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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationThu, 12 Feb 2015 15:46:02 +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/2015/Feb/12/t1423756042rzer85svkbfqowe.htm/, Retrieved Sat, 18 May 2024 01:59:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=277187, Retrieved Sat, 18 May 2024 01:59:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact63

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] [] [2015-02-12 15:46:02] [efb69546851bccb1c0576f78d5afa44b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
75.6
74
75.3
83.1
84.9
83.5
88.2
87.4
77.8
74.5
75.3
78.7
71.4
75.8
79.2
84.4
84.4
87.2
92.4
88.5
94.8
100.9
110
107.9
111.2
116.7
125.8
131.5
146.2
155.4
157.5
137.2
121.3
89.1
69.6
56.7
58.5
56.4
60.5
64.6
73.2
84.6
80.4
88.4
84.6
90.8
94.9
93.1
96.6
93.1
98.3
105
95.6
94.3
95.3
97.1
98.1
104.4
107.8
114.3
118.7
124.1
134.2
142.4
133.8
131
133.2
125.9
126.2
122.7
126.6
124.8
128
134.1
138.8
134
124
110.4
116.7
124.7
126
122.8
120.2
121.2
125.4
127.9
122
117.5
117.9
117.9
122.7
125.7
126.1
123.2
120.6
123.5

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'Sir Maurice George Kendall' @ kendall.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 & 1 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=277187&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=277187&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=277187&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'Sir Maurice George Kendall' @ kendall.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0156.91873990376811.22465584956731
0.0258.21169105765442.72327145708657
0.0360.22010710866724.14062873972276
0.0462.6955334876245.06815342818103
0.0565.31302090267925.29601178453132
0.0667.77456272281164.90472666552585
0.0769.88721751500354.16957988879593
0.0871.5866415997923.37910047846878
0.0972.90964711119182.72902553916231
0.173.94658640637412.31048750731797
0.1174.80055006570862.13943038289727
0.1275.56282821819442.17893374493816
0.1376.30203820636142.36101985187229
0.1477.06145030881742.60989949742198
0.1577.86069696468462.859118364927
0.1678.70000987836853.05766623243527
0.1779.56600978290753.1745202412367
0.1880.4381710825473.19880959232997
0.1981.29499132312013.13946332588647
0.282.11894526181213.02110186572823
0.2182.89956692787082.87660386306046
0.2283.6344230343172.74022215349037
0.2384.3282060487432.63889252955071
0.2484.99055216053912.58762357222361
0.2585.63336488477312.5883108573614
0.2686.26835756748922.63288259237572
0.2786.90527346838332.70815187710764
0.2887.55092625038552.80014056766455
0.2988.20895642352922.89611859933403
0.388.88009182513352.98555285827762
0.3189.56272232485513.05959530834874
0.3290.25368234902643.11304073528829
0.3390.94920164988523.14476762491651
0.3491.64598988798943.15901701309245
0.3592.34236730546743.16651594434812
0.3693.03928106288363.18346593328935
0.3793.74100218111313.22936303030922
0.3894.45531267864993.32428219596058
0.3995.19307008455323.48314904129118
0.495.96715639081243.71357177558752
0.4196.79094737806924.01255745916515
0.4297.67654261681224.36676483267353
