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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, 14 Oct 2010 14:02:45 +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/14/t1287064913u7mxo1irkanp0m1.htm/, Retrieved Wed, 01 May 2024 23:37:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=83299, Retrieved Wed, 01 May 2024 23:37:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W42
Estimated Impact106

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] [] [2010-10-14 14:02:45] [b831d618c4f08b1797d6e909807842bd] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
78.1
66.7
79
65.2
66.5
77.2
80.2
77.9
78
86.8
92.9
185.8
91
79.1
84.2
70.1
71.3
79.6
92.3
78.7
82.5
98.2
115.4
205.6
94
83.2
80.3
70.4
71.1
78.8
86.3
77.5
80.1
89.8
99.9
218
85.4
77.5
78.6
68.8
64.8
79.8
94.3
79.9
87.5
99.1
109.9
273.6
91.3
80.6
80.4
71.8
75.5
86.6
91.5
86.8
84.6
88.6
102.1
260.3
79
70.6
79.3
66.8
61.2
72.5
83.5
75.8
83.4
89.4
104.9
251.6
80
76.3
81.1
63.1
63.5
78.8
91.7
83.8
83.8
95.8
108.9
258.2
88.7
79.5
74.3
70.5
59.1
73.2
81.2
75
74.6
89.5
107
246.4
83.6
72.1
68.7
60.1
61.1
72.7
85.3
71.4
75.2
89.8
100.9
222.7

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=83299&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=83299&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=83299&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0159.70995409269660.990871785852658
0.0260.62115996120291.15329371101994
0.0361.56525313544061.43345907207224
0.0462.51796405541831.67737871711750
0.0563.47137536922571.8030936261776
0.0664.39567469929231.84388577621663
0.0765.27034600199121.85733491775417
0.0866.09312329306411.87200034637392
0.0966.86984360461591.88402628671562
0.167.60359329074861.87065755976557
0.1168.29066927405771.81060688767449
0.1268.92297331975941.70064017368709
0.1369.4935203527121.55831011861131
0.1470.00133856300731.41491483774823
0.1570.45336731280421.30170328757686
0.1670.86307959415551.23942288787318
0.1771.24713852406281.23408436566252
0.1871.62178033700151.27799168243555
0.1972.00009346436951.35558963977327
0.272.39060646192171.44933097419587
0.2172.79706510136861.54259735426573
0.2273.21905843578641.6230368010806
0.2373.6531248536971.68196782091425
0.2474.09400659410791.71619119490398
0.2574.53577950624721.72576441698736
0.2674.97267257054991.71303990206797
0.2775.39951263270061.68058527628113
0.2875.81185479469741.63090522128021
0.2976.20594132562061.56566696410999
0.376.57864167440671.48636806329594
0.3176.92747038548881.39509685354215
0.3277.2506965769791.29553695801266
0.3377.5474922121911.19193113934548
0.3477.81804255799111.08901093639354
0.3578.06356004084090.991875134825036
0.3678.28618259720.904569267884717
0.3778.48877689516790.829907255651241
0.3878.67469150575550.769955399808534
0.3978.84751256236930.725438125772721
0.479.01086870794730.696246714830105
0.4179.16831785836530.68217468754477
0.4279.32332789707740.682689781121699
0.4379.4793381562070.697825154031972
0.4479.63986164983720.728596671042344
0.4579.80856639024590.776443917266273
0.4679.98926701731650.842472472979738
0.4780.18577314638580.92656710880697
