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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davies.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationWed, 29 Oct 2008 11:06:21 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/29/t1225300064nwwumqg3rsjdvez.htm/, Retrieved Tue, 14 May 2024 04:09:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19915, Retrieved Tue, 14 May 2024 04:09:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact193

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Mean Plot] [workshop 3] [2007-10-26 12:14:28] [e9ffc5de6f8a7be62f22b142b5b6b1a8]
F   PD  [Mean Plot] [seasonality on cl...] [2008-10-29 14:26:50] [495cd80c1a9baafb03c09cd9ab8d8fb5]
- RMPD      [Harrell-Davis Quantiles] [Task 4: Harrell-D...] [2008-10-29 17:06:21] [46e0445318a71ab85f6f82e54c656dac] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
109.20
88.60
94.30
98.30
86.40
80.60
104.10
108.20
93.40
71.90
94.10
94.90
96.40
91.10
84.40
86.40
88.00
75.10
109.70
103.00
82.10
68.00
96.40
94.30
90.00
88.00
76.10
82.50
81.40
66.50
97.20
94.10
80.70
70.50
87.80
89.50
99.60
84.20
75.10
92.00
80.80
73.10
99.80
90.00
83.10
72.40
78.80
87.30
91.00
80.10
73.60
86.40
74.50
71.20
92.40
81.50
85.30
69.90
84.20
90.70
100.30

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=19915&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=19915&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19915&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
0.0166.93552886464051.50511131042239
0.0267.62662295947281.55528123210153
0.0368.40365649869881.55840306390958
0.0469.14829610372211.48997525875405
0.0569.8113477903611.39238765195124
0.0670.38872235001741.31575761513653
0.0770.89631578145481.28157625519233
0.0871.35473629064721.28693064439856
0.0971.78237395683861.32099687991950
0.172.19340759201551.37596600777784
0.1172.59817503509491.44826178181682
0.1273.00430006486451.53751708650657
0.1373.41771564883211.64450126428302
0.1473.84324585240831.76932839521715
0.1574.28471853228241.90975783855626
0.1674.74472999439272.05984925490576
0.1775.2242403964692.21014931294521
0.1875.72219010393242.34820126929340
0.1976.23530634845842.46077239426292
0.276.75821681579582.53598849433557
0.2177.28390767866032.56568833999510
0.2277.80447501548632.54703463334982
0.2378.31204393282692.48279387933267
0.2478.79968929089582.38097318152519
0.2579.2621949302212.2535082783281
0.2679.69653030221722.11444854425374
0.2780.10198927951471.97775860058947
0.2880.48000602161471.85550425738537
0.2980.83371956247481.75659652120608
0.381.16739145285141.68576404301868
0.3181.48578678140711.64332585943454
0.3281.79361268195951.62639026614228
0.3382.09507858356211.62956183525773
0.3482.39360842319671.64671267325676
0.3582.69170461555641.67186456274807
0.3682.99094157370961.69967575099472
0.3783.29205464829111.72614692208603
0.3883.59508761662191.74832031549168
0.3983.89956588207141.76406435257018
0.484.20467036761671.77245010895322
0.4184.5093959633421.77327081904245
0.4284.81268627300541.76660147709101
0.4385.11354214311691.7532409417548
0.4485.41110474001071.73435520356541
0.4585.70471511723331.71116567949486
0.4685.99395203514081.68549250903118
0.4786.27864912521291.65877047012667
0.4886.5588920837641.63276799918921
