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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 computationTue, 12 Oct 2010 18:54:24 +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/Oct/12/t1286909661amxdo4990dx1voy.htm/, Retrieved Tue, 30 Apr 2024 16:09:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=83034, Retrieved Tue, 30 Apr 2024 16:09:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W42
Estimated Impact104

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Quartiles] [oef 1 opgave 3 st...] [2010-10-12 16:28:52] [ee977c9178adbf77d0a6da27ad6d4827]
- RM D  [Harrell-Davis Quantiles] [opgave 4 oef 1] [2010-10-12 18:05:34] [ee977c9178adbf77d0a6da27ad6d4827]
-    D      [Harrell-Davis Quantiles] [opgave 4 oef 2 st...] [2010-10-12 18:54:24] [3c84fba69796ffa9703fc49b6977555d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
102,8
106,3
103,7
106,9
104,3
105,4
96,2
95,7
95,9
93,6
94,7
94,5
96,6
96,7
98,9
102
105,2
106,4
99,3
96,4
93,1
95,6
93,3
96,7
105,6
105,2
107
104,9
104,5
105,2
99,7
100,2
98,5
98,4
97,1
98,4
100,6
111,3
119
117,8
108,8
109,3
103,5
103,7
110
105,5
110,4
106,7
110,2
105,2
108
108,1
107,2
106
99,4
100,2
100,3
100,8
99,5
100,2
103
111
120,5
109,5
106,6
105,5
103,9
104,9
104,8
99,6
97
95,4
99,3
103,9
107,4
107,4
111
113,2
108,5
113,3
113,8
105,3
107,5
109,4
118,9
119
115
124,1
120,5
117,7
117,1
118,1
119,6
118,8
124,9
124
124,9
121,7
121,6
125,1
127,9
129
130,1
130,3
127,9
124,1
125,7
129,2
129,2
132,6
131,5
131
125,8
127,2
127,3
127,5
122
118,4
118,3
115,5

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=83034&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=83034&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=83034&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'Gwilym Jenkins' @ 72.249.127.135






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0193.32191321015490.38680674624885
0.0293.76276867164350.664289576250056
0.0394.29407720710880.77036552505903
0.0494.8028011233620.73435140940704
0.0595.23491129392070.655277249529436
0.0695.5893970365310.592163426001349
0.0795.8887013229350.567370090259177
0.0896.15836017722160.581952101086422
0.0996.41965798693220.632297568532424
0.196.68859367935040.714551245193542
0.1196.9756207947040.815496777853025
0.1297.2843820344430.911533933237807
0.1397.61084508019080.977995894572305
0.1497.94468435589290.99995420533113
0.1598.27298820183440.978214717891954
0.1698.58467275435650.926266624487212
0.1798.87374238389730.865026230791227
0.1899.14048013383830.816712020190273
0.1999.3907637839280.798136945243876
0.299.63427560451740.820167906267709
0.2199.8823440659110.885116027472448
0.22100.1458497543620.987769711900614
0.23100.4333784651391.11564983772383
0.24100.7497453062941.25156346236253
0.25101.0950787549451.37602956141815
0.26101.4646904350701.47010477992910
0.27101.8498532819861.52079431800195
0.28102.2393722604491.52187364197982
0.29102.6215703703361.47608017962455
0.3102.9861710383081.39305681909039
0.31103.3256166905531.28607997130441
0.32103.6355936491031.16867492155270
0.33103.9148210602371.05197684627041
0.34104.1643767530910.943433215270677
0.35104.3868995553720.84699135106343
0.36104.5859307443290.764755609287866
