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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, 07 Mar 2012 10:42:01 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Mar/07/t1331134943k0m7nja7afz5pb6.htm/, Retrieved Mon, 29 Apr 2024 00:22:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=163633, Retrieved Mon, 29 Apr 2024 00:22:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDG201142
Estimated Impact134

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Maximumprijs vr t...] [2012-02-21 13:55:35] [adc168f2d81c407e2daa68e328480c63]
- RMPD  [Harrell-Davis Quantiles] [Gem. consumptiepr...] [2012-02-21 15:33:06] [100b5e8dde441e7bc35b34fcac5a963d]
-   PD    [Harrell-Davis Quantiles] [# Inschrijvingen ...] [2012-03-07 15:27:54] [adc168f2d81c407e2daa68e328480c63]
-   PD        [Harrell-Davis Quantiles] [Gem. consumptiepr...] [2012-03-07 15:42:01] [08ac479f43b71ff391b5d339ed1ce3ff] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
73.97	
73.97	
73.97	
73.97	
73.97	
73.97	
73.96	
74.44	
75.43	
75.77	
75.82	
75.85	
75.85	
75.85	
77.95	
82.07	
84.82	
85.08	
85.34	
85.65	
85.65	
85.72	
85.73	
85.73	
85.73	
85.73	
85.74	
86.32	
87.59	
87.81	
87.87	
87.94	
87.96	
88.01	
88.01	
88.01	
88.01	
88.01	
88.59	
89.43	
89.63	
89.73	
89.88	
89.89	
89.90	
89.91	
89.86	
90.07	
90.17	
90.17	
90.28	
90.87	
92.05	
92.10	
92.16	
92.22	
92.25	
92.29	
92.29	
92.29

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=163633&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=163633&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=163633&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'Gertrude Mary Cox' @ cox.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0173.96212053876640.00818781477409279
0.0273.96545302966520.00766177965645073
0.0373.97018568264470.0146058582995516
0.0473.97813576846180.0345955079152785
0.0573.9928633373190.0726392766319489
0.0674.01926784706790.133282908917386
0.0774.06286633629970.218011027246995
0.0874.12886293867890.323780949207163
0.0974.22120811345510.443314188547005
0.174.34194223613440.567218440250358
0.1174.49108934193860.686935923683534
0.1274.66720300653990.798665824843741
0.1374.86844146855660.905627293775413
0.1475.09385873399551.01889145438012
0.1575.34451304033721.15560773248571
0.1675.62403685334261.33329207538386
0.1775.93846046834571.56392467695722
0.1876.29528178435361.84917699675364
0.1976.7019678637682.17892760800669
0.277.16421026477192.53359920812908
0.2177.68430803609222.88683248338178
0.2278.26001592853183.20932757191584
0.2378.88408771649043.47240395336438
0.2479.54459619380313.65231077683708
0.2580.22595832977613.73340919158643
0.2680.91046904157543.70957669693825
0.2781.58007295281483.58464833143893
0.2882.21808943116273.37163514218137
0.2982.81064700949843.08998015591725
0.383.3476627320072.76282931969375
0.3183.82329798645042.41444164723391
0.3284.23591318886162.0673053338253
0.3384.58761272162541.7405704644197
0.3484.88351028374541.44864499316908
0.3585.13085309768971.20178580847346
0.3685.33812749982671.00558685859193
0.3785.51423803921710.862534028964796
0.3885.66781736070650.771066243925281
0.3985.80669280560550.725977149642307
0.485.93751244324250.718293410727037