0.4986.83499690154041.60892397043196
0.587.10747129869441.58841444237799
0.5187.37696330829751.57220071469155
0.5287.6442028502091.56037475427818
0.5387.90994355463871.55289208286734
0.5488.17491246073861.54921312328353
0.5588.4397741471191.54853798547242
0.5688.70511327533851.55014908485959
0.5788.97143575023381.55334410415646
0.5889.23918440148711.55755742207872
0.5989.50876122610831.56274120503065
0.689.78054585423761.56906300750029
0.6190.05489991274721.57676934616907
0.6290.3321498490461.58582364818683
0.6390.61254639259581.59629914679656
0.6490.89620628210511.60726385444782
0.6591.18304959626431.61730888106727
0.6691.47275198710961.62458617851067
0.6791.76473331558931.62713163169544
0.6892.0582011494821.62295561738323
0.6992.35225888704431.61101605956269
0.792.64607492844621.59150165164844
0.7192.9390938270361.56589672406022
0.7293.23125631960611.53749031718487
0.7393.52318647049061.51083097240274
0.7493.81630399746631.49116487634845
0.7594.1128294622241.48377073506729
0.7694.41566821443721.49251938093099
0.7794.72818227110751.51910600120464
0.7895.05388292421221.56283090024246
0.7995.39609639379321.62049586574660
0.895.75766767920661.68717813272473
0.8196.1407734522571.75730465039923
0.8296.54691376930951.82568897305951
0.8396.97714328817891.88808663822137
0.8497.43258060305851.94277148376724
0.8597.91519121097981.99146410485058
0.8698.42876858585792.04037373562957
0.8798.97993893571332.10051447513023
0.8899.57889825800492.18619484603964
0.89100.2394715309012.31111651856638
0.9100.9779833185912.48202259890824
0.91101.8103874647642.6930702561356
0.92102.7472326267862.92032025385456
0.93103.7865704214563.11775865522207
0.94104.9061096980373.21559520741125
0.95106.0577068531333.12921637118292
0.96107.1686316139792.78944884233111
0.97108.1528821988152.19331516715887
0.98108.9308025163171.45270844641198
0.99109.4496391059270.80110033342081

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 66.9355288646405 & 1.50511131042239 \tabularnewline
0.02 & 67.6266229594728 & 1.55528123210153 \tabularnewline
0.03 & 68.4036564986988 & 1.55840306390958 \tabularnewline
0.04 & 69.1482961037221 & 1.48997525875405 \tabularnewline
0.05 & 69.811347790361 & 1.39238765195124 \tabularnewline
0.06 & 70.3887223500174 & 1.31575761513653 \tabularnewline
0.07 & 70.8963157814548 & 1.28157625519233 \tabularnewline
0.08 & 71.3547362906472 & 1.28693064439856 \tabularnewline
0.09 & 71.7823739568386 & 1.32099687991950 \tabularnewline
0.1 & 72.1934075920155 & 1.37596600777784 \tabularnewline
0.11 & 72.5981750350949 & 1.44826178181682 \tabularnewline
0.12 & 73.0043000648645 & 1.53751708650657 \tabularnewline
0.13 & 73.4177156488321 & 1.64450126428302 \tabularnewline
0.14 & 73.8432458524083 & 1.76932839521715 \tabularnewline
0.15 & 74.2847185322824 & 1.90975783855626 \tabularnewline
0.16 & 74.7447299943927 & 2.05984925490576 \tabularnewline
0.17 & 75.224240396469 & 2.21014931294521 \tabularnewline
0.18 & 75.7221901039324 & 2.34820126929340 \tabularnewline
0.19 & 76.2353063484584 & 2.46077239426292 \tabularnewline
0.2 & 76.7582168157958 & 2.53598849433557 \tabularnewline
0.21 & 77.2839076786603 & 2.56568833999510 \tabularnewline
0.22 & 77.8044750154863 & 2.54703463334982 \tabularnewline
