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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 computationWed, 11 May 2011 16:05:07 +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/2011/May/11/t1305129673d2x9i63bebdjmrh.htm/, Retrieved Sun, 12 May 2024 12:27:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=121486, Retrieved Sun, 12 May 2024 12:27:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W42
Estimated Impact182

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] [Alexander De Raey...] [2011-03-28 14:07:28] [675ca10949301e72ce218fb68f2a4e5b]
-   PD  [Harrell-Davis Quantiles] [Alexander De Raey...] [2011-05-11 16:01:21] [09fc22fedfbb751b12100a70db5b24cf]
- R P       [Harrell-Davis Quantiles] [Alexander De Raey...] [2011-05-11 16:05:07] [5a7d09d873e8aad035bee87e31ebac43] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2435
1379
1511
2021
1614
1680
1630
870
1877
2428
1711
127
3192
1934
2075
1700
1198
1582
1705
911
1817
1168
920
84
2254
1485
1886
1358
1167
1781
1218
779
1418
1641
1196
132
2926
1777
2094
1648
1646
1537
1917
977
1475
2124
1209
135
2917
1981
1398
1171
903
1390
1280
781
1828
1631
1063
186
2275
1342
1070
950
1121
1305
1586
548
1225
1419
880
124
2044
1143
897
1264
1326
1529
1373
587
1137
1426
1016
176
2614

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=121486&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=121486&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121486&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
084NA
0.0197.081763614630229.3068315689719
0.02114.31041782950821.7543907937685
0.03131.72511088158632.5795295234754
0.04153.71304055820563.5193019884044
0.05186.841514924497109.084692758121
0.06235.373611173666160.937242764593
0.07299.696845884276207.976283170907
0.08376.465649874422240.272325362983
0.09459.847531923452252.628251667365
0.1543.313448412625245.592094412968
0.11621.276418055778223.991173178971
0.12690.06982648997194.396194368679
0.13748.154053138708162.938491039453
0.14795.759436044943134.157750628166
0.15834.280517211715110.783715294261
0.16865.67391194290894.0155966790647
0.17891.98979289203483.8728005044779
0.18915.06664926797379.4385089749947
0.19936.36704643270379.1677973927888
0.2956.91811728604881.3029554789697
0.21977.32431845973884.2645931071315
0.22997.82730724384786.8375525506272
0.231018.393100083388.2192044248175
0.241038.8098841163488.0019372728325
0.251058.7825433064786.1318969852454
0.261078.0132272623982.8265830596978
0.271096.2612516352678.5030981882432
0.281113.379741335873.6762899354276
0.291129.3300262758868.8803898819203
0.31144.1773816060864.6004264012855
0.311158.0731007606161.221052358421
0.321171.2282209811658.9860898153158
0.331183.8837865830357.9844209639244
0.341196.2816841081158.1446760711926
0.351208.6391101759559.2680902720871
0.361221.1288173798861.0630085476483
0.371233.8664823933863.1968373544244
0.381246.9058206838965.337033623809
0.391260.2413709504767.1923636798005
0.41273.8181550400468.544268118452
0.411287.5467136755869.2668684585149
0.421301.321413971369.3386427623625
0.431315.0395389689468.8312134945127
0.441328.6186017951967.9115850073946