0.37104.7655038653990.69822529177827
0.38104.9299455240380.648803628368757
0.39105.0837685345210.617970281610159
0.4105.2315382595720.606534664741462
0.41105.3776510015300.613977653050623
0.42105.5260401962770.637076723920624
0.43105.6798850200750.671467997601368
0.44105.8414155547380.712558196952925
0.45106.0118864828160.755434661643687
0.46106.191740198820.797297121497194
0.47106.3809210712950.836823512972044
0.48106.5792566151820.874902408429496
0.49106.7868037992360.91363377256689
0.5107.0040748999930.955703102200314
0.51107.2321014839761.00368330068224
0.52107.4723525086451.05901347881159
0.53107.7265739067651.12201988564789
0.54107.9966443393891.19243609289908
0.55108.2845339166811.26985958259931
0.56108.5924092514901.35523266379378
0.57108.9228607469691.45068760501846
0.58109.2791574243421.56019357885463
0.59109.6653854419151.68760431574628
0.6110.0863194944561.83618464469986
0.61110.546921451332.00532835999419
0.62111.0514528627942.19053056007221
0.63111.6023074617532.38048025968975
0.64112.1987861096922.55946792403880
0.65112.8361159638422.70832351871674
0.66113.5050288419502.80788279349842
0.67114.1921440906882.84252871040972
0.68114.8812508748672.80375052922341
0.69115.5553787757072.69287016659543
0.7116.1993309952302.52196135930618
0.71116.8021915154912.31257830023942
0.72117.3592621301172.09337562914902
0.73117.8729674089491.894646562495
0.74118.3524736087381.74399272404875
0.75118.8120470129861.65959375560091
0.76119.2684496994921.64652112845571
0.77119.7378649258901.69452988316353
0.78120.2329254436391.78183448171944
0.79120.7603979757441.88066278568373
0.8121.3199932059241.96319540677302
0.81121.9046403865152.00603288519984
0.82122.5023505946931.99568944591487
0.83123.0994207316641.93166794341113
0.84123.6841987562281.82741217549991
0.85124.2501323166631.70646847717727
0.86124.7967580693751.59334865454855
0.87125.3280307213361.5020936321631
0.88125.8488479224401.42952204801362
0.89126.3619444668601.36044505689775
0.9126.8672548815561.28225288309058
0.91127.3639384553731.19571990116645
0.92127.8530110530841.11137292929986
0.93128.3384577303061.03648087344968
0.94128.8271308681090.97015377027508
0.95129.3292714971520.913154905609269
0.96129.8599535470770.86837201362608
0.97130.4429638158540.829043720809081
0.98131.1251575101500.795930407996445
0.99131.9436231769660.86984634747216

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 93.3219132101549 & 0.38680674624885 \tabularnewline
0.02 & 93.7627686716435 & 0.664289576250056 \tabularnewline
0.03 & 94.2940772071088 & 0.77036552505903 \tabularnewline
0.04 & 94.802801123362 & 0.73435140940704 \tabularnewline
0.05 & 95.2349112939207 & 0.655277249529436 \tabularnewline
0.06 & 95.589397036531 & 0.592163426001349 \tabularnewline
0.07 & 95.888701322935 & 0.567370090259177 \tabularnewline
0.08 & 96.1583601772216 & 0.581952101086422 \tabularnewline
0.09 & 96.4196579869322 & 0.632297568532424 \tabularnewline
0.1 & 96.6885936793504 & 0.714551245193542 \tabularnewline
0.11 & 96.975620794704 & 0.815496777853025 \tabularnewline
0.12 & 97.284382034443 & 0.911533933237807 \tabularnewline
0.13 & 97.6108450801908 & 0.977995894572305 \tabularnewline