0.4880.40157982971721.02631844501351
0.4980.63944067319951.13693927075536
0.580.90091908335561.25123517059275
0.5181.18604727308411.36039246777784
0.5281.49321873855081.45673429511398
0.5381.81939178188771.53320309570020
0.5482.16059911843721.58713443885541
0.5582.51266640506681.61939182822999
0.5682.87197253333131.63518936770129
0.5783.23606360168881.64166045015475
0.5883.60397082473171.64750031815540
0.5983.97616829527441.65953288335647
0.684.35420924755651.68158412358780
0.6184.74016303339681.71420988336979
0.6285.1360124564041.75486195597973
0.6385.54315572721.79902430768364
0.6485.96210395750361.84193759883748
0.6586.39240122595791.87906426520607
0.6686.83274558600531.90682647669782
0.6787.28126833239141.92355436135891
0.6887.73593130399861.92936758254071
0.6988.19501360323661.92579320478459
0.788.65766561640991.91723471038939
0.7189.12450282826561.91049226715462
0.7289.5981953265961.91472186916748
0.7390.08398433215391.94100708899861
0.7490.59002742956762.00080328249638
0.7591.12744643640012.10551403292429
0.7691.70994705648272.26324683735734
0.7792.35293772505332.47691417603115
0.7893.07224575779332.74232471206503
0.7993.88284845980253.04833058164918
0.894.79851488460573.38107619179883
0.8195.83389212050573.73380810773483
0.8297.0113917950794.1237615690826
0.8398.37619661770074.61950206584102
0.84100.0232923030145.38485926414483
0.85102.1388677058096.73161345645276
0.86105.0513103585039.13640479925724
0.87109.27118129729813.1405564271841
0.88115.47794304437119.1019676991947
0.89124.40055378168526.8369613222613
0.9136.56842527540335.2902908309256
0.91151.99552966071942.537277141037
0.92169.96538227946646.398058868171
0.93189.10295673775845.531740714595
0.94207.76413741566940.2750293031136
0.95224.52806934332232.3870110244989
0.96238.51971593453123.8015014106090
0.97249.59573059546715.8329439580384
0.98258.65916897084310.0787635802642
0.99267.2001437210259.7813618001406

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 59.7099540926966 & 0.990871785852658 \tabularnewline
0.02 & 60.6211599612029 & 1.15329371101994 \tabularnewline
0.03 & 61.5652531354406 & 1.43345907207224 \tabularnewline
0.04 & 62.5179640554183 & 1.67737871711750 \tabularnewline
0.05 & 63.4713753692257 & 1.8030936261776 \tabularnewline
0.06 & 64.3956746992923 & 1.84388577621663 \tabularnewline
0.07 & 65.2703460019912 & 1.85733491775417 \tabularnewline
0.08 & 66.0931232930641 & 1.87200034637392 \tabularnewline
0.09 & 66.8698436046159 & 1.88402628671562 \tabularnewline
0.1 & 67.6035932907486 & 1.87065755976557 \tabularnewline
0.11 & 68.2906692740577 & 1.81060688767449 \tabularnewline
0.12 & 68.9229733197594 & 1.70064017368709 \tabularnewline
0.13 & 69.493520352712 & 1.55831011861131 \tabularnewline
0.14 & 70.0013385630073 & 1.41491483774823 \tabularnewline
0.15 & 70.4533673128042 & 1.30170328757686 \tabularnewline
0.16 & 70.8630795941555 & 1.23942288787318 \tabularnewline
0.17 & 71.2471385240628 & 1.23408436566252 \tabularnewline
0.18 & 71.6217803370015 & 1.27799168243555 \tabularnewline
0.19 & 72.0000934643695 & 1.35558963977327 \tabularnewline