0.23 & 78.3120439328269 & 2.48279387933267 \tabularnewline
0.24 & 78.7996892908958 & 2.38097318152519 \tabularnewline
0.25 & 79.262194930221 & 2.2535082783281 \tabularnewline
0.26 & 79.6965303022172 & 2.11444854425374 \tabularnewline
0.27 & 80.1019892795147 & 1.97775860058947 \tabularnewline
0.28 & 80.4800060216147 & 1.85550425738537 \tabularnewline
0.29 & 80.8337195624748 & 1.75659652120608 \tabularnewline
0.3 & 81.1673914528514 & 1.68576404301868 \tabularnewline
0.31 & 81.4857867814071 & 1.64332585943454 \tabularnewline
0.32 & 81.7936126819595 & 1.62639026614228 \tabularnewline
0.33 & 82.0950785835621 & 1.62956183525773 \tabularnewline
0.34 & 82.3936084231967 & 1.64671267325676 \tabularnewline
0.35 & 82.6917046155564 & 1.67186456274807 \tabularnewline
0.36 & 82.9909415737096 & 1.69967575099472 \tabularnewline
0.37 & 83.2920546482911 & 1.72614692208603 \tabularnewline
0.38 & 83.5950876166219 & 1.74832031549168 \tabularnewline
0.39 & 83.8995658820714 & 1.76406435257018 \tabularnewline
0.4 & 84.2046703676167 & 1.77245010895322 \tabularnewline
0.41 & 84.509395963342 & 1.77327081904245 \tabularnewline
0.42 & 84.8126862730054 & 1.76660147709101 \tabularnewline
0.43 & 85.1135421431169 & 1.7532409417548 \tabularnewline
0.44 & 85.4111047400107 & 1.73435520356541 \tabularnewline
0.45 & 85.7047151172333 & 1.71116567949486 \tabularnewline
0.46 & 85.9939520351408 & 1.68549250903118 \tabularnewline
0.47 & 86.2786491252129 & 1.65877047012667 \tabularnewline
0.48 & 86.558892083764 & 1.63276799918921 \tabularnewline
0.49 & 86.8349969015404 & 1.60892397043196 \tabularnewline
0.5 & 87.1074712986944 & 1.58841444237799 \tabularnewline
0.51 & 87.3769633082975 & 1.57220071469155 \tabularnewline
0.52 & 87.644202850209 & 1.56037475427818 \tabularnewline
0.53 & 87.9099435546387 & 1.55289208286734 \tabularnewline
0.54 & 88.1749124607386 & 1.54921312328353 \tabularnewline
0.55 & 88.439774147119 & 1.54853798547242 \tabularnewline
0.56 & 88.7051132753385 & 1.55014908485959 \tabularnewline
0.57 & 88.9714357502338 & 1.55334410415646 \tabularnewline
0.58 & 89.2391844014871 & 1.55755742207872 \tabularnewline
0.59 & 89.5087612261083 & 1.56274120503065 \tabularnewline
0.6 & 89.7805458542376 & 1.56906300750029 \tabularnewline
0.61 & 90.0548999127472 & 1.57676934616907 \tabularnewline
0.62 & 90.332149849046 & 1.58582364818683 \tabularnewline
0.63 & 90.6125463925958 & 1.59629914679656 \tabularnewline
0.64 & 90.8962062821051 & 1.60726385444782 \tabularnewline
0.65 & 91.1830495962643 & 1.61730888106727 \tabularnewline
0.66 & 91.4727519871096 & 1.62458617851067 \tabularnewline
0.67 & 91.7647333155893 & 1.62713163169544 \tabularnewline
0.68 & 92.058201149482 & 1.62295561738323 \tabularnewline
0.69 & 92.3522588870443 & 1.61101605956269 \tabularnewline
0.7 & 92.6460749284462 & 1.59150165164844 \tabularnewline
0.71 & 92.939093827036 & 1.56589672406022 \tabularnewline
0.72 & 93.2312563196061 & 1.53749031718487 \tabularnewline
0.73 & 93.5231864704906 & 1.51083097240274 \tabularnewline
0.74 & 93.8163039974663 & 1.49116487634845 \tabularnewline
0.75 & 94.112829462224 & 1.48377073506729 \tabularnewline
0.76 & 94.4156682144372 & 1.49251938093099 \tabularnewline
0.77 & 94.7281822711075 & 1.51910600120464 \tabularnewline
