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Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationSun, 07 Mar 2010 07:07:44 -0700
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/Mar/07/t1267971042hwlw2rx2cyy77zh.htm/, Retrieved Wed, 19 Jan 2022 11:30:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=74053, Retrieved Wed, 19 Jan 2022 11:30:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W42
Estimated Impact131
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Harrell-Davis Quantiles] [Percentielen Milk] [2010-03-07 14:07:44] [0e5311d1fc10a1511b42f76588fb6510] [Current]
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Dataseries X:
81.28
69.39
67.63
51.25
103.97
133.83
162.37
172.91
163.01
151.50
111.73
88.58
74.29
63.98
61.18
76.48
107.98
124.97
145.57
140.20
143.84
138.80
104.06
74.70
60.18
55.16
35.62
56.18
85.44
114.08
133.64
67.14
95.58
89.37
75.24
69.18
54.49
57.50
62.16
76.67
110.04
127.38
156.47
167.56
153.54
124.08
100.97
79.17
68.13
61.77
54.31
60.30
84.18
104.05
114.66
105.55
96.61
70.94
63.91
58.61
44.53
49.58
57.39
76.76
104.57
125.41
143.11
136.35
135.15
131.70
96.87
70.63
66.29
63.49
62.97
66.43
101.49
127.69
133.21
158.72
148.61
134.31
100.99
75.16
59.74
52.87
52.07
57.38
79.43
101.40
120.19
134.38
135.97
113.83
84.38
70.28
65.96
56.36
49.57
68.33
90.32
117.06
134.69
131.67
129.25
118.77
88.44
76.79
75.28
73.89
76.24
88.58
105.83
115.84
127.76
131.75
119.63
93.38
75.55
51.79




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=74053&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=74053&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74053&T=0

As an alternative you can also use a 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
0.0140.65294957744976.44055537862614
0.0246.00533901143633.83977219503982
0.0349.11244905029072.29982938447040
0.0450.79143189899021.74397562616879
0.0551.90796855197811.66395513311463
0.0652.83848998347661.72435243937378
0.0753.70363531698321.79074084653352
0.0854.53056881561221.82151212983194
0.0955.32056034335471.82727219706330
0.156.07468130436491.83570202213093
0.1156.80052222915231.86807722674682
0.1257.50981672871011.92941246140392
0.1358.213588963072.00931740957477
0.1458.91876620078572.09170887690375
0.1559.62756587603062.16494888616755
0.1660.33906350542152.22616450332467
0.1761.05142855790472.27954629098481
0.1861.76345373617142.33041936011435
0.1962.4748518683682.38115038096804
0.263.18567554865652.43005107530583
0.2163.89561676489282.47304054746362
0.2264.60380157921992.50772652733493
0.2365.30925672711122.53492283407552
0.2466.01178748468372.5607925677896
0.2566.71276179131062.59439829015487
0.2667.41531028194712.64438843003516
0.2768.12369099188182.71430126728268
0.2868.84192544735022.79957655464214
0.2969.57214837859062.88777305121951
0.370.31329584451272.96144349969375
0.3171.06071176067613.00371163881299
0.3271.80698891767573.00502246825176
0.3372.54396548376082.96623072145906
0.3473.26540757974332.90240794888379
0.3573.96965680454432.83995943306992
0.3674.66149157296832.81259132258093
0.3775.35264700383612.85488734007986
0.3876.06079040891452.9922517774548
0.3976.80714766255973.23308634803172