0.4398.63305130149174.75471717380292
0.4499.66522205847935.15006083560401
0.45100.7726375201815.52471665530927
0.46101.94958181515.85301534404678
0.47103.1855574295486.1137521395414
0.48104.4663093060636.29268511069429
0.49105.7751381460036.38317976129522
0.5107.0942690800556.38445996842707
0.51108.4060845479076.30171202522008
0.52109.6941105980476.14296189660313
0.53110.9437316933615.91861351508301
0.54112.142669966555.640540753316
0.55113.2812844465635.32103004516501
0.56114.3527281267234.97356379419633
0.57115.3529666904534.61187124283328
0.58116.2806384238434.24880992713721
0.59117.1367383458223.89613952070376
0.6117.9241419844163.56260936474679
0.61118.6470299202953.25374843705822
0.62119.3103095251922.9713794228546
0.63119.9191357277112.71495480722442
0.64120.4786023426092.48299084924194
0.65120.9936198269372.2733019975709
0.66121.4689355087462.08520146549111
0.67121.9092109047411.91825530830652
0.68122.3190624052621.77316314875467
0.69122.7029984308861.64959154746292
0.7123.0652383393711.54624053631326
0.71123.409459002251.46011931184384
0.72123.7385661645631.38664685313015
0.73124.0546151448941.32091366685984
0.74124.3590004637931.25886563310872
0.75124.6529934424741.19930528647024
0.76124.9386321711931.14508818273923
0.77125.2198656041641.10479659062734
0.78125.5037351447481.09253597657163
0.79125.80126404691.12667507715849
0.8126.1276496600981.22494737833554
0.81126.5013595068621.39759964411437
0.82126.9418683290661.64036250025366
0.83127.4660791678291.93312043969877
0.84128.0839517595992.24016270332167
0.85128.7944513875982.51455367175372
0.86129.5834654333882.70647414682551
0.87130.4255380734122.77841686452913
0.88131.290804604942.72042661596655
0.89132.1570981531772.56516786937029
0.9133.0249398847592.39431102269311
0.91133.9308397517652.33049853335987
0.92134.9538086967792.49482788903312
0.93136.2132416532022.93762597913912
0.94137.8628855407463.62664219439522
0.95140.086906743734.51219039071463
0.96143.0801327357015.55640364515428
0.97146.9370160814736.53898212475537
0.98151.3634682585886.58371006409021
0.99155.3583827326324.56128610409242

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 56.9187399037681 & 1.22465584956731 \tabularnewline
0.02 & 58.2116910576544 & 2.72327145708657 \tabularnewline
0.03 & 60.2201071086672 & 4.14062873972276 \tabularnewline
0.04 & 62.695533487624 & 5.06815342818103 \tabularnewline
0.05 & 65.3130209026792 & 5.29601178453132 \tabularnewline
0.06 & 67.7745627228116 & 4.90472666552585 \tabularnewline
0.07 & 69.8872175150035 & 4.16957988879593 \tabularnewline
0.08 & 71.586641599792 & 3.37910047846878 \tabularnewline
0.09 & 72.9096471111918 & 2.72902553916231 \tabularnewline
0.1 & 73.9465864063741 & 2.31048750731797 \tabularnewline
0.11 & 74.8005500657086 & 2.13943038289727 \tabularnewline
0.12 & 75.5628282181944 & 2.17893374493816 \tabularnewline
0.13 & 76.3020382063614 & 2.36101985187229 \tabularnewline
0.14 & 77.0614503088174 & 2.60989949742198 \tabularnewline
0.15 & 77.8606969646846 & 2.859118364927 \tabularnewline
0.16 & 78.7000098783685 & 3.05766623243527 \tabularnewline
0.17 & 79.5660097829075 & 3.1745202412367 \tabularnewline
