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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 computationFri, 09 Oct 2015 10:59:07 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Oct/09/t14443847796x79ghgguktv1ds.htm/, Retrieved Tue, 14 May 2024 15:54:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=281790, Retrieved Tue, 14 May 2024 15:54:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact55

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] [] [2015-10-09 09:59:07] [45f7fcffe569af381f5269bedb4e9f14] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
79.55
80.08
80.15
80.69
81.56
81.23
81.39
81.61
82.25
82.06
82.82
82.3
83.09
83.21
83.13
84.31
83.62
83.75
84.1
83.71
84.2
85.13
86.16
86.65
87.44
87.62
88.03
89.1
89.68
89.47
90.13
89.49
89.52
89.86
89.77
89.8
90.89
90.82
90.68
90.92
90.82
90.09
89.71
89.34
89.2
89.48
89.72
89.58
90.65
90.93
91.42
91.52
91.76
91.47
91.37
91.35
91.74
91.78
91.88
91.99
92.55
92.94
92.81
93.35
93.72
93.94
94.03
93.66
93.78
94.1
94.85
94.83
95.06
95.87
95.97
95.96
96.3
96.17
96.18
96.55
96.76
97.63
97.86
97.82
98.62
99.24
99.63
100.27
100.84
101.05
100.38
100.02
99.97
99.95
100
100.04
100.51
100.29
100.22
101.29
100.29
100.26
100.39
99.3
98.9
98.76
99.12
99.28

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' @ fisher.wessa.net

\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' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281790&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' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=281790&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281790&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' @ fisher.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0179.81883279224330.419729354766253
0.0280.19346712233040.458028850589454
0.0380.56508947343140.551954133209754
0.0480.91773315289540.568053544848888
0.0581.23743213138660.540455574348212
0.0681.52085586880960.530549780799092
0.0781.77979668523030.553321598942079
0.0882.02838133286560.590958739762165
0.0982.27431016083090.624935196071731
0.182.51888301487930.6480926939531
0.1182.76097920637740.664489669965949
0.1283.00081455281030.685506507916521
0.1383.24198494133790.726369481722571
0.1483.49176836433510.800816539628046
0.1583.76006216963630.916144187058295
0.1684.05739728127991.07034903275923
0.1784.39252829054341.2512619309744
0.1884.77016736923421.43899181397904
0.1985.18942463626011.61007261720917
0.285.643364736421.74163889954469
0.2186.11979451947551.81663833555019
0.2286.60305721479561.82596884673842
0.2387.07635892528721.76970996819164
0.2487.52408147006091.65582212025113
0.2587.93363668484131.49869996737356
0.2688.29661394797671.31513002615273
0.2788.60917351297091.12247157895958
0.2888.87178505112930.936615115072543
0.2989.08848965589280.770215733946453
0.389.26588739392870.632344209243193
0.3189.41203962413270.527787131718421
0.3289.5354393338040.458452389770969
0.3389.64415384670470.421773304915928
0.3489.74519308155860.412709167179134
0.3589.84411388809170.423636969847667
0.3689.94484371400770.446584959714916
0.3790.04969455065580.474483412340907
0.3890.15953416778950.501595385490048
0.3990.2740782637260.523403258262791
