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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 computationTue, 26 Feb 2013 06:55:19 -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/2013/Feb/26/t1361879769tia0qjb6xl1wwfm.htm/, Retrieved Sun, 05 May 2024 00:05:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=207004, Retrieved Sun, 05 May 2024 00:05:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact111

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] [Harrell Davis ins...] [2013-02-26 11:55:19] [4c761713f35dbef288fd2ff7b731829c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971
20036
22485
18730
14538
27561
25985
34670
32066
27186
29586
21359
21553
19573
24256
22380
16167
27297
28287
33474
28229
28785
25597
18130
20198
22849
23118
21925
20801
18785
20659
29367
23992
20645
22356
17902
15879
16963
21035
17988
10437

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 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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=207004&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 Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=207004&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=207004&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 Maurice George Kendall' @ kendall.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.019865.169616186511133.69645490713
0.0210695.27123491141399.18327141453
0.0311649.04447903611690.83157335809
0.0412614.47209549811846.25745353132
0.0513527.2491100221822.85949156042
0.0614341.29963359841662.44194790882
0.0715032.1516600691441.25416148816
0.0815599.13598591821224.74452029955
0.0916058.16914490131045.8379025508
0.116431.4431111546908.684441972562
0.1116739.9068035588804.116128752503
0.1217000.085772106722.195505813239
0.1317223.9905467077656.813305018367
0.1417420.3076397493605.18950576131
0.1517595.6783502812566.642951248735
0.1617755.6052593794541.479723607736
0.1717904.9495780462530.479773598828
0.1818048.1167064853533.915578322333
0.1918189.0315425181550.933693341845
0.218330.9883336295579.029288878539
0.2118476.4526202937614.340649865564
0.2218626.8869486346652.189448139045
0.2318782.6576203248687.600575164158
0.2418943.0568075622716.03689640365
0.2519106.4486592975733.757336603072
0.2619270.5248038848738.360449711972
0.2719432.6365086111729.047495032777
0.2819590.1588190917706.843144836256
0.2919740.8373362615674.189668452417
0.319883.0718288497634.84153320996
0.3120016.1023205576593.363458049867
0.3220140.0802936122554.413607721005
0.3320256.0262242551522.44622419904
0.3420365.6905812596501.018425199301
0.3520471.3457672076492.586598679035
0.3620575.5405216744497.998945571183
0.3720680.8472486265516.660005403973
0.3820789.6287501759546.559382382735
0.3920903.8459040491584.83233989841
0.421024.9228704347628.161734145001
0.4121153.6812895159673.067298884795
0.4221290.348822439716.559149553166
0.4321434.6396145417756.168211618084
0.4421585.8949644821790.461520494279
0.4521743.2629403217819.057429950763
0.4621905.8880696665842.630185704833
0.4722073.0789310165862.756871035664