0.14 & 97.9446843558929 & 0.99995420533113 \tabularnewline
0.15 & 98.2729882018344 & 0.978214717891954 \tabularnewline
0.16 & 98.5846727543565 & 0.926266624487212 \tabularnewline
0.17 & 98.8737423838973 & 0.865026230791227 \tabularnewline
0.18 & 99.1404801338383 & 0.816712020190273 \tabularnewline
0.19 & 99.390763783928 & 0.798136945243876 \tabularnewline
0.2 & 99.6342756045174 & 0.820167906267709 \tabularnewline
0.21 & 99.882344065911 & 0.885116027472448 \tabularnewline
0.22 & 100.145849754362 & 0.987769711900614 \tabularnewline
0.23 & 100.433378465139 & 1.11564983772383 \tabularnewline
0.24 & 100.749745306294 & 1.25156346236253 \tabularnewline
0.25 & 101.095078754945 & 1.37602956141815 \tabularnewline
0.26 & 101.464690435070 & 1.47010477992910 \tabularnewline
0.27 & 101.849853281986 & 1.52079431800195 \tabularnewline
0.28 & 102.239372260449 & 1.52187364197982 \tabularnewline
0.29 & 102.621570370336 & 1.47608017962455 \tabularnewline
0.3 & 102.986171038308 & 1.39305681909039 \tabularnewline
0.31 & 103.325616690553 & 1.28607997130441 \tabularnewline
0.32 & 103.635593649103 & 1.16867492155270 \tabularnewline
0.33 & 103.914821060237 & 1.05197684627041 \tabularnewline
0.34 & 104.164376753091 & 0.943433215270677 \tabularnewline
0.35 & 104.386899555372 & 0.84699135106343 \tabularnewline
0.36 & 104.585930744329 & 0.764755609287866 \tabularnewline
0.37 & 104.765503865399 & 0.69822529177827 \tabularnewline
0.38 & 104.929945524038 & 0.648803628368757 \tabularnewline
0.39 & 105.083768534521 & 0.617970281610159 \tabularnewline
0.4 & 105.231538259572 & 0.606534664741462 \tabularnewline
0.41 & 105.377651001530 & 0.613977653050623 \tabularnewline
0.42 & 105.526040196277 & 0.637076723920624 \tabularnewline
0.43 & 105.679885020075 & 0.671467997601368 \tabularnewline
0.44 & 105.841415554738 & 0.712558196952925 \tabularnewline
0.45 & 106.011886482816 & 0.755434661643687 \tabularnewline
0.46 & 106.19174019882 & 0.797297121497194 \tabularnewline
0.47 & 106.380921071295 & 0.836823512972044 \tabularnewline
0.48 & 106.579256615182 & 0.874902408429496 \tabularnewline
0.49 & 106.786803799236 & 0.91363377256689 \tabularnewline
0.5 & 107.004074899993 & 0.955703102200314 \tabularnewline
0.51 & 107.232101483976 & 1.00368330068224 \tabularnewline
0.52 & 107.472352508645 & 1.05901347881159 \tabularnewline
0.53 & 107.726573906765 & 1.12201988564789 \tabularnewline
0.54 & 107.996644339389 & 1.19243609289908 \tabularnewline
0.55 & 108.284533916681 & 1.26985958259931 \tabularnewline
0.56 & 108.592409251490 & 1.35523266379378 \tabularnewline
0.57 & 108.922860746969 & 1.45068760501846 \tabularnewline
0.58 & 109.279157424342 & 1.56019357885463 \tabularnewline
0.59 & 109.665385441915 & 1.68760431574628 \tabularnewline
0.6 & 110.086319494456 & 1.83618464469986 \tabularnewline
0.61 & 110.54692145133 & 2.00532835999419 \tabularnewline
0.62 & 111.051452862794 & 2.19053056007221 \tabularnewline
0.63 & 111.602307461753 & 2.38048025968975 \tabularnewline
0.64 & 112.198786109692 & 2.55946792403880 \tabularnewline
0.65 & 112.836115963842 & 2.70832351871674 \tabularnewline
0.66 & 113.505028841950 & 2.80788279349842 \tabularnewline
0.67 & 114.192144090688 & 2.84252871040972 \tabularnewline
