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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 computationSat, 06 Mar 2010 10:19:12 -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/06/t1267896304nzj3k6t2vts3ddx.htm/, Retrieved Mon, 01 Jun 2026 12:44:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=74042, Retrieved Mon, 01 Jun 2026 12:44:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact580

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] [opgave 4 oefening 2 ] [2010-03-06 17:19:12] [de7054811a4039cd82332eb5d7e753fd] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
14861
14583.3
15305.8
17903.9
16379.4
15420.3
17870.5
15912.8
13866.5
17823.2
17872
17420.4
16704.4
15991.2
16583.6
19123.5
17838.7
17209.4
18586.5
16258.1
15141.6
19202.1
17746.5
19090.1
18040.3
17515.5
17751.8
21072.4
17170
19439.5
19795.4
17574.9
16165.4
19464.6
19932.1
19961.2
17343.4
18924.2
18574.1
21350.6
18594.6
19823.1
20844.4
19640.2
17735.4
19813.6
22160
20664.3
17877.4
20906.5
21164.1
21374.4
22952.3
21343.5
23899.3
22392.9
18274.1
22786.7
22321.5
17842.2
16373.5
16087.1
16555.9
17880.2
16764.5
16049
18288.3
17570.4
15133.4
19334.2
19291.8
20176.7

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74042&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]1 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=74042&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74042&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0114074.4915491713597.590485710454
0.0214364.9627971773466.416271346619
0.0314634.3817616435372.185208092007
0.0414848.5569163217320.965130055830
0.0515016.5142595035302.597245049007
0.0615156.9777724031309.263572456937
0.0715284.3138433272330.43498311886
0.0815406.2896596452352.826530134636
0.0915525.4039075232365.784716870944
0.115640.8515825164364.478255721981
0.1115750.4382305454349.872879259817
0.1215852.1125529942326.96664443782
0.1315944.8754114806302.192856170147
0.1416029.0335631775281.328060532339
0.1516105.9708053609268.025824499923
0.1616177.6933511715263.550394032764
0.1716246.3701122187267.249304444551
0.1816313.9924080370277.606249455278
0.1916382.1826660650292.869695703900
0.216452.1219568897311.39691493736
0.2116524.5469632341331.513023750155
0.2216599.7758677080351.682087265321
0.2316677.7425780048370.167317516231
0.2416758.0363811294385.448564442888
0.2516839.9530990523396.11565690207
0.2616922.5637780381401.154105172761
0.2717004.8011724702400.071529444903
0.2817085.5571148947392.917574019482
0.2917163.7788245171380.229645487662
0.317238.5511044711362.951009173849
0.3117309.1542133629342.290329402649
0.3217375.0926381302319.457165866662
0.3317436.0961259808295.660796710159
0.3417492.0993758390271.826958584342
0.3517543.2096080923248.734977766448
0.3617589.6715136990226.952738311473
0.3717631.8372352204206.901560915647
0.3817670.1458891613188.977652712632
0.3917705.1136411984173.567745210396
0.417737.3322820619161.112409716302
0.4117767.4721283483152.254019966656
0.4217796.2841013214147.597408601276
0.4317824.5959969487147.831559419781
0.4417853.2990803094153.395011471733
0.4517883.3229580675164.563610004182