0.490.39226058345660.538088889818244
0.4190.51263062415070.544966039780307
0.4290.63372631310490.544916452860593
0.4390.7543769902390.540165602130125
0.4490.87391009185860.533631258509141
0.4590.9922573592370.528495287832186
0.4691.10997469523630.527319147694054
0.4791.22819741395820.532303454025446
0.4891.34854858540290.546045609352644
0.4991.47300761250570.569873769909235
0.591.60373763362620.604225493072137
0.5191.74287122455270.648407813378718
0.5291.89226641889820.700268520196873
0.5392.05326476884960.756726330412986
0.5492.22650039429750.813653309384672
0.5592.41181308930940.86688626088058
0.5692.60830290375360.913036134387225
0.5792.81452921304110.950027893655842
0.5893.0288136875310.977691741433956
0.5993.24956921300990.997474035513631
0.693.47556150438211.01209950962003
0.6193.7060265674161.02452726981662
0.6293.94061381344681.03674885457151
0.6394.17918762019121.04916305397314
0.6494.42157675964741.06067273250223
0.6594.66738771094361.06915036621359
0.6694.91597936488631.07282418091321
0.6795.16663419610091.07130253799435
0.6895.41887431240191.06616904818074
0.6995.67279287739451.06091633552965
0.795.92923671605761.0602581085579
0.7196.18970589354271.0673572997487
0.7296.45592789408971.08306916212651
0.7396.7291884542881.10401104889652
0.7497.00961162473521.12348602208018
0.7597.29563234660031.13299645089515
0.7697.58386945653671.12486749693956
0.7797.8694906544391.09407709214542
0.7898.14699952740851.0398342580988
0.7998.41122337920470.965917481692043
0.898.65819626421680.879263592606408
0.8198.8856546079690.788185902849453
0.8299.09299990657720.699976332397865
0.8399.28079429539670.618693483329409
0.8499.45005334418310.544785008599234
0.8599.60168008983320.476252901084551
0.8699.73628017473310.410939708627348
0.8799.85435202335620.348401535472788
0.8899.95661679332820.289994765656542
0.89100.0442217188090.237960922605497
0.9100.1187635119310.193299412675636
0.91100.1823671230980.156296254334237
0.92100.238164757050.127898713508963
0.93100.2913558673090.112204438577539
0.94100.3506665101220.116842344300322
0.95100.4293349334650.148743004584912
0.96100.5435098324140.204972548868453
0.97100.7057105681810.261658603882506
0.98100.9144964716370.278057561965499
0.99101.139201961220.248119953397125

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 79.8188327922433 & 0.419729354766253 \tabularnewline
0.02 & 80.1934671223304 & 0.458028850589454 \tabularnewline
0.03 & 80.5650894734314 & 0.551954133209754 \tabularnewline
0.04 & 80.9177331528954 & 0.568053544848888 \tabularnewline
0.05 & 81.2374321313866 & 0.540455574348212 \tabularnewline
0.06 & 81.5208558688096 & 0.530549780799092 \tabularnewline
0.07 & 81.7797966852303 & 0.553321598942079 \tabularnewline
0.08 & 82.0283813328656 & 0.590958739762165 \tabularnewline
0.09 & 82.2743101608309 & 0.624935196071731 \tabularnewline
0.1 & 82.5188830148793 & 0.6480926939531 \tabularnewline
0.11 & 82.7609792063774 & 0.664489669965949 \tabularnewline
0.12 & 83.0008145528103 & 0.685506507916521 \tabularnewline
0.13 & 83.2419849413379 & 0.726369481722571 \tabularnewline
0.14 & 83.4917683643351 & 0.800816539628046 \tabularnewline
0.15 & 83.7600621696363 & 0.916144187058295 \tabularnewline