0.4186.06551934518780.736997221084356
0.4286.19445689234730.770863090750595
0.4386.32658690764020.810243533880606
0.4486.46280338307850.847171836568534
0.4586.60282519163870.875502760355624
0.4686.74545029810330.890928465397065
0.4786.88885165986870.890843703886401
0.4887.03089215297990.874979307826096
0.4987.1694337483370.844363820448767
0.587.3026159439620.801694635261435
0.5187.42908078910820.750913960534557
0.5287.5481267376750.696722269879333
0.5387.65978049139840.644319050831367
0.5487.76478402280790.59855947969296
0.5587.86450208833630.564154826790621
0.5687.96076286257740.544302044688659
0.5788.05565020581290.540437621823319
0.5888.15127014069980.551884203019523
0.5988.24951617136180.575884602622555
0.688.35185803216670.608117366555394
0.6188.4591762415630.643632533423909
0.6288.57166044909150.677502777897654
0.6388.6887831376670.705173181142475
0.6488.80935218467080.722628633255076
0.6588.93163685804570.727178365159282
0.6689.0535531384630.71744754229991
0.6789.17288713369770.693370061752436
0.6889.28753105553040.656329202632907
0.6989.39570566998320.608942010680015
0.789.49614656953330.55463698080036
0.7189.58823849408050.497362251235692
0.7289.67209087010290.441525905772786
0.7389.74855674258850.391147200913968
0.7489.81920408609580.350403384924394
0.7589.88625110508180.322829035260623
0.7689.95247443589560.311642239887666
0.7790.02109146504290.319108343639778
0.7890.09560749311810.345872995885425
0.7990.17960935173330.391006884254298
0.890.27648478470.452083637801625
0.8190.38905669624660.525001551238585
0.8290.51914596568420.603866534241379
0.8390.66711348943210.680864652381818
0.8490.83147209811330.746760557027102
0.8591.00868638062390.79200330894431
0.8691.19327541077160.808207175439515
0.8791.37828731444910.790091982944503
0.8891.55612661812430.736937518726371
0.8991.71960551614090.653366613235596
0.991.86299558011240.548674067466721
0.9191.9828190779330.435035890108979
0.9292.07816757474410.324952070758995
0.9392.1504675814050.228502542974279
0.9492.20278892409290.151498819547535
0.9592.23894408149450.0949326344043264
0.9692.26268676129470.0560073657378541
0.9792.27724640899680.0302000841980588
0.9892.28525117943920.013621833523439
0.9992.28888253843350.00402816281066952

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 73.9621205387664 & 0.00818781477409279 \tabularnewline
0.02 & 73.9654530296652 & 0.00766177965645073 \tabularnewline
0.03 & 73.9701856826447 & 0.0146058582995516 \tabularnewline
0.04 & 73.9781357684618 & 0.0345955079152785 \tabularnewline
0.05 & 73.992863337319 & 0.0726392766319489 \tabularnewline
0.06 & 74.0192678470679 & 0.133282908917386 \tabularnewline
0.07 & 74.0628663362997 & 0.218011027246995 \tabularnewline
0.08 & 74.1288629386789 & 0.323780949207163 \tabularnewline
0.09 & 74.2212081134551 & 0.443314188547005 \tabularnewline
0.1 & 74.3419422361344 & 0.567218440250358 \tabularnewline
0.11 & 74.4910893419386 & 0.686935923683534 \tabularnewline
0.12 & 74.6672030065399 & 0.798665824843741 \tabularnewline
0.13 & 74.8684414685566 & 0.905627293775413 \tabularnewline
0.14 & 75.0938587339955 & 1.01889145438012 \tabularnewline
0.15 & 75.3445130403372 & 1.15560773248571 \tabularnewline