0.4822244.4241761087881.536083011005
0.4922419.836443803901.023750771632
0.522599.5172455863922.866845673768
0.5122783.8512311165947.703812427113
0.5222973.2517265322975.092890143417
0.5323167.98805098871003.63488852743
0.5423368.02726240011030.99676565937
0.5523572.91886106791054.52860902713
0.5623781.74228302051071.53106038772
0.5723993.12613550061079.70843939484
0.5824205.33725173431077.39175475525
0.5924416.42815435651063.97850028645
0.624624.42394613911039.67091680962
0.6124827.52410833581005.87682175687
0.6225024.2914867097964.892962811923
0.6325213.800724007919.863086114323
0.6425395.722726933874.153117254796
0.6525570.3312042766831.127518248801
0.6625738.4313340689793.549499992728
0.6725901.2267852698763.271384505866
0.6826060.155550912740.91912096378
0.6926216.7327241442726.16732335836
0.726372.4359923269717.973288977022
0.7126528.6565035238715.17121859969
0.7226686.7166681855717.073517505604
0.7326847.9332590426723.592265882953
0.7427013.6861516824735.204851695744
0.7527185.4466553497752.571243841262
0.7627364.7281612777775.962500554769
0.7727552.9452308366804.681728778841
0.7827751.2005023051836.745282653361
0.7927960.0536585472868.962546049662
0.828179.3525209909897.429376305676
0.8128408.2115812307918.363835595574
0.8228645.1980402822929.14018253784
0.8328888.7256705581929.314811732119
0.8429137.5700947873921.108393972335
0.8529391.3293738718909.014323287727
0.8629650.6018002461898.408357701458
0.8729916.688373482892.887726720528
0.8830190.7937159821891.805574877198
0.8930473.0089491087889.082194773521
0.930761.760841369875.28149731788
0.9131054.7292055613843.159571743312
0.9231352.1010448085795.862050009902
0.9331661.8868238755.561624832106
0.9432004.4522493969764.914286439574
0.9532410.0983861253857.883765901782
0.9632902.6086350202999.819804888438
0.9733468.78998332241067.94928417664
0.9834032.063348922912.479952398685
0.9934465.751933602511.535529158207

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 9865.16961618651 & 1133.69645490713 \tabularnewline
0.02 & 10695.2712349114 & 1399.18327141453 \tabularnewline
0.03 & 11649.0444790361 & 1690.83157335809 \tabularnewline
0.04 & 12614.4720954981 & 1846.25745353132 \tabularnewline
0.05 & 13527.249110022 & 1822.85949156042 \tabularnewline
0.06 & 14341.2996335984 & 1662.44194790882 \tabularnewline
0.07 & 15032.151660069 & 1441.25416148816 \tabularnewline
0.08 & 15599.1359859182 & 1224.74452029955 \tabularnewline
0.09 & 16058.1691449013 & 1045.8379025508 \tabularnewline
0.1 & 16431.4431111546 & 908.684441972562 \tabularnewline
0.11 & 16739.9068035588 & 804.116128752503 \tabularnewline
0.12 & 17000.085772106 & 722.195505813239 \tabularnewline
0.13 & 17223.9905467077 & 656.813305018367 \tabularnewline
0.14 & 17420.3076397493 & 605.18950576131 \tabularnewline
0.15 & 17595.6783502812 & 566.642951248735 \tabularnewline
0.16 & 17755.6052593794 & 541.479723607736 \tabularnewline
0.17 & 17904.9495780462 & 530.479773598828 \tabularnewline
0.18 & 18048.1167064853 & 533.915578322333 \tabularnewline
0.19 & 18189.0315425181 & 550.933693341845 \tabularnewline
0.2 & 18330.9883336295 & 579.029288878539 \tabularnewline