0.4617915.5988913828181.108800502327
0.4717951.013958346202.475483887346
0.4817990.3603932609227.809271107406
0.4918034.2856805741256.005215245470
0.518083.2493185082285.807834859217
0.5118137.4915102366315.892738020307
0.5218197.0175149749344.905916301329
0.5318261.5993196870371.632247747444
0.5418330.7941158863395.000494375895
0.5518403.9772231587414.128485536350
0.5618480.3858959956428.463776186646
0.5718559.1699680060437.709865086663
0.5818639.4453874647441.854309156231
0.5918720.3470985922441.117201875985
0.618801.0781416173436.001884052008
0.6118880.9521396271427.238894245158
0.6218959.426586258415.676071602355
0.6319036.1248060361402.29452344755
0.6419110.8454365858388.14479989966
0.6519183.5599354007374.190063316587
0.6619254.4007703092361.294585861158
0.6719323.6450400849350.125216378049
0.6819391.6994189433341.250450335998
0.6919459.0916335448335.046129244502
0.719526.4706437888331.945634924157
0.7119594.6125497288332.494339208733
0.7219664.4232076896337.301069036365
0.7319736.9237107653346.987344721883
0.7419813.2037488588361.999463780437
0.7519894.3324023266382.111348350754
0.7619981.2266575144406.355372905523
0.7720074.4931704497432.709950661801
0.7820174.2746011897458.329986918111
0.7920280.1429079541479.994178025052
0.820391.0834376752494.61499008779
0.8120505.6029020511499.966118835752
0.8220621.9722025206495.117056288888
0.8320738.5852159462481.075430726027
0.8420854.3815850270460.70830422973
0.8520969.2489769981438.661222241615
0.8621084.2923223896420.821322390593
0.8721201.8440378635413.12573627702
0.8821325.1111586708419.523038253767
0.8921457.440925891439.453386274129
0.921601.3484206487466.666193345857
0.9121757.6496916651490.835152205146
0.9221925.1800375484501.486652820851
0.9322101.553636974492.849195403615
0.9422285.2790654232467.210908259650
0.9522479.4016072506435.219831487168
0.9622696.1195568217415.334101784151
0.9722958.0481592315440.577586069104
0.9823283.0759861586556.261355226034
0.9923638.7449135055757.183161074458

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 14074.4915491713 & 597.590485710454 \tabularnewline
0.02 & 14364.9627971773 & 466.416271346619 \tabularnewline
0.03 & 14634.3817616435 & 372.185208092007 \tabularnewline
0.04 & 14848.5569163217 & 320.965130055830 \tabularnewline
0.05 & 15016.5142595035 & 302.597245049007 \tabularnewline
0.06 & 15156.9777724031 & 309.263572456937 \tabularnewline
0.07 & 15284.3138433272 & 330.43498311886 \tabularnewline
0.08 & 15406.2896596452 & 352.826530134636 \tabularnewline
0.09 & 15525.4039075232 & 365.784716870944 \tabularnewline
0.1 & 15640.8515825164 & 364.478255721981 \tabularnewline
0.11 & 15750.4382305454 & 349.872879259817 \tabularnewline
0.12 & 15852.1125529942 & 326.96664443782 \tabularnewline
0.13 & 15944.8754114806 & 302.192856170147 \tabularnewline
0.14 & 16029.0335631775 & 281.328060532339 \tabularnewline
0.15 & 16105.9708053609 & 268.025824499923 \tabularnewline
0.16 & 16177.6933511715 & 263.550394032764 \tabularnewline
0.17 & 16246.3701122187 & 267.249304444551 \tabularnewline
0.18 & 16313.9924080370 & 277.606249455278 \tabularnewline