0.477.6133093174953.56842611176112
0.4178.4979338413583.97337770040682
0.4279.47407052310824.41537140380969
0.4380.547650113254.85913958874626
0.4481.71737958308585.274519570218
0.4582.9759061290355.63961752872508
0.4684.31178695547995.94404081948432
0.4785.71161785050786.18621487751166
0.4887.16170162729026.37096723339106
0.4988.64887487543536.50298775411605
0.590.16047705783236.58381944595907
0.5191.68380394679576.61035834010582
0.5293.20559906895846.57659628045832
0.5394.7121181507666.47815175058552
0.5496.19005876846956.3168664892416
0.5597.62827436342536.10549460412446
0.5699.01983112755465.86729907362865
0.57100.3637535178525.63324794673863
0.58101.6658190915755.43712572275672
0.59102.9380056732705.30718633199557
0.6104.1965870783255.25963346083963
0.61105.4592906656795.29339553993023
0.62106.7422313171045.39160931353158
0.63108.0574126553095.52766163964248
0.64109.4113975524635.67246276019038
0.65110.8053500290935.80255020951329
0.66112.2361808709195.90367930837646
0.67113.6981734039155.97078517230152
0.68115.1843743852166.00503046846402
0.69116.6872502199496.00775797084256
0.7118.1985314848935.97649160946513
0.71119.7085943540505.90445435289684
0.72121.2059441072155.78261839241472
0.73122.6772684704525.60336098529145
0.74124.1081841091375.36562463813404
0.75125.4844175548435.07433463178187
0.76126.7929759642464.73962940745695
0.77128.0229896395584.37372371269105
0.78129.1662688971613.98780862753725
0.79130.2179820314863.5939973835562
0.8131.1779832484953.20765026298166
0.81132.0530802575992.85186339593154
0.82132.8599923240802.56083676524391
0.83133.6281071634882.37884710783795
0.84134.4006533917292.35265002798323
0.85135.2328449114792.51384040822893
0.86136.1862108882542.8586918552878
0.87137.3198262923853.34406051672652
0.88138.6810766695393.89986385859696
0.89140.2996554232944.45151643224647
0.9142.1871727410514.94160361384314
0.91144.3410488178815.33803291624511
0.92146.7481458021635.62010333069281
0.93149.3844695148685.75850235079898
0.94152.2116551915405.71673153132909
0.95155.1759477576705.46507810090352
0.96158.2296412442864.99881249549688
0.97161.4262014838324.44831094306853
0.98165.0816822720364.2557287124976
0.99169.4645007950354.6729933143613

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 40.6529495774497 & 6.44055537862614 \tabularnewline
0.02 & 46.0053390114363 & 3.83977219503982 \tabularnewline
0.03 & 49.1124490502907 & 2.29982938447040 \tabularnewline
0.04 & 50.7914318989902 & 1.74397562616879 \tabularnewline
0.05 & 51.9079685519781 & 1.66395513311463 \tabularnewline
0.06 & 52.8384899834766 & 1.72435243937378 \tabularnewline
0.07 & 53.7036353169832 & 1.79074084653352 \tabularnewline
0.08 & 54.5305688156122 & 1.82151212983194 \tabularnewline
0.09 & 55.3205603433547 & 1.82727219706330 \tabularnewline
0.1 & 56.0746813043649 & 1.83570202213093 \tabularnewline
0.11 & 56.8005222291523 & 1.86807722674682 \tabularnewline
0.12 & 57.5098167287101 & 1.92941246140392 \tabularnewline
0.13 & 58.21358896307 & 2.00931740957477 \tabularnewline
0.14 & 58.9187662007857 & 2.09170887690375 \tabularnewline
0.15 & 59.6275658760306 & 2.16494888616755 \tabularnewline