0.68 & 114.881250874867 & 2.80375052922341 \tabularnewline
0.69 & 115.555378775707 & 2.69287016659543 \tabularnewline
0.7 & 116.199330995230 & 2.52196135930618 \tabularnewline
0.71 & 116.802191515491 & 2.31257830023942 \tabularnewline
0.72 & 117.359262130117 & 2.09337562914902 \tabularnewline
0.73 & 117.872967408949 & 1.894646562495 \tabularnewline
0.74 & 118.352473608738 & 1.74399272404875 \tabularnewline
0.75 & 118.812047012986 & 1.65959375560091 \tabularnewline
0.76 & 119.268449699492 & 1.64652112845571 \tabularnewline
0.77 & 119.737864925890 & 1.69452988316353 \tabularnewline
0.78 & 120.232925443639 & 1.78183448171944 \tabularnewline
0.79 & 120.760397975744 & 1.88066278568373 \tabularnewline
0.8 & 121.319993205924 & 1.96319540677302 \tabularnewline
0.81 & 121.904640386515 & 2.00603288519984 \tabularnewline
0.82 & 122.502350594693 & 1.99568944591487 \tabularnewline
0.83 & 123.099420731664 & 1.93166794341113 \tabularnewline
0.84 & 123.684198756228 & 1.82741217549991 \tabularnewline
0.85 & 124.250132316663 & 1.70646847717727 \tabularnewline
0.86 & 124.796758069375 & 1.59334865454855 \tabularnewline
0.87 & 125.328030721336 & 1.5020936321631 \tabularnewline
0.88 & 125.848847922440 & 1.42952204801362 \tabularnewline
0.89 & 126.361944466860 & 1.36044505689775 \tabularnewline
0.9 & 126.867254881556 & 1.28225288309058 \tabularnewline
0.91 & 127.363938455373 & 1.19571990116645 \tabularnewline
0.92 & 127.853011053084 & 1.11137292929986 \tabularnewline
0.93 & 128.338457730306 & 1.03648087344968 \tabularnewline
0.94 & 128.827130868109 & 0.97015377027508 \tabularnewline
0.95 & 129.329271497152 & 0.913154905609269 \tabularnewline
0.96 & 129.859953547077 & 0.86837201362608 \tabularnewline
0.97 & 130.442963815854 & 0.829043720809081 \tabularnewline
0.98 & 131.125157510150 & 0.795930407996445 \tabularnewline
0.99 & 131.943623176966 & 0.86984634747216 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=83034&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]93.3219132101549[/C][C]0.38680674624885[/C][/ROW]
[ROW][C]0.02[/C][C]93.7627686716435[/C][C]0.664289576250056[/C][/ROW]
[ROW][C]0.03[/C][C]94.2940772071088[/C][C]0.77036552505903[/C][/ROW]
[ROW][C]0.04[/C][C]94.802801123362[/C][C]0.73435140940704[/C][/ROW]
[ROW][C]0.05[/C][C]95.2349112939207[/C][C]0.655277249529436[/C][/ROW]
[ROW][C]0.06[/C][C]95.589397036531[/C][C]0.592163426001349[/C][/ROW]
[ROW][C]0.07[/C][C]95.888701322935[/C][C]0.567370090259177[/C][/ROW]
[ROW][C]0.08[/C][C]96.1583601772216[/C][C]0.581952101086422[/C][/ROW]
[ROW][C]0.09[/C][C]96.4196579869322[/C][C]0.632297568532424[/C][/ROW]
[ROW][C]0.1[/C][C]96.6885936793504[/C][C]0.714551245193542[/C][/ROW]
[ROW][C]0.11[/C][C]96.975620794704[/C][C]0.815496777853025[/C][/ROW]
[ROW][C]0.12[/C][C]97.284382034443[/C][C]0.911533933237807[/C][/ROW]
[ROW][C]0.13[/C][C]97.6108450801908[/C][C]0.977995894572305[/C][/ROW]
[ROW][C]0.14[/C][C]97.9446843558929[/C][C]0.99995420533113[/C][/ROW]
[ROW][C]0.15[/C][C]98.2729882018344[/C][C]0.978214717891954[/C][/ROW]
[ROW][C]0.16[/C][C]98.5846727543565[/C][C]0.926266624487212[/C][/ROW]
[ROW][C]0.17[/C][C]98.8737423838973[/C][C]0.865026230791227[/C][/ROW]