0.16 & 84.0573972812799 & 1.07034903275923 \tabularnewline
0.17 & 84.3925282905434 & 1.2512619309744 \tabularnewline
0.18 & 84.7701673692342 & 1.43899181397904 \tabularnewline
0.19 & 85.1894246362601 & 1.61007261720917 \tabularnewline
0.2 & 85.64336473642 & 1.74163889954469 \tabularnewline
0.21 & 86.1197945194755 & 1.81663833555019 \tabularnewline
0.22 & 86.6030572147956 & 1.82596884673842 \tabularnewline
0.23 & 87.0763589252872 & 1.76970996819164 \tabularnewline
0.24 & 87.5240814700609 & 1.65582212025113 \tabularnewline
0.25 & 87.9336366848413 & 1.49869996737356 \tabularnewline
0.26 & 88.2966139479767 & 1.31513002615273 \tabularnewline
0.27 & 88.6091735129709 & 1.12247157895958 \tabularnewline
0.28 & 88.8717850511293 & 0.936615115072543 \tabularnewline
0.29 & 89.0884896558928 & 0.770215733946453 \tabularnewline
0.3 & 89.2658873939287 & 0.632344209243193 \tabularnewline
0.31 & 89.4120396241327 & 0.527787131718421 \tabularnewline
0.32 & 89.535439333804 & 0.458452389770969 \tabularnewline
0.33 & 89.6441538467047 & 0.421773304915928 \tabularnewline
0.34 & 89.7451930815586 & 0.412709167179134 \tabularnewline
0.35 & 89.8441138880917 & 0.423636969847667 \tabularnewline
0.36 & 89.9448437140077 & 0.446584959714916 \tabularnewline
0.37 & 90.0496945506558 & 0.474483412340907 \tabularnewline
0.38 & 90.1595341677895 & 0.501595385490048 \tabularnewline
0.39 & 90.274078263726 & 0.523403258262791 \tabularnewline
0.4 & 90.3922605834566 & 0.538088889818244 \tabularnewline
0.41 & 90.5126306241507 & 0.544966039780307 \tabularnewline
0.42 & 90.6337263131049 & 0.544916452860593 \tabularnewline
0.43 & 90.754376990239 & 0.540165602130125 \tabularnewline
0.44 & 90.8739100918586 & 0.533631258509141 \tabularnewline
0.45 & 90.992257359237 & 0.528495287832186 \tabularnewline
0.46 & 91.1099746952363 & 0.527319147694054 \tabularnewline
0.47 & 91.2281974139582 & 0.532303454025446 \tabularnewline
0.48 & 91.3485485854029 & 0.546045609352644 \tabularnewline
0.49 & 91.4730076125057 & 0.569873769909235 \tabularnewline
0.5 & 91.6037376336262 & 0.604225493072137 \tabularnewline
0.51 & 91.7428712245527 & 0.648407813378718 \tabularnewline
0.52 & 91.8922664188982 & 0.700268520196873 \tabularnewline
0.53 & 92.0532647688496 & 0.756726330412986 \tabularnewline
0.54 & 92.2265003942975 & 0.813653309384672 \tabularnewline
0.55 & 92.4118130893094 & 0.86688626088058 \tabularnewline
0.56 & 92.6083029037536 & 0.913036134387225 \tabularnewline
0.57 & 92.8145292130411 & 0.950027893655842 \tabularnewline
0.58 & 93.028813687531 & 0.977691741433956 \tabularnewline
0.59 & 93.2495692130099 & 0.997474035513631 \tabularnewline
0.6 & 93.4755615043821 & 1.01209950962003 \tabularnewline
0.61 & 93.706026567416 & 1.02452726981662 \tabularnewline
0.62 & 93.9406138134468 & 1.03674885457151 \tabularnewline
0.63 & 94.1791876201912 & 1.04916305397314 \tabularnewline
0.64 & 94.4215767596474 & 1.06067273250223 \tabularnewline
0.65 & 94.6673877109436 & 1.06915036621359 \tabularnewline
0.66 & 94.9159793648863 & 1.07282418091321 \tabularnewline
0.67 & 95.1666341961009 & 1.07130253799435 \tabularnewline
0.68 & 95.4188743124019 & 1.06616904818074 \tabularnewline