0.18 & 80.438171082547 & 3.19880959232997 \tabularnewline
0.19 & 81.2949913231201 & 3.13946332588647 \tabularnewline
0.2 & 82.1189452618121 & 3.02110186572823 \tabularnewline
0.21 & 82.8995669278708 & 2.87660386306046 \tabularnewline
0.22 & 83.634423034317 & 2.74022215349037 \tabularnewline
0.23 & 84.328206048743 & 2.63889252955071 \tabularnewline
0.24 & 84.9905521605391 & 2.58762357222361 \tabularnewline
0.25 & 85.6333648847731 & 2.5883108573614 \tabularnewline
0.26 & 86.2683575674892 & 2.63288259237572 \tabularnewline
0.27 & 86.9052734683833 & 2.70815187710764 \tabularnewline
0.28 & 87.5509262503855 & 2.80014056766455 \tabularnewline
0.29 & 88.2089564235292 & 2.89611859933403 \tabularnewline
0.3 & 88.8800918251335 & 2.98555285827762 \tabularnewline
0.31 & 89.5627223248551 & 3.05959530834874 \tabularnewline
0.32 & 90.2536823490264 & 3.11304073528829 \tabularnewline
0.33 & 90.9492016498852 & 3.14476762491651 \tabularnewline
0.34 & 91.6459898879894 & 3.15901701309245 \tabularnewline
0.35 & 92.3423673054674 & 3.16651594434812 \tabularnewline
0.36 & 93.0392810628836 & 3.18346593328935 \tabularnewline
0.37 & 93.7410021811131 & 3.22936303030922 \tabularnewline
0.38 & 94.4553126786499 & 3.32428219596058 \tabularnewline
0.39 & 95.1930700845532 & 3.48314904129118 \tabularnewline
0.4 & 95.9671563908124 & 3.71357177558752 \tabularnewline
0.41 & 96.7909473780692 & 4.01255745916515 \tabularnewline
0.42 & 97.6765426168122 & 4.36676483267353 \tabularnewline
0.43 & 98.6330513014917 & 4.75471717380292 \tabularnewline
0.44 & 99.6652220584793 & 5.15006083560401 \tabularnewline
0.45 & 100.772637520181 & 5.52471665530927 \tabularnewline
0.46 & 101.9495818151 & 5.85301534404678 \tabularnewline
0.47 & 103.185557429548 & 6.1137521395414 \tabularnewline
0.48 & 104.466309306063 & 6.29268511069429 \tabularnewline
0.49 & 105.775138146003 & 6.38317976129522 \tabularnewline
0.5 & 107.094269080055 & 6.38445996842707 \tabularnewline
0.51 & 108.406084547907 & 6.30171202522008 \tabularnewline
0.52 & 109.694110598047 & 6.14296189660313 \tabularnewline
0.53 & 110.943731693361 & 5.91861351508301 \tabularnewline
0.54 & 112.14266996655 & 5.640540753316 \tabularnewline
0.55 & 113.281284446563 & 5.32103004516501 \tabularnewline
0.56 & 114.352728126723 & 4.97356379419633 \tabularnewline
0.57 & 115.352966690453 & 4.61187124283328 \tabularnewline
0.58 & 116.280638423843 & 4.24880992713721 \tabularnewline
0.59 & 117.136738345822 & 3.89613952070376 \tabularnewline
0.6 & 117.924141984416 & 3.56260936474679 \tabularnewline
0.61 & 118.647029920295 & 3.25374843705822 \tabularnewline
0.62 & 119.310309525192 & 2.9713794228546 \tabularnewline
0.63 & 119.919135727711 & 2.71495480722442 \tabularnewline
0.64 & 120.478602342609 & 2.48299084924194 \tabularnewline
0.65 & 120.993619826937 & 2.2733019975709 \tabularnewline
0.66 & 121.468935508746 & 2.08520146549111 \tabularnewline
0.67 & 121.909210904741 & 1.91825530830652 \tabularnewline
0.68 & 122.319062405262 & 1.77316314875467 \tabularnewline
0.69 & 122.702998430886 & 1.64959154746292 \tabularnewline
0.7 & 123.065238339371 & 1.54624053631326 \tabularnewline
