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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 computationThu, 12 Aug 2010 10:41:18 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Aug/12/t1281609633keiqrw18mah6yk6.htm/, Retrieved Sat, 04 May 2024 15:44:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=78671, Retrieved Sat, 04 May 2024 15:44:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact159

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] [] [2010-08-12 09:55:01] [0054c34847e75ef4340aed26951eb951]
- RMP   [Central Tendency] [] [2010-08-12 10:10:20] [0054c34847e75ef4340aed26951eb951]
- RMPD    [Histogram] [] [2010-08-12 10:26:14] [2ee36997fb1be82ef07372b18c1a823d]
- RMP       [Kernel Density Estimation] [] [2010-08-12 10:31:03] [0054c34847e75ef4340aed26951eb951]
- RM D        [Notched Boxplots] [] [2010-08-12 10:35:05] [0054c34847e75ef4340aed26951eb951]
- RM D            [Harrell-Davis Quantiles] [] [2010-08-12 10:41:18] [ea4db07d8da34007b79212461ea6aa7b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
158
157
156
154
152
151
152
154
155
155
156
158
155
151
152
156
147
159
152
148
146
148
142
141
139
143
146
150
141
153
142
139
134
152
142
139
137
132
137
134
127
140
127
120
112
128
119
117
115
104
108
104
98
111
104
98
91
94
82
81
70
64
71
73
71
80
72
68
60
71
62
69
55
58
67
69
71
85
76
79
69
95
94
99

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' @ 72.249.76.132

\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' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78671&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' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78671&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78671&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' @ 72.249.76.132






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0156.2100967505782.73547385703459
0.0258.03259635274822.72117583460437
0.0359.90583049017472.95005046094339
0.0461.65746991188313.17322855769011
0.0563.26887280654083.22628949240648
0.0664.72063641505853.06342663204724
0.0765.98256409411992.73289370746289
0.0867.03921238117742.33349092495521
0.0967.9021762166451.96596900347696
0.168.60608916262811.70000286972248
0.1169.19749830263931.56546966237173
0.1269.72467088890741.56409892627648
0.1370.23193402046361.68870601979791
0.1470.7582167054971.93584382192745
0.1571.3375899750962.30323202529504
0.1671.9997199538682.78081848438934
0.1772.76930854532173.3481179598848
0.1873.66476701825413.97547108830345
0.1974.69694280941154.6293050497093
0.275.86862222057775.27804618423726
0.2177.17504763710765.89527900665061
0.2278.60520099287016.46091329628245
0.2380.14337727757516.95979605023134
0.2481.77065125507547.37914212202863
0.2583.46609992418857.70817604367046
0.2685.20789202030867.9393529113615
0.2786.97445374676498.07064962984198
0.2888.74583736515398.1092662151794
0.2990.50522877981338.07189207053119
0.392.2403493865447.98417309167553
0.3193.9444320917197.8770039675222
0.3295.61651354984747.78138213900618
0.3397.26094927839277.72329347371365
0.3498.8862515746247.72005906599697
0.35100.5034987036747.77869343696094
0.36102.1246245445057.897189038821