0.451342.0096195670766.7986062265285
0.461355.204702050165.7459470955709
0.471368.2381574960164.9928224185893
0.481381.1812523438464.72816820833
0.491394.1316334902165.073951021536
0.51407.1991029778166.048782376116
0.511420.4898369017467.5757981514171
0.521434.0912256108469.4966987424578
0.531448.0592964849371.5944743497955
0.541462.4102267125273.6257237813611
0.551477.1168576749375.3496353703775
0.561492.1104914918676.5621210011385
0.571507.2876750696377.0997851970544
0.581522.5212114427876.8749303779795
0.591537.6742915564375.8745063652148
0.61552.6163885984674.1682651289256
0.611567.2393731716471.9022037182451
0.621581.4721873457769.2947049511555
0.631595.2923955231666.6197335098441
0.641608.7330768487264.1811483241213
0.651621.8839007348762.2846634414821
0.661634.8858515278461.1900479990978
0.671647.9198845698161.0827357170007
0.681661.1906773305562.0347425340362
0.691674.9074224371263.9952199990695
0.71689.2641425012666.7997321444275
0.711704.422188292170.2056566499631
0.721720.4973732512673.9250349556622
0.731737.5536091812177.66808036174
0.741755.6039815293481.1785538325891
0.751774.6190120893784.2638139587517
0.761794.5405442831786.8194146913606
0.771815.2985160013588.8318920030265
0.781836.8272712907290.366635342687
0.791859.0785022838691.5412901421407
0.81882.0297717117292.4783072983284
0.811905.690716958593.2934110898817
0.821930.1124832212294.0823294967156
0.831955.4077049865594.980880744953
0.841981.7860483447496.2534093548655
0.852009.6025458979498.3613518792472
0.862039.40440408867101.982056898875
0.872071.95312048742107.824395492911
0.882108.20322848118116.311387201953
0.892149.24616926982127.276906667633
0.92196.27381040073140.018570068123
0.912250.64668202903153.85103609956
0.922314.09374576773168.966556213991
0.932388.85272394793186.771569675201
0.942477.27062392948208.070935647954
0.952580.50426099497228.422434078977
0.962697.18969983584235.452446710049
0.972824.48773226026218.106481493237
0.982960.67460847002193.019225114481
0.993096.85339511136212.304934476003
13192NA

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0 & 84 & NA \tabularnewline
0.01 & 97.0817636146302 & 29.3068315689719 \tabularnewline
0.02 & 114.310417829508 & 21.7543907937685 \tabularnewline
0.03 & 131.725110881586 & 32.5795295234754 \tabularnewline
0.04 & 153.713040558205 & 63.5193019884044 \tabularnewline
0.05 & 186.841514924497 & 109.084692758121 \tabularnewline
0.06 & 235.373611173666 & 160.937242764593 \tabularnewline
0.07 & 299.696845884276 & 207.976283170907 \tabularnewline
0.08 & 376.465649874422 & 240.272325362983 \tabularnewline
0.09 & 459.847531923452 & 252.628251667365 \tabularnewline
0.1 & 543.313448412625 & 245.592094412968 \tabularnewline
0.11 & 621.276418055778 & 223.991173178971 \tabularnewline
0.12 & 690.06982648997 & 194.396194368679 \tabularnewline
0.13 & 748.154053138708 & 162.938491039453 \tabularnewline
0.14 & 795.759436044943 & 134.157750628166 \tabularnewline
0.15 & 834.280517211715 & 110.783715294261 \tabularnewline
0.16 & 865.673911942908 & 94.0155966790647 \tabularnewline
0.17 & 891.989792892034 & 83.8728005044779 \tabularnewline
0.18 & 915.066649267973 & 79.4385089749947 \tabularnewline