0.16 & 60.3390635054215 & 2.22616450332467 \tabularnewline
0.17 & 61.0514285579047 & 2.27954629098481 \tabularnewline
0.18 & 61.7634537361714 & 2.33041936011435 \tabularnewline
0.19 & 62.474851868368 & 2.38115038096804 \tabularnewline
0.2 & 63.1856755486565 & 2.43005107530583 \tabularnewline
0.21 & 63.8956167648928 & 2.47304054746362 \tabularnewline
0.22 & 64.6038015792199 & 2.50772652733493 \tabularnewline
0.23 & 65.3092567271112 & 2.53492283407552 \tabularnewline
0.24 & 66.0117874846837 & 2.5607925677896 \tabularnewline
0.25 & 66.7127617913106 & 2.59439829015487 \tabularnewline
0.26 & 67.4153102819471 & 2.64438843003516 \tabularnewline
0.27 & 68.1236909918818 & 2.71430126728268 \tabularnewline
0.28 & 68.8419254473502 & 2.79957655464214 \tabularnewline
0.29 & 69.5721483785906 & 2.88777305121951 \tabularnewline
0.3 & 70.3132958445127 & 2.96144349969375 \tabularnewline
0.31 & 71.0607117606761 & 3.00371163881299 \tabularnewline
0.32 & 71.8069889176757 & 3.00502246825176 \tabularnewline
0.33 & 72.5439654837608 & 2.96623072145906 \tabularnewline
0.34 & 73.2654075797433 & 2.90240794888379 \tabularnewline
0.35 & 73.9696568045443 & 2.83995943306992 \tabularnewline
0.36 & 74.6614915729683 & 2.81259132258093 \tabularnewline
0.37 & 75.3526470038361 & 2.85488734007986 \tabularnewline
0.38 & 76.0607904089145 & 2.9922517774548 \tabularnewline
0.39 & 76.8071476625597 & 3.23308634803172 \tabularnewline
0.4 & 77.613309317495 & 3.56842611176112 \tabularnewline
0.41 & 78.497933841358 & 3.97337770040682 \tabularnewline
0.42 & 79.4740705231082 & 4.41537140380969 \tabularnewline
0.43 & 80.54765011325 & 4.85913958874626 \tabularnewline
0.44 & 81.7173795830858 & 5.274519570218 \tabularnewline
0.45 & 82.975906129035 & 5.63961752872508 \tabularnewline
0.46 & 84.3117869554799 & 5.94404081948432 \tabularnewline
0.47 & 85.7116178505078 & 6.18621487751166 \tabularnewline
0.48 & 87.1617016272902 & 6.37096723339106 \tabularnewline
0.49 & 88.6488748754353 & 6.50298775411605 \tabularnewline
0.5 & 90.1604770578323 & 6.58381944595907 \tabularnewline
0.51 & 91.6838039467957 & 6.61035834010582 \tabularnewline
0.52 & 93.2055990689584 & 6.57659628045832 \tabularnewline
0.53 & 94.712118150766 & 6.47815175058552 \tabularnewline
0.54 & 96.1900587684695 & 6.3168664892416 \tabularnewline
0.55 & 97.6282743634253 & 6.10549460412446 \tabularnewline
0.56 & 99.0198311275546 & 5.86729907362865 \tabularnewline
0.57 & 100.363753517852 & 5.63324794673863 \tabularnewline
0.58 & 101.665819091575 & 5.43712572275672 \tabularnewline
0.59 & 102.938005673270 & 5.30718633199557 \tabularnewline
0.6 & 104.196587078325 & 5.25963346083963 \tabularnewline
0.61 & 105.459290665679 & 5.29339553993023 \tabularnewline
0.62 & 106.742231317104 & 5.39160931353158 \tabularnewline
0.63 & 108.057412655309 & 5.52766163964248 \tabularnewline
0.64 & 109.411397552463 & 5.67246276019038 \tabularnewline
0.65 & 110.805350029093 & 5.80255020951329 \tabularnewline
0.66 & 112.236180870919 & 5.90367930837646 \tabularnewline
0.67 & 113.698173403915 & 5.97078517230152 \tabularnewline
0.68 & 115.184374385216 & 6.00503046846402 \tabularnewline
0.69 & 116.687250219949 & 6.00775797084256 \tabularnewline