0.37103.7608677922898.06555557348567
0.38105.4215672679738.2700804158754
0.39107.1133761847428.49489695482607
0.4108.8398700077588.7238192876668
0.41110.6014614319818.94126894990698
0.42112.3955167248499.13334355721412
0.43114.2165821776939.28712727167048
0.44116.0566631553959.39074834931198
0.45117.9055359592019.43381185724692
0.46119.7511022944859.40754152038988
0.47121.5798105491249.30492385565720
0.48123.3771658717819.1222382775991
0.49125.1283355067738.85882075966826
0.5126.8188334068518.518134300846
0.51128.4352461195438.10757142772942
0.52129.9659464082567.63843653936912
0.53131.4017354309687.12468672827616
0.54132.7363588865896.58305116671057
0.55133.9668551831336.03153625772376
0.56135.0937108397275.48825647435558
0.57136.1208162406574.97030665428829
0.58137.0552303766824.49414691671462
0.59137.9067743442754.07318553340969
0.6138.6874795855733.71813877914764
0.61139.4109191952643.4363398724849
0.62140.0914515628513.23119806516974
0.63140.7434082602423.10110151740852
0.64141.3802647272363.03943661549376
0.65142.0138428153603.03509272180624
0.66142.6536051253093.07289941657704
0.67143.3061061867413.13517433279768
0.68143.9746587736053.20376336971629
0.69144.6592525824363.26187094072334
0.7145.3567310394833.29503811768393
0.71146.0612001096753.2921017234104
0.72146.7646225794813.24581674359936
0.73147.4575497479453.15283505025318
0.74148.1299569735913.01315920073096
0.75148.7721660444902.83064591371826
0.76149.3758360897062.61315804527345
0.77149.9349709643822.37210847955186
0.78150.4468263268232.12266068336495
0.79150.9125278582361.88274887403686
0.8151.337174933121.67114415253997
0.81151.7292451670891.50369122077004
0.82152.0992571939121.38996914382181
0.83152.4578720436581.32778377276593
0.84152.8138481155491.30324027707343
0.85153.1724080403401.29487869786739
0.86153.5345344634301.28117405461255
0.87153.8974611172881.24669888410409
0.88154.2562532587931.18619182060145
0.89154.6060612704691.10384468769260
0.9154.9445459834891.01166226457385
0.91155.2740667118360.925491607307447
0.92155.6031389041280.863594970722519
0.93155.9460456782860.843857961018087
0.94156.3188236562260.871244311185866
0.95156.7312957279330.915734850467907
0.96157.180620965460.912743000405367
0.97157.6570361173020.81753479226791
0.98158.1568744840040.708625359228917
0.99158.6527803073880.7895895079004

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 56.210096750578 & 2.73547385703459 \tabularnewline
0.02 & 58.0325963527482 & 2.72117583460437 \tabularnewline
0.03 & 59.9058304901747 & 2.95005046094339 \tabularnewline
0.04 & 61.6574699118831 & 3.17322855769011 \tabularnewline
0.05 & 63.2688728065408 & 3.22628949240648 \tabularnewline
0.06 & 64.7206364150585 & 3.06342663204724 \tabularnewline
0.07 & 65.9825640941199 & 2.73289370746289 \tabularnewline
0.08 & 67.0392123811774 & 2.33349092495521 \tabularnewline
0.09 & 67.902176216645 & 1.96596900347696 \tabularnewline
0.1 & 68.6060891626281 & 1.70000286972248 \tabularnewline
0.11 & 69.1974983026393 & 1.56546966237173 \tabularnewline
0.12 & 69.7246708889074 & 1.56409892627648 \tabularnewline
0.13 & 70.2319340204636 & 1.68870601979791 \tabularnewline