0.19 & 936.367046432703 & 79.1677973927888 \tabularnewline
0.2 & 956.918117286048 & 81.3029554789697 \tabularnewline
0.21 & 977.324318459738 & 84.2645931071315 \tabularnewline
0.22 & 997.827307243847 & 86.8375525506272 \tabularnewline
0.23 & 1018.3931000833 & 88.2192044248175 \tabularnewline
0.24 & 1038.80988411634 & 88.0019372728325 \tabularnewline
0.25 & 1058.78254330647 & 86.1318969852454 \tabularnewline
0.26 & 1078.01322726239 & 82.8265830596978 \tabularnewline
0.27 & 1096.26125163526 & 78.5030981882432 \tabularnewline
0.28 & 1113.3797413358 & 73.6762899354276 \tabularnewline
0.29 & 1129.33002627588 & 68.8803898819203 \tabularnewline
0.3 & 1144.17738160608 & 64.6004264012855 \tabularnewline
0.31 & 1158.07310076061 & 61.221052358421 \tabularnewline
0.32 & 1171.22822098116 & 58.9860898153158 \tabularnewline
0.33 & 1183.88378658303 & 57.9844209639244 \tabularnewline
0.34 & 1196.28168410811 & 58.1446760711926 \tabularnewline
0.35 & 1208.63911017595 & 59.2680902720871 \tabularnewline
0.36 & 1221.12881737988 & 61.0630085476483 \tabularnewline
0.37 & 1233.86648239338 & 63.1968373544244 \tabularnewline
0.38 & 1246.90582068389 & 65.337033623809 \tabularnewline
0.39 & 1260.24137095047 & 67.1923636798005 \tabularnewline
0.4 & 1273.81815504004 & 68.544268118452 \tabularnewline
0.41 & 1287.54671367558 & 69.2668684585149 \tabularnewline
0.42 & 1301.3214139713 & 69.3386427623625 \tabularnewline
0.43 & 1315.03953896894 & 68.8312134945127 \tabularnewline
0.44 & 1328.61860179519 & 67.9115850073946 \tabularnewline
0.45 & 1342.00961956707 & 66.7986062265285 \tabularnewline
0.46 & 1355.2047020501 & 65.7459470955709 \tabularnewline
0.47 & 1368.23815749601 & 64.9928224185893 \tabularnewline
0.48 & 1381.18125234384 & 64.72816820833 \tabularnewline
0.49 & 1394.13163349021 & 65.073951021536 \tabularnewline
0.5 & 1407.19910297781 & 66.048782376116 \tabularnewline
0.51 & 1420.48983690174 & 67.5757981514171 \tabularnewline
0.52 & 1434.09122561084 & 69.4966987424578 \tabularnewline
0.53 & 1448.05929648493 & 71.5944743497955 \tabularnewline
0.54 & 1462.41022671252 & 73.6257237813611 \tabularnewline
0.55 & 1477.11685767493 & 75.3496353703775 \tabularnewline
0.56 & 1492.11049149186 & 76.5621210011385 \tabularnewline
0.57 & 1507.28767506963 & 77.0997851970544 \tabularnewline
0.58 & 1522.52121144278 & 76.8749303779795 \tabularnewline
0.59 & 1537.67429155643 & 75.8745063652148 \tabularnewline
0.6 & 1552.61638859846 & 74.1682651289256 \tabularnewline
0.61 & 1567.23937317164 & 71.9022037182451 \tabularnewline
0.62 & 1581.47218734577 & 69.2947049511555 \tabularnewline
0.63 & 1595.29239552316 & 66.6197335098441 \tabularnewline
0.64 & 1608.73307684872 & 64.1811483241213 \tabularnewline
0.65 & 1621.88390073487 & 62.2846634414821 \tabularnewline
0.66 & 1634.88585152784 & 61.1900479990978 \tabularnewline
0.67 & 1647.91988456981 & 61.0827357170007 \tabularnewline
0.68 & 1661.19067733055 & 62.0347425340362 \tabularnewline
0.69 & 1674.90742243712 & 63.9952199990695 \tabularnewline
0.7 & 1689.26414250126 & 66.7997321444275 \tabularnewline
0.71 & 1704.4221882921 & 70.2056566499631 \tabularnewline