0.21 & 18476.4526202937 & 614.340649865564 \tabularnewline
0.22 & 18626.8869486346 & 652.189448139045 \tabularnewline
0.23 & 18782.6576203248 & 687.600575164158 \tabularnewline
0.24 & 18943.0568075622 & 716.03689640365 \tabularnewline
0.25 & 19106.4486592975 & 733.757336603072 \tabularnewline
0.26 & 19270.5248038848 & 738.360449711972 \tabularnewline
0.27 & 19432.6365086111 & 729.047495032777 \tabularnewline
0.28 & 19590.1588190917 & 706.843144836256 \tabularnewline
0.29 & 19740.8373362615 & 674.189668452417 \tabularnewline
0.3 & 19883.0718288497 & 634.84153320996 \tabularnewline
0.31 & 20016.1023205576 & 593.363458049867 \tabularnewline
0.32 & 20140.0802936122 & 554.413607721005 \tabularnewline
0.33 & 20256.0262242551 & 522.44622419904 \tabularnewline
0.34 & 20365.6905812596 & 501.018425199301 \tabularnewline
0.35 & 20471.3457672076 & 492.586598679035 \tabularnewline
0.36 & 20575.5405216744 & 497.998945571183 \tabularnewline
0.37 & 20680.8472486265 & 516.660005403973 \tabularnewline
0.38 & 20789.6287501759 & 546.559382382735 \tabularnewline
0.39 & 20903.8459040491 & 584.83233989841 \tabularnewline
0.4 & 21024.9228704347 & 628.161734145001 \tabularnewline
0.41 & 21153.6812895159 & 673.067298884795 \tabularnewline
0.42 & 21290.348822439 & 716.559149553166 \tabularnewline
0.43 & 21434.6396145417 & 756.168211618084 \tabularnewline
0.44 & 21585.8949644821 & 790.461520494279 \tabularnewline
0.45 & 21743.2629403217 & 819.057429950763 \tabularnewline
0.46 & 21905.8880696665 & 842.630185704833 \tabularnewline
0.47 & 22073.0789310165 & 862.756871035664 \tabularnewline
0.48 & 22244.4241761087 & 881.536083011005 \tabularnewline
0.49 & 22419.836443803 & 901.023750771632 \tabularnewline
0.5 & 22599.5172455863 & 922.866845673768 \tabularnewline
0.51 & 22783.8512311165 & 947.703812427113 \tabularnewline
0.52 & 22973.2517265322 & 975.092890143417 \tabularnewline
0.53 & 23167.9880509887 & 1003.63488852743 \tabularnewline
0.54 & 23368.0272624001 & 1030.99676565937 \tabularnewline
0.55 & 23572.9188610679 & 1054.52860902713 \tabularnewline
0.56 & 23781.7422830205 & 1071.53106038772 \tabularnewline
0.57 & 23993.1261355006 & 1079.70843939484 \tabularnewline
0.58 & 24205.3372517343 & 1077.39175475525 \tabularnewline
0.59 & 24416.4281543565 & 1063.97850028645 \tabularnewline
0.6 & 24624.4239461391 & 1039.67091680962 \tabularnewline
0.61 & 24827.5241083358 & 1005.87682175687 \tabularnewline
0.62 & 25024.2914867097 & 964.892962811923 \tabularnewline
0.63 & 25213.800724007 & 919.863086114323 \tabularnewline
0.64 & 25395.722726933 & 874.153117254796 \tabularnewline
0.65 & 25570.3312042766 & 831.127518248801 \tabularnewline
0.66 & 25738.4313340689 & 793.549499992728 \tabularnewline
0.67 & 25901.2267852698 & 763.271384505866 \tabularnewline
0.68 & 26060.155550912 & 740.91912096378 \tabularnewline
0.69 & 26216.7327241442 & 726.16732335836 \tabularnewline
0.7 & 26372.4359923269 & 717.973288977022 \tabularnewline
0.71 & 26528.6565035238 & 715.17121859969 \tabularnewline
0.72 & 26686.7166681855 & 717.073517505604 \tabularnewline