0.14 & 70.758216705497 & 1.93584382192745 \tabularnewline
0.15 & 71.337589975096 & 2.30323202529504 \tabularnewline
0.16 & 71.999719953868 & 2.78081848438934 \tabularnewline
0.17 & 72.7693085453217 & 3.3481179598848 \tabularnewline
0.18 & 73.6647670182541 & 3.97547108830345 \tabularnewline
0.19 & 74.6969428094115 & 4.6293050497093 \tabularnewline
0.2 & 75.8686222205777 & 5.27804618423726 \tabularnewline
0.21 & 77.1750476371076 & 5.89527900665061 \tabularnewline
0.22 & 78.6052009928701 & 6.46091329628245 \tabularnewline
0.23 & 80.1433772775751 & 6.95979605023134 \tabularnewline
0.24 & 81.7706512550754 & 7.37914212202863 \tabularnewline
0.25 & 83.4660999241885 & 7.70817604367046 \tabularnewline
0.26 & 85.2078920203086 & 7.9393529113615 \tabularnewline
0.27 & 86.9744537467649 & 8.07064962984198 \tabularnewline
0.28 & 88.7458373651539 & 8.1092662151794 \tabularnewline
0.29 & 90.5052287798133 & 8.07189207053119 \tabularnewline
0.3 & 92.240349386544 & 7.98417309167553 \tabularnewline
0.31 & 93.944432091719 & 7.8770039675222 \tabularnewline
0.32 & 95.6165135498474 & 7.78138213900618 \tabularnewline
0.33 & 97.2609492783927 & 7.72329347371365 \tabularnewline
0.34 & 98.886251574624 & 7.72005906599697 \tabularnewline
0.35 & 100.503498703674 & 7.77869343696094 \tabularnewline
0.36 & 102.124624544505 & 7.897189038821 \tabularnewline
0.37 & 103.760867792289 & 8.06555557348567 \tabularnewline
0.38 & 105.421567267973 & 8.2700804158754 \tabularnewline
0.39 & 107.113376184742 & 8.49489695482607 \tabularnewline
0.4 & 108.839870007758 & 8.7238192876668 \tabularnewline
0.41 & 110.601461431981 & 8.94126894990698 \tabularnewline
0.42 & 112.395516724849 & 9.13334355721412 \tabularnewline
0.43 & 114.216582177693 & 9.28712727167048 \tabularnewline
0.44 & 116.056663155395 & 9.39074834931198 \tabularnewline
0.45 & 117.905535959201 & 9.43381185724692 \tabularnewline
0.46 & 119.751102294485 & 9.40754152038988 \tabularnewline
0.47 & 121.579810549124 & 9.30492385565720 \tabularnewline
0.48 & 123.377165871781 & 9.1222382775991 \tabularnewline
0.49 & 125.128335506773 & 8.85882075966826 \tabularnewline
0.5 & 126.818833406851 & 8.518134300846 \tabularnewline
0.51 & 128.435246119543 & 8.10757142772942 \tabularnewline
0.52 & 129.965946408256 & 7.63843653936912 \tabularnewline
0.53 & 131.401735430968 & 7.12468672827616 \tabularnewline
0.54 & 132.736358886589 & 6.58305116671057 \tabularnewline
0.55 & 133.966855183133 & 6.03153625772376 \tabularnewline
0.56 & 135.093710839727 & 5.48825647435558 \tabularnewline
0.57 & 136.120816240657 & 4.97030665428829 \tabularnewline
0.58 & 137.055230376682 & 4.49414691671462 \tabularnewline
0.59 & 137.906774344275 & 4.07318553340969 \tabularnewline
0.6 & 138.687479585573 & 3.71813877914764 \tabularnewline
0.61 & 139.410919195264 & 3.4363398724849 \tabularnewline
0.62 & 140.091451562851 & 3.23119806516974 \tabularnewline
0.63 & 140.743408260242 & 3.10110151740852 \tabularnewline
0.64 & 141.380264727236 & 3.03943661549376 \tabularnewline
0.65 & 142.013842815360 & 3.03509272180624 \tabularnewline
0.66 & 142.653605125309 & 3.07289941657704 \tabularnewline
0.67 & 143.306106186741 & 3.13517433279768 \tabularnewline
