[/C][/ROW]
[ROW][C]0.77[/C][C]10838.6838531862[/C][C]119.376516972092[/C][/ROW]
[ROW][C]0.78[/C][C]10871.425611741[/C][C]125.085265732129[/C][/ROW]
[ROW][C]0.79[/C][C]10905.8655944711[/C][C]129.195873476039[/C][/ROW]
[ROW][C]0.8[/C][C]10941.5605264704[/C][C]130.973653268876[/C][/ROW]
[ROW][C]0.81[/C][C]10977.9451559985[/C][C]130.137843252351[/C][/ROW]
[ROW][C]0.82[/C][C]11014.4486663109[/C][C]126.939955223327[/C][/ROW]
[ROW][C]0.83[/C][C]11050.6126485505[/C][C]122.076091252571[/C][/ROW]
[ROW][C]0.84[/C][C]11086.184065503[/C][C]116.459819379324[/C][/ROW]
[ROW][C]0.85[/C][C]11121.1728448662[/C][C]111.057475170593[/C][/ROW]
[ROW][C]0.86[/C][C]11155.8864427816[/C][C]106.726027053225[/C][/ROW]
[ROW][C]0.87[/C][C]11190.9631394217[/C][C]104.308234639638[/C][/ROW]
[ROW][C]0.88[/C][C]11227.404734512[/C][C]104.705201862767[/C][/ROW]
[ROW][C]0.89[/C][C]11266.5708230003[/C][C]108.771451568873[/C][/ROW]
[ROW][C]0.9[/C][C]11310.1056120906[/C][C]116.734486491147[/C][/ROW]
[ROW][C]0.91[/C][C]11359.8997515191[/C][C]127.846060956921[/C][/ROW]
[ROW][C]0.92[/C][C]11418.3956312542[/C][C]141.538371831827[/C][/ROW]
[ROW][C]0.93[/C][C]11489.5424236484[/C][C]160.129417265198[/C][/ROW]
[ROW][C]0.94[/C][C]11580.1389624736[/C][C]189.590123171005[/C][/ROW]
[ROW][C]0.95[/C][C]11700.1378456075[/C][C]234.259690537364[/C][/ROW]
[ROW][C]0.96[/C][C]11859.1505580472[/C][C]287.229302938197[/C][/ROW]
[ROW][C]0.97[/C][C]12055.9284260927[/C][C]320.955978636857[/C][/ROW]
[ROW][C]0.98[/C][C]12262.0705242851[/C][C]285.273798074749[/C][/ROW]
[ROW][C]0.99[/C][C]12418.5911150036[/C][C]147.551901307613[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211094&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211094&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
0.017960.97417984623266.786595073661
0.028192.37729579617266.718358838385
0.038390.57802761896222.419686315845
0.048536.6586054515185.851148906787
0.058644.20906877407161.482108710055
0.068725.59335804806134.922597324916
0.078786.88363136003105.626052089395
0.088832.2122686045681.407888261282
0.098866.5587405554169.5464556778687
0.18895.4795066309272.0644177505178
0.118923.7124965454384.1925075725966
0.128954.1619661362499.0331926260424
0.138987.72325014971111.471014000218
0.149023.79226069953119.015882791758
0.159061.06885200626121.664164830905
0.169098.26603205621120.972061364436
0.179134.49648781628118.765419913984
0.189169.32122350893116.179903645335
0.199202.59958565824113.442326474684
0.29234.31581395539110.329842102682
0.219264.49327384679106.775361955796
0.229293.20998577145103.199762258902
0.239320.66026525864100.455290371718
0.249347.193147787799.4627978686061
0.259373.28765927283100.779574458709
0.269399.46879574122104.339629716248
0.279426.19987516005109.486839072666
0.289453.79441894484115.270417920812
0.299482.3765504395120.83125683649
0.39511.89478091656125.54895234955
0.319542.17306497321129.149225878722
0.329572.97358234275131.617698863766
0.339604.04916238508133.079969809708
0.349635.17492646992133.689150692749
0.359666.16131652639133.578458793345
0.369696.858168447132.808816070842
0.379727.15954607504131.560879525177
0.389757.01336462746130.066680554746
0.399786.43253596176128.688278138807
0.49815.49964855633127.820950580952
0.419844.35732843481127.764944485236
0.429873.18106214009128.639008861912
0.439902.13802772382130.292869896735
0.449931.34136031533132.325420983148
0.459960.81197829313134.16088338607
0.469990.45879327547135.202953691962
0.4710020.0834854413134.941936875469
0.4810049.4096834406133.090829341185
0.4910078.1302939085129.629361960307
0.510105.9625738221124.811731145574
0.5110132.6993768393119.10478635905
0.5210158.2469865631113.175659692459
0.5310182.6442566215107.680880075963
0.5410206.0628025735103.277051677251
0.5510228.7918655967100.438179808128
0.5610251.212834225899.5530704664759
0.5710273.7671112358100.783740909156
0.5810296.9182930447104.178253196252
0.5910321.1076091854109.529108535011
0.610346.7021483535116.393948343796
0.6110373.9391179662124.039802319637
0.6210402.8749013394131.47810810488
0.6310433.3522022614137.649519080536
0.6410464.9991460406141.566601258737
0.6510497.2692231253142.525369868128
0.6610529.5211265178140.278582817394
0.6710561.1258502455135.117568326802
0.6810591.5790961255127.842776143055
0.6910620.5938009744119.623362616767
0.710648.152040308111.7824715996
0.7110674.5062886024105.541796855787
0.7210700.1330214088101.805712435271
0.7310725.6520266665100.988665159151
0.7410751.7291310771102.984412451328
0.7510778.9782646751107.281026803655
0.7610807.8741590715113.076159542337
0.7710838.6838531862119.376516972092
0.7810871.425611741125.085265732129
0.7910905.8655944711129.195873476039
0.810941.5605264704130.973653268876
0.8110977.9451559985130.137843252351
0.8211014.4486663109126.939955223327
0.8311050.6126485505122.076091252571
0.8411086.184065503116.459819379324
0.8511121.1728448662111.057475170593
0.8611155.8864427816106.726027053225
0.8711190.9631394217104.308234639638
0.8811227.404734512104.705201862767
0.8911266.5708230003108.771451568873
0.911310.1056120906116.734486491147
0.9111359.8997515191127.846060956921
0.9211418.3956312542141.538371831827
0.9311489.5424236484160.129417265198
0.9411580.1389624736189.590123171005
0.9511700.1378456075234.259690537364
0.9611859.1505580472287.229302938197
0.9712055.9284260927320.955978636857
0.9812262.0705242851285.273798074749
0.9912418.5911150036147.551901307613


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')