[ROW][C]0.18[/C][C]99.1404801338383[/C][C]0.816712020190273[/C][/ROW]
[ROW][C]0.19[/C][C]99.390763783928[/C][C]0.798136945243876[/C][/ROW]
[ROW][C]0.2[/C][C]99.6342756045174[/C][C]0.820167906267709[/C][/ROW]
[ROW][C]0.21[/C][C]99.882344065911[/C][C]0.885116027472448[/C][/ROW]
[ROW][C]0.22[/C][C]100.145849754362[/C][C]0.987769711900614[/C][/ROW]
[ROW][C]0.23[/C][C]100.433378465139[/C][C]1.11564983772383[/C][/ROW]
[ROW][C]0.24[/C][C]100.749745306294[/C][C]1.25156346236253[/C][/ROW]
[ROW][C]0.25[/C][C]101.095078754945[/C][C]1.37602956141815[/C][/ROW]
[ROW][C]0.26[/C][C]101.464690435070[/C][C]1.47010477992910[/C][/ROW]
[ROW][C]0.27[/C][C]101.849853281986[/C][C]1.52079431800195[/C][/ROW]
[ROW][C]0.28[/C][C]102.239372260449[/C][C]1.52187364197982[/C][/ROW]
[ROW][C]0.29[/C][C]102.621570370336[/C][C]1.47608017962455[/C][/ROW]
[ROW][C]0.3[/C][C]102.986171038308[/C][C]1.39305681909039[/C][/ROW]
[ROW][C]0.31[/C][C]103.325616690553[/C][C]1.28607997130441[/C][/ROW]
[ROW][C]0.32[/C][C]103.635593649103[/C][C]1.16867492155270[/C][/ROW]
[ROW][C]0.33[/C][C]103.914821060237[/C][C]1.05197684627041[/C][/ROW]
[ROW][C]0.34[/C][C]104.164376753091[/C][C]0.943433215270677[/C][/ROW]
[ROW][C]0.35[/C][C]104.386899555372[/C][C]0.84699135106343[/C][/ROW]
[ROW][C]0.36[/C][C]104.585930744329[/C][C]0.764755609287866[/C][/ROW]
[ROW][C]0.37[/C][C]104.765503865399[/C][C]0.69822529177827[/C][/ROW]
[ROW][C]0.38[/C][C]104.929945524038[/C][C]0.648803628368757[/C][/ROW]
[ROW][C]0.39[/C][C]105.083768534521[/C][C]0.617970281610159[/C][/ROW]
[ROW][C]0.4[/C][C]105.231538259572[/C][C]0.606534664741462[/C][/ROW]
[ROW][C]0.41[/C][C]105.377651001530[/C][C]0.613977653050623[/C][/ROW]
[ROW][C]0.42[/C][C]105.526040196277[/C][C]0.637076723920624[/C][/ROW]
[ROW][C]0.43[/C][C]105.679885020075[/C][C]0.671467997601368[/C][/ROW]
[ROW][C]0.44[/C][C]105.841415554738[/C][C]0.712558196952925[/C][/ROW]
[ROW][C]0.45[/C][C]106.011886482816[/C][C]0.755434661643687[/C][/ROW]
[ROW][C]0.46[/C][C]106.19174019882[/C][C]0.797297121497194[/C][/ROW]
[ROW][C]0.47[/C][C]106.380921071295[/C][C]0.836823512972044[/C][/ROW]
[ROW][C]0.48[/C][C]106.579256615182[/C][C]0.874902408429496[/C][/ROW]
[ROW][C]0.49[/C][C]106.786803799236[/C][C]0.91363377256689[/C][/ROW]
[ROW][C]0.5[/C][C]107.004074899993[/C][C]0.955703102200314[/C][/ROW]
[ROW][C]0.51[/C][C]107.232101483976[/C][C]1.00368330068224[/C][/ROW]
[ROW][C]0.52[/C][C]107.472352508645[/C][C]1.05901347881159[/C][/ROW]
[ROW][C]0.53[/C][C]107.726573906765[/C][C]1.12201988564789[/C][/ROW]
[ROW][C]0.54[/C][C]107.996644339389[/C][C]1.19243609289908[/C][/ROW]
[ROW][C]0.55[/C][C]108.284533916681[/C][C]1.26985958259931[/C][/ROW]
[ROW][C]0.56[/C][C]108.592409251490[/C][C]1.35523266379378[/C][/ROW]
[ROW][C]0.57[/C][C]108.922860746969[/C][C]1.45068760501846[/C][/ROW]
[ROW][C]0.58[/C][C]109.279157424342[/C][C]1.56019357885463[/C][/ROW]
[ROW][C]0.59[/C][C]109.665385441915[/C][C]1.68760431574628[/C][/ROW]
[ROW][C]0.6[/C][C]110.086319494456[/C][C]1.83618464469986[/C][/ROW]
[ROW][C]0.61[/C][C]110.54692145133[/C][C]2.00532835999419[/C][/ROW]
[ROW][C]0.62[/C][C]111.051452862794[/C][C]2.19053056007221[/C][/ROW]
[ROW][C]0.63[/C][C]111.602307461753[/C][C]2.38048025968975[/C][/ROW]