0.68 & 143.974658773605 & 3.20376336971629 \tabularnewline
0.69 & 144.659252582436 & 3.26187094072334 \tabularnewline
0.7 & 145.356731039483 & 3.29503811768393 \tabularnewline
0.71 & 146.061200109675 & 3.2921017234104 \tabularnewline
0.72 & 146.764622579481 & 3.24581674359936 \tabularnewline
0.73 & 147.457549747945 & 3.15283505025318 \tabularnewline
0.74 & 148.129956973591 & 3.01315920073096 \tabularnewline
0.75 & 148.772166044490 & 2.83064591371826 \tabularnewline
0.76 & 149.375836089706 & 2.61315804527345 \tabularnewline
0.77 & 149.934970964382 & 2.37210847955186 \tabularnewline
0.78 & 150.446826326823 & 2.12266068336495 \tabularnewline
0.79 & 150.912527858236 & 1.88274887403686 \tabularnewline
0.8 & 151.33717493312 & 1.67114415253997 \tabularnewline
0.81 & 151.729245167089 & 1.50369122077004 \tabularnewline
0.82 & 152.099257193912 & 1.38996914382181 \tabularnewline
0.83 & 152.457872043658 & 1.32778377276593 \tabularnewline
0.84 & 152.813848115549 & 1.30324027707343 \tabularnewline
0.85 & 153.172408040340 & 1.29487869786739 \tabularnewline
0.86 & 153.534534463430 & 1.28117405461255 \tabularnewline
0.87 & 153.897461117288 & 1.24669888410409 \tabularnewline
0.88 & 154.256253258793 & 1.18619182060145 \tabularnewline
0.89 & 154.606061270469 & 1.10384468769260 \tabularnewline
0.9 & 154.944545983489 & 1.01166226457385 \tabularnewline
0.91 & 155.274066711836 & 0.925491607307447 \tabularnewline
0.92 & 155.603138904128 & 0.863594970722519 \tabularnewline
0.93 & 155.946045678286 & 0.843857961018087 \tabularnewline
0.94 & 156.318823656226 & 0.871244311185866 \tabularnewline
0.95 & 156.731295727933 & 0.915734850467907 \tabularnewline
0.96 & 157.18062096546 & 0.912743000405367 \tabularnewline
0.97 & 157.657036117302 & 0.81753479226791 \tabularnewline
0.98 & 158.156874484004 & 0.708625359228917 \tabularnewline
0.99 & 158.652780307388 & 0.7895895079004 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78671&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]56.210096750578[/C][C]2.73547385703459[/C][/ROW]
[ROW][C]0.02[/C][C]58.0325963527482[/C][C]2.72117583460437[/C][/ROW]
[ROW][C]0.03[/C][C]59.9058304901747[/C][C]2.95005046094339[/C][/ROW]
[ROW][C]0.04[/C][C]61.6574699118831[/C][C]3.17322855769011[/C][/ROW]
[ROW][C]0.05[/C][C]63.2688728065408[/C][C]3.22628949240648[/C][/ROW]
[ROW][C]0.06[/C][C]64.7206364150585[/C][C]3.06342663204724[/C][/ROW]
[ROW][C]0.07[/C][C]65.9825640941199[/C][C]2.73289370746289[/C][/ROW]
[ROW][C]0.08[/C][C]67.0392123811774[/C][C]2.33349092495521[/C][/ROW]
[ROW][C]0.09[/C][C]67.902176216645[/C][C]1.96596900347696[/C][/ROW]
[ROW][C]0.1[/C][C]68.6060891626281[/C][C]1.70000286972248[/C][/ROW]
[ROW][C]0.11[/C][C]69.1974983026393[/C][C]1.56546966237173[/C][/ROW]
[ROW][C]0.12[/C][C]69.7246708889074[/C][C]1.56409892627648[/C][/ROW]
[ROW][C]0.13[/C][C]70.2319340204636[/C][C]1.68870601979791[/C][/ROW]
[ROW][C]0.14[/C][C]70.758216705497[/C][C]1.93584382192745[/C][/ROW]
[ROW][C]0.15[/C][C]71.337589975096[/C][C]2.30323202529504[/C][/ROW]
[ROW][C]0.16[/C][C]71.999719953868[/C][C]2.78081848438934[/C][/ROW]
[ROW][C]0.17[/C][C]72.7693085453217[/C][C]3.3481179598848[/C][/ROW]
[ROW][C]0.18[/C][C]73.6647670182541[/C][C]3.97547108830345[/C][/ROW]