0.7 & 118.198531484893 & 5.97649160946513 \tabularnewline
0.71 & 119.708594354050 & 5.90445435289684 \tabularnewline
0.72 & 121.205944107215 & 5.78261839241472 \tabularnewline
0.73 & 122.677268470452 & 5.60336098529145 \tabularnewline
0.74 & 124.108184109137 & 5.36562463813404 \tabularnewline
0.75 & 125.484417554843 & 5.07433463178187 \tabularnewline
0.76 & 126.792975964246 & 4.73962940745695 \tabularnewline
0.77 & 128.022989639558 & 4.37372371269105 \tabularnewline
0.78 & 129.166268897161 & 3.98780862753725 \tabularnewline
0.79 & 130.217982031486 & 3.5939973835562 \tabularnewline
0.8 & 131.177983248495 & 3.20765026298166 \tabularnewline
0.81 & 132.053080257599 & 2.85186339593154 \tabularnewline
0.82 & 132.859992324080 & 2.56083676524391 \tabularnewline
0.83 & 133.628107163488 & 2.37884710783795 \tabularnewline
0.84 & 134.400653391729 & 2.35265002798323 \tabularnewline
0.85 & 135.232844911479 & 2.51384040822893 \tabularnewline
0.86 & 136.186210888254 & 2.8586918552878 \tabularnewline
0.87 & 137.319826292385 & 3.34406051672652 \tabularnewline
0.88 & 138.681076669539 & 3.89986385859696 \tabularnewline
0.89 & 140.299655423294 & 4.45151643224647 \tabularnewline
0.9 & 142.187172741051 & 4.94160361384314 \tabularnewline
0.91 & 144.341048817881 & 5.33803291624511 \tabularnewline
0.92 & 146.748145802163 & 5.62010333069281 \tabularnewline
0.93 & 149.384469514868 & 5.75850235079898 \tabularnewline
0.94 & 152.211655191540 & 5.71673153132909 \tabularnewline
0.95 & 155.175947757670 & 5.46507810090352 \tabularnewline
0.96 & 158.229641244286 & 4.99881249549688 \tabularnewline
0.97 & 161.426201483832 & 4.44831094306853 \tabularnewline
0.98 & 165.081682272036 & 4.2557287124976 \tabularnewline
0.99 & 169.464500795035 & 4.6729933143613 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74053&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]40.6529495774497[/C][C]6.44055537862614[/C][/ROW]
[ROW][C]0.02[/C][C]46.0053390114363[/C][C]3.83977219503982[/C][/ROW]
[ROW][C]0.03[/C][C]49.1124490502907[/C][C]2.29982938447040[/C][/ROW]
[ROW][C]0.04[/C][C]50.7914318989902[/C][C]1.74397562616879[/C][/ROW]
[ROW][C]0.05[/C][C]51.9079685519781[/C][C]1.66395513311463[/C][/ROW]
[ROW][C]0.06[/C][C]52.8384899834766[/C][C]1.72435243937378[/C][/ROW]
[ROW][C]0.07[/C][C]53.7036353169832[/C][C]1.79074084653352[/C][/ROW]
[ROW][C]0.08[/C][C]54.5305688156122[/C][C]1.82151212983194[/C][/ROW]
[ROW][C]0.09[/C][C]55.3205603433547[/C][C]1.82727219706330[/C][/ROW]
[ROW][C]0.1[/C][C]56.0746813043649[/C][C]1.83570202213093[/C][/ROW]
[ROW][C]0.11[/C][C]56.8005222291523[/C][C]1.86807722674682[/C][/ROW]
[ROW][C]0.12[/C][C]57.5098167287101[/C][C]1.92941246140392[/C][/ROW]
[ROW][C]0.13[/C][C]58.21358896307[/C][C]2.00931740957477[/C][/ROW]
[ROW][C]0.14[/C][C]58.9187662007857[/C][C]2.09170887690375[/C][/ROW]
[ROW][C]0.15[/C][C]59.6275658760306[/C][C]2.16494888616755[/C][/ROW]
[ROW][C]0.16[/C][C]60.3390635054215[/C][C]2.22616450332467[/C][/ROW]
[ROW][C]0.17[/C][C]61.0514285579047[/C][C]2.27954629098481[/C][/ROW]
[ROW][C]0.18[/C][C]61.7634537361714[/C][C]2.33041936011435[/C][/ROW]
[ROW][C]0.19[/C][C]62.474851868368[/C][C]2.38115038096804[/C][/ROW]