[ROW][C]0.64[/C][C]112.198786109692[/C][C]2.55946792403880[/C][/ROW]
[ROW][C]0.65[/C][C]112.836115963842[/C][C]2.70832351871674[/C][/ROW]
[ROW][C]0.66[/C][C]113.505028841950[/C][C]2.80788279349842[/C][/ROW]
[ROW][C]0.67[/C][C]114.192144090688[/C][C]2.84252871040972[/C][/ROW]
[ROW][C]0.68[/C][C]114.881250874867[/C][C]2.80375052922341[/C][/ROW]
[ROW][C]0.69[/C][C]115.555378775707[/C][C]2.69287016659543[/C][/ROW]
[ROW][C]0.7[/C][C]116.199330995230[/C][C]2.52196135930618[/C][/ROW]
[ROW][C]0.71[/C][C]116.802191515491[/C][C]2.31257830023942[/C][/ROW]
[ROW][C]0.72[/C][C]117.359262130117[/C][C]2.09337562914902[/C][/ROW]
[ROW][C]0.73[/C][C]117.872967408949[/C][C]1.894646562495[/C][/ROW]
[ROW][C]0.74[/C][C]118.352473608738[/C][C]1.74399272404875[/C][/ROW]
[ROW][C]0.75[/C][C]118.812047012986[/C][C]1.65959375560091[/C][/ROW]
[ROW][C]0.76[/C][C]119.268449699492[/C][C]1.64652112845571[/C][/ROW]
[ROW][C]0.77[/C][C]119.737864925890[/C][C]1.69452988316353[/C][/ROW]
[ROW][C]0.78[/C][C]120.232925443639[/C][C]1.78183448171944[/C][/ROW]
[ROW][C]0.79[/C][C]120.760397975744[/C][C]1.88066278568373[/C][/ROW]
[ROW][C]0.8[/C][C]121.319993205924[/C][C]1.96319540677302[/C][/ROW]
[ROW][C]0.81[/C][C]121.904640386515[/C][C]2.00603288519984[/C][/ROW]
[ROW][C]0.82[/C][C]122.502350594693[/C][C]1.99568944591487[/C][/ROW]
[ROW][C]0.83[/C][C]123.099420731664[/C][C]1.93166794341113[/C][/ROW]
[ROW][C]0.84[/C][C]123.684198756228[/C][C]1.82741217549991[/C][/ROW]
[ROW][C]0.85[/C][C]124.250132316663[/C][C]1.70646847717727[/C][/ROW]
[ROW][C]0.86[/C][C]124.796758069375[/C][C]1.59334865454855[/C][/ROW]
[ROW][C]0.87[/C][C]125.328030721336[/C][C]1.5020936321631[/C][/ROW]
[ROW][C]0.88[/C][C]125.848847922440[/C][C]1.42952204801362[/C][/ROW]
[ROW][C]0.89[/C][C]126.361944466860[/C][C]1.36044505689775[/C][/ROW]
[ROW][C]0.9[/C][C]126.867254881556[/C][C]1.28225288309058[/C][/ROW]
[ROW][C]0.91[/C][C]127.363938455373[/C][C]1.19571990116645[/C][/ROW]
[ROW][C]0.92[/C][C]127.853011053084[/C][C]1.11137292929986[/C][/ROW]
[ROW][C]0.93[/C][C]128.338457730306[/C][C]1.03648087344968[/C][/ROW]
[ROW][C]0.94[/C][C]128.827130868109[/C][C]0.97015377027508[/C][/ROW]
[ROW][C]0.95[/C][C]129.329271497152[/C][C]0.913154905609269[/C][/ROW]
[ROW][C]0.96[/C][C]129.859953547077[/C][C]0.86837201362608[/C][/ROW]
[ROW][C]0.97[/C][C]130.442963815854[/C][C]0.829043720809081[/C][/ROW]
[ROW][C]0.98[/C][C]131.125157510150[/C][C]0.795930407996445[/C][/ROW]
[ROW][C]0.99[/C][C]131.943623176966[/C][C]0.86984634747216[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=83034&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=83034&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
0.0193.32191321015490.38680674624885
0.0293.76276867164350.664289576250056
0.0394.29407720710880.77036552505903
0.0494.8028011233620.73435140940704
0.0595.23491129392070.655277249529436
0.0695.5893970365310.592163426001349
0.0795.8887013229350.567370090259177
0.0896.15836017722160.581952101086422
0.0996.41965798693220.632297568532424
0.196.68859367935040.714551245193542
0.1196.9756207947040.815496777853025
0.1297.2843820344430.911533933237807
0.1397.61084508019080.977995894572305
0.1497.94468435589290.99995420533113
0.1598.27298820183440.978214717891954