[ROW][C]0.19[/C][C]74.6969428094115[/C][C]4.6293050497093[/C][/ROW]
[ROW][C]0.2[/C][C]75.8686222205777[/C][C]5.27804618423726[/C][/ROW]
[ROW][C]0.21[/C][C]77.1750476371076[/C][C]5.89527900665061[/C][/ROW]
[ROW][C]0.22[/C][C]78.6052009928701[/C][C]6.46091329628245[/C][/ROW]
[ROW][C]0.23[/C][C]80.1433772775751[/C][C]6.95979605023134[/C][/ROW]
[ROW][C]0.24[/C][C]81.7706512550754[/C][C]7.37914212202863[/C][/ROW]
[ROW][C]0.25[/C][C]83.4660999241885[/C][C]7.70817604367046[/C][/ROW]
[ROW][C]0.26[/C][C]85.2078920203086[/C][C]7.9393529113615[/C][/ROW]
[ROW][C]0.27[/C][C]86.9744537467649[/C][C]8.07064962984198[/C][/ROW]
[ROW][C]0.28[/C][C]88.7458373651539[/C][C]8.1092662151794[/C][/ROW]
[ROW][C]0.29[/C][C]90.5052287798133[/C][C]8.07189207053119[/C][/ROW]
[ROW][C]0.3[/C][C]92.240349386544[/C][C]7.98417309167553[/C][/ROW]
[ROW][C]0.31[/C][C]93.944432091719[/C][C]7.8770039675222[/C][/ROW]
[ROW][C]0.32[/C][C]95.6165135498474[/C][C]7.78138213900618[/C][/ROW]
[ROW][C]0.33[/C][C]97.2609492783927[/C][C]7.72329347371365[/C][/ROW]
[ROW][C]0.34[/C][C]98.886251574624[/C][C]7.72005906599697[/C][/ROW]
[ROW][C]0.35[/C][C]100.503498703674[/C][C]7.77869343696094[/C][/ROW]
[ROW][C]0.36[/C][C]102.124624544505[/C][C]7.897189038821[/C][/ROW]
[ROW][C]0.37[/C][C]103.760867792289[/C][C]8.06555557348567[/C][/ROW]
[ROW][C]0.38[/C][C]105.421567267973[/C][C]8.2700804158754[/C][/ROW]
[ROW][C]0.39[/C][C]107.113376184742[/C][C]8.49489695482607[/C][/ROW]
[ROW][C]0.4[/C][C]108.839870007758[/C][C]8.7238192876668[/C][/ROW]
[ROW][C]0.41[/C][C]110.601461431981[/C][C]8.94126894990698[/C][/ROW]
[ROW][C]0.42[/C][C]112.395516724849[/C][C]9.13334355721412[/C][/ROW]
[ROW][C]0.43[/C][C]114.216582177693[/C][C]9.28712727167048[/C][/ROW]
[ROW][C]0.44[/C][C]116.056663155395[/C][C]9.39074834931198[/C][/ROW]
[ROW][C]0.45[/C][C]117.905535959201[/C][C]9.43381185724692[/C][/ROW]
[ROW][C]0.46[/C][C]119.751102294485[/C][C]9.40754152038988[/C][/ROW]
[ROW][C]0.47[/C][C]121.579810549124[/C][C]9.30492385565720[/C][/ROW]
[ROW][C]0.48[/C][C]123.377165871781[/C][C]9.1222382775991[/C][/ROW]
[ROW][C]0.49[/C][C]125.128335506773[/C][C]8.85882075966826[/C][/ROW]
[ROW][C]0.5[/C][C]126.818833406851[/C][C]8.518134300846[/C][/ROW]
[ROW][C]0.51[/C][C]128.435246119543[/C][C]8.10757142772942[/C][/ROW]
[ROW][C]0.52[/C][C]129.965946408256[/C][C]7.63843653936912[/C][/ROW]
[ROW][C]0.53[/C][C]131.401735430968[/C][C]7.12468672827616[/C][/ROW]
[ROW][C]0.54[/C][C]132.736358886589[/C][C]6.58305116671057[/C][/ROW]
[ROW][C]0.55[/C][C]133.966855183133[/C][C]6.03153625772376[/C][/ROW]
[ROW][C]0.56[/C][C]135.093710839727[/C][C]5.48825647435558[/C][/ROW]
[ROW][C]0.57[/C][C]136.120816240657[/C][C]4.97030665428829[/C][/ROW]
[ROW][C]0.58[/C][C]137.055230376682[/C][C]4.49414691671462[/C][/ROW]
[ROW][C]0.59[/C][C]137.906774344275[/C][C]4.07318553340969[/C][/ROW]
[ROW][C]0.6[/C][C]138.687479585573[/C][C]3.71813877914764[/C][/ROW]
[ROW][C]0.61[/C][C]139.410919195264[/C][C]3.4363398724849[/C][/ROW]
[ROW][C]0.62[/C][C]140.091451562851[/C][C]3.23119806516974[/C][/ROW]
[ROW][C]0.63[/C][C]140.743408260242[/C][C]3.10110151740852[/C][/ROW]
[ROW][C]0.64[/C][C]141.380264727236[/C][C]3.03943661549376[/C][/ROW]