0.2 & 72.3906064619217 & 1.44933097419587 \tabularnewline
0.21 & 72.7970651013686 & 1.54259735426573 \tabularnewline
0.22 & 73.2190584357864 & 1.6230368010806 \tabularnewline
0.23 & 73.653124853697 & 1.68196782091425 \tabularnewline
0.24 & 74.0940065941079 & 1.71619119490398 \tabularnewline
0.25 & 74.5357795062472 & 1.72576441698736 \tabularnewline
0.26 & 74.9726725705499 & 1.71303990206797 \tabularnewline
0.27 & 75.3995126327006 & 1.68058527628113 \tabularnewline
0.28 & 75.8118547946974 & 1.63090522128021 \tabularnewline
0.29 & 76.2059413256206 & 1.56566696410999 \tabularnewline
0.3 & 76.5786416744067 & 1.48636806329594 \tabularnewline
0.31 & 76.9274703854888 & 1.39509685354215 \tabularnewline
0.32 & 77.250696576979 & 1.29553695801266 \tabularnewline
0.33 & 77.547492212191 & 1.19193113934548 \tabularnewline
0.34 & 77.8180425579911 & 1.08901093639354 \tabularnewline
0.35 & 78.0635600408409 & 0.991875134825036 \tabularnewline
0.36 & 78.2861825972 & 0.904569267884717 \tabularnewline
0.37 & 78.4887768951679 & 0.829907255651241 \tabularnewline
0.38 & 78.6746915057555 & 0.769955399808534 \tabularnewline
0.39 & 78.8475125623693 & 0.725438125772721 \tabularnewline
0.4 & 79.0108687079473 & 0.696246714830105 \tabularnewline
0.41 & 79.1683178583653 & 0.68217468754477 \tabularnewline
0.42 & 79.3233278970774 & 0.682689781121699 \tabularnewline
0.43 & 79.479338156207 & 0.697825154031972 \tabularnewline
0.44 & 79.6398616498372 & 0.728596671042344 \tabularnewline
0.45 & 79.8085663902459 & 0.776443917266273 \tabularnewline
0.46 & 79.9892670173165 & 0.842472472979738 \tabularnewline
0.47 & 80.1857731463858 & 0.92656710880697 \tabularnewline
0.48 & 80.4015798297172 & 1.02631844501351 \tabularnewline
0.49 & 80.6394406731995 & 1.13693927075536 \tabularnewline
0.5 & 80.9009190833556 & 1.25123517059275 \tabularnewline
0.51 & 81.1860472730841 & 1.36039246777784 \tabularnewline
0.52 & 81.4932187385508 & 1.45673429511398 \tabularnewline
0.53 & 81.8193917818877 & 1.53320309570020 \tabularnewline
0.54 & 82.1605991184372 & 1.58713443885541 \tabularnewline
0.55 & 82.5126664050668 & 1.61939182822999 \tabularnewline
0.56 & 82.8719725333313 & 1.63518936770129 \tabularnewline
0.57 & 83.2360636016888 & 1.64166045015475 \tabularnewline
0.58 & 83.6039708247317 & 1.64750031815540 \tabularnewline
0.59 & 83.9761682952744 & 1.65953288335647 \tabularnewline
0.6 & 84.3542092475565 & 1.68158412358780 \tabularnewline
0.61 & 84.7401630333968 & 1.71420988336979 \tabularnewline
0.62 & 85.136012456404 & 1.75486195597973 \tabularnewline
0.63 & 85.5431557272 & 1.79902430768364 \tabularnewline
0.64 & 85.9621039575036 & 1.84193759883748 \tabularnewline
0.65 & 86.3924012259579 & 1.87906426520607 \tabularnewline
0.66 & 86.8327455860053 & 1.90682647669782 \tabularnewline
0.67 & 87.2812683323914 & 1.92355436135891 \tabularnewline
0.68 & 87.7359313039986 & 1.92936758254071 \tabularnewline
0.69 & 88.1950136032366 & 1.92579320478459 \tabularnewline
0.7 & 88.6576656164099 & 1.91723471038939 \tabularnewline
0.71 & 89.1245028282656 & 1.91049226715462 \tabularnewline
0.72 & 89.598195326596 & 1.91472186916748 \tabularnewline