[ROW][C]0.2[/C][C]63.1856755486565[/C][C]2.43005107530583[/C][/ROW]
[ROW][C]0.21[/C][C]63.8956167648928[/C][C]2.47304054746362[/C][/ROW]
[ROW][C]0.22[/C][C]64.6038015792199[/C][C]2.50772652733493[/C][/ROW]
[ROW][C]0.23[/C][C]65.3092567271112[/C][C]2.53492283407552[/C][/ROW]
[ROW][C]0.24[/C][C]66.0117874846837[/C][C]2.5607925677896[/C][/ROW]
[ROW][C]0.25[/C][C]66.7127617913106[/C][C]2.59439829015487[/C][/ROW]
[ROW][C]0.26[/C][C]67.4153102819471[/C][C]2.64438843003516[/C][/ROW]
[ROW][C]0.27[/C][C]68.1236909918818[/C][C]2.71430126728268[/C][/ROW]
[ROW][C]0.28[/C][C]68.8419254473502[/C][C]2.79957655464214[/C][/ROW]
[ROW][C]0.29[/C][C]69.5721483785906[/C][C]2.88777305121951[/C][/ROW]
[ROW][C]0.3[/C][C]70.3132958445127[/C][C]2.96144349969375[/C][/ROW]
[ROW][C]0.31[/C][C]71.0607117606761[/C][C]3.00371163881299[/C][/ROW]
[ROW][C]0.32[/C][C]71.8069889176757[/C][C]3.00502246825176[/C][/ROW]
[ROW][C]0.33[/C][C]72.5439654837608[/C][C]2.96623072145906[/C][/ROW]
[ROW][C]0.34[/C][C]73.2654075797433[/C][C]2.90240794888379[/C][/ROW]
[ROW][C]0.35[/C][C]73.9696568045443[/C][C]2.83995943306992[/C][/ROW]
[ROW][C]0.36[/C][C]74.6614915729683[/C][C]2.81259132258093[/C][/ROW]
[ROW][C]0.37[/C][C]75.3526470038361[/C][C]2.85488734007986[/C][/ROW]
[ROW][C]0.38[/C][C]76.0607904089145[/C][C]2.9922517774548[/C][/ROW]
[ROW][C]0.39[/C][C]76.8071476625597[/C][C]3.23308634803172[/C][/ROW]
[ROW][C]0.4[/C][C]77.613309317495[/C][C]3.56842611176112[/C][/ROW]
[ROW][C]0.41[/C][C]78.497933841358[/C][C]3.97337770040682[/C][/ROW]
[ROW][C]0.42[/C][C]79.4740705231082[/C][C]4.41537140380969[/C][/ROW]
[ROW][C]0.43[/C][C]80.54765011325[/C][C]4.85913958874626[/C][/ROW]
[ROW][C]0.44[/C][C]81.7173795830858[/C][C]5.274519570218[/C][/ROW]
[ROW][C]0.45[/C][C]82.975906129035[/C][C]5.63961752872508[/C][/ROW]
[ROW][C]0.46[/C][C]84.3117869554799[/C][C]5.94404081948432[/C][/ROW]
[ROW][C]0.47[/C][C]85.7116178505078[/C][C]6.18621487751166[/C][/ROW]
[ROW][C]0.48[/C][C]87.1617016272902[/C][C]6.37096723339106[/C][/ROW]
[ROW][C]0.49[/C][C]88.6488748754353[/C][C]6.50298775411605[/C][/ROW]
[ROW][C]0.5[/C][C]90.1604770578323[/C][C]6.58381944595907[/C][/ROW]
[ROW][C]0.51[/C][C]91.6838039467957[/C][C]6.61035834010582[/C][/ROW]
[ROW][C]0.52[/C][C]93.2055990689584[/C][C]6.57659628045832[/C][/ROW]
[ROW][C]0.53[/C][C]94.712118150766[/C][C]6.47815175058552[/C][/ROW]
[ROW][C]0.54[/C][C]96.1900587684695[/C][C]6.3168664892416[/C][/ROW]
[ROW][C]0.55[/C][C]97.6282743634253[/C][C]6.10549460412446[/C][/ROW]
[ROW][C]0.56[/C][C]99.0198311275546[/C][C]5.86729907362865[/C][/ROW]
[ROW][C]0.57[/C][C]100.363753517852[/C][C]5.63324794673863[/C][/ROW]
[ROW][C]0.58[/C][C]101.665819091575[/C][C]5.43712572275672[/C][/ROW]
[ROW][C]0.59[/C][C]102.938005673270[/C][C]5.30718633199557[/C][/ROW]
[ROW][C]0.6[/C][C]104.196587078325[/C][C]5.25963346083963[/C][/ROW]
[ROW][C]0.61[/C][C]105.459290665679[/C][C]5.29339553993023[/C][/ROW]
[ROW][C]0.62[/C][C]106.742231317104[/C][C]5.39160931353158[/C][/ROW]
[ROW][C]0.63[/C][C]108.057412655309[/C][C]5.52766163964248[/C][/ROW]
[ROW][C]0.64[/C][C]109.411397552463[/C][C]5.67246276019038[/C][/ROW]