0.72 & 1720.49737325126 & 73.9250349556622 \tabularnewline
0.73 & 1737.55360918121 & 77.66808036174 \tabularnewline
0.74 & 1755.60398152934 & 81.1785538325891 \tabularnewline
0.75 & 1774.61901208937 & 84.2638139587517 \tabularnewline
0.76 & 1794.54054428317 & 86.8194146913606 \tabularnewline
0.77 & 1815.29851600135 & 88.8318920030265 \tabularnewline
0.78 & 1836.82727129072 & 90.366635342687 \tabularnewline
0.79 & 1859.07850228386 & 91.5412901421407 \tabularnewline
0.8 & 1882.02977171172 & 92.4783072983284 \tabularnewline
0.81 & 1905.6907169585 & 93.2934110898817 \tabularnewline
0.82 & 1930.11248322122 & 94.0823294967156 \tabularnewline
0.83 & 1955.40770498655 & 94.980880744953 \tabularnewline
0.84 & 1981.78604834474 & 96.2534093548655 \tabularnewline
0.85 & 2009.60254589794 & 98.3613518792472 \tabularnewline
0.86 & 2039.40440408867 & 101.982056898875 \tabularnewline
0.87 & 2071.95312048742 & 107.824395492911 \tabularnewline
0.88 & 2108.20322848118 & 116.311387201953 \tabularnewline
0.89 & 2149.24616926982 & 127.276906667633 \tabularnewline
0.9 & 2196.27381040073 & 140.018570068123 \tabularnewline
0.91 & 2250.64668202903 & 153.85103609956 \tabularnewline
0.92 & 2314.09374576773 & 168.966556213991 \tabularnewline
0.93 & 2388.85272394793 & 186.771569675201 \tabularnewline
0.94 & 2477.27062392948 & 208.070935647954 \tabularnewline
0.95 & 2580.50426099497 & 228.422434078977 \tabularnewline
0.96 & 2697.18969983584 & 235.452446710049 \tabularnewline
0.97 & 2824.48773226026 & 218.106481493237 \tabularnewline
0.98 & 2960.67460847002 & 193.019225114481 \tabularnewline
0.99 & 3096.85339511136 & 212.304934476003 \tabularnewline
1 & 3192 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121486&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[/C][C]84[/C][C]NA[/C][/ROW]
[ROW][C]0.01[/C][C]97.0817636146302[/C][C]29.3068315689719[/C][/ROW]
[ROW][C]0.02[/C][C]114.310417829508[/C][C]21.7543907937685[/C][/ROW]
[ROW][C]0.03[/C][C]131.725110881586[/C][C]32.5795295234754[/C][/ROW]
[ROW][C]0.04[/C][C]153.713040558205[/C][C]63.5193019884044[/C][/ROW]
[ROW][C]0.05[/C][C]186.841514924497[/C][C]109.084692758121[/C][/ROW]
[ROW][C]0.06[/C][C]235.373611173666[/C][C]160.937242764593[/C][/ROW]
[ROW][C]0.07[/C][C]299.696845884276[/C][C]207.976283170907[/C][/ROW]
[ROW][C]0.08[/C][C]376.465649874422[/C][C]240.272325362983[/C][/ROW]
[ROW][C]0.09[/C][C]459.847531923452[/C][C]252.628251667365[/C][/ROW]
[ROW][C]0.1[/C][C]543.313448412625[/C][C]245.592094412968[/C][/ROW]
[ROW][C]0.11[/C][C]621.276418055778[/C][C]223.991173178971[/C][/ROW]
[ROW][C]0.12[/C][C]690.06982648997[/C][C]194.396194368679[/C][/ROW]
[ROW][C]0.13[/C][C]748.154053138708[/C][C]162.938491039453[/C][/ROW]
[ROW][C]0.14[/C][C]795.759436044943[/C][C]134.157750628166[/C][/ROW]
[ROW][C]0.15[/C][C]834.280517211715[/C][C]110.783715294261[/C][/ROW]
[ROW][C]0.16[/C][C]865.673911942908[/C][C]94.0155966790647[/C][/ROW]
[ROW][C]0.17[/C][C]891.989792892034[/C][C]83.8728005044779[/C][/ROW]
[ROW][C]0.18[/C][C]915.066649267973[/C][C]79.4385089749947[/C][/ROW]
[ROW][C]0.19[/C][C]936.367046432703[/C][C]79.1677973927888[/C][/ROW]
[ROW][C]0.2[/C][C]956.918117286048[/C][C]81.3029554789697[/C][/ROW]