0.73 & 90.0839843321539 & 1.94100708899861 \tabularnewline
0.74 & 90.5900274295676 & 2.00080328249638 \tabularnewline
0.75 & 91.1274464364001 & 2.10551403292429 \tabularnewline
0.76 & 91.7099470564827 & 2.26324683735734 \tabularnewline
0.77 & 92.3529377250533 & 2.47691417603115 \tabularnewline
0.78 & 93.0722457577933 & 2.74232471206503 \tabularnewline
0.79 & 93.8828484598025 & 3.04833058164918 \tabularnewline
0.8 & 94.7985148846057 & 3.38107619179883 \tabularnewline
0.81 & 95.8338921205057 & 3.73380810773483 \tabularnewline
0.82 & 97.011391795079 & 4.1237615690826 \tabularnewline
0.83 & 98.3761966177007 & 4.61950206584102 \tabularnewline
0.84 & 100.023292303014 & 5.38485926414483 \tabularnewline
0.85 & 102.138867705809 & 6.73161345645276 \tabularnewline
0.86 & 105.051310358503 & 9.13640479925724 \tabularnewline
0.87 & 109.271181297298 & 13.1405564271841 \tabularnewline
0.88 & 115.477943044371 & 19.1019676991947 \tabularnewline
0.89 & 124.400553781685 & 26.8369613222613 \tabularnewline
0.9 & 136.568425275403 & 35.2902908309256 \tabularnewline
0.91 & 151.995529660719 & 42.537277141037 \tabularnewline
0.92 & 169.965382279466 & 46.398058868171 \tabularnewline
0.93 & 189.102956737758 & 45.531740714595 \tabularnewline
0.94 & 207.764137415669 & 40.2750293031136 \tabularnewline
0.95 & 224.528069343322 & 32.3870110244989 \tabularnewline
0.96 & 238.519715934531 & 23.8015014106090 \tabularnewline
0.97 & 249.595730595467 & 15.8329439580384 \tabularnewline
0.98 & 258.659168970843 & 10.0787635802642 \tabularnewline
0.99 & 267.200143721025 & 9.7813618001406 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=83299&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]59.7099540926966[/C][C]0.990871785852658[/C][/ROW]
[ROW][C]0.02[/C][C]60.6211599612029[/C][C]1.15329371101994[/C][/ROW]
[ROW][C]0.03[/C][C]61.5652531354406[/C][C]1.43345907207224[/C][/ROW]
[ROW][C]0.04[/C][C]62.5179640554183[/C][C]1.67737871711750[/C][/ROW]
[ROW][C]0.05[/C][C]63.4713753692257[/C][C]1.8030936261776[/C][/ROW]
[ROW][C]0.06[/C][C]64.3956746992923[/C][C]1.84388577621663[/C][/ROW]
[ROW][C]0.07[/C][C]65.2703460019912[/C][C]1.85733491775417[/C][/ROW]
[ROW][C]0.08[/C][C]66.0931232930641[/C][C]1.87200034637392[/C][/ROW]
[ROW][C]0.09[/C][C]66.8698436046159[/C][C]1.88402628671562[/C][/ROW]
[ROW][C]0.1[/C][C]67.6035932907486[/C][C]1.87065755976557[/C][/ROW]
[ROW][C]0.11[/C][C]68.2906692740577[/C][C]1.81060688767449[/C][/ROW]
[ROW][C]0.12[/C][C]68.9229733197594[/C][C]1.70064017368709[/C][/ROW]
[ROW][C]0.13[/C][C]69.493520352712[/C][C]1.55831011861131[/C][/ROW]
[ROW][C]0.14[/C][C]70.0013385630073[/C][C]1.41491483774823[/C][/ROW]
[ROW][C]0.15[/C][C]70.4533673128042[/C][C]1.30170328757686[/C][/ROW]
[ROW][C]0.16[/C][C]70.8630795941555[/C][C]1.23942288787318[/C][/ROW]
[ROW][C]0.17[/C][C]71.2471385240628[/C][C]1.23408436566252[/C][/ROW]
[ROW][C]0.18[/C][C]71.6217803370015[/C][C]1.27799168243555[/C][/ROW]
[ROW][C]0.19[/C][C]72.0000934643695[/C][C]1.35558963977327[/C][/ROW]
[ROW][C]0.2[/C][C]72.3906064619217[/C][C]1.44933097419587[/C][/ROW]