0.69 & 95.6727928773945 & 1.06091633552965 \tabularnewline
0.7 & 95.9292367160576 & 1.0602581085579 \tabularnewline
0.71 & 96.1897058935427 & 1.0673572997487 \tabularnewline
0.72 & 96.4559278940897 & 1.08306916212651 \tabularnewline
0.73 & 96.729188454288 & 1.10401104889652 \tabularnewline
0.74 & 97.0096116247352 & 1.12348602208018 \tabularnewline
0.75 & 97.2956323466003 & 1.13299645089515 \tabularnewline
0.76 & 97.5838694565367 & 1.12486749693956 \tabularnewline
0.77 & 97.869490654439 & 1.09407709214542 \tabularnewline
0.78 & 98.1469995274085 & 1.0398342580988 \tabularnewline
0.79 & 98.4112233792047 & 0.965917481692043 \tabularnewline
0.8 & 98.6581962642168 & 0.879263592606408 \tabularnewline
0.81 & 98.885654607969 & 0.788185902849453 \tabularnewline
0.82 & 99.0929999065772 & 0.699976332397865 \tabularnewline
0.83 & 99.2807942953967 & 0.618693483329409 \tabularnewline
0.84 & 99.4500533441831 & 0.544785008599234 \tabularnewline
0.85 & 99.6016800898332 & 0.476252901084551 \tabularnewline
0.86 & 99.7362801747331 & 0.410939708627348 \tabularnewline
0.87 & 99.8543520233562 & 0.348401535472788 \tabularnewline
0.88 & 99.9566167933282 & 0.289994765656542 \tabularnewline
0.89 & 100.044221718809 & 0.237960922605497 \tabularnewline
0.9 & 100.118763511931 & 0.193299412675636 \tabularnewline
0.91 & 100.182367123098 & 0.156296254334237 \tabularnewline
0.92 & 100.23816475705 & 0.127898713508963 \tabularnewline
0.93 & 100.291355867309 & 0.112204438577539 \tabularnewline
0.94 & 100.350666510122 & 0.116842344300322 \tabularnewline
0.95 & 100.429334933465 & 0.148743004584912 \tabularnewline
0.96 & 100.543509832414 & 0.204972548868453 \tabularnewline
0.97 & 100.705710568181 & 0.261658603882506 \tabularnewline
0.98 & 100.914496471637 & 0.278057561965499 \tabularnewline
0.99 & 101.13920196122 & 0.248119953397125 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281790&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]79.8188327922433[/C][C]0.419729354766253[/C][/ROW]
[ROW][C]0.02[/C][C]80.1934671223304[/C][C]0.458028850589454[/C][/ROW]
[ROW][C]0.03[/C][C]80.5650894734314[/C][C]0.551954133209754[/C][/ROW]
[ROW][C]0.04[/C][C]80.9177331528954[/C][C]0.568053544848888[/C][/ROW]
[ROW][C]0.05[/C][C]81.2374321313866[/C][C]0.540455574348212[/C][/ROW]
[ROW][C]0.06[/C][C]81.5208558688096[/C][C]0.530549780799092[/C][/ROW]
[ROW][C]0.07[/C][C]81.7797966852303[/C][C]0.553321598942079[/C][/ROW]
[ROW][C]0.08[/C][C]82.0283813328656[/C][C]0.590958739762165[/C][/ROW]
[ROW][C]0.09[/C][C]82.2743101608309[/C][C]0.624935196071731[/C][/ROW]
[ROW][C]0.1[/C][C]82.5188830148793[/C][C]0.6480926939531[/C][/ROW]
[ROW][C]0.11[/C][C]82.7609792063774[/C][C]0.664489669965949[/C][/ROW]
[ROW][C]0.12[/C][C]83.0008145528103[/C][C]0.685506507916521[/C][/ROW]
[ROW][C]0.13[/C][C]83.2419849413379[/C][C]0.726369481722571[/C][/ROW]
[ROW][C]0.14[/C][C]83.4917683643351[/C][C]0.800816539628046[/C][/ROW]
[ROW][C]0.15[/C][C]83.7600621696363[/C][C]0.916144187058295[/C][/ROW]
[ROW][C]0.16[/C][C]84.0573972812799[/C][C]1.07034903275923[/C][/ROW]
[ROW][C]0.17[/C][C]84.3925282905434[/C][C]1.2512619309744[/C][/ROW]
[ROW][C]0.18[/C][C]84.7701673692342[/C][C]1.43899181397904[/C][/ROW]