[ROW][C]0.21[/C][C]977.324318459738[/C][C]84.2645931071315[/C][/ROW]
[ROW][C]0.22[/C][C]997.827307243847[/C][C]86.8375525506272[/C][/ROW]
[ROW][C]0.23[/C][C]1018.3931000833[/C][C]88.2192044248175[/C][/ROW]
[ROW][C]0.24[/C][C]1038.80988411634[/C][C]88.0019372728325[/C][/ROW]
[ROW][C]0.25[/C][C]1058.78254330647[/C][C]86.1318969852454[/C][/ROW]
[ROW][C]0.26[/C][C]1078.01322726239[/C][C]82.8265830596978[/C][/ROW]
[ROW][C]0.27[/C][C]1096.26125163526[/C][C]78.5030981882432[/C][/ROW]
[ROW][C]0.28[/C][C]1113.3797413358[/C][C]73.6762899354276[/C][/ROW]
[ROW][C]0.29[/C][C]1129.33002627588[/C][C]68.8803898819203[/C][/ROW]
[ROW][C]0.3[/C][C]1144.17738160608[/C][C]64.6004264012855[/C][/ROW]
[ROW][C]0.31[/C][C]1158.07310076061[/C][C]61.221052358421[/C][/ROW]
[ROW][C]0.32[/C][C]1171.22822098116[/C][C]58.9860898153158[/C][/ROW]
[ROW][C]0.33[/C][C]1183.88378658303[/C][C]57.9844209639244[/C][/ROW]
[ROW][C]0.34[/C][C]1196.28168410811[/C][C]58.1446760711926[/C][/ROW]
[ROW][C]0.35[/C][C]1208.63911017595[/C][C]59.2680902720871[/C][/ROW]
[ROW][C]0.36[/C][C]1221.12881737988[/C][C]61.0630085476483[/C][/ROW]
[ROW][C]0.37[/C][C]1233.86648239338[/C][C]63.1968373544244[/C][/ROW]
[ROW][C]0.38[/C][C]1246.90582068389[/C][C]65.337033623809[/C][/ROW]
[ROW][C]0.39[/C][C]1260.24137095047[/C][C]67.1923636798005[/C][/ROW]
[ROW][C]0.4[/C][C]1273.81815504004[/C][C]68.544268118452[/C][/ROW]
[ROW][C]0.41[/C][C]1287.54671367558[/C][C]69.2668684585149[/C][/ROW]
[ROW][C]0.42[/C][C]1301.3214139713[/C][C]69.3386427623625[/C][/ROW]
[ROW][C]0.43[/C][C]1315.03953896894[/C][C]68.8312134945127[/C][/ROW]
[ROW][C]0.44[/C][C]1328.61860179519[/C][C]67.9115850073946[/C][/ROW]
[ROW][C]0.45[/C][C]1342.00961956707[/C][C]66.7986062265285[/C][/ROW]
[ROW][C]0.46[/C][C]1355.2047020501[/C][C]65.7459470955709[/C][/ROW]
[ROW][C]0.47[/C][C]1368.23815749601[/C][C]64.9928224185893[/C][/ROW]
[ROW][C]0.48[/C][C]1381.18125234384[/C][C]64.72816820833[/C][/ROW]
[ROW][C]0.49[/C][C]1394.13163349021[/C][C]65.073951021536[/C][/ROW]
[ROW][C]0.5[/C][C]1407.19910297781[/C][C]66.048782376116[/C][/ROW]
[ROW][C]0.51[/C][C]1420.48983690174[/C][C]67.5757981514171[/C][/ROW]
[ROW][C]0.52[/C][C]1434.09122561084[/C][C]69.4966987424578[/C][/ROW]
[ROW][C]0.53[/C][C]1448.05929648493[/C][C]71.5944743497955[/C][/ROW]
[ROW][C]0.54[/C][C]1462.41022671252[/C][C]73.6257237813611[/C][/ROW]
[ROW][C]0.55[/C][C]1477.11685767493[/C][C]75.3496353703775[/C][/ROW]
[ROW][C]0.56[/C][C]1492.11049149186[/C][C]76.5621210011385[/C][/ROW]
[ROW][C]0.57[/C][C]1507.28767506963[/C][C]77.0997851970544[/C][/ROW]
[ROW][C]0.58[/C][C]1522.52121144278[/C][C]76.8749303779795[/C][/ROW]
[ROW][C]0.59[/C][C]1537.67429155643[/C][C]75.8745063652148[/C][/ROW]
[ROW][C]0.6[/C][C]1552.61638859846[/C][C]74.1682651289256[/C][/ROW]
[ROW][C]0.61[/C][C]1567.23937317164[/C][C]71.9022037182451[/C][/ROW]
[ROW][C]0.62[/C][C]1581.47218734577[/C][C]69.2947049511555[/C][/ROW]
[ROW][C]0.63[/C][C]1595.29239552316[/C][C]66.6197335098441[/C][/ROW]
[ROW][C]0.64[/C][C]1608.73307684872[/C][C]64.1811483241213[/C][/ROW]
[ROW][C]0.65[/C][C]1621.88390073487[/C][C]62.2846634414821[/C][/ROW]
[ROW][C]0.66[/C][C]1634.88585152784[/C][C]61.1900479990978[/C][/ROW]