[ROW][C]0.65[/C][C]142.013842815360[/C][C]3.03509272180624[/C][/ROW]
[ROW][C]0.66[/C][C]142.653605125309[/C][C]3.07289941657704[/C][/ROW]
[ROW][C]0.67[/C][C]143.306106186741[/C][C]3.13517433279768[/C][/ROW]
[ROW][C]0.68[/C][C]143.974658773605[/C][C]3.20376336971629[/C][/ROW]
[ROW][C]0.69[/C][C]144.659252582436[/C][C]3.26187094072334[/C][/ROW]
[ROW][C]0.7[/C][C]145.356731039483[/C][C]3.29503811768393[/C][/ROW]
[ROW][C]0.71[/C][C]146.061200109675[/C][C]3.2921017234104[/C][/ROW]
[ROW][C]0.72[/C][C]146.764622579481[/C][C]3.24581674359936[/C][/ROW]
[ROW][C]0.73[/C][C]147.457549747945[/C][C]3.15283505025318[/C][/ROW]
[ROW][C]0.74[/C][C]148.129956973591[/C][C]3.01315920073096[/C][/ROW]
[ROW][C]0.75[/C][C]148.772166044490[/C][C]2.83064591371826[/C][/ROW]
[ROW][C]0.76[/C][C]149.375836089706[/C][C]2.61315804527345[/C][/ROW]
[ROW][C]0.77[/C][C]149.934970964382[/C][C]2.37210847955186[/C][/ROW]
[ROW][C]0.78[/C][C]150.446826326823[/C][C]2.12266068336495[/C][/ROW]
[ROW][C]0.79[/C][C]150.912527858236[/C][C]1.88274887403686[/C][/ROW]
[ROW][C]0.8[/C][C]151.33717493312[/C][C]1.67114415253997[/C][/ROW]
[ROW][C]0.81[/C][C]151.729245167089[/C][C]1.50369122077004[/C][/ROW]
[ROW][C]0.82[/C][C]152.099257193912[/C][C]1.38996914382181[/C][/ROW]
[ROW][C]0.83[/C][C]152.457872043658[/C][C]1.32778377276593[/C][/ROW]
[ROW][C]0.84[/C][C]152.813848115549[/C][C]1.30324027707343[/C][/ROW]
[ROW][C]0.85[/C][C]153.172408040340[/C][C]1.29487869786739[/C][/ROW]
[ROW][C]0.86[/C][C]153.534534463430[/C][C]1.28117405461255[/C][/ROW]
[ROW][C]0.87[/C][C]153.897461117288[/C][C]1.24669888410409[/C][/ROW]
[ROW][C]0.88[/C][C]154.256253258793[/C][C]1.18619182060145[/C][/ROW]
[ROW][C]0.89[/C][C]154.606061270469[/C][C]1.10384468769260[/C][/ROW]
[ROW][C]0.9[/C][C]154.944545983489[/C][C]1.01166226457385[/C][/ROW]
[ROW][C]0.91[/C][C]155.274066711836[/C][C]0.925491607307447[/C][/ROW]
[ROW][C]0.92[/C][C]155.603138904128[/C][C]0.863594970722519[/C][/ROW]
[ROW][C]0.93[/C][C]155.946045678286[/C][C]0.843857961018087[/C][/ROW]
[ROW][C]0.94[/C][C]156.318823656226[/C][C]0.871244311185866[/C][/ROW]
[ROW][C]0.95[/C][C]156.731295727933[/C][C]0.915734850467907[/C][/ROW]
[ROW][C]0.96[/C][C]157.18062096546[/C][C]0.912743000405367[/C][/ROW]
[ROW][C]0.97[/C][C]157.657036117302[/C][C]0.81753479226791[/C][/ROW]
[ROW][C]0.98[/C][C]158.156874484004[/C][C]0.708625359228917[/C][/ROW]
[ROW][C]0.99[/C][C]158.652780307388[/C][C]0.7895895079004[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78671&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78671&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
0.0156.2100967505782.73547385703459
0.0258.03259635274822.72117583460437
0.0359.90583049017472.95005046094339
0.0461.65746991188313.17322855769011
0.0563.26887280654083.22628949240648
0.0664.72063641505853.06342663204724
0.0765.98256409411992.73289370746289
0.0867.03921238117742.33349092495521
0.0967.9021762166451.96596900347696
0.168.60608916262811.70000286972248
0.1169.19749830263931.56546966237173
0.1269.72467088890741.56409892627648
0.1370.23193402046361.68870601979791
0.1470.7582167054971.93584382192745
0.1571.3375899750962.30323202529504
0.1671.9997199538682.78081848438934