0.1698.58467275435650.926266624487212
0.1798.87374238389730.865026230791227
0.1899.14048013383830.816712020190273
0.1999.3907637839280.798136945243876
0.299.63427560451740.820167906267709
0.2199.8823440659110.885116027472448
0.22100.1458497543620.987769711900614
0.23100.4333784651391.11564983772383
0.24100.7497453062941.25156346236253
0.25101.0950787549451.37602956141815
0.26101.4646904350701.47010477992910
0.27101.8498532819861.52079431800195
0.28102.2393722604491.52187364197982
0.29102.6215703703361.47608017962455
0.3102.9861710383081.39305681909039
0.31103.3256166905531.28607997130441
0.32103.6355936491031.16867492155270
0.33103.9148210602371.05197684627041
0.34104.1643767530910.943433215270677
0.35104.3868995553720.84699135106343
0.36104.5859307443290.764755609287866
0.37104.7655038653990.69822529177827
0.38104.9299455240380.648803628368757
0.39105.0837685345210.617970281610159
0.4105.2315382595720.606534664741462
0.41105.3776510015300.613977653050623
0.42105.5260401962770.637076723920624
0.43105.6798850200750.671467997601368
0.44105.8414155547380.712558196952925
0.45106.0118864828160.755434661643687
0.46106.191740198820.797297121497194
0.47106.3809210712950.836823512972044
0.48106.5792566151820.874902408429496
0.49106.7868037992360.91363377256689
0.5107.0040748999930.955703102200314
0.51107.2321014839761.00368330068224
0.52107.4723525086451.05901347881159
0.53107.7265739067651.12201988564789
0.54107.9966443393891.19243609289908
0.55108.2845339166811.26985958259931
0.56108.5924092514901.35523266379378
0.57108.9228607469691.45068760501846
0.58109.2791574243421.56019357885463
0.59109.6653854419151.68760431574628
0.6110.0863194944561.83618464469986
0.61110.546921451332.00532835999419
0.62111.0514528627942.19053056007221
0.63111.6023074617532.38048025968975
0.64112.1987861096922.55946792403880
0.65112.8361159638422.70832351871674
0.66113.5050288419502.80788279349842
0.67114.1921440906882.84252871040972
0.68114.8812508748672.80375052922341
0.69115.5553787757072.69287016659543
0.7116.1993309952302.52196135930618
0.71116.8021915154912.31257830023942
0.72117.3592621301172.09337562914902
0.73117.8729674089491.894646562495
0.74118.3524736087381.74399272404875
0.75118.8120470129861.65959375560091
0.76119.2684496994921.64652112845571
0.77119.7378649258901.69452988316353
0.78120.2329254436391.78183448171944
0.79120.7603979757441.88066278568373
0.8121.3199932059241.96319540677302
0.81121.9046403865152.00603288519984
0.82122.5023505946931.99568944591487
0.83123.0994207316641.93166794341113
0.84123.6841987562281.82741217549991
0.85124.2501323166631.70646847717727
0.86124.7967580693751.59334865454855
0.87125.3280307213361.5020936321631
0.88125.8488479224401.42952204801362
0.89126.3619444668601.36044505689775
0.9126.8672548815561.28225288309058
0.91127.3639384553731.19571990116645
0.92127.8530110530841.11137292929986
0.93128.3384577303061.03648087344968
0.94128.8271308681090.97015377027508
0.95129.3292714971520.913154905609269
0.96129.8599535470770.86837201362608
0.97130.4429638158540.829043720809081
0.98131.1251575101500.795930407996445
0.99131.9436231769660.86984634747216


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')