0.73 & 26847.9332590426 & 723.592265882953 \tabularnewline
0.74 & 27013.6861516824 & 735.204851695744 \tabularnewline
0.75 & 27185.4466553497 & 752.571243841262 \tabularnewline
0.76 & 27364.7281612777 & 775.962500554769 \tabularnewline
0.77 & 27552.9452308366 & 804.681728778841 \tabularnewline
0.78 & 27751.2005023051 & 836.745282653361 \tabularnewline
0.79 & 27960.0536585472 & 868.962546049662 \tabularnewline
0.8 & 28179.3525209909 & 897.429376305676 \tabularnewline
0.81 & 28408.2115812307 & 918.363835595574 \tabularnewline
0.82 & 28645.1980402822 & 929.14018253784 \tabularnewline
0.83 & 28888.7256705581 & 929.314811732119 \tabularnewline
0.84 & 29137.5700947873 & 921.108393972335 \tabularnewline
0.85 & 29391.3293738718 & 909.014323287727 \tabularnewline
0.86 & 29650.6018002461 & 898.408357701458 \tabularnewline
0.87 & 29916.688373482 & 892.887726720528 \tabularnewline
0.88 & 30190.7937159821 & 891.805574877198 \tabularnewline
0.89 & 30473.0089491087 & 889.082194773521 \tabularnewline
0.9 & 30761.760841369 & 875.28149731788 \tabularnewline
0.91 & 31054.7292055613 & 843.159571743312 \tabularnewline
0.92 & 31352.1010448085 & 795.862050009902 \tabularnewline
0.93 & 31661.8868238 & 755.561624832106 \tabularnewline
0.94 & 32004.4522493969 & 764.914286439574 \tabularnewline
0.95 & 32410.0983861253 & 857.883765901782 \tabularnewline
0.96 & 32902.6086350202 & 999.819804888438 \tabularnewline
0.97 & 33468.7899833224 & 1067.94928417664 \tabularnewline
0.98 & 34032.063348922 & 912.479952398685 \tabularnewline
0.99 & 34465.751933602 & 511.535529158207 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=207004&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]9865.16961618651[/C][C]1133.69645490713[/C][/ROW]
[ROW][C]0.02[/C][C]10695.2712349114[/C][C]1399.18327141453[/C][/ROW]
[ROW][C]0.03[/C][C]11649.0444790361[/C][C]1690.83157335809[/C][/ROW]
[ROW][C]0.04[/C][C]12614.4720954981[/C][C]1846.25745353132[/C][/ROW]
[ROW][C]0.05[/C][C]13527.249110022[/C][C]1822.85949156042[/C][/ROW]
[ROW][C]0.06[/C][C]14341.2996335984[/C][C]1662.44194790882[/C][/ROW]
[ROW][C]0.07[/C][C]15032.151660069[/C][C]1441.25416148816[/C][/ROW]
[ROW][C]0.08[/C][C]15599.1359859182[/C][C]1224.74452029955[/C][/ROW]
[ROW][C]0.09[/C][C]16058.1691449013[/C][C]1045.8379025508[/C][/ROW]
[ROW][C]0.1[/C][C]16431.4431111546[/C][C]908.684441972562[/C][/ROW]
[ROW][C]0.11[/C][C]16739.9068035588[/C][C]804.116128752503[/C][/ROW]
[ROW][C]0.12[/C][C]17000.085772106[/C][C]722.195505813239[/C][/ROW]
[ROW][C]0.13[/C][C]17223.9905467077[/C][C]656.813305018367[/C][/ROW]
[ROW][C]0.14[/C][C]17420.3076397493[/C][C]605.18950576131[/C][/ROW]
[ROW][C]0.15[/C][C]17595.6783502812[/C][C]566.642951248735[/C][/ROW]
[ROW][C]0.16[/C][C]17755.6052593794[/C][C]541.479723607736[/C][/ROW]
[ROW][C]0.17[/C][C]17904.9495780462[/C][C]530.479773598828[/C][/ROW]
[ROW][C]0.18[/C][C]18048.1167064853[/C][C]533.915578322333[/C][/ROW]
[ROW][C]0.19[/C][C]18189.0315425181[/C][C]550.933693341845[/C][/ROW]
[ROW][C]0.2[/C][C]18330.9883336295[/C][C]579.029288878539[/C][/ROW]
[ROW][C]0.21[/C][C]18476.4526202937[/C][C]614.340649865564[/C][/ROW]