0.71 & 123.40945900225 & 1.46011931184384 \tabularnewline
0.72 & 123.738566164563 & 1.38664685313015 \tabularnewline
0.73 & 124.054615144894 & 1.32091366685984 \tabularnewline
0.74 & 124.359000463793 & 1.25886563310872 \tabularnewline
0.75 & 124.652993442474 & 1.19930528647024 \tabularnewline
0.76 & 124.938632171193 & 1.14508818273923 \tabularnewline
0.77 & 125.219865604164 & 1.10479659062734 \tabularnewline
0.78 & 125.503735144748 & 1.09253597657163 \tabularnewline
0.79 & 125.8012640469 & 1.12667507715849 \tabularnewline
0.8 & 126.127649660098 & 1.22494737833554 \tabularnewline
0.81 & 126.501359506862 & 1.39759964411437 \tabularnewline
0.82 & 126.941868329066 & 1.64036250025366 \tabularnewline
0.83 & 127.466079167829 & 1.93312043969877 \tabularnewline
0.84 & 128.083951759599 & 2.24016270332167 \tabularnewline
0.85 & 128.794451387598 & 2.51455367175372 \tabularnewline
0.86 & 129.583465433388 & 2.70647414682551 \tabularnewline
0.87 & 130.425538073412 & 2.77841686452913 \tabularnewline
0.88 & 131.29080460494 & 2.72042661596655 \tabularnewline
0.89 & 132.157098153177 & 2.56516786937029 \tabularnewline
0.9 & 133.024939884759 & 2.39431102269311 \tabularnewline
0.91 & 133.930839751765 & 2.33049853335987 \tabularnewline
0.92 & 134.953808696779 & 2.49482788903312 \tabularnewline
0.93 & 136.213241653202 & 2.93762597913912 \tabularnewline
0.94 & 137.862885540746 & 3.62664219439522 \tabularnewline
0.95 & 140.08690674373 & 4.51219039071463 \tabularnewline
0.96 & 143.080132735701 & 5.55640364515428 \tabularnewline
0.97 & 146.937016081473 & 6.53898212475537 \tabularnewline
0.98 & 151.363468258588 & 6.58371006409021 \tabularnewline
0.99 & 155.358382732632 & 4.56128610409242 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=277187&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]56.9187399037681[/C][C]1.22465584956731[/C][/ROW]
[ROW][C]0.02[/C][C]58.2116910576544[/C][C]2.72327145708657[/C][/ROW]
[ROW][C]0.03[/C][C]60.2201071086672[/C][C]4.14062873972276[/C][/ROW]
[ROW][C]0.04[/C][C]62.695533487624[/C][C]5.06815342818103[/C][/ROW]
[ROW][C]0.05[/C][C]65.3130209026792[/C][C]5.29601178453132[/C][/ROW]
[ROW][C]0.06[/C][C]67.7745627228116[/C][C]4.90472666552585[/C][/ROW]
[ROW][C]0.07[/C][C]69.8872175150035[/C][C]4.16957988879593[/C][/ROW]
[ROW][C]0.08[/C][C]71.586641599792[/C][C]3.37910047846878[/C][/ROW]
[ROW][C]0.09[/C][C]72.9096471111918[/C][C]2.72902553916231[/C][/ROW]
[ROW][C]0.1[/C][C]73.9465864063741[/C][C]2.31048750731797[/C][/ROW]
[ROW][C]0.11[/C][C]74.8005500657086[/C][C]2.13943038289727[/C][/ROW]
[ROW][C]0.12[/C][C]75.5628282181944[/C][C]2.17893374493816[/C][/ROW]
[ROW][C]0.13[/C][C]76.3020382063614[/C][C]2.36101985187229[/C][/ROW]
[ROW][C]0.14[/C][C]77.0614503088174[/C][C]2.60989949742198[/C][/ROW]
[ROW][C]0.15[/C][C]77.8606969646846[/C][C]2.859118364927[/C][/ROW]
[ROW][C]0.16[/C][C]78.7000098783685[/C][C]3.05766623243527[/C][/ROW]
[ROW][C]0.17[/C][C]79.5660097829075[/C][C]3.1745202412367[/C][/ROW]
[ROW][C]0.18[/C][C]80.438171082547[/C][C]3.19880959232997[/C][/ROW]
[ROW][C]0.19[/C][C]81.2949913231201[/C][C]3.13946332588647[/C][/ROW]
[ROW][C]0.2[/C][C]82.1189452618121[/C][C]3.02110186572823[/C][/ROW]