[ROW][C]0.21[/C][C]72.7970651013686[/C][C]1.54259735426573[/C][/ROW]
[ROW][C]0.22[/C][C]73.2190584357864[/C][C]1.6230368010806[/C][/ROW]
[ROW][C]0.23[/C][C]73.653124853697[/C][C]1.68196782091425[/C][/ROW]
[ROW][C]0.24[/C][C]74.0940065941079[/C][C]1.71619119490398[/C][/ROW]
[ROW][C]0.25[/C][C]74.5357795062472[/C][C]1.72576441698736[/C][/ROW]
[ROW][C]0.26[/C][C]74.9726725705499[/C][C]1.71303990206797[/C][/ROW]
[ROW][C]0.27[/C][C]75.3995126327006[/C][C]1.68058527628113[/C][/ROW]
[ROW][C]0.28[/C][C]75.8118547946974[/C][C]1.63090522128021[/C][/ROW]
[ROW][C]0.29[/C][C]76.2059413256206[/C][C]1.56566696410999[/C][/ROW]
[ROW][C]0.3[/C][C]76.5786416744067[/C][C]1.48636806329594[/C][/ROW]
[ROW][C]0.31[/C][C]76.9274703854888[/C][C]1.39509685354215[/C][/ROW]
[ROW][C]0.32[/C][C]77.250696576979[/C][C]1.29553695801266[/C][/ROW]
[ROW][C]0.33[/C][C]77.547492212191[/C][C]1.19193113934548[/C][/ROW]
[ROW][C]0.34[/C][C]77.8180425579911[/C][C]1.08901093639354[/C][/ROW]
[ROW][C]0.35[/C][C]78.0635600408409[/C][C]0.991875134825036[/C][/ROW]
[ROW][C]0.36[/C][C]78.2861825972[/C][C]0.904569267884717[/C][/ROW]
[ROW][C]0.37[/C][C]78.4887768951679[/C][C]0.829907255651241[/C][/ROW]
[ROW][C]0.38[/C][C]78.6746915057555[/C][C]0.769955399808534[/C][/ROW]
[ROW][C]0.39[/C][C]78.8475125623693[/C][C]0.725438125772721[/C][/ROW]
[ROW][C]0.4[/C][C]79.0108687079473[/C][C]0.696246714830105[/C][/ROW]
[ROW][C]0.41[/C][C]79.1683178583653[/C][C]0.68217468754477[/C][/ROW]
[ROW][C]0.42[/C][C]79.3233278970774[/C][C]0.682689781121699[/C][/ROW]
[ROW][C]0.43[/C][C]79.479338156207[/C][C]0.697825154031972[/C][/ROW]
[ROW][C]0.44[/C][C]79.6398616498372[/C][C]0.728596671042344[/C][/ROW]
[ROW][C]0.45[/C][C]79.8085663902459[/C][C]0.776443917266273[/C][/ROW]
[ROW][C]0.46[/C][C]79.9892670173165[/C][C]0.842472472979738[/C][/ROW]
[ROW][C]0.47[/C][C]80.1857731463858[/C][C]0.92656710880697[/C][/ROW]
[ROW][C]0.48[/C][C]80.4015798297172[/C][C]1.02631844501351[/C][/ROW]
[ROW][C]0.49[/C][C]80.6394406731995[/C][C]1.13693927075536[/C][/ROW]
[ROW][C]0.5[/C][C]80.9009190833556[/C][C]1.25123517059275[/C][/ROW]
[ROW][C]0.51[/C][C]81.1860472730841[/C][C]1.36039246777784[/C][/ROW]
[ROW][C]0.52[/C][C]81.4932187385508[/C][C]1.45673429511398[/C][/ROW]
[ROW][C]0.53[/C][C]81.8193917818877[/C][C]1.53320309570020[/C][/ROW]
[ROW][C]0.54[/C][C]82.1605991184372[/C][C]1.58713443885541[/C][/ROW]
[ROW][C]0.55[/C][C]82.5126664050668[/C][C]1.61939182822999[/C][/ROW]
[ROW][C]0.56[/C][C]82.8719725333313[/C][C]1.63518936770129[/C][/ROW]
[ROW][C]0.57[/C][C]83.2360636016888[/C][C]1.64166045015475[/C][/ROW]
[ROW][C]0.58[/C][C]83.6039708247317[/C][C]1.64750031815540[/C][/ROW]
[ROW][C]0.59[/C][C]83.9761682952744[/C][C]1.65953288335647[/C][/ROW]
[ROW][C]0.6[/C][C]84.3542092475565[/C][C]1.68158412358780[/C][/ROW]
[ROW][C]0.61[/C][C]84.7401630333968[/C][C]1.71420988336979[/C][/ROW]
[ROW][C]0.62[/C][C]85.136012456404[/C][C]1.75486195597973[/C][/ROW]
[ROW][C]0.63[/C][C]85.5431557272[/C][C]1.79902430768364[/C][/ROW]
[ROW][C]0.64[/C][C]85.9621039575036[/C][C]1.84193759883748[/C][/ROW]
[ROW][C]0.65[/C][C]86.3924012259579[/C][C]1.87906426520607[/C][/ROW]