0.19 & 16382.1826660650 & 292.869695703900 \tabularnewline
0.2 & 16452.1219568897 & 311.39691493736 \tabularnewline
0.21 & 16524.5469632341 & 331.513023750155 \tabularnewline
0.22 & 16599.7758677080 & 351.682087265321 \tabularnewline
0.23 & 16677.7425780048 & 370.167317516231 \tabularnewline
0.24 & 16758.0363811294 & 385.448564442888 \tabularnewline
0.25 & 16839.9530990523 & 396.11565690207 \tabularnewline
0.26 & 16922.5637780381 & 401.154105172761 \tabularnewline
0.27 & 17004.8011724702 & 400.071529444903 \tabularnewline
0.28 & 17085.5571148947 & 392.917574019482 \tabularnewline
0.29 & 17163.7788245171 & 380.229645487662 \tabularnewline
0.3 & 17238.5511044711 & 362.951009173849 \tabularnewline
0.31 & 17309.1542133629 & 342.290329402649 \tabularnewline
0.32 & 17375.0926381302 & 319.457165866662 \tabularnewline
0.33 & 17436.0961259808 & 295.660796710159 \tabularnewline
0.34 & 17492.0993758390 & 271.826958584342 \tabularnewline
0.35 & 17543.2096080923 & 248.734977766448 \tabularnewline
0.36 & 17589.6715136990 & 226.952738311473 \tabularnewline
0.37 & 17631.8372352204 & 206.901560915647 \tabularnewline
0.38 & 17670.1458891613 & 188.977652712632 \tabularnewline
0.39 & 17705.1136411984 & 173.567745210396 \tabularnewline
0.4 & 17737.3322820619 & 161.112409716302 \tabularnewline
0.41 & 17767.4721283483 & 152.254019966656 \tabularnewline
0.42 & 17796.2841013214 & 147.597408601276 \tabularnewline
0.43 & 17824.5959969487 & 147.831559419781 \tabularnewline
0.44 & 17853.2990803094 & 153.395011471733 \tabularnewline
0.45 & 17883.3229580675 & 164.563610004182 \tabularnewline
0.46 & 17915.5988913828 & 181.108800502327 \tabularnewline
0.47 & 17951.013958346 & 202.475483887346 \tabularnewline
0.48 & 17990.3603932609 & 227.809271107406 \tabularnewline
0.49 & 18034.2856805741 & 256.005215245470 \tabularnewline
0.5 & 18083.2493185082 & 285.807834859217 \tabularnewline
0.51 & 18137.4915102366 & 315.892738020307 \tabularnewline
0.52 & 18197.0175149749 & 344.905916301329 \tabularnewline
0.53 & 18261.5993196870 & 371.632247747444 \tabularnewline
0.54 & 18330.7941158863 & 395.000494375895 \tabularnewline
0.55 & 18403.9772231587 & 414.128485536350 \tabularnewline
0.56 & 18480.3858959956 & 428.463776186646 \tabularnewline
0.57 & 18559.1699680060 & 437.709865086663 \tabularnewline
0.58 & 18639.4453874647 & 441.854309156231 \tabularnewline
0.59 & 18720.3470985922 & 441.117201875985 \tabularnewline
0.6 & 18801.0781416173 & 436.001884052008 \tabularnewline
0.61 & 18880.9521396271 & 427.238894245158 \tabularnewline
0.62 & 18959.426586258 & 415.676071602355 \tabularnewline
0.63 & 19036.1248060361 & 402.29452344755 \tabularnewline
0.64 & 19110.8454365858 & 388.14479989966 \tabularnewline
0.65 & 19183.5599354007 & 374.190063316587 \tabularnewline
0.66 & 19254.4007703092 & 361.294585861158 \tabularnewline
0.67 & 19323.6450400849 & 350.125216378049 \tabularnewline
0.68 & 19391.6994189433 & 341.250450335998 \tabularnewline
0.69 & 19459.0916335448 & 335.046129244502 \tabularnewline
0.7 & 19526.4706437888 & 331.945634924157 \tabularnewline
0.71 & 19594.6125497288 & 332.494339208733 \tabularnewline