0.16 & 75.6240368533426 & 1.33329207538386 \tabularnewline
0.17 & 75.9384604683457 & 1.56392467695722 \tabularnewline
0.18 & 76.2952817843536 & 1.84917699675364 \tabularnewline
0.19 & 76.701967863768 & 2.17892760800669 \tabularnewline
0.2 & 77.1642102647719 & 2.53359920812908 \tabularnewline
0.21 & 77.6843080360922 & 2.88683248338178 \tabularnewline
0.22 & 78.2600159285318 & 3.20932757191584 \tabularnewline
0.23 & 78.8840877164904 & 3.47240395336438 \tabularnewline
0.24 & 79.5445961938031 & 3.65231077683708 \tabularnewline
0.25 & 80.2259583297761 & 3.73340919158643 \tabularnewline
0.26 & 80.9104690415754 & 3.70957669693825 \tabularnewline
0.27 & 81.5800729528148 & 3.58464833143893 \tabularnewline
0.28 & 82.2180894311627 & 3.37163514218137 \tabularnewline
0.29 & 82.8106470094984 & 3.08998015591725 \tabularnewline
0.3 & 83.347662732007 & 2.76282931969375 \tabularnewline
0.31 & 83.8232979864504 & 2.41444164723391 \tabularnewline
0.32 & 84.2359131888616 & 2.0673053338253 \tabularnewline
0.33 & 84.5876127216254 & 1.7405704644197 \tabularnewline
0.34 & 84.8835102837454 & 1.44864499316908 \tabularnewline
0.35 & 85.1308530976897 & 1.20178580847346 \tabularnewline
0.36 & 85.3381274998267 & 1.00558685859193 \tabularnewline
0.37 & 85.5142380392171 & 0.862534028964796 \tabularnewline
0.38 & 85.6678173607065 & 0.771066243925281 \tabularnewline
0.39 & 85.8066928056055 & 0.725977149642307 \tabularnewline
0.4 & 85.9375124432425 & 0.718293410727037 \tabularnewline
0.41 & 86.0655193451878 & 0.736997221084356 \tabularnewline
0.42 & 86.1944568923473 & 0.770863090750595 \tabularnewline
0.43 & 86.3265869076402 & 0.810243533880606 \tabularnewline
0.44 & 86.4628033830785 & 0.847171836568534 \tabularnewline
0.45 & 86.6028251916387 & 0.875502760355624 \tabularnewline
0.46 & 86.7454502981033 & 0.890928465397065 \tabularnewline
0.47 & 86.8888516598687 & 0.890843703886401 \tabularnewline
0.48 & 87.0308921529799 & 0.874979307826096 \tabularnewline
0.49 & 87.169433748337 & 0.844363820448767 \tabularnewline
0.5 & 87.302615943962 & 0.801694635261435 \tabularnewline
0.51 & 87.4290807891082 & 0.750913960534557 \tabularnewline
0.52 & 87.548126737675 & 0.696722269879333 \tabularnewline
0.53 & 87.6597804913984 & 0.644319050831367 \tabularnewline
0.54 & 87.7647840228079 & 0.59855947969296 \tabularnewline
0.55 & 87.8645020883363 & 0.564154826790621 \tabularnewline
0.56 & 87.9607628625774 & 0.544302044688659 \tabularnewline
0.57 & 88.0556502058129 & 0.540437621823319 \tabularnewline
0.58 & 88.1512701406998 & 0.551884203019523 \tabularnewline
0.59 & 88.2495161713618 & 0.575884602622555 \tabularnewline
0.6 & 88.3518580321667 & 0.608117366555394 \tabularnewline
0.61 & 88.459176241563 & 0.643632533423909 \tabularnewline
0.62 & 88.5716604490915 & 0.677502777897654 \tabularnewline
0.63 & 88.688783137667 & 0.705173181142475 \tabularnewline
0.64 & 88.8093521846708 & 0.722628633255076 \tabularnewline
0.65 & 88.9316368580457 & 0.727178365159282 \tabularnewline
0.66 & 89.053553138463 & 0.71744754229991 \tabularnewline
0.67 & 89.1728871336977 & 0.693370061752436 \tabularnewline
0.68 & 89.2875310555304 & 0.656329202632907 \tabularnewline
0.69 & 89.3957056699832 & 0.608942010680015 \tabularnewline