0.78 & 95.0538829242122 & 1.56283090024246 \tabularnewline
0.79 & 95.3960963937932 & 1.62049586574660 \tabularnewline
0.8 & 95.7576676792066 & 1.68717813272473 \tabularnewline
0.81 & 96.140773452257 & 1.75730465039923 \tabularnewline
0.82 & 96.5469137693095 & 1.82568897305951 \tabularnewline
0.83 & 96.9771432881789 & 1.88808663822137 \tabularnewline
0.84 & 97.4325806030585 & 1.94277148376724 \tabularnewline
0.85 & 97.9151912109798 & 1.99146410485058 \tabularnewline
0.86 & 98.4287685858579 & 2.04037373562957 \tabularnewline
0.87 & 98.9799389357133 & 2.10051447513023 \tabularnewline
0.88 & 99.5788982580049 & 2.18619484603964 \tabularnewline
0.89 & 100.239471530901 & 2.31111651856638 \tabularnewline
0.9 & 100.977983318591 & 2.48202259890824 \tabularnewline
0.91 & 101.810387464764 & 2.6930702561356 \tabularnewline
0.92 & 102.747232626786 & 2.92032025385456 \tabularnewline
0.93 & 103.786570421456 & 3.11775865522207 \tabularnewline
0.94 & 104.906109698037 & 3.21559520741125 \tabularnewline
0.95 & 106.057706853133 & 3.12921637118292 \tabularnewline
0.96 & 107.168631613979 & 2.78944884233111 \tabularnewline
0.97 & 108.152882198815 & 2.19331516715887 \tabularnewline
0.98 & 108.930802516317 & 1.45270844641198 \tabularnewline
0.99 & 109.449639105927 & 0.80110033342081 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19915&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]66.9355288646405[/C][C]1.50511131042239[/C][/ROW]
[ROW][C]0.02[/C][C]67.6266229594728[/C][C]1.55528123210153[/C][/ROW]
[ROW][C]0.03[/C][C]68.4036564986988[/C][C]1.55840306390958[/C][/ROW]
[ROW][C]0.04[/C][C]69.1482961037221[/C][C]1.48997525875405[/C][/ROW]
[ROW][C]0.05[/C][C]69.811347790361[/C][C]1.39238765195124[/C][/ROW]
[ROW][C]0.06[/C][C]70.3887223500174[/C][C]1.31575761513653[/C][/ROW]
[ROW][C]0.07[/C][C]70.8963157814548[/C][C]1.28157625519233[/C][/ROW]
[ROW][C]0.08[/C][C]71.3547362906472[/C][C]1.28693064439856[/C][/ROW]
[ROW][C]0.09[/C][C]71.7823739568386[/C][C]1.32099687991950[/C][/ROW]
[ROW][C]0.1[/C][C]72.1934075920155[/C][C]1.37596600777784[/C][/ROW]
[ROW][C]0.11[/C][C]72.5981750350949[/C][C]1.44826178181682[/C][/ROW]
[ROW][C]0.12[/C][C]73.0043000648645[/C][C]1.53751708650657[/C][/ROW]
[ROW][C]0.13[/C][C]73.4177156488321[/C][C]1.64450126428302[/C][/ROW]
[ROW][C]0.14[/C][C]73.8432458524083[/C][C]1.76932839521715[/C][/ROW]
[ROW][C]0.15[/C][C]74.2847185322824[/C][C]1.90975783855626[/C][/ROW]
[ROW][C]0.16[/C][C]74.7447299943927[/C][C]2.05984925490576[/C][/ROW]
[ROW][C]0.17[/C][C]75.224240396469[/C][C]2.21014931294521[/C][/ROW]
[ROW][C]0.18[/C][C]75.7221901039324[/C][C]2.34820126929340[/C][/ROW]
[ROW][C]0.19[/C][C]76.2353063484584[/C][C]2.46077239426292[/C][/ROW]
[ROW][C]0.2[/C][C]76.7582168157958[/C][C]2.53598849433557[/C][/ROW]
[ROW][C]0.21[/C][C]77.2839076786603[/C][C]2.56568833999510[/C][/ROW]
[ROW][C]0.22[/C][C]77.8044750154863[/C][C]2.54703463334982[/C][/ROW]
[ROW][C]0.23[/C][C]78.3120439328269[/C][C]2.48279387933267[/C][/ROW]
[ROW][C]0.24[/C][C]78.7996892908958[/C][C]2.38097318152519[/C][/ROW]
[ROW][C]0.25[/C][C]79.262194930221[/C][C]2.2535082783281[/C][/ROW]
[ROW][C]0.26[/C][C]79.6965303022172[/C][C]2.11444854425374[/C][/ROW]
[ROW][C]0.27[/C][C]80.1019892795147[/C][C]1.97775860058947[/C][/ROW]