[ROW][C]0.22[/C][C]18626.8869486346[/C][C]652.189448139045[/C][/ROW]
[ROW][C]0.23[/C][C]18782.6576203248[/C][C]687.600575164158[/C][/ROW]
[ROW][C]0.24[/C][C]18943.0568075622[/C][C]716.03689640365[/C][/ROW]
[ROW][C]0.25[/C][C]19106.4486592975[/C][C]733.757336603072[/C][/ROW]
[ROW][C]0.26[/C][C]19270.5248038848[/C][C]738.360449711972[/C][/ROW]
[ROW][C]0.27[/C][C]19432.6365086111[/C][C]729.047495032777[/C][/ROW]
[ROW][C]0.28[/C][C]19590.1588190917[/C][C]706.843144836256[/C][/ROW]
[ROW][C]0.29[/C][C]19740.8373362615[/C][C]674.189668452417[/C][/ROW]
[ROW][C]0.3[/C][C]19883.0718288497[/C][C]634.84153320996[/C][/ROW]
[ROW][C]0.31[/C][C]20016.1023205576[/C][C]593.363458049867[/C][/ROW]
[ROW][C]0.32[/C][C]20140.0802936122[/C][C]554.413607721005[/C][/ROW]
[ROW][C]0.33[/C][C]20256.0262242551[/C][C]522.44622419904[/C][/ROW]
[ROW][C]0.34[/C][C]20365.6905812596[/C][C]501.018425199301[/C][/ROW]
[ROW][C]0.35[/C][C]20471.3457672076[/C][C]492.586598679035[/C][/ROW]
[ROW][C]0.36[/C][C]20575.5405216744[/C][C]497.998945571183[/C][/ROW]
[ROW][C]0.37[/C][C]20680.8472486265[/C][C]516.660005403973[/C][/ROW]
[ROW][C]0.38[/C][C]20789.6287501759[/C][C]546.559382382735[/C][/ROW]
[ROW][C]0.39[/C][C]20903.8459040491[/C][C]584.83233989841[/C][/ROW]
[ROW][C]0.4[/C][C]21024.9228704347[/C][C]628.161734145001[/C][/ROW]
[ROW][C]0.41[/C][C]21153.6812895159[/C][C]673.067298884795[/C][/ROW]
[ROW][C]0.42[/C][C]21290.348822439[/C][C]716.559149553166[/C][/ROW]
[ROW][C]0.43[/C][C]21434.6396145417[/C][C]756.168211618084[/C][/ROW]
[ROW][C]0.44[/C][C]21585.8949644821[/C][C]790.461520494279[/C][/ROW]
[ROW][C]0.45[/C][C]21743.2629403217[/C][C]819.057429950763[/C][/ROW]
[ROW][C]0.46[/C][C]21905.8880696665[/C][C]842.630185704833[/C][/ROW]
[ROW][C]0.47[/C][C]22073.0789310165[/C][C]862.756871035664[/C][/ROW]
[ROW][C]0.48[/C][C]22244.4241761087[/C][C]881.536083011005[/C][/ROW]
[ROW][C]0.49[/C][C]22419.836443803[/C][C]901.023750771632[/C][/ROW]
[ROW][C]0.5[/C][C]22599.5172455863[/C][C]922.866845673768[/C][/ROW]
[ROW][C]0.51[/C][C]22783.8512311165[/C][C]947.703812427113[/C][/ROW]
[ROW][C]0.52[/C][C]22973.2517265322[/C][C]975.092890143417[/C][/ROW]
[ROW][C]0.53[/C][C]23167.9880509887[/C][C]1003.63488852743[/C][/ROW]
[ROW][C]0.54[/C][C]23368.0272624001[/C][C]1030.99676565937[/C][/ROW]
[ROW][C]0.55[/C][C]23572.9188610679[/C][C]1054.52860902713[/C][/ROW]
[ROW][C]0.56[/C][C]23781.7422830205[/C][C]1071.53106038772[/C][/ROW]
[ROW][C]0.57[/C][C]23993.1261355006[/C][C]1079.70843939484[/C][/ROW]
[ROW][C]0.58[/C][C]24205.3372517343[/C][C]1077.39175475525[/C][/ROW]
[ROW][C]0.59[/C][C]24416.4281543565[/C][C]1063.97850028645[/C][/ROW]
[ROW][C]0.6[/C][C]24624.4239461391[/C][C]1039.67091680962[/C][/ROW]
[ROW][C]0.61[/C][C]24827.5241083358[/C][C]1005.87682175687[/C][/ROW]
[ROW][C]0.62[/C][C]25024.2914867097[/C][C]964.892962811923[/C][/ROW]
[ROW][C]0.63[/C][C]25213.800724007[/C][C]919.863086114323[/C][/ROW]
[ROW][C]0.64[/C][C]25395.722726933[/C][C]874.153117254796[/C][/ROW]
[ROW][C]0.65[/C][C]25570.3312042766[/C][C]831.127518248801[/C][/ROW]
[ROW][C]0.66[/C][C]25738.4313340689[/C][C]793.549499992728[/C][/ROW]