0.7 & 89.4961465695333 & 0.55463698080036 \tabularnewline
0.71 & 89.5882384940805 & 0.497362251235692 \tabularnewline
0.72 & 89.6720908701029 & 0.441525905772786 \tabularnewline
0.73 & 89.7485567425885 & 0.391147200913968 \tabularnewline
0.74 & 89.8192040860958 & 0.350403384924394 \tabularnewline
0.75 & 89.8862511050818 & 0.322829035260623 \tabularnewline
0.76 & 89.9524744358956 & 0.311642239887666 \tabularnewline
0.77 & 90.0210914650429 & 0.319108343639778 \tabularnewline
0.78 & 90.0956074931181 & 0.345872995885425 \tabularnewline
0.79 & 90.1796093517333 & 0.391006884254298 \tabularnewline
0.8 & 90.2764847847 & 0.452083637801625 \tabularnewline
0.81 & 90.3890566962466 & 0.525001551238585 \tabularnewline
0.82 & 90.5191459656842 & 0.603866534241379 \tabularnewline
0.83 & 90.6671134894321 & 0.680864652381818 \tabularnewline
0.84 & 90.8314720981133 & 0.746760557027102 \tabularnewline
0.85 & 91.0086863806239 & 0.79200330894431 \tabularnewline
0.86 & 91.1932754107716 & 0.808207175439515 \tabularnewline
0.87 & 91.3782873144491 & 0.790091982944503 \tabularnewline
0.88 & 91.5561266181243 & 0.736937518726371 \tabularnewline
0.89 & 91.7196055161409 & 0.653366613235596 \tabularnewline
0.9 & 91.8629955801124 & 0.548674067466721 \tabularnewline
0.91 & 91.982819077933 & 0.435035890108979 \tabularnewline
0.92 & 92.0781675747441 & 0.324952070758995 \tabularnewline
0.93 & 92.150467581405 & 0.228502542974279 \tabularnewline
0.94 & 92.2027889240929 & 0.151498819547535 \tabularnewline
0.95 & 92.2389440814945 & 0.0949326344043264 \tabularnewline
0.96 & 92.2626867612947 & 0.0560073657378541 \tabularnewline
0.97 & 92.2772464089968 & 0.0302000841980588 \tabularnewline
0.98 & 92.2852511794392 & 0.013621833523439 \tabularnewline
0.99 & 92.2888825384335 & 0.00402816281066952 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=163633&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]73.9621205387664[/C][C]0.00818781477409279[/C][/ROW]
[ROW][C]0.02[/C][C]73.9654530296652[/C][C]0.00766177965645073[/C][/ROW]
[ROW][C]0.03[/C][C]73.9701856826447[/C][C]0.0146058582995516[/C][/ROW]
[ROW][C]0.04[/C][C]73.9781357684618[/C][C]0.0345955079152785[/C][/ROW]
[ROW][C]0.05[/C][C]73.992863337319[/C][C]0.0726392766319489[/C][/ROW]
[ROW][C]0.06[/C][C]74.0192678470679[/C][C]0.133282908917386[/C][/ROW]
[ROW][C]0.07[/C][C]74.0628663362997[/C][C]0.218011027246995[/C][/ROW]
[ROW][C]0.08[/C][C]74.1288629386789[/C][C]0.323780949207163[/C][/ROW]
[ROW][C]0.09[/C][C]74.2212081134551[/C][C]0.443314188547005[/C][/ROW]
[ROW][C]0.1[/C][C]74.3419422361344[/C][C]0.567218440250358[/C][/ROW]
[ROW][C]0.11[/C][C]74.4910893419386[/C][C]0.686935923683534[/C][/ROW]
[ROW][C]0.12[/C][C]74.6672030065399[/C][C]0.798665824843741[/C][/ROW]
[ROW][C]0.13[/C][C]74.8684414685566[/C][C]0.905627293775413[/C][/ROW]
[ROW][C]0.14[/C][C]75.0938587339955[/C][C]1.01889145438012[/C][/ROW]
[ROW][C]0.15[/C][C]75.3445130403372[/C][C]1.15560773248571[/C][/ROW]
[ROW][C]0.16[/C][C]75.6240368533426[/C][C]1.33329207538386[/C][/ROW]
[ROW][C]0.17[/C][C]75.9384604683457[/C][C]1.56392467695722[/C][/ROW]
[ROW][C]0.18[/C][C]76.2952817843536[/C][C]1.84917699675364[/C][/ROW]