[ROW][C]0.28[/C][C]80.4800060216147[/C][C]1.85550425738537[/C][/ROW]
[ROW][C]0.29[/C][C]80.8337195624748[/C][C]1.75659652120608[/C][/ROW]
[ROW][C]0.3[/C][C]81.1673914528514[/C][C]1.68576404301868[/C][/ROW]
[ROW][C]0.31[/C][C]81.4857867814071[/C][C]1.64332585943454[/C][/ROW]
[ROW][C]0.32[/C][C]81.7936126819595[/C][C]1.62639026614228[/C][/ROW]
[ROW][C]0.33[/C][C]82.0950785835621[/C][C]1.62956183525773[/C][/ROW]
[ROW][C]0.34[/C][C]82.3936084231967[/C][C]1.64671267325676[/C][/ROW]
[ROW][C]0.35[/C][C]82.6917046155564[/C][C]1.67186456274807[/C][/ROW]
[ROW][C]0.36[/C][C]82.9909415737096[/C][C]1.69967575099472[/C][/ROW]
[ROW][C]0.37[/C][C]83.2920546482911[/C][C]1.72614692208603[/C][/ROW]
[ROW][C]0.38[/C][C]83.5950876166219[/C][C]1.74832031549168[/C][/ROW]
[ROW][C]0.39[/C][C]83.8995658820714[/C][C]1.76406435257018[/C][/ROW]
[ROW][C]0.4[/C][C]84.2046703676167[/C][C]1.77245010895322[/C][/ROW]
[ROW][C]0.41[/C][C]84.509395963342[/C][C]1.77327081904245[/C][/ROW]
[ROW][C]0.42[/C][C]84.8126862730054[/C][C]1.76660147709101[/C][/ROW]
[ROW][C]0.43[/C][C]85.1135421431169[/C][C]1.7532409417548[/C][/ROW]
[ROW][C]0.44[/C][C]85.4111047400107[/C][C]1.73435520356541[/C][/ROW]
[ROW][C]0.45[/C][C]85.7047151172333[/C][C]1.71116567949486[/C][/ROW]
[ROW][C]0.46[/C][C]85.9939520351408[/C][C]1.68549250903118[/C][/ROW]
[ROW][C]0.47[/C][C]86.2786491252129[/C][C]1.65877047012667[/C][/ROW]
[ROW][C]0.48[/C][C]86.558892083764[/C][C]1.63276799918921[/C][/ROW]
[ROW][C]0.49[/C][C]86.8349969015404[/C][C]1.60892397043196[/C][/ROW]
[ROW][C]0.5[/C][C]87.1074712986944[/C][C]1.58841444237799[/C][/ROW]
[ROW][C]0.51[/C][C]87.3769633082975[/C][C]1.57220071469155[/C][/ROW]
[ROW][C]0.52[/C][C]87.644202850209[/C][C]1.56037475427818[/C][/ROW]
[ROW][C]0.53[/C][C]87.9099435546387[/C][C]1.55289208286734[/C][/ROW]
[ROW][C]0.54[/C][C]88.1749124607386[/C][C]1.54921312328353[/C][/ROW]
[ROW][C]0.55[/C][C]88.439774147119[/C][C]1.54853798547242[/C][/ROW]
[ROW][C]0.56[/C][C]88.7051132753385[/C][C]1.55014908485959[/C][/ROW]
[ROW][C]0.57[/C][C]88.9714357502338[/C][C]1.55334410415646[/C][/ROW]
[ROW][C]0.58[/C][C]89.2391844014871[/C][C]1.55755742207872[/C][/ROW]
[ROW][C]0.59[/C][C]89.5087612261083[/C][C]1.56274120503065[/C][/ROW]
[ROW][C]0.6[/C][C]89.7805458542376[/C][C]1.56906300750029[/C][/ROW]
[ROW][C]0.61[/C][C]90.0548999127472[/C][C]1.57676934616907[/C][/ROW]
[ROW][C]0.62[/C][C]90.332149849046[/C][C]1.58582364818683[/C][/ROW]
[ROW][C]0.63[/C][C]90.6125463925958[/C][C]1.59629914679656[/C][/ROW]
[ROW][C]0.64[/C][C]90.8962062821051[/C][C]1.60726385444782[/C][/ROW]
[ROW][C]0.65[/C][C]91.1830495962643[/C][C]1.61730888106727[/C][/ROW]
[ROW][C]0.66[/C][C]91.4727519871096[/C][C]1.62458617851067[/C][/ROW]
[ROW][C]0.67[/C][C]91.7647333155893[/C][C]1.62713163169544[/C][/ROW]
[ROW][C]0.68[/C][C]92.058201149482[/C][C]1.62295561738323[/C][/ROW]
[ROW][C]0.69[/C][C]92.3522588870443[/C][C]1.61101605956269[/C][/ROW]
[ROW][C]0.7[/C][C]92.6460749284462[/C][C]1.59150165164844[/C][/ROW]
[ROW][C]0.71[/C][C]92.939093827036[/C][C]1.56589672406022[/C][/ROW]
[ROW][C]0.72[/C][C]93.2312563196061[/C][C]1.53749031718487[/C][/ROW]
[ROW][C]0.73[/C][C]93.5231864704906[/C][C]1.51083097240274[/C][/ROW]
[ROW][C]0.74[/C][C]93.8163039974663[/C][C]1.49116487634845[/C][/ROW]
[ROW][C]0.75[/C][C]94.112829462224[/C][C]1.48377073506729[/C][/ROW]