[ROW][C]0.19[/C][C]85.1894246362601[/C][C]1.61007261720917[/C][/ROW]
[ROW][C]0.2[/C][C]85.64336473642[/C][C]1.74163889954469[/C][/ROW]
[ROW][C]0.21[/C][C]86.1197945194755[/C][C]1.81663833555019[/C][/ROW]
[ROW][C]0.22[/C][C]86.6030572147956[/C][C]1.82596884673842[/C][/ROW]
[ROW][C]0.23[/C][C]87.0763589252872[/C][C]1.76970996819164[/C][/ROW]
[ROW][C]0.24[/C][C]87.5240814700609[/C][C]1.65582212025113[/C][/ROW]
[ROW][C]0.25[/C][C]87.9336366848413[/C][C]1.49869996737356[/C][/ROW]
[ROW][C]0.26[/C][C]88.2966139479767[/C][C]1.31513002615273[/C][/ROW]
[ROW][C]0.27[/C][C]88.6091735129709[/C][C]1.12247157895958[/C][/ROW]
[ROW][C]0.28[/C][C]88.8717850511293[/C][C]0.936615115072543[/C][/ROW]
[ROW][C]0.29[/C][C]89.0884896558928[/C][C]0.770215733946453[/C][/ROW]
[ROW][C]0.3[/C][C]89.2658873939287[/C][C]0.632344209243193[/C][/ROW]
[ROW][C]0.31[/C][C]89.4120396241327[/C][C]0.527787131718421[/C][/ROW]
[ROW][C]0.32[/C][C]89.535439333804[/C][C]0.458452389770969[/C][/ROW]
[ROW][C]0.33[/C][C]89.6441538467047[/C][C]0.421773304915928[/C][/ROW]
[ROW][C]0.34[/C][C]89.7451930815586[/C][C]0.412709167179134[/C][/ROW]
[ROW][C]0.35[/C][C]89.8441138880917[/C][C]0.423636969847667[/C][/ROW]
[ROW][C]0.36[/C][C]89.9448437140077[/C][C]0.446584959714916[/C][/ROW]
[ROW][C]0.37[/C][C]90.0496945506558[/C][C]0.474483412340907[/C][/ROW]
[ROW][C]0.38[/C][C]90.1595341677895[/C][C]0.501595385490048[/C][/ROW]
[ROW][C]0.39[/C][C]90.274078263726[/C][C]0.523403258262791[/C][/ROW]
[ROW][C]0.4[/C][C]90.3922605834566[/C][C]0.538088889818244[/C][/ROW]
[ROW][C]0.41[/C][C]90.5126306241507[/C][C]0.544966039780307[/C][/ROW]
[ROW][C]0.42[/C][C]90.6337263131049[/C][C]0.544916452860593[/C][/ROW]
[ROW][C]0.43[/C][C]90.754376990239[/C][C]0.540165602130125[/C][/ROW]
[ROW][C]0.44[/C][C]90.8739100918586[/C][C]0.533631258509141[/C][/ROW]
[ROW][C]0.45[/C][C]90.992257359237[/C][C]0.528495287832186[/C][/ROW]
[ROW][C]0.46[/C][C]91.1099746952363[/C][C]0.527319147694054[/C][/ROW]
[ROW][C]0.47[/C][C]91.2281974139582[/C][C]0.532303454025446[/C][/ROW]
[ROW][C]0.48[/C][C]91.3485485854029[/C][C]0.546045609352644[/C][/ROW]
[ROW][C]0.49[/C][C]91.4730076125057[/C][C]0.569873769909235[/C][/ROW]
[ROW][C]0.5[/C][C]91.6037376336262[/C][C]0.604225493072137[/C][/ROW]
[ROW][C]0.51[/C][C]91.7428712245527[/C][C]0.648407813378718[/C][/ROW]
[ROW][C]0.52[/C][C]91.8922664188982[/C][C]0.700268520196873[/C][/ROW]
[ROW][C]0.53[/C][C]92.0532647688496[/C][C]0.756726330412986[/C][/ROW]
[ROW][C]0.54[/C][C]92.2265003942975[/C][C]0.813653309384672[/C][/ROW]
[ROW][C]0.55[/C][C]92.4118130893094[/C][C]0.86688626088058[/C][/ROW]
[ROW][C]0.56[/C][C]92.6083029037536[/C][C]0.913036134387225[/C][/ROW]
[ROW][C]0.57[/C][C]92.8145292130411[/C][C]0.950027893655842[/C][/ROW]
[ROW][C]0.58[/C][C]93.028813687531[/C][C]0.977691741433956[/C][/ROW]
[ROW][C]0.59[/C][C]93.2495692130099[/C][C]0.997474035513631[/C][/ROW]
[ROW][C]0.6[/C][C]93.4755615043821[/C][C]1.01209950962003[/C][/ROW]
[ROW][C]0.61[/C][C]93.706026567416[/C][C]1.02452726981662[/C][/ROW]
[ROW][C]0.62[/C][C]93.9406138134468[/C][C]1.03674885457151[/C][/ROW]
[ROW][C]0.63[/C][C]94.1791876201912[/C][C]1.04916305397314[/C][/ROW]
[ROW][C]0.64[/C][C]94.4215767596474[/C][C]1.06067273250223[/C][/ROW]