[ROW][C]0.66[/C][C]86.8327455860053[/C][C]1.90682647669782[/C][/ROW]
[ROW][C]0.67[/C][C]87.2812683323914[/C][C]1.92355436135891[/C][/ROW]
[ROW][C]0.68[/C][C]87.7359313039986[/C][C]1.92936758254071[/C][/ROW]
[ROW][C]0.69[/C][C]88.1950136032366[/C][C]1.92579320478459[/C][/ROW]
[ROW][C]0.7[/C][C]88.6576656164099[/C][C]1.91723471038939[/C][/ROW]
[ROW][C]0.71[/C][C]89.1245028282656[/C][C]1.91049226715462[/C][/ROW]
[ROW][C]0.72[/C][C]89.598195326596[/C][C]1.91472186916748[/C][/ROW]
[ROW][C]0.73[/C][C]90.0839843321539[/C][C]1.94100708899861[/C][/ROW]
[ROW][C]0.74[/C][C]90.5900274295676[/C][C]2.00080328249638[/C][/ROW]
[ROW][C]0.75[/C][C]91.1274464364001[/C][C]2.10551403292429[/C][/ROW]
[ROW][C]0.76[/C][C]91.7099470564827[/C][C]2.26324683735734[/C][/ROW]
[ROW][C]0.77[/C][C]92.3529377250533[/C][C]2.47691417603115[/C][/ROW]
[ROW][C]0.78[/C][C]93.0722457577933[/C][C]2.74232471206503[/C][/ROW]
[ROW][C]0.79[/C][C]93.8828484598025[/C][C]3.04833058164918[/C][/ROW]
[ROW][C]0.8[/C][C]94.7985148846057[/C][C]3.38107619179883[/C][/ROW]
[ROW][C]0.81[/C][C]95.8338921205057[/C][C]3.73380810773483[/C][/ROW]
[ROW][C]0.82[/C][C]97.011391795079[/C][C]4.1237615690826[/C][/ROW]
[ROW][C]0.83[/C][C]98.3761966177007[/C][C]4.61950206584102[/C][/ROW]
[ROW][C]0.84[/C][C]100.023292303014[/C][C]5.38485926414483[/C][/ROW]
[ROW][C]0.85[/C][C]102.138867705809[/C][C]6.73161345645276[/C][/ROW]
[ROW][C]0.86[/C][C]105.051310358503[/C][C]9.13640479925724[/C][/ROW]
[ROW][C]0.87[/C][C]109.271181297298[/C][C]13.1405564271841[/C][/ROW]
[ROW][C]0.88[/C][C]115.477943044371[/C][C]19.1019676991947[/C][/ROW]
[ROW][C]0.89[/C][C]124.400553781685[/C][C]26.8369613222613[/C][/ROW]
[ROW][C]0.9[/C][C]136.568425275403[/C][C]35.2902908309256[/C][/ROW]
[ROW][C]0.91[/C][C]151.995529660719[/C][C]42.537277141037[/C][/ROW]
[ROW][C]0.92[/C][C]169.965382279466[/C][C]46.398058868171[/C][/ROW]
[ROW][C]0.93[/C][C]189.102956737758[/C][C]45.531740714595[/C][/ROW]
[ROW][C]0.94[/C][C]207.764137415669[/C][C]40.2750293031136[/C][/ROW]
[ROW][C]0.95[/C][C]224.528069343322[/C][C]32.3870110244989[/C][/ROW]
[ROW][C]0.96[/C][C]238.519715934531[/C][C]23.8015014106090[/C][/ROW]
[ROW][C]0.97[/C][C]249.595730595467[/C][C]15.8329439580384[/C][/ROW]
[ROW][C]0.98[/C][C]258.659168970843[/C][C]10.0787635802642[/C][/ROW]
[ROW][C]0.99[/C][C]267.200143721025[/C][C]9.7813618001406[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=83299&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=83299&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
0.0159.70995409269660.990871785852658
0.0260.62115996120291.15329371101994
0.0361.56525313544061.43345907207224
0.0462.51796405541831.67737871711750
0.0563.47137536922571.8030936261776
0.0664.39567469929231.84388577621663
0.0765.27034600199121.85733491775417
0.0866.09312329306411.87200034637392
0.0966.86984360461591.88402628671562
0.167.60359329074861.87065755976557
0.1168.29066927405771.81060688767449
0.1268.92297331975941.70064017368709
0.1369.4935203527121.55831011861131
0.1470.00133856300731.41491483774823
0.1570.45336731280421.30170328757686
0.1670.86307959415551.23942288787318
0.1771.24713852406281.23408436566252