[ROW][C]0.76[/C][C]94.4156682144372[/C][C]1.49251938093099[/C][/ROW]
[ROW][C]0.77[/C][C]94.7281822711075[/C][C]1.51910600120464[/C][/ROW]
[ROW][C]0.78[/C][C]95.0538829242122[/C][C]1.56283090024246[/C][/ROW]
[ROW][C]0.79[/C][C]95.3960963937932[/C][C]1.62049586574660[/C][/ROW]
[ROW][C]0.8[/C][C]95.7576676792066[/C][C]1.68717813272473[/C][/ROW]
[ROW][C]0.81[/C][C]96.140773452257[/C][C]1.75730465039923[/C][/ROW]
[ROW][C]0.82[/C][C]96.5469137693095[/C][C]1.82568897305951[/C][/ROW]
[ROW][C]0.83[/C][C]96.9771432881789[/C][C]1.88808663822137[/C][/ROW]
[ROW][C]0.84[/C][C]97.4325806030585[/C][C]1.94277148376724[/C][/ROW]
[ROW][C]0.85[/C][C]97.9151912109798[/C][C]1.99146410485058[/C][/ROW]
[ROW][C]0.86[/C][C]98.4287685858579[/C][C]2.04037373562957[/C][/ROW]
[ROW][C]0.87[/C][C]98.9799389357133[/C][C]2.10051447513023[/C][/ROW]
[ROW][C]0.88[/C][C]99.5788982580049[/C][C]2.18619484603964[/C][/ROW]
[ROW][C]0.89[/C][C]100.239471530901[/C][C]2.31111651856638[/C][/ROW]
[ROW][C]0.9[/C][C]100.977983318591[/C][C]2.48202259890824[/C][/ROW]
[ROW][C]0.91[/C][C]101.810387464764[/C][C]2.6930702561356[/C][/ROW]
[ROW][C]0.92[/C][C]102.747232626786[/C][C]2.92032025385456[/C][/ROW]
[ROW][C]0.93[/C][C]103.786570421456[/C][C]3.11775865522207[/C][/ROW]
[ROW][C]0.94[/C][C]104.906109698037[/C][C]3.21559520741125[/C][/ROW]
[ROW][C]0.95[/C][C]106.057706853133[/C][C]3.12921637118292[/C][/ROW]
[ROW][C]0.96[/C][C]107.168631613979[/C][C]2.78944884233111[/C][/ROW]
[ROW][C]0.97[/C][C]108.152882198815[/C][C]2.19331516715887[/C][/ROW]
[ROW][C]0.98[/C][C]108.930802516317[/C][C]1.45270844641198[/C][/ROW]
[ROW][C]0.99[/C][C]109.449639105927[/C][C]0.80110033342081[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19915&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19915&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
0.0166.93552886464051.50511131042239
0.0267.62662295947281.55528123210153
0.0368.40365649869881.55840306390958
0.0469.14829610372211.48997525875405
0.0569.8113477903611.39238765195124
0.0670.38872235001741.31575761513653
0.0770.89631578145481.28157625519233
0.0871.35473629064721.28693064439856
0.0971.78237395683861.32099687991950
0.172.19340759201551.37596600777784
0.1172.59817503509491.44826178181682
0.1273.00430006486451.53751708650657
0.1373.41771564883211.64450126428302
0.1473.84324585240831.76932839521715
0.1574.28471853228241.90975783855626
0.1674.74472999439272.05984925490576
0.1775.2242403964692.21014931294521
0.1875.72219010393242.34820126929340
0.1976.23530634845842.46077239426292
0.276.75821681579582.53598849433557
0.2177.28390767866032.56568833999510
0.2277.80447501548632.54703463334982
0.2378.31204393282692.48279387933267
0.2478.79968929089582.38097318152519
0.2579.2621949302212.2535082783281
0.2679.69653030221722.11444854425374
0.2780.10198927951471.97775860058947
0.2880.48000602161471.85550425738537
0.2980.83371956247481.75659652120608
0.381.16739145285141.68576404301868
0.3181.48578678140711.64332585943454
0.3281.79361268195951.62639026614228
0.3382.09507858356211.62956183525773
0.3482.39360842319671.64671267325676
0.3582.69170461555641.67186456274807
0.3682.99094157370961.69967575099472
0.3783.29205464829111.72614692208603
0.3883.59508761662191.74832031549168