[ROW][C]0.21[/C][C]82.8995669278708[/C][C]2.87660386306046[/C][/ROW]
[ROW][C]0.22[/C][C]83.634423034317[/C][C]2.74022215349037[/C][/ROW]
[ROW][C]0.23[/C][C]84.328206048743[/C][C]2.63889252955071[/C][/ROW]
[ROW][C]0.24[/C][C]84.9905521605391[/C][C]2.58762357222361[/C][/ROW]
[ROW][C]0.25[/C][C]85.6333648847731[/C][C]2.5883108573614[/C][/ROW]
[ROW][C]0.26[/C][C]86.2683575674892[/C][C]2.63288259237572[/C][/ROW]
[ROW][C]0.27[/C][C]86.9052734683833[/C][C]2.70815187710764[/C][/ROW]
[ROW][C]0.28[/C][C]87.5509262503855[/C][C]2.80014056766455[/C][/ROW]
[ROW][C]0.29[/C][C]88.2089564235292[/C][C]2.89611859933403[/C][/ROW]
[ROW][C]0.3[/C][C]88.8800918251335[/C][C]2.98555285827762[/C][/ROW]
[ROW][C]0.31[/C][C]89.5627223248551[/C][C]3.05959530834874[/C][/ROW]
[ROW][C]0.32[/C][C]90.2536823490264[/C][C]3.11304073528829[/C][/ROW]
[ROW][C]0.33[/C][C]90.9492016498852[/C][C]3.14476762491651[/C][/ROW]
[ROW][C]0.34[/C][C]91.6459898879894[/C][C]3.15901701309245[/C][/ROW]
[ROW][C]0.35[/C][C]92.3423673054674[/C][C]3.16651594434812[/C][/ROW]
[ROW][C]0.36[/C][C]93.0392810628836[/C][C]3.18346593328935[/C][/ROW]
[ROW][C]0.37[/C][C]93.7410021811131[/C][C]3.22936303030922[/C][/ROW]
[ROW][C]0.38[/C][C]94.4553126786499[/C][C]3.32428219596058[/C][/ROW]
[ROW][C]0.39[/C][C]95.1930700845532[/C][C]3.48314904129118[/C][/ROW]
[ROW][C]0.4[/C][C]95.9671563908124[/C][C]3.71357177558752[/C][/ROW]
[ROW][C]0.41[/C][C]96.7909473780692[/C][C]4.01255745916515[/C][/ROW]
[ROW][C]0.42[/C][C]97.6765426168122[/C][C]4.36676483267353[/C][/ROW]
[ROW][C]0.43[/C][C]98.6330513014917[/C][C]4.75471717380292[/C][/ROW]
[ROW][C]0.44[/C][C]99.6652220584793[/C][C]5.15006083560401[/C][/ROW]
[ROW][C]0.45[/C][C]100.772637520181[/C][C]5.52471665530927[/C][/ROW]
[ROW][C]0.46[/C][C]101.9495818151[/C][C]5.85301534404678[/C][/ROW]
[ROW][C]0.47[/C][C]103.185557429548[/C][C]6.1137521395414[/C][/ROW]
[ROW][C]0.48[/C][C]104.466309306063[/C][C]6.29268511069429[/C][/ROW]
[ROW][C]0.49[/C][C]105.775138146003[/C][C]6.38317976129522[/C][/ROW]
[ROW][C]0.5[/C][C]107.094269080055[/C][C]6.38445996842707[/C][/ROW]
[ROW][C]0.51[/C][C]108.406084547907[/C][C]6.30171202522008[/C][/ROW]
[ROW][C]0.52[/C][C]109.694110598047[/C][C]6.14296189660313[/C][/ROW]
[ROW][C]0.53[/C][C]110.943731693361[/C][C]5.91861351508301[/C][/ROW]
[ROW][C]0.54[/C][C]112.14266996655[/C][C]5.640540753316[/C][/ROW]
[ROW][C]0.55[/C][C]113.281284446563[/C][C]5.32103004516501[/C][/ROW]
[ROW][C]0.56[/C][C]114.352728126723[/C][C]4.97356379419633[/C][/ROW]
[ROW][C]0.57[/C][C]115.352966690453[/C][C]4.61187124283328[/C][/ROW]
[ROW][C]0.58[/C][C]116.280638423843[/C][C]4.24880992713721[/C][/ROW]
[ROW][C]0.59[/C][C]117.136738345822[/C][C]3.89613952070376[/C][/ROW]
[ROW][C]0.6[/C][C]117.924141984416[/C][C]3.56260936474679[/C][/ROW]
[ROW][C]0.61[/C][C]118.647029920295[/C][C]3.25374843705822[/C][/ROW]
[ROW][C]0.62[/C][C]119.310309525192[/C][C]2.9713794228546[/C][/ROW]
[ROW][C]0.63[/C][C]119.919135727711[/C][C]2.71495480722442[/C][/ROW]
[ROW][C]0.64[/C][C]120.478602342609[/C][C]2.48299084924194[/C][/ROW]
[ROW][C]0.65[/C][C]120.993619826937[/C][C]2.2733019975709[/C][/ROW]