[ROW][C]0.65[/C][C]110.805350029093[/C][C]5.80255020951329[/C][/ROW]
[ROW][C]0.66[/C][C]112.236180870919[/C][C]5.90367930837646[/C][/ROW]
[ROW][C]0.67[/C][C]113.698173403915[/C][C]5.97078517230152[/C][/ROW]
[ROW][C]0.68[/C][C]115.184374385216[/C][C]6.00503046846402[/C][/ROW]
[ROW][C]0.69[/C][C]116.687250219949[/C][C]6.00775797084256[/C][/ROW]
[ROW][C]0.7[/C][C]118.198531484893[/C][C]5.97649160946513[/C][/ROW]
[ROW][C]0.71[/C][C]119.708594354050[/C][C]5.90445435289684[/C][/ROW]
[ROW][C]0.72[/C][C]121.205944107215[/C][C]5.78261839241472[/C][/ROW]
[ROW][C]0.73[/C][C]122.677268470452[/C][C]5.60336098529145[/C][/ROW]
[ROW][C]0.74[/C][C]124.108184109137[/C][C]5.36562463813404[/C][/ROW]
[ROW][C]0.75[/C][C]125.484417554843[/C][C]5.07433463178187[/C][/ROW]
[ROW][C]0.76[/C][C]126.792975964246[/C][C]4.73962940745695[/C][/ROW]
[ROW][C]0.77[/C][C]128.022989639558[/C][C]4.37372371269105[/C][/ROW]
[ROW][C]0.78[/C][C]129.166268897161[/C][C]3.98780862753725[/C][/ROW]
[ROW][C]0.79[/C][C]130.217982031486[/C][C]3.5939973835562[/C][/ROW]
[ROW][C]0.8[/C][C]131.177983248495[/C][C]3.20765026298166[/C][/ROW]
[ROW][C]0.81[/C][C]132.053080257599[/C][C]2.85186339593154[/C][/ROW]
[ROW][C]0.82[/C][C]132.859992324080[/C][C]2.56083676524391[/C][/ROW]
[ROW][C]0.83[/C][C]133.628107163488[/C][C]2.37884710783795[/C][/ROW]
[ROW][C]0.84[/C][C]134.400653391729[/C][C]2.35265002798323[/C][/ROW]
[ROW][C]0.85[/C][C]135.232844911479[/C][C]2.51384040822893[/C][/ROW]
[ROW][C]0.86[/C][C]136.186210888254[/C][C]2.8586918552878[/C][/ROW]
[ROW][C]0.87[/C][C]137.319826292385[/C][C]3.34406051672652[/C][/ROW]
[ROW][C]0.88[/C][C]138.681076669539[/C][C]3.89986385859696[/C][/ROW]
[ROW][C]0.89[/C][C]140.299655423294[/C][C]4.45151643224647[/C][/ROW]
[ROW][C]0.9[/C][C]142.187172741051[/C][C]4.94160361384314[/C][/ROW]
[ROW][C]0.91[/C][C]144.341048817881[/C][C]5.33803291624511[/C][/ROW]
[ROW][C]0.92[/C][C]146.748145802163[/C][C]5.62010333069281[/C][/ROW]
[ROW][C]0.93[/C][C]149.384469514868[/C][C]5.75850235079898[/C][/ROW]
[ROW][C]0.94[/C][C]152.211655191540[/C][C]5.71673153132909[/C][/ROW]
[ROW][C]0.95[/C][C]155.175947757670[/C][C]5.46507810090352[/C][/ROW]
[ROW][C]0.96[/C][C]158.229641244286[/C][C]4.99881249549688[/C][/ROW]
[ROW][C]0.97[/C][C]161.426201483832[/C][C]4.44831094306853[/C][/ROW]
[ROW][C]0.98[/C][C]165.081682272036[/C][C]4.2557287124976[/C][/ROW]
[ROW][C]0.99[/C][C]169.464500795035[/C][C]4.6729933143613[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74053&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74053&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Harrell-Davis Quantiles
quantilesvaluestandard error
0.0140.65294957744976.44055537862614
0.0246.00533901143633.83977219503982
0.0349.11244905029072.29982938447040
0.0450.79143189899021.74397562616879
0.0551.90796855197811.66395513311463
0.0652.83848998347661.72435243937378
0.0753.70363531698321.79074084653352
0.0854.53056881561221.82151212983194
0.0955.32056034335471.82727219706330
0.156.07468130436491.83570202213093
0.1156.80052222915231.86807722674682
0.1257.50981672871011.92941246140392
0.1358.213588963072.00931740957477
0.1458.91876620078572.09170887690375
0.1559.62756587603062.16494888616755