[ROW][C]0.19[/C][C]76.701967863768[/C][C]2.17892760800669[/C][/ROW]
[ROW][C]0.2[/C][C]77.1642102647719[/C][C]2.53359920812908[/C][/ROW]
[ROW][C]0.21[/C][C]77.6843080360922[/C][C]2.88683248338178[/C][/ROW]
[ROW][C]0.22[/C][C]78.2600159285318[/C][C]3.20932757191584[/C][/ROW]
[ROW][C]0.23[/C][C]78.8840877164904[/C][C]3.47240395336438[/C][/ROW]
[ROW][C]0.24[/C][C]79.5445961938031[/C][C]3.65231077683708[/C][/ROW]
[ROW][C]0.25[/C][C]80.2259583297761[/C][C]3.73340919158643[/C][/ROW]
[ROW][C]0.26[/C][C]80.9104690415754[/C][C]3.70957669693825[/C][/ROW]
[ROW][C]0.27[/C][C]81.5800729528148[/C][C]3.58464833143893[/C][/ROW]
[ROW][C]0.28[/C][C]82.2180894311627[/C][C]3.37163514218137[/C][/ROW]
[ROW][C]0.29[/C][C]82.8106470094984[/C][C]3.08998015591725[/C][/ROW]
[ROW][C]0.3[/C][C]83.347662732007[/C][C]2.76282931969375[/C][/ROW]
[ROW][C]0.31[/C][C]83.8232979864504[/C][C]2.41444164723391[/C][/ROW]
[ROW][C]0.32[/C][C]84.2359131888616[/C][C]2.0673053338253[/C][/ROW]
[ROW][C]0.33[/C][C]84.5876127216254[/C][C]1.7405704644197[/C][/ROW]
[ROW][C]0.34[/C][C]84.8835102837454[/C][C]1.44864499316908[/C][/ROW]
[ROW][C]0.35[/C][C]85.1308530976897[/C][C]1.20178580847346[/C][/ROW]
[ROW][C]0.36[/C][C]85.3381274998267[/C][C]1.00558685859193[/C][/ROW]
[ROW][C]0.37[/C][C]85.5142380392171[/C][C]0.862534028964796[/C][/ROW]
[ROW][C]0.38[/C][C]85.6678173607065[/C][C]0.771066243925281[/C][/ROW]
[ROW][C]0.39[/C][C]85.8066928056055[/C][C]0.725977149642307[/C][/ROW]
[ROW][C]0.4[/C][C]85.9375124432425[/C][C]0.718293410727037[/C][/ROW]
[ROW][C]0.41[/C][C]86.0655193451878[/C][C]0.736997221084356[/C][/ROW]
[ROW][C]0.42[/C][C]86.1944568923473[/C][C]0.770863090750595[/C][/ROW]
[ROW][C]0.43[/C][C]86.3265869076402[/C][C]0.810243533880606[/C][/ROW]
[ROW][C]0.44[/C][C]86.4628033830785[/C][C]0.847171836568534[/C][/ROW]
[ROW][C]0.45[/C][C]86.6028251916387[/C][C]0.875502760355624[/C][/ROW]
[ROW][C]0.46[/C][C]86.7454502981033[/C][C]0.890928465397065[/C][/ROW]
[ROW][C]0.47[/C][C]86.8888516598687[/C][C]0.890843703886401[/C][/ROW]
[ROW][C]0.48[/C][C]87.0308921529799[/C][C]0.874979307826096[/C][/ROW]
[ROW][C]0.49[/C][C]87.169433748337[/C][C]0.844363820448767[/C][/ROW]
[ROW][C]0.5[/C][C]87.302615943962[/C][C]0.801694635261435[/C][/ROW]
[ROW][C]0.51[/C][C]87.4290807891082[/C][C]0.750913960534557[/C][/ROW]
[ROW][C]0.52[/C][C]87.548126737675[/C][C]0.696722269879333[/C][/ROW]
[ROW][C]0.53[/C][C]87.6597804913984[/C][C]0.644319050831367[/C][/ROW]
[ROW][C]0.54[/C][C]87.7647840228079[/C][C]0.59855947969296[/C][/ROW]
[ROW][C]0.55[/C][C]87.8645020883363[/C][C]0.564154826790621[/C][/ROW]
[ROW][C]0.56[/C][C]87.9607628625774[/C][C]0.544302044688659[/C][/ROW]
[ROW][C]0.57[/C][C]88.0556502058129[/C][C]0.540437621823319[/C][/ROW]
[ROW][C]0.58[/C][C]88.1512701406998[/C][C]0.551884203019523[/C][/ROW]
[ROW][C]0.59[/C][C]88.2495161713618[/C][C]0.575884602622555[/C][/ROW]
[ROW][C]0.6[/C][C]88.3518580321667[/C][C]0.608117366555394[/C][/ROW]
[ROW][C]0.61[/C][C]88.459176241563[/C][C]0.643632533423909[/C][/ROW]
[ROW][C]0.62[/C][C]88.5716604490915[/C][C]0.677502777897654[/C][/ROW]
[ROW][C]0.63[/C][C]88.688783137667[/C][C]0.705173181142475[/C][/ROW]
[ROW][C]0.64[/C][C]88.8093521846708[/C][C]0.722628633255076[/C][/ROW]