[ROW][C]0.67[/C][C]1647.91988456981[/C][C]61.0827357170007[/C][/ROW]
[ROW][C]0.68[/C][C]1661.19067733055[/C][C]62.0347425340362[/C][/ROW]
[ROW][C]0.69[/C][C]1674.90742243712[/C][C]63.9952199990695[/C][/ROW]
[ROW][C]0.7[/C][C]1689.26414250126[/C][C]66.7997321444275[/C][/ROW]
[ROW][C]0.71[/C][C]1704.4221882921[/C][C]70.2056566499631[/C][/ROW]
[ROW][C]0.72[/C][C]1720.49737325126[/C][C]73.9250349556622[/C][/ROW]
[ROW][C]0.73[/C][C]1737.55360918121[/C][C]77.66808036174[/C][/ROW]
[ROW][C]0.74[/C][C]1755.60398152934[/C][C]81.1785538325891[/C][/ROW]
[ROW][C]0.75[/C][C]1774.61901208937[/C][C]84.2638139587517[/C][/ROW]
[ROW][C]0.76[/C][C]1794.54054428317[/C][C]86.8194146913606[/C][/ROW]
[ROW][C]0.77[/C][C]1815.29851600135[/C][C]88.8318920030265[/C][/ROW]
[ROW][C]0.78[/C][C]1836.82727129072[/C][C]90.366635342687[/C][/ROW]
[ROW][C]0.79[/C][C]1859.07850228386[/C][C]91.5412901421407[/C][/ROW]
[ROW][C]0.8[/C][C]1882.02977171172[/C][C]92.4783072983284[/C][/ROW]
[ROW][C]0.81[/C][C]1905.6907169585[/C][C]93.2934110898817[/C][/ROW]
[ROW][C]0.82[/C][C]1930.11248322122[/C][C]94.0823294967156[/C][/ROW]
[ROW][C]0.83[/C][C]1955.40770498655[/C][C]94.980880744953[/C][/ROW]
[ROW][C]0.84[/C][C]1981.78604834474[/C][C]96.2534093548655[/C][/ROW]
[ROW][C]0.85[/C][C]2009.60254589794[/C][C]98.3613518792472[/C][/ROW]
[ROW][C]0.86[/C][C]2039.40440408867[/C][C]101.982056898875[/C][/ROW]
[ROW][C]0.87[/C][C]2071.95312048742[/C][C]107.824395492911[/C][/ROW]
[ROW][C]0.88[/C][C]2108.20322848118[/C][C]116.311387201953[/C][/ROW]
[ROW][C]0.89[/C][C]2149.24616926982[/C][C]127.276906667633[/C][/ROW]
[ROW][C]0.9[/C][C]2196.27381040073[/C][C]140.018570068123[/C][/ROW]
[ROW][C]0.91[/C][C]2250.64668202903[/C][C]153.85103609956[/C][/ROW]
[ROW][C]0.92[/C][C]2314.09374576773[/C][C]168.966556213991[/C][/ROW]
[ROW][C]0.93[/C][C]2388.85272394793[/C][C]186.771569675201[/C][/ROW]
[ROW][C]0.94[/C][C]2477.27062392948[/C][C]208.070935647954[/C][/ROW]
[ROW][C]0.95[/C][C]2580.50426099497[/C][C]228.422434078977[/C][/ROW]
[ROW][C]0.96[/C][C]2697.18969983584[/C][C]235.452446710049[/C][/ROW]
[ROW][C]0.97[/C][C]2824.48773226026[/C][C]218.106481493237[/C][/ROW]
[ROW][C]0.98[/C][C]2960.67460847002[/C][C]193.019225114481[/C][/ROW]
[ROW][C]0.99[/C][C]3096.85339511136[/C][C]212.304934476003[/C][/ROW]
[ROW][C]1[/C][C]3192[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121486&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121486&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
084NA
0.0197.081763614630229.3068315689719
0.02114.31041782950821.7543907937685
0.03131.72511088158632.5795295234754
0.04153.71304055820563.5193019884044
0.05186.841514924497109.084692758121
0.06235.373611173666160.937242764593
0.07299.696845884276207.976283170907
0.08376.465649874422240.272325362983
0.09459.847531923452252.628251667365
0.1543.313448412625245.592094412968
0.11621.276418055778223.991173178971
0.12690.06982648997194.396194368679
0.13748.154053138708162.938491039453
0.14795.759436044943134.157750628166
0.15834.280517211715110.783715294261
0.16865.67391194290894.0155966790647
0.17891.98979289203483.8728005044779
0.18915.06664926797379.4385089749947