0.3983.89956588207141.76406435257018
0.484.20467036761671.77245010895322
0.4184.5093959633421.77327081904245
0.4284.81268627300541.76660147709101
0.4385.11354214311691.7532409417548
0.4485.41110474001071.73435520356541
0.4585.70471511723331.71116567949486
0.4685.99395203514081.68549250903118
0.4786.27864912521291.65877047012667
0.4886.5588920837641.63276799918921
0.4986.83499690154041.60892397043196
0.587.10747129869441.58841444237799
0.5187.37696330829751.57220071469155
0.5287.6442028502091.56037475427818
0.5387.90994355463871.55289208286734
0.5488.17491246073861.54921312328353
0.5588.4397741471191.54853798547242
0.5688.70511327533851.55014908485959
0.5788.97143575023381.55334410415646
0.5889.23918440148711.55755742207872
0.5989.50876122610831.56274120503065
0.689.78054585423761.56906300750029
0.6190.05489991274721.57676934616907
0.6290.3321498490461.58582364818683
0.6390.61254639259581.59629914679656
0.6490.89620628210511.60726385444782
0.6591.18304959626431.61730888106727
0.6691.47275198710961.62458617851067
0.6791.76473331558931.62713163169544
0.6892.0582011494821.62295561738323
0.6992.35225888704431.61101605956269
0.792.64607492844621.59150165164844
0.7192.9390938270361.56589672406022
0.7293.23125631960611.53749031718487
0.7393.52318647049061.51083097240274
0.7493.81630399746631.49116487634845
0.7594.1128294622241.48377073506729
0.7694.41566821443721.49251938093099
0.7794.72818227110751.51910600120464
0.7895.05388292421221.56283090024246
0.7995.39609639379321.62049586574660
0.895.75766767920661.68717813272473
0.8196.1407734522571.75730465039923
0.8296.54691376930951.82568897305951
0.8396.97714328817891.88808663822137
0.8497.43258060305851.94277148376724
0.8597.91519121097981.99146410485058
0.8698.42876858585792.04037373562957
0.8798.97993893571332.10051447513023
0.8899.57889825800492.18619484603964
0.89100.2394715309012.31111651856638
0.9100.9779833185912.48202259890824
0.91101.8103874647642.6930702561356
0.92102.7472326267862.92032025385456
0.93103.7865704214563.11775865522207
0.94104.9061096980373.21559520741125
0.95106.0577068531333.12921637118292
0.96107.1686316139792.78944884233111
0.97108.1528821988152.19331516715887
0.98108.9308025163171.45270844641198
0.99109.4496391059270.80110033342081


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 500 ; par2 = 12 ;
Parameters (R input):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
R code (references can be found in the software module):
par1 <- as(par1,'numeric')
par2 <- as(par2,'numeric')
par3 <- as(par3,'numeric')
library(Hmisc)
myseq <- seq(par1, par2, par3)
hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE)
bitmap(file='test1.png')
plot(myseq,hd,col=2,main=main,xlab=xlab,ylab=ylab)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Harrell-Davis Quantiles',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'quantiles',header=TRUE)
a<-table.element(a,'value',header=TRUE)
a<-table.element(a,'standard error',header=TRUE)
a<-table.row.end(a)
length(hd)
for (i in 1:length(hd))
{
a<-table.row.start(a)
a<-table.element(a,as(labels(hd)[i],'numeric'),header=TRUE)
a<-table.element(a,as.matrix(hd[i])[1,1])
a<-table.element(a,as.matrix(attr(hd,'se')[i])[1,1])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')