0.72 & 19664.4232076896 & 337.301069036365 \tabularnewline
0.73 & 19736.9237107653 & 346.987344721883 \tabularnewline
0.74 & 19813.2037488588 & 361.999463780437 \tabularnewline
0.75 & 19894.3324023266 & 382.111348350754 \tabularnewline
0.76 & 19981.2266575144 & 406.355372905523 \tabularnewline
0.77 & 20074.4931704497 & 432.709950661801 \tabularnewline
0.78 & 20174.2746011897 & 458.329986918111 \tabularnewline
0.79 & 20280.1429079541 & 479.994178025052 \tabularnewline
0.8 & 20391.0834376752 & 494.61499008779 \tabularnewline
0.81 & 20505.6029020511 & 499.966118835752 \tabularnewline
0.82 & 20621.9722025206 & 495.117056288888 \tabularnewline
0.83 & 20738.5852159462 & 481.075430726027 \tabularnewline
0.84 & 20854.3815850270 & 460.70830422973 \tabularnewline
0.85 & 20969.2489769981 & 438.661222241615 \tabularnewline
0.86 & 21084.2923223896 & 420.821322390593 \tabularnewline
0.87 & 21201.8440378635 & 413.12573627702 \tabularnewline
0.88 & 21325.1111586708 & 419.523038253767 \tabularnewline
0.89 & 21457.440925891 & 439.453386274129 \tabularnewline
0.9 & 21601.3484206487 & 466.666193345857 \tabularnewline
0.91 & 21757.6496916651 & 490.835152205146 \tabularnewline
0.92 & 21925.1800375484 & 501.486652820851 \tabularnewline
0.93 & 22101.553636974 & 492.849195403615 \tabularnewline
0.94 & 22285.2790654232 & 467.210908259650 \tabularnewline
0.95 & 22479.4016072506 & 435.219831487168 \tabularnewline
0.96 & 22696.1195568217 & 415.334101784151 \tabularnewline
0.97 & 22958.0481592315 & 440.577586069104 \tabularnewline
0.98 & 23283.0759861586 & 556.261355226034 \tabularnewline
0.99 & 23638.7449135055 & 757.183161074458 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74042&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]14074.4915491713[/C][C]597.590485710454[/C][/ROW]
[ROW][C]0.02[/C][C]14364.9627971773[/C][C]466.416271346619[/C][/ROW]
[ROW][C]0.03[/C][C]14634.3817616435[/C][C]372.185208092007[/C][/ROW]
[ROW][C]0.04[/C][C]14848.5569163217[/C][C]320.965130055830[/C][/ROW]
[ROW][C]0.05[/C][C]15016.5142595035[/C][C]302.597245049007[/C][/ROW]
[ROW][C]0.06[/C][C]15156.9777724031[/C][C]309.263572456937[/C][/ROW]
[ROW][C]0.07[/C][C]15284.3138433272[/C][C]330.43498311886[/C][/ROW]
[ROW][C]0.08[/C][C]15406.2896596452[/C][C]352.826530134636[/C][/ROW]
[ROW][C]0.09[/C][C]15525.4039075232[/C][C]365.784716870944[/C][/ROW]
[ROW][C]0.1[/C][C]15640.8515825164[/C][C]364.478255721981[/C][/ROW]
[ROW][C]0.11[/C][C]15750.4382305454[/C][C]349.872879259817[/C][/ROW]
[ROW][C]0.12[/C][C]15852.1125529942[/C][C]326.96664443782[/C][/ROW]
[ROW][C]0.13[/C][C]15944.8754114806[/C][C]302.192856170147[/C][/ROW]
[ROW][C]0.14[/C][C]16029.0335631775[/C][C]281.328060532339[/C][/ROW]
[ROW][C]0.15[/C][C]16105.9708053609[/C][C]268.025824499923[/C][/ROW]
[ROW][C]0.16[/C][C]16177.6933511715[/C][C]263.550394032764[/C][/ROW]
[ROW][C]0.17[/C][C]16246.3701122187[/C][C]267.249304444551[/C][/ROW]
[ROW][C]0.18[/C][C]16313.9924080370[/C][C]277.606249455278[/C][/ROW]
[ROW][C]0.19[/C][C]16382.1826660650[/C][C]292.869695703900[/C][/ROW]
[ROW][C]0.2[/C][C]16452.1219568897[/C][C]311.39691493736[/C][/ROW]