0.1660.33906350542152.22616450332467
0.1761.05142855790472.27954629098481
0.1861.76345373617142.33041936011435
0.1962.4748518683682.38115038096804
0.263.18567554865652.43005107530583
0.2163.89561676489282.47304054746362
0.2264.60380157921992.50772652733493
0.2365.30925672711122.53492283407552
0.2466.01178748468372.5607925677896
0.2566.71276179131062.59439829015487
0.2667.41531028194712.64438843003516
0.2768.12369099188182.71430126728268
0.2868.84192544735022.79957655464214
0.2969.57214837859062.88777305121951
0.370.31329584451272.96144349969375
0.3171.06071176067613.00371163881299
0.3271.80698891767573.00502246825176
0.3372.54396548376082.96623072145906
0.3473.26540757974332.90240794888379
0.3573.96965680454432.83995943306992
0.3674.66149157296832.81259132258093
0.3775.35264700383612.85488734007986
0.3876.06079040891452.9922517774548
0.3976.80714766255973.23308634803172
0.477.6133093174953.56842611176112
0.4178.4979338413583.97337770040682
0.4279.47407052310824.41537140380969
0.4380.547650113254.85913958874626
0.4481.71737958308585.274519570218
0.4582.9759061290355.63961752872508
0.4684.31178695547995.94404081948432
0.4785.71161785050786.18621487751166
0.4887.16170162729026.37096723339106
0.4988.64887487543536.50298775411605
0.590.16047705783236.58381944595907
0.5191.68380394679576.61035834010582
0.5293.20559906895846.57659628045832
0.5394.7121181507666.47815175058552
0.5496.19005876846956.3168664892416
0.5597.62827436342536.10549460412446
0.5699.01983112755465.86729907362865
0.57100.3637535178525.63324794673863
0.58101.6658190915755.43712572275672
0.59102.9380056732705.30718633199557
0.6104.1965870783255.25963346083963
0.61105.4592906656795.29339553993023
0.62106.7422313171045.39160931353158
0.63108.0574126553095.52766163964248
0.64109.4113975524635.67246276019038
0.65110.8053500290935.80255020951329
0.66112.2361808709195.90367930837646
0.67113.6981734039155.97078517230152
0.68115.1843743852166.00503046846402
0.69116.6872502199496.00775797084256
0.7118.1985314848935.97649160946513
0.71119.7085943540505.90445435289684
0.72121.2059441072155.78261839241472
0.73122.6772684704525.60336098529145
0.74124.1081841091375.36562463813404
0.75125.4844175548435.07433463178187
0.76126.7929759642464.73962940745695
0.77128.0229896395584.37372371269105
0.78129.1662688971613.98780862753725
0.79130.2179820314863.5939973835562
0.8131.1779832484953.20765026298166
0.81132.0530802575992.85186339593154
0.82132.8599923240802.56083676524391
0.83133.6281071634882.37884710783795
0.84134.4006533917292.35265002798323
0.85135.2328449114792.51384040822893
0.86136.1862108882542.8586918552878
0.87137.3198262923853.34406051672652
0.88138.6810766695393.89986385859696
0.89140.2996554232944.45151643224647
0.9142.1871727410514.94160361384314
0.91144.3410488178815.33803291624511
0.92146.7481458021635.62010333069281
0.93149.3844695148685.75850235079898
0.94152.2116551915405.71673153132909
0.95155.1759477576705.46507810090352
0.96158.2296412442864.99881249549688
0.97161.4262014838324.44831094306853
0.98165.0816822720364.2557287124976
0.99169.4645007950354.6729933143613



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')