0.19936.36704643270379.1677973927888
0.2956.91811728604881.3029554789697
0.21977.32431845973884.2645931071315
0.22997.82730724384786.8375525506272
0.231018.393100083388.2192044248175
0.241038.8098841163488.0019372728325
0.251058.7825433064786.1318969852454
0.261078.0132272623982.8265830596978
0.271096.2612516352678.5030981882432
0.281113.379741335873.6762899354276
0.291129.3300262758868.8803898819203
0.31144.1773816060864.6004264012855
0.311158.0731007606161.221052358421
0.321171.2282209811658.9860898153158
0.331183.8837865830357.9844209639244
0.341196.2816841081158.1446760711926
0.351208.6391101759559.2680902720871
0.361221.1288173798861.0630085476483
0.371233.8664823933863.1968373544244
0.381246.9058206838965.337033623809
0.391260.2413709504767.1923636798005
0.41273.8181550400468.544268118452
0.411287.5467136755869.2668684585149
0.421301.321413971369.3386427623625
0.431315.0395389689468.8312134945127
0.441328.6186017951967.9115850073946
0.451342.0096195670766.7986062265285
0.461355.204702050165.7459470955709
0.471368.2381574960164.9928224185893
0.481381.1812523438464.72816820833
0.491394.1316334902165.073951021536
0.51407.1991029778166.048782376116
0.511420.4898369017467.5757981514171
0.521434.0912256108469.4966987424578
0.531448.0592964849371.5944743497955
0.541462.4102267125273.6257237813611
0.551477.1168576749375.3496353703775
0.561492.1104914918676.5621210011385
0.571507.2876750696377.0997851970544
0.581522.5212114427876.8749303779795
0.591537.6742915564375.8745063652148
0.61552.6163885984674.1682651289256
0.611567.2393731716471.9022037182451
0.621581.4721873457769.2947049511555
0.631595.2923955231666.6197335098441
0.641608.7330768487264.1811483241213
0.651621.8839007348762.2846634414821
0.661634.8858515278461.1900479990978
0.671647.9198845698161.0827357170007
0.681661.1906773305562.0347425340362
0.691674.9074224371263.9952199990695
0.71689.2641425012666.7997321444275
0.711704.422188292170.2056566499631
0.721720.4973732512673.9250349556622
0.731737.5536091812177.66808036174
0.741755.6039815293481.1785538325891
0.751774.6190120893784.2638139587517
0.761794.5405442831786.8194146913606
0.771815.2985160013588.8318920030265
0.781836.8272712907290.366635342687
0.791859.0785022838691.5412901421407
0.81882.0297717117292.4783072983284
0.811905.690716958593.2934110898817
0.821930.1124832212294.0823294967156
0.831955.4077049865594.980880744953
0.841981.7860483447496.2534093548655
0.852009.6025458979498.3613518792472
0.862039.40440408867101.982056898875
0.872071.95312048742107.824395492911
0.882108.20322848118116.311387201953
0.892149.24616926982127.276906667633
0.92196.27381040073140.018570068123
0.912250.64668202903153.85103609956
0.922314.09374576773168.966556213991
0.932388.85272394793186.771569675201
0.942477.27062392948208.070935647954
0.952580.50426099497228.422434078977
0.962697.18969983584235.452446710049
0.972824.48773226026218.106481493237
0.982960.67460847002193.019225114481
0.993096.85339511136212.304934476003
13192NA


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 1 ; par3 = 0.01 ;
Parameters (R input):
par1 = 0 ; par2 = 1 ; 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')