0.1871.62178033700151.27799168243555
0.1972.00009346436951.35558963977327
0.272.39060646192171.44933097419587
0.2172.79706510136861.54259735426573
0.2273.21905843578641.6230368010806
0.2373.6531248536971.68196782091425
0.2474.09400659410791.71619119490398
0.2574.53577950624721.72576441698736
0.2674.97267257054991.71303990206797
0.2775.39951263270061.68058527628113
0.2875.81185479469741.63090522128021
0.2976.20594132562061.56566696410999
0.376.57864167440671.48636806329594
0.3176.92747038548881.39509685354215
0.3277.2506965769791.29553695801266
0.3377.5474922121911.19193113934548
0.3477.81804255799111.08901093639354
0.3578.06356004084090.991875134825036
0.3678.28618259720.904569267884717
0.3778.48877689516790.829907255651241
0.3878.67469150575550.769955399808534
0.3978.84751256236930.725438125772721
0.479.01086870794730.696246714830105
0.4179.16831785836530.68217468754477
0.4279.32332789707740.682689781121699
0.4379.4793381562070.697825154031972
0.4479.63986164983720.728596671042344
0.4579.80856639024590.776443917266273
0.4679.98926701731650.842472472979738
0.4780.18577314638580.92656710880697
0.4880.40157982971721.02631844501351
0.4980.63944067319951.13693927075536
0.580.90091908335561.25123517059275
0.5181.18604727308411.36039246777784
0.5281.49321873855081.45673429511398
0.5381.81939178188771.53320309570020
0.5482.16059911843721.58713443885541
0.5582.51266640506681.61939182822999
0.5682.87197253333131.63518936770129
0.5783.23606360168881.64166045015475
0.5883.60397082473171.64750031815540
0.5983.97616829527441.65953288335647
0.684.35420924755651.68158412358780
0.6184.74016303339681.71420988336979
0.6285.1360124564041.75486195597973
0.6385.54315572721.79902430768364
0.6485.96210395750361.84193759883748
0.6586.39240122595791.87906426520607
0.6686.83274558600531.90682647669782
0.6787.28126833239141.92355436135891
0.6887.73593130399861.92936758254071
0.6988.19501360323661.92579320478459
0.788.65766561640991.91723471038939
0.7189.12450282826561.91049226715462
0.7289.5981953265961.91472186916748
0.7390.08398433215391.94100708899861
0.7490.59002742956762.00080328249638
0.7591.12744643640012.10551403292429
0.7691.70994705648272.26324683735734
0.7792.35293772505332.47691417603115
0.7893.07224575779332.74232471206503
0.7993.88284845980253.04833058164918
0.894.79851488460573.38107619179883
0.8195.83389212050573.73380810773483
0.8297.0113917950794.1237615690826
0.8398.37619661770074.61950206584102
0.84100.0232923030145.38485926414483
0.85102.1388677058096.73161345645276
0.86105.0513103585039.13640479925724
0.87109.27118129729813.1405564271841
0.88115.47794304437119.1019676991947
0.89124.40055378168526.8369613222613
0.9136.56842527540335.2902908309256
0.91151.99552966071942.537277141037
0.92169.96538227946646.398058868171
0.93189.10295673775845.531740714595
0.94207.76413741566940.2750293031136
0.95224.52806934332232.3870110244989
0.96238.51971593453123.8015014106090
0.97249.59573059546715.8329439580384
0.98258.65916897084310.0787635802642
0.99267.2001437210259.7813618001406


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')