[ROW][C]0.66[/C][C]121.468935508746[/C][C]2.08520146549111[/C][/ROW]
[ROW][C]0.67[/C][C]121.909210904741[/C][C]1.91825530830652[/C][/ROW]
[ROW][C]0.68[/C][C]122.319062405262[/C][C]1.77316314875467[/C][/ROW]
[ROW][C]0.69[/C][C]122.702998430886[/C][C]1.64959154746292[/C][/ROW]
[ROW][C]0.7[/C][C]123.065238339371[/C][C]1.54624053631326[/C][/ROW]
[ROW][C]0.71[/C][C]123.40945900225[/C][C]1.46011931184384[/C][/ROW]
[ROW][C]0.72[/C][C]123.738566164563[/C][C]1.38664685313015[/C][/ROW]
[ROW][C]0.73[/C][C]124.054615144894[/C][C]1.32091366685984[/C][/ROW]
[ROW][C]0.74[/C][C]124.359000463793[/C][C]1.25886563310872[/C][/ROW]
[ROW][C]0.75[/C][C]124.652993442474[/C][C]1.19930528647024[/C][/ROW]
[ROW][C]0.76[/C][C]124.938632171193[/C][C]1.14508818273923[/C][/ROW]
[ROW][C]0.77[/C][C]125.219865604164[/C][C]1.10479659062734[/C][/ROW]
[ROW][C]0.78[/C][C]125.503735144748[/C][C]1.09253597657163[/C][/ROW]
[ROW][C]0.79[/C][C]125.8012640469[/C][C]1.12667507715849[/C][/ROW]
[ROW][C]0.8[/C][C]126.127649660098[/C][C]1.22494737833554[/C][/ROW]
[ROW][C]0.81[/C][C]126.501359506862[/C][C]1.39759964411437[/C][/ROW]
[ROW][C]0.82[/C][C]126.941868329066[/C][C]1.64036250025366[/C][/ROW]
[ROW][C]0.83[/C][C]127.466079167829[/C][C]1.93312043969877[/C][/ROW]
[ROW][C]0.84[/C][C]128.083951759599[/C][C]2.24016270332167[/C][/ROW]
[ROW][C]0.85[/C][C]128.794451387598[/C][C]2.51455367175372[/C][/ROW]
[ROW][C]0.86[/C][C]129.583465433388[/C][C]2.70647414682551[/C][/ROW]
[ROW][C]0.87[/C][C]130.425538073412[/C][C]2.77841686452913[/C][/ROW]
[ROW][C]0.88[/C][C]131.29080460494[/C][C]2.72042661596655[/C][/ROW]
[ROW][C]0.89[/C][C]132.157098153177[/C][C]2.56516786937029[/C][/ROW]
[ROW][C]0.9[/C][C]133.024939884759[/C][C]2.39431102269311[/C][/ROW]
[ROW][C]0.91[/C][C]133.930839751765[/C][C]2.33049853335987[/C][/ROW]
[ROW][C]0.92[/C][C]134.953808696779[/C][C]2.49482788903312[/C][/ROW]
[ROW][C]0.93[/C][C]136.213241653202[/C][C]2.93762597913912[/C][/ROW]
[ROW][C]0.94[/C][C]137.862885540746[/C][C]3.62664219439522[/C][/ROW]
[ROW][C]0.95[/C][C]140.08690674373[/C][C]4.51219039071463[/C][/ROW]
[ROW][C]0.96[/C][C]143.080132735701[/C][C]5.55640364515428[/C][/ROW]
[ROW][C]0.97[/C][C]146.937016081473[/C][C]6.53898212475537[/C][/ROW]
[ROW][C]0.98[/C][C]151.363468258588[/C][C]6.58371006409021[/C][/ROW]
[ROW][C]0.99[/C][C]155.358382732632[/C][C]4.56128610409242[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=277187&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=277187&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
0.0156.91873990376811.22465584956731
0.0258.21169105765442.72327145708657
0.0360.22010710866724.14062873972276
0.0462.6955334876245.06815342818103
0.0565.31302090267925.29601178453132
0.0667.77456272281164.90472666552585
0.0769.88721751500354.16957988879593
0.0871.5866415997923.37910047846878
0.0972.90964711119182.72902553916231
0.173.94658640637412.31048750731797
0.1174.80055006570862.13943038289727
0.1275.56282821819442.17893374493816
0.1376.30203820636142.36101985187229
0.1477.06145030881742.60989949742198
0.1577.86069696468462.859118364927
0.1678.70000987836853.05766623243527
0.1779.56600978290753.1745202412367
0.1880.4381710825473.19880959232997