[ROW][C]0.21[/C][C]16524.5469632341[/C][C]331.513023750155[/C][/ROW]
[ROW][C]0.22[/C][C]16599.7758677080[/C][C]351.682087265321[/C][/ROW]
[ROW][C]0.23[/C][C]16677.7425780048[/C][C]370.167317516231[/C][/ROW]
[ROW][C]0.24[/C][C]16758.0363811294[/C][C]385.448564442888[/C][/ROW]
[ROW][C]0.25[/C][C]16839.9530990523[/C][C]396.11565690207[/C][/ROW]
[ROW][C]0.26[/C][C]16922.5637780381[/C][C]401.154105172761[/C][/ROW]
[ROW][C]0.27[/C][C]17004.8011724702[/C][C]400.071529444903[/C][/ROW]
[ROW][C]0.28[/C][C]17085.5571148947[/C][C]392.917574019482[/C][/ROW]
[ROW][C]0.29[/C][C]17163.7788245171[/C][C]380.229645487662[/C][/ROW]
[ROW][C]0.3[/C][C]17238.5511044711[/C][C]362.951009173849[/C][/ROW]
[ROW][C]0.31[/C][C]17309.1542133629[/C][C]342.290329402649[/C][/ROW]
[ROW][C]0.32[/C][C]17375.0926381302[/C][C]319.457165866662[/C][/ROW]
[ROW][C]0.33[/C][C]17436.0961259808[/C][C]295.660796710159[/C][/ROW]
[ROW][C]0.34[/C][C]17492.0993758390[/C][C]271.826958584342[/C][/ROW]
[ROW][C]0.35[/C][C]17543.2096080923[/C][C]248.734977766448[/C][/ROW]
[ROW][C]0.36[/C][C]17589.6715136990[/C][C]226.952738311473[/C][/ROW]
[ROW][C]0.37[/C][C]17631.8372352204[/C][C]206.901560915647[/C][/ROW]
[ROW][C]0.38[/C][C]17670.1458891613[/C][C]188.977652712632[/C][/ROW]
[ROW][C]0.39[/C][C]17705.1136411984[/C][C]173.567745210396[/C][/ROW]
[ROW][C]0.4[/C][C]17737.3322820619[/C][C]161.112409716302[/C][/ROW]
[ROW][C]0.41[/C][C]17767.4721283483[/C][C]152.254019966656[/C][/ROW]
[ROW][C]0.42[/C][C]17796.2841013214[/C][C]147.597408601276[/C][/ROW]
[ROW][C]0.43[/C][C]17824.5959969487[/C][C]147.831559419781[/C][/ROW]
[ROW][C]0.44[/C][C]17853.2990803094[/C][C]153.395011471733[/C][/ROW]
[ROW][C]0.45[/C][C]17883.3229580675[/C][C]164.563610004182[/C][/ROW]
[ROW][C]0.46[/C][C]17915.5988913828[/C][C]181.108800502327[/C][/ROW]
[ROW][C]0.47[/C][C]17951.013958346[/C][C]202.475483887346[/C][/ROW]
[ROW][C]0.48[/C][C]17990.3603932609[/C][C]227.809271107406[/C][/ROW]
[ROW][C]0.49[/C][C]18034.2856805741[/C][C]256.005215245470[/C][/ROW]
[ROW][C]0.5[/C][C]18083.2493185082[/C][C]285.807834859217[/C][/ROW]
[ROW][C]0.51[/C][C]18137.4915102366[/C][C]315.892738020307[/C][/ROW]
[ROW][C]0.52[/C][C]18197.0175149749[/C][C]344.905916301329[/C][/ROW]
[ROW][C]0.53[/C][C]18261.5993196870[/C][C]371.632247747444[/C][/ROW]
[ROW][C]0.54[/C][C]18330.7941158863[/C][C]395.000494375895[/C][/ROW]
[ROW][C]0.55[/C][C]18403.9772231587[/C][C]414.128485536350[/C][/ROW]
[ROW][C]0.56[/C][C]18480.3858959956[/C][C]428.463776186646[/C][/ROW]
[ROW][C]0.57[/C][C]18559.1699680060[/C][C]437.709865086663[/C][/ROW]
[ROW][C]0.58[/C][C]18639.4453874647[/C][C]441.854309156231[/C][/ROW]
[ROW][C]0.59[/C][C]18720.3470985922[/C][C]441.117201875985[/C][/ROW]
[ROW][C]0.6[/C][C]18801.0781416173[/C][C]436.001884052008[/C][/ROW]
[ROW][C]0.61[/C][C]18880.9521396271[/C][C]427.238894245158[/C][/ROW]
[ROW][C]0.62[/C][C]18959.426586258[/C][C]415.676071602355[/C][/ROW]
[ROW][C]0.63[/C][C]19036.1248060361[/C][C]402.29452344755[/C][/ROW]
[ROW][C]0.64[/C][C]19110.8454365858[/C][C]388.14479989966[/C][/ROW]
[ROW][C]0.65[/C][C]19183.5599354007[/C][C]374.190063316587[/C][/ROW]