[ROW][C]0.65[/C][C]88.9316368580457[/C][C]0.727178365159282[/C][/ROW]
[ROW][C]0.66[/C][C]89.053553138463[/C][C]0.71744754229991[/C][/ROW]
[ROW][C]0.67[/C][C]89.1728871336977[/C][C]0.693370061752436[/C][/ROW]
[ROW][C]0.68[/C][C]89.2875310555304[/C][C]0.656329202632907[/C][/ROW]
[ROW][C]0.69[/C][C]89.3957056699832[/C][C]0.608942010680015[/C][/ROW]
[ROW][C]0.7[/C][C]89.4961465695333[/C][C]0.55463698080036[/C][/ROW]
[ROW][C]0.71[/C][C]89.5882384940805[/C][C]0.497362251235692[/C][/ROW]
[ROW][C]0.72[/C][C]89.6720908701029[/C][C]0.441525905772786[/C][/ROW]
[ROW][C]0.73[/C][C]89.7485567425885[/C][C]0.391147200913968[/C][/ROW]
[ROW][C]0.74[/C][C]89.8192040860958[/C][C]0.350403384924394[/C][/ROW]
[ROW][C]0.75[/C][C]89.8862511050818[/C][C]0.322829035260623[/C][/ROW]
[ROW][C]0.76[/C][C]89.9524744358956[/C][C]0.311642239887666[/C][/ROW]
[ROW][C]0.77[/C][C]90.0210914650429[/C][C]0.319108343639778[/C][/ROW]
[ROW][C]0.78[/C][C]90.0956074931181[/C][C]0.345872995885425[/C][/ROW]
[ROW][C]0.79[/C][C]90.1796093517333[/C][C]0.391006884254298[/C][/ROW]
[ROW][C]0.8[/C][C]90.2764847847[/C][C]0.452083637801625[/C][/ROW]
[ROW][C]0.81[/C][C]90.3890566962466[/C][C]0.525001551238585[/C][/ROW]
[ROW][C]0.82[/C][C]90.5191459656842[/C][C]0.603866534241379[/C][/ROW]
[ROW][C]0.83[/C][C]90.6671134894321[/C][C]0.680864652381818[/C][/ROW]
[ROW][C]0.84[/C][C]90.8314720981133[/C][C]0.746760557027102[/C][/ROW]
[ROW][C]0.85[/C][C]91.0086863806239[/C][C]0.79200330894431[/C][/ROW]
[ROW][C]0.86[/C][C]91.1932754107716[/C][C]0.808207175439515[/C][/ROW]
[ROW][C]0.87[/C][C]91.3782873144491[/C][C]0.790091982944503[/C][/ROW]
[ROW][C]0.88[/C][C]91.5561266181243[/C][C]0.736937518726371[/C][/ROW]
[ROW][C]0.89[/C][C]91.7196055161409[/C][C]0.653366613235596[/C][/ROW]
[ROW][C]0.9[/C][C]91.8629955801124[/C][C]0.548674067466721[/C][/ROW]
[ROW][C]0.91[/C][C]91.982819077933[/C][C]0.435035890108979[/C][/ROW]
[ROW][C]0.92[/C][C]92.0781675747441[/C][C]0.324952070758995[/C][/ROW]
[ROW][C]0.93[/C][C]92.150467581405[/C][C]0.228502542974279[/C][/ROW]
[ROW][C]0.94[/C][C]92.2027889240929[/C][C]0.151498819547535[/C][/ROW]
[ROW][C]0.95[/C][C]92.2389440814945[/C][C]0.0949326344043264[/C][/ROW]
[ROW][C]0.96[/C][C]92.2626867612947[/C][C]0.0560073657378541[/C][/ROW]
[ROW][C]0.97[/C][C]92.2772464089968[/C][C]0.0302000841980588[/C][/ROW]
[ROW][C]0.98[/C][C]92.2852511794392[/C][C]0.013621833523439[/C][/ROW]
[ROW][C]0.99[/C][C]92.2888825384335[/C][C]0.00402816281066952[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=163633&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=163633&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
0.0173.96212053876640.00818781477409279
0.0273.96545302966520.00766177965645073
0.0373.97018568264470.0146058582995516
0.0473.97813576846180.0345955079152785
0.0573.9928633373190.0726392766319489
0.0674.01926784706790.133282908917386
0.0774.06286633629970.218011027246995
0.0874.12886293867890.323780949207163
0.0974.22120811345510.443314188547005
0.174.34194223613440.567218440250358
0.1174.49108934193860.686935923683534
0.1274.66720300653990.798665824843741
0.1374.86844146855660.905627293775413
0.1475.09385873399551.01889145438012
0.1575.34451304033721.15560773248571
0.1675.62403685334261.33329207538386