[ROW][C]0.65[/C][C]94.6673877109436[/C][C]1.06915036621359[/C][/ROW]
[ROW][C]0.66[/C][C]94.9159793648863[/C][C]1.07282418091321[/C][/ROW]
[ROW][C]0.67[/C][C]95.1666341961009[/C][C]1.07130253799435[/C][/ROW]
[ROW][C]0.68[/C][C]95.4188743124019[/C][C]1.06616904818074[/C][/ROW]
[ROW][C]0.69[/C][C]95.6727928773945[/C][C]1.06091633552965[/C][/ROW]
[ROW][C]0.7[/C][C]95.9292367160576[/C][C]1.0602581085579[/C][/ROW]
[ROW][C]0.71[/C][C]96.1897058935427[/C][C]1.0673572997487[/C][/ROW]
[ROW][C]0.72[/C][C]96.4559278940897[/C][C]1.08306916212651[/C][/ROW]
[ROW][C]0.73[/C][C]96.729188454288[/C][C]1.10401104889652[/C][/ROW]
[ROW][C]0.74[/C][C]97.0096116247352[/C][C]1.12348602208018[/C][/ROW]
[ROW][C]0.75[/C][C]97.2956323466003[/C][C]1.13299645089515[/C][/ROW]
[ROW][C]0.76[/C][C]97.5838694565367[/C][C]1.12486749693956[/C][/ROW]
[ROW][C]0.77[/C][C]97.869490654439[/C][C]1.09407709214542[/C][/ROW]
[ROW][C]0.78[/C][C]98.1469995274085[/C][C]1.0398342580988[/C][/ROW]
[ROW][C]0.79[/C][C]98.4112233792047[/C][C]0.965917481692043[/C][/ROW]
[ROW][C]0.8[/C][C]98.6581962642168[/C][C]0.879263592606408[/C][/ROW]
[ROW][C]0.81[/C][C]98.885654607969[/C][C]0.788185902849453[/C][/ROW]
[ROW][C]0.82[/C][C]99.0929999065772[/C][C]0.699976332397865[/C][/ROW]
[ROW][C]0.83[/C][C]99.2807942953967[/C][C]0.618693483329409[/C][/ROW]
[ROW][C]0.84[/C][C]99.4500533441831[/C][C]0.544785008599234[/C][/ROW]
[ROW][C]0.85[/C][C]99.6016800898332[/C][C]0.476252901084551[/C][/ROW]
[ROW][C]0.86[/C][C]99.7362801747331[/C][C]0.410939708627348[/C][/ROW]
[ROW][C]0.87[/C][C]99.8543520233562[/C][C]0.348401535472788[/C][/ROW]
[ROW][C]0.88[/C][C]99.9566167933282[/C][C]0.289994765656542[/C][/ROW]
[ROW][C]0.89[/C][C]100.044221718809[/C][C]0.237960922605497[/C][/ROW]
[ROW][C]0.9[/C][C]100.118763511931[/C][C]0.193299412675636[/C][/ROW]
[ROW][C]0.91[/C][C]100.182367123098[/C][C]0.156296254334237[/C][/ROW]
[ROW][C]0.92[/C][C]100.23816475705[/C][C]0.127898713508963[/C][/ROW]
[ROW][C]0.93[/C][C]100.291355867309[/C][C]0.112204438577539[/C][/ROW]
[ROW][C]0.94[/C][C]100.350666510122[/C][C]0.116842344300322[/C][/ROW]
[ROW][C]0.95[/C][C]100.429334933465[/C][C]0.148743004584912[/C][/ROW]
[ROW][C]0.96[/C][C]100.543509832414[/C][C]0.204972548868453[/C][/ROW]
[ROW][C]0.97[/C][C]100.705710568181[/C][C]0.261658603882506[/C][/ROW]
[ROW][C]0.98[/C][C]100.914496471637[/C][C]0.278057561965499[/C][/ROW]
[ROW][C]0.99[/C][C]101.13920196122[/C][C]0.248119953397125[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=281790&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281790&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
0.0179.81883279224330.419729354766253
0.0280.19346712233040.458028850589454
0.0380.56508947343140.551954133209754
0.0480.91773315289540.568053544848888
0.0581.23743213138660.540455574348212
0.0681.52085586880960.530549780799092
0.0781.77979668523030.553321598942079
0.0882.02838133286560.590958739762165
0.0982.27431016083090.624935196071731
0.182.51888301487930.6480926939531
0.1182.76097920637740.664489669965949
0.1283.00081455281030.685506507916521
0.1383.24198494133790.726369481722571
0.1483.49176836433510.800816539628046
0.1583.76006216963630.916144187058295