[ROW][C]0.66[/C][C]19254.4007703092[/C][C]361.294585861158[/C][/ROW]
[ROW][C]0.67[/C][C]19323.6450400849[/C][C]350.125216378049[/C][/ROW]
[ROW][C]0.68[/C][C]19391.6994189433[/C][C]341.250450335998[/C][/ROW]
[ROW][C]0.69[/C][C]19459.0916335448[/C][C]335.046129244502[/C][/ROW]
[ROW][C]0.7[/C][C]19526.4706437888[/C][C]331.945634924157[/C][/ROW]
[ROW][C]0.71[/C][C]19594.6125497288[/C][C]332.494339208733[/C][/ROW]
[ROW][C]0.72[/C][C]19664.4232076896[/C][C]337.301069036365[/C][/ROW]
[ROW][C]0.73[/C][C]19736.9237107653[/C][C]346.987344721883[/C][/ROW]
[ROW][C]0.74[/C][C]19813.2037488588[/C][C]361.999463780437[/C][/ROW]
[ROW][C]0.75[/C][C]19894.3324023266[/C][C]382.111348350754[/C][/ROW]
[ROW][C]0.76[/C][C]19981.2266575144[/C][C]406.355372905523[/C][/ROW]
[ROW][C]0.77[/C][C]20074.4931704497[/C][C]432.709950661801[/C][/ROW]
[ROW][C]0.78[/C][C]20174.2746011897[/C][C]458.329986918111[/C][/ROW]
[ROW][C]0.79[/C][C]20280.1429079541[/C][C]479.994178025052[/C][/ROW]
[ROW][C]0.8[/C][C]20391.0834376752[/C][C]494.61499008779[/C][/ROW]
[ROW][C]0.81[/C][C]20505.6029020511[/C][C]499.966118835752[/C][/ROW]
[ROW][C]0.82[/C][C]20621.9722025206[/C][C]495.117056288888[/C][/ROW]
[ROW][C]0.83[/C][C]20738.5852159462[/C][C]481.075430726027[/C][/ROW]
[ROW][C]0.84[/C][C]20854.3815850270[/C][C]460.70830422973[/C][/ROW]
[ROW][C]0.85[/C][C]20969.2489769981[/C][C]438.661222241615[/C][/ROW]
[ROW][C]0.86[/C][C]21084.2923223896[/C][C]420.821322390593[/C][/ROW]
[ROW][C]0.87[/C][C]21201.8440378635[/C][C]413.12573627702[/C][/ROW]
[ROW][C]0.88[/C][C]21325.1111586708[/C][C]419.523038253767[/C][/ROW]
[ROW][C]0.89[/C][C]21457.440925891[/C][C]439.453386274129[/C][/ROW]
[ROW][C]0.9[/C][C]21601.3484206487[/C][C]466.666193345857[/C][/ROW]
[ROW][C]0.91[/C][C]21757.6496916651[/C][C]490.835152205146[/C][/ROW]
[ROW][C]0.92[/C][C]21925.1800375484[/C][C]501.486652820851[/C][/ROW]
[ROW][C]0.93[/C][C]22101.553636974[/C][C]492.849195403615[/C][/ROW]
[ROW][C]0.94[/C][C]22285.2790654232[/C][C]467.210908259650[/C][/ROW]
[ROW][C]0.95[/C][C]22479.4016072506[/C][C]435.219831487168[/C][/ROW]
[ROW][C]0.96[/C][C]22696.1195568217[/C][C]415.334101784151[/C][/ROW]
[ROW][C]0.97[/C][C]22958.0481592315[/C][C]440.577586069104[/C][/ROW]
[ROW][C]0.98[/C][C]23283.0759861586[/C][C]556.261355226034[/C][/ROW]
[ROW][C]0.99[/C][C]23638.7449135055[/C][C]757.183161074458[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74042&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74042&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
0.0114074.4915491713597.590485710454
0.0214364.9627971773466.416271346619
0.0314634.3817616435372.185208092007
0.0414848.5569163217320.965130055830
0.0515016.5142595035302.597245049007
0.0615156.9777724031309.263572456937
0.0715284.3138433272330.43498311886
0.0815406.2896596452352.826530134636
0.0915525.4039075232365.784716870944
0.115640.8515825164364.478255721981
0.1115750.4382305454349.872879259817
0.1215852.1125529942326.96664443782
0.1315944.8754114806302.192856170147
0.1416029.0335631775281.328060532339
0.1516105.9708053609268.025824499923
0.1616177.6933511715263.550394032764