0.1775.93846046834571.56392467695722
0.1876.29528178435361.84917699675364
0.1976.7019678637682.17892760800669
0.277.16421026477192.53359920812908
0.2177.68430803609222.88683248338178
0.2278.26001592853183.20932757191584
0.2378.88408771649043.47240395336438
0.2479.54459619380313.65231077683708
0.2580.22595832977613.73340919158643
0.2680.91046904157543.70957669693825
0.2781.58007295281483.58464833143893
0.2882.21808943116273.37163514218137
0.2982.81064700949843.08998015591725
0.383.3476627320072.76282931969375
0.3183.82329798645042.41444164723391
0.3284.23591318886162.0673053338253
0.3384.58761272162541.7405704644197
0.3484.88351028374541.44864499316908
0.3585.13085309768971.20178580847346
0.3685.33812749982671.00558685859193
0.3785.51423803921710.862534028964796
0.3885.66781736070650.771066243925281
0.3985.80669280560550.725977149642307
0.485.93751244324250.718293410727037
0.4186.06551934518780.736997221084356
0.4286.19445689234730.770863090750595
0.4386.32658690764020.810243533880606
0.4486.46280338307850.847171836568534
0.4586.60282519163870.875502760355624
0.4686.74545029810330.890928465397065
0.4786.88885165986870.890843703886401
0.4887.03089215297990.874979307826096
0.4987.1694337483370.844363820448767
0.587.3026159439620.801694635261435
0.5187.42908078910820.750913960534557
0.5287.5481267376750.696722269879333
0.5387.65978049139840.644319050831367
0.5487.76478402280790.59855947969296
0.5587.86450208833630.564154826790621
0.5687.96076286257740.544302044688659
0.5788.05565020581290.540437621823319
0.5888.15127014069980.551884203019523
0.5988.24951617136180.575884602622555
0.688.35185803216670.608117366555394
0.6188.4591762415630.643632533423909
0.6288.57166044909150.677502777897654
0.6388.6887831376670.705173181142475
0.6488.80935218467080.722628633255076
0.6588.93163685804570.727178365159282
0.6689.0535531384630.71744754229991
0.6789.17288713369770.693370061752436
0.6889.28753105553040.656329202632907
0.6989.39570566998320.608942010680015
0.789.49614656953330.55463698080036
0.7189.58823849408050.497362251235692
0.7289.67209087010290.441525905772786
0.7389.74855674258850.391147200913968
0.7489.81920408609580.350403384924394
0.7589.88625110508180.322829035260623
0.7689.95247443589560.311642239887666
0.7790.02109146504290.319108343639778
0.7890.09560749311810.345872995885425
0.7990.17960935173330.391006884254298
0.890.27648478470.452083637801625
0.8190.38905669624660.525001551238585
0.8290.51914596568420.603866534241379
0.8390.66711348943210.680864652381818
0.8490.83147209811330.746760557027102
0.8591.00868638062390.79200330894431
0.8691.19327541077160.808207175439515
0.8791.37828731444910.790091982944503
0.8891.55612661812430.736937518726371
0.8991.71960551614090.653366613235596
0.991.86299558011240.548674067466721
0.9191.9828190779330.435035890108979
0.9292.07816757474410.324952070758995
0.9392.1504675814050.228502542974279
0.9492.20278892409290.151498819547535
0.9592.23894408149450.0949326344043264
0.9692.26268676129470.0560073657378541
0.9792.27724640899680.0302000841980588
0.9892.28525117943920.013621833523439
0.9992.28888253843350.00402816281066952


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')