0.1684.05739728127991.07034903275923
0.1784.39252829054341.2512619309744
0.1884.77016736923421.43899181397904
0.1985.18942463626011.61007261720917
0.285.643364736421.74163889954469
0.2186.11979451947551.81663833555019
0.2286.60305721479561.82596884673842
0.2387.07635892528721.76970996819164
0.2487.52408147006091.65582212025113
0.2587.93363668484131.49869996737356
0.2688.29661394797671.31513002615273
0.2788.60917351297091.12247157895958
0.2888.87178505112930.936615115072543
0.2989.08848965589280.770215733946453
0.389.26588739392870.632344209243193
0.3189.41203962413270.527787131718421
0.3289.5354393338040.458452389770969
0.3389.64415384670470.421773304915928
0.3489.74519308155860.412709167179134
0.3589.84411388809170.423636969847667
0.3689.94484371400770.446584959714916
0.3790.04969455065580.474483412340907
0.3890.15953416778950.501595385490048
0.3990.2740782637260.523403258262791
0.490.39226058345660.538088889818244
0.4190.51263062415070.544966039780307
0.4290.63372631310490.544916452860593
0.4390.7543769902390.540165602130125
0.4490.87391009185860.533631258509141
0.4590.9922573592370.528495287832186
0.4691.10997469523630.527319147694054
0.4791.22819741395820.532303454025446
0.4891.34854858540290.546045609352644
0.4991.47300761250570.569873769909235
0.591.60373763362620.604225493072137
0.5191.74287122455270.648407813378718
0.5291.89226641889820.700268520196873
0.5392.05326476884960.756726330412986
0.5492.22650039429750.813653309384672
0.5592.41181308930940.86688626088058
0.5692.60830290375360.913036134387225
0.5792.81452921304110.950027893655842
0.5893.0288136875310.977691741433956
0.5993.24956921300990.997474035513631
0.693.47556150438211.01209950962003
0.6193.7060265674161.02452726981662
0.6293.94061381344681.03674885457151
0.6394.17918762019121.04916305397314
0.6494.42157675964741.06067273250223
0.6594.66738771094361.06915036621359
0.6694.91597936488631.07282418091321
0.6795.16663419610091.07130253799435
0.6895.41887431240191.06616904818074
0.6995.67279287739451.06091633552965
0.795.92923671605761.0602581085579
0.7196.18970589354271.0673572997487
0.7296.45592789408971.08306916212651
0.7396.7291884542881.10401104889652
0.7497.00961162473521.12348602208018
0.7597.29563234660031.13299645089515
0.7697.58386945653671.12486749693956
0.7797.8694906544391.09407709214542
0.7898.14699952740851.0398342580988
0.7998.41122337920470.965917481692043
0.898.65819626421680.879263592606408
0.8198.8856546079690.788185902849453
0.8299.09299990657720.699976332397865
0.8399.28079429539670.618693483329409
0.8499.45005334418310.544785008599234
0.8599.60168008983320.476252901084551
0.8699.73628017473310.410939708627348
0.8799.85435202335620.348401535472788
0.8899.95661679332820.289994765656542
0.89100.0442217188090.237960922605497
0.9100.1187635119310.193299412675636
0.91100.1823671230980.156296254334237
0.92100.238164757050.127898713508963
0.93100.2913558673090.112204438577539
0.94100.3506665101220.116842344300322
0.95100.4293349334650.148743004584912
0.96100.5435098324140.204972548868453
0.97100.7057105681810.261658603882506
0.98100.9144964716370.278057561965499
0.99101.139201961220.248119953397125


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')