[ROW][C]0.67[/C][C]25901.2267852698[/C][C]763.271384505866[/C][/ROW]
[ROW][C]0.68[/C][C]26060.155550912[/C][C]740.91912096378[/C][/ROW]
[ROW][C]0.69[/C][C]26216.7327241442[/C][C]726.16732335836[/C][/ROW]
[ROW][C]0.7[/C][C]26372.4359923269[/C][C]717.973288977022[/C][/ROW]
[ROW][C]0.71[/C][C]26528.6565035238[/C][C]715.17121859969[/C][/ROW]
[ROW][C]0.72[/C][C]26686.7166681855[/C][C]717.073517505604[/C][/ROW]
[ROW][C]0.73[/C][C]26847.9332590426[/C][C]723.592265882953[/C][/ROW]
[ROW][C]0.74[/C][C]27013.6861516824[/C][C]735.204851695744[/C][/ROW]
[ROW][C]0.75[/C][C]27185.4466553497[/C][C]752.571243841262[/C][/ROW]
[ROW][C]0.76[/C][C]27364.7281612777[/C][C]775.962500554769[/C][/ROW]
[ROW][C]0.77[/C][C]27552.9452308366[/C][C]804.681728778841[/C][/ROW]
[ROW][C]0.78[/C][C]27751.2005023051[/C][C]836.745282653361[/C][/ROW]
[ROW][C]0.79[/C][C]27960.0536585472[/C][C]868.962546049662[/C][/ROW]
[ROW][C]0.8[/C][C]28179.3525209909[/C][C]897.429376305676[/C][/ROW]
[ROW][C]0.81[/C][C]28408.2115812307[/C][C]918.363835595574[/C][/ROW]
[ROW][C]0.82[/C][C]28645.1980402822[/C][C]929.14018253784[/C][/ROW]
[ROW][C]0.83[/C][C]28888.7256705581[/C][C]929.314811732119[/C][/ROW]
[ROW][C]0.84[/C][C]29137.5700947873[/C][C]921.108393972335[/C][/ROW]
[ROW][C]0.85[/C][C]29391.3293738718[/C][C]909.014323287727[/C][/ROW]
[ROW][C]0.86[/C][C]29650.6018002461[/C][C]898.408357701458[/C][/ROW]
[ROW][C]0.87[/C][C]29916.688373482[/C][C]892.887726720528[/C][/ROW]
[ROW][C]0.88[/C][C]30190.7937159821[/C][C]891.805574877198[/C][/ROW]
[ROW][C]0.89[/C][C]30473.0089491087[/C][C]889.082194773521[/C][/ROW]
[ROW][C]0.9[/C][C]30761.760841369[/C][C]875.28149731788[/C][/ROW]
[ROW][C]0.91[/C][C]31054.7292055613[/C][C]843.159571743312[/C][/ROW]
[ROW][C]0.92[/C][C]31352.1010448085[/C][C]795.862050009902[/C][/ROW]
[ROW][C]0.93[/C][C]31661.8868238[/C][C]755.561624832106[/C][/ROW]
[ROW][C]0.94[/C][C]32004.4522493969[/C][C]764.914286439574[/C][/ROW]
[ROW][C]0.95[/C][C]32410.0983861253[/C][C]857.883765901782[/C][/ROW]
[ROW][C]0.96[/C][C]32902.6086350202[/C][C]999.819804888438[/C][/ROW]
[ROW][C]0.97[/C][C]33468.7899833224[/C][C]1067.94928417664[/C][/ROW]
[ROW][C]0.98[/C][C]34032.063348922[/C][C]912.479952398685[/C][/ROW]
[ROW][C]0.99[/C][C]34465.751933602[/C][C]511.535529158207[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=207004&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=207004&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
0.019865.169616186511133.69645490713
0.0210695.27123491141399.18327141453
0.0311649.04447903611690.83157335809
0.0412614.47209549811846.25745353132
0.0513527.2491100221822.85949156042
0.0614341.29963359841662.44194790882
0.0715032.1516600691441.25416148816
0.0815599.13598591821224.74452029955
0.0916058.16914490131045.8379025508
0.116431.4431111546908.684441972562
0.1116739.9068035588804.116128752503
0.1217000.085772106722.195505813239
0.1317223.9905467077656.813305018367
0.1417420.3076397493605.18950576131
0.1517595.6783502812566.642951248735
0.1617755.6052593794541.479723607736
0.1717904.9495780462530.479773598828
0.1818048.1167064853533.915578322333