0.1716246.3701122187267.249304444551
0.1816313.9924080370277.606249455278
0.1916382.1826660650292.869695703900
0.216452.1219568897311.39691493736
0.2116524.5469632341331.513023750155
0.2216599.7758677080351.682087265321
0.2316677.7425780048370.167317516231
0.2416758.0363811294385.448564442888
0.2516839.9530990523396.11565690207
0.2616922.5637780381401.154105172761
0.2717004.8011724702400.071529444903
0.2817085.5571148947392.917574019482
0.2917163.7788245171380.229645487662
0.317238.5511044711362.951009173849
0.3117309.1542133629342.290329402649
0.3217375.0926381302319.457165866662
0.3317436.0961259808295.660796710159
0.3417492.0993758390271.826958584342
0.3517543.2096080923248.734977766448
0.3617589.6715136990226.952738311473
0.3717631.8372352204206.901560915647
0.3817670.1458891613188.977652712632
0.3917705.1136411984173.567745210396
0.417737.3322820619161.112409716302
0.4117767.4721283483152.254019966656
0.4217796.2841013214147.597408601276
0.4317824.5959969487147.831559419781
0.4417853.2990803094153.395011471733
0.4517883.3229580675164.563610004182
0.4617915.5988913828181.108800502327
0.4717951.013958346202.475483887346
0.4817990.3603932609227.809271107406
0.4918034.2856805741256.005215245470
0.518083.2493185082285.807834859217
0.5118137.4915102366315.892738020307
0.5218197.0175149749344.905916301329
0.5318261.5993196870371.632247747444
0.5418330.7941158863395.000494375895
0.5518403.9772231587414.128485536350
0.5618480.3858959956428.463776186646
0.5718559.1699680060437.709865086663
0.5818639.4453874647441.854309156231
0.5918720.3470985922441.117201875985
0.618801.0781416173436.001884052008
0.6118880.9521396271427.238894245158
0.6218959.426586258415.676071602355
0.6319036.1248060361402.29452344755
0.6419110.8454365858388.14479989966
0.6519183.5599354007374.190063316587
0.6619254.4007703092361.294585861158
0.6719323.6450400849350.125216378049
0.6819391.6994189433341.250450335998
0.6919459.0916335448335.046129244502
0.719526.4706437888331.945634924157
0.7119594.6125497288332.494339208733
0.7219664.4232076896337.301069036365
0.7319736.9237107653346.987344721883
0.7419813.2037488588361.999463780437
0.7519894.3324023266382.111348350754
0.7619981.2266575144406.355372905523
0.7720074.4931704497432.709950661801
0.7820174.2746011897458.329986918111
0.7920280.1429079541479.994178025052
0.820391.0834376752494.61499008779
0.8120505.6029020511499.966118835752
0.8220621.9722025206495.117056288888
0.8320738.5852159462481.075430726027
0.8420854.3815850270460.70830422973
0.8520969.2489769981438.661222241615
0.8621084.2923223896420.821322390593
0.8721201.8440378635413.12573627702
0.8821325.1111586708419.523038253767
0.8921457.440925891439.453386274129
0.921601.3484206487466.666193345857
0.9121757.6496916651490.835152205146
0.9221925.1800375484501.486652820851
0.9322101.553636974492.849195403615
0.9422285.2790654232467.210908259650
0.9522479.4016072506435.219831487168
0.9622696.1195568217415.334101784151
0.9722958.0481592315440.577586069104
0.9823283.0759861586556.261355226034
0.9923638.7449135055757.183161074458


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')