0.1981.29499132312013.13946332588647
0.282.11894526181213.02110186572823
0.2182.89956692787082.87660386306046
0.2283.6344230343172.74022215349037
0.2384.3282060487432.63889252955071
0.2484.99055216053912.58762357222361
0.2585.63336488477312.5883108573614
0.2686.26835756748922.63288259237572
0.2786.90527346838332.70815187710764
0.2887.55092625038552.80014056766455
0.2988.20895642352922.89611859933403
0.388.88009182513352.98555285827762
0.3189.56272232485513.05959530834874
0.3290.25368234902643.11304073528829
0.3390.94920164988523.14476762491651
0.3491.64598988798943.15901701309245
0.3592.34236730546743.16651594434812
0.3693.03928106288363.18346593328935
0.3793.74100218111313.22936303030922
0.3894.45531267864993.32428219596058
0.3995.19307008455323.48314904129118
0.495.96715639081243.71357177558752
0.4196.79094737806924.01255745916515
0.4297.67654261681224.36676483267353
0.4398.63305130149174.75471717380292
0.4499.66522205847935.15006083560401
0.45100.7726375201815.52471665530927
0.46101.94958181515.85301534404678
0.47103.1855574295486.1137521395414
0.48104.4663093060636.29268511069429
0.49105.7751381460036.38317976129522
0.5107.0942690800556.38445996842707
0.51108.4060845479076.30171202522008
0.52109.6941105980476.14296189660313
0.53110.9437316933615.91861351508301
0.54112.142669966555.640540753316
0.55113.2812844465635.32103004516501
0.56114.3527281267234.97356379419633
0.57115.3529666904534.61187124283328
0.58116.2806384238434.24880992713721
0.59117.1367383458223.89613952070376
0.6117.9241419844163.56260936474679
0.61118.6470299202953.25374843705822
0.62119.3103095251922.9713794228546
0.63119.9191357277112.71495480722442
0.64120.4786023426092.48299084924194
0.65120.9936198269372.2733019975709
0.66121.4689355087462.08520146549111
0.67121.9092109047411.91825530830652
0.68122.3190624052621.77316314875467
0.69122.7029984308861.64959154746292
0.7123.0652383393711.54624053631326
0.71123.409459002251.46011931184384
0.72123.7385661645631.38664685313015
0.73124.0546151448941.32091366685984
0.74124.3590004637931.25886563310872
0.75124.6529934424741.19930528647024
0.76124.9386321711931.14508818273923
0.77125.2198656041641.10479659062734
0.78125.5037351447481.09253597657163
0.79125.80126404691.12667507715849
0.8126.1276496600981.22494737833554
0.81126.5013595068621.39759964411437
0.82126.9418683290661.64036250025366
0.83127.4660791678291.93312043969877
0.84128.0839517595992.24016270332167
0.85128.7944513875982.51455367175372
0.86129.5834654333882.70647414682551
0.87130.4255380734122.77841686452913
0.88131.290804604942.72042661596655
0.89132.1570981531772.56516786937029
0.9133.0249398847592.39431102269311
0.91133.9308397517652.33049853335987
0.92134.9538086967792.49482788903312
0.93136.2132416532022.93762597913912
0.94137.8628855407463.62664219439522
0.95140.086906743734.51219039071463
0.96143.0801327357015.55640364515428
0.97146.9370160814736.53898212475537
0.98151.3634682585886.58371006409021
0.99155.3583827326324.56128610409242


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):
par3 <- '0.01'
par2 <- '0.09'
par1 <- '0.01'
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')