0.1918189.0315425181550.933693341845
0.218330.9883336295579.029288878539
0.2118476.4526202937614.340649865564
0.2218626.8869486346652.189448139045
0.2318782.6576203248687.600575164158
0.2418943.0568075622716.03689640365
0.2519106.4486592975733.757336603072
0.2619270.5248038848738.360449711972
0.2719432.6365086111729.047495032777
0.2819590.1588190917706.843144836256
0.2919740.8373362615674.189668452417
0.319883.0718288497634.84153320996
0.3120016.1023205576593.363458049867
0.3220140.0802936122554.413607721005
0.3320256.0262242551522.44622419904
0.3420365.6905812596501.018425199301
0.3520471.3457672076492.586598679035
0.3620575.5405216744497.998945571183
0.3720680.8472486265516.660005403973
0.3820789.6287501759546.559382382735
0.3920903.8459040491584.83233989841
0.421024.9228704347628.161734145001
0.4121153.6812895159673.067298884795
0.4221290.348822439716.559149553166
0.4321434.6396145417756.168211618084
0.4421585.8949644821790.461520494279
0.4521743.2629403217819.057429950763
0.4621905.8880696665842.630185704833
0.4722073.0789310165862.756871035664
0.4822244.4241761087881.536083011005
0.4922419.836443803901.023750771632
0.522599.5172455863922.866845673768
0.5122783.8512311165947.703812427113
0.5222973.2517265322975.092890143417
0.5323167.98805098871003.63488852743
0.5423368.02726240011030.99676565937
0.5523572.91886106791054.52860902713
0.5623781.74228302051071.53106038772
0.5723993.12613550061079.70843939484
0.5824205.33725173431077.39175475525
0.5924416.42815435651063.97850028645
0.624624.42394613911039.67091680962
0.6124827.52410833581005.87682175687
0.6225024.2914867097964.892962811923
0.6325213.800724007919.863086114323
0.6425395.722726933874.153117254796
0.6525570.3312042766831.127518248801
0.6625738.4313340689793.549499992728
0.6725901.2267852698763.271384505866
0.6826060.155550912740.91912096378
0.6926216.7327241442726.16732335836
0.726372.4359923269717.973288977022
0.7126528.6565035238715.17121859969
0.7226686.7166681855717.073517505604
0.7326847.9332590426723.592265882953
0.7427013.6861516824735.204851695744
0.7527185.4466553497752.571243841262
0.7627364.7281612777775.962500554769
0.7727552.9452308366804.681728778841
0.7827751.2005023051836.745282653361
0.7927960.0536585472868.962546049662
0.828179.3525209909897.429376305676
0.8128408.2115812307918.363835595574
0.8228645.1980402822929.14018253784
0.8328888.7256705581929.314811732119
0.8429137.5700947873921.108393972335
0.8529391.3293738718909.014323287727
0.8629650.6018002461898.408357701458
0.8729916.688373482892.887726720528
0.8830190.7937159821891.805574877198
0.8930473.0089491087889.082194773521
0.930761.760841369875.28149731788
0.9131054.7292055613843.159571743312
0.9231352.1010448085795.862050009902
0.9331661.8868238755.561624832106
0.9432004.4522493969764.914286439574
0.9532410.0983861253857.883765901782
0.9632902.6086350202999.819804888438
0.9733468.78998332241067.94928417664
0.9834032.063348922912.479952398685
0.9934465.751933602511.535529158207


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 <- '0.99'
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')