0.1772.76930854532173.3481179598848
0.1873.66476701825413.97547108830345
0.1974.69694280941154.6293050497093
0.275.86862222057775.27804618423726
0.2177.17504763710765.89527900665061
0.2278.60520099287016.46091329628245
0.2380.14337727757516.95979605023134
0.2481.77065125507547.37914212202863
0.2583.46609992418857.70817604367046
0.2685.20789202030867.9393529113615
0.2786.97445374676498.07064962984198
0.2888.74583736515398.1092662151794
0.2990.50522877981338.07189207053119
0.392.2403493865447.98417309167553
0.3193.9444320917197.8770039675222
0.3295.61651354984747.78138213900618
0.3397.26094927839277.72329347371365
0.3498.8862515746247.72005906599697
0.35100.5034987036747.77869343696094
0.36102.1246245445057.897189038821
0.37103.7608677922898.06555557348567
0.38105.4215672679738.2700804158754
0.39107.1133761847428.49489695482607
0.4108.8398700077588.7238192876668
0.41110.6014614319818.94126894990698
0.42112.3955167248499.13334355721412
0.43114.2165821776939.28712727167048
0.44116.0566631553959.39074834931198
0.45117.9055359592019.43381185724692
0.46119.7511022944859.40754152038988
0.47121.5798105491249.30492385565720
0.48123.3771658717819.1222382775991
0.49125.1283355067738.85882075966826
0.5126.8188334068518.518134300846
0.51128.4352461195438.10757142772942
0.52129.9659464082567.63843653936912
0.53131.4017354309687.12468672827616
0.54132.7363588865896.58305116671057
0.55133.9668551831336.03153625772376
0.56135.0937108397275.48825647435558
0.57136.1208162406574.97030665428829
0.58137.0552303766824.49414691671462
0.59137.9067743442754.07318553340969
0.6138.6874795855733.71813877914764
0.61139.4109191952643.4363398724849
0.62140.0914515628513.23119806516974
0.63140.7434082602423.10110151740852
0.64141.3802647272363.03943661549376
0.65142.0138428153603.03509272180624
0.66142.6536051253093.07289941657704
0.67143.3061061867413.13517433279768
0.68143.9746587736053.20376336971629
0.69144.6592525824363.26187094072334
0.7145.3567310394833.29503811768393
0.71146.0612001096753.2921017234104
0.72146.7646225794813.24581674359936
0.73147.4575497479453.15283505025318
0.74148.1299569735913.01315920073096
0.75148.7721660444902.83064591371826
0.76149.3758360897062.61315804527345
0.77149.9349709643822.37210847955186
0.78150.4468263268232.12266068336495
0.79150.9125278582361.88274887403686
0.8151.337174933121.67114415253997
0.81151.7292451670891.50369122077004
0.82152.0992571939121.38996914382181
0.83152.4578720436581.32778377276593
0.84152.8138481155491.30324027707343
0.85153.1724080403401.29487869786739
0.86153.5345344634301.28117405461255
0.87153.8974611172881.24669888410409
0.88154.2562532587931.18619182060145
0.89154.6060612704691.10384468769260
0.9154.9445459834891.01166226457385
0.91155.2740667118360.925491607307447
0.92155.6031389041280.863594970722519
0.93155.9460456782860.843857961018087
0.94156.3188236562260.871244311185866
0.95156.7312957279330.915734850467907
0.96157.180620965460.912743000405367
0.97157.6570361173020.81753479226791
0.98158.1568744840040.708625359228917
0.99158.6527803073880.7895895079004


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ;
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')