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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, 12 Aug 2009 05:14:40 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Aug/12/t1250075729g1uaebr6p2ku9dx.htm/, Retrieved Sun, 28 Apr 2024 05:26:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=42577, Retrieved Sun, 28 Apr 2024 05:26:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact266

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] [Harrel-Davis deci...] [2009-08-12 11:14:40] [768ad88abce8b6ce0be22cfe8ac9beaf] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
613,20
614,70
618,40
628,20
629,00
629,70
630,40
630,40
639,30
639,40
640,90
640,80
642,10
645,30
647,60
648,40
648,80
648,90
648,90
648,90
650,30
650,30
650,00
650,00
650,50
658,40
666,00
675,50
680,70
690,60
690,60
691,10
692,90
693,80
692,80
697,50
699,00
702,10
704,80
715,50
721,80
726,40
727,70
727,40
731,30
734,40
733,40
733,40
738,10
742,60
747,20
751,10
752,60
758,90
759,10
764,30
765,60
767,60
767,60
765,60
768,20
770,90
775,10
777,60
778,60
778,90
779,40
779,90
781,70
789,10
788,70
788,80
790,80
794,10
795,10
797,30
803,80
805,60
804,60
804,50
805,80
806,80
805,20
814,90
816,60
819,50
823,00
824,00
831,40
831,70
831,10
832,10
833,30
838,80
838,00
837,30
994,20
994,20
994,20
994,20
994,20
1092,60
1100,00
1100,00
1092,60
1000,70
1000,70
1000,50
1000,50
1000,50
1000,50
1000,50
1000,50
1087,70
1113,20
1116,00
1085,20
1031,30
1028,70
1027,50
1027,50
1027,50
1027,50
1027,50
1027,50
1152,20
1155,30
1154,00
1119,90
1079,30
1074,30
1069,80

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=42577&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=42577&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42577&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
0.01615.6243951376724.10151071277923
0.02620.3311288176516.14003860052541
0.03625.1444736329045.45386085165971
0.04628.9130522587544.53319998311044
0.05631.8835163981864.71289239432622
0.06634.5879508865775.17009137344141
0.07637.2026772473725.24208025315773
0.08639.6512985220524.96065481633674
0.09641.843999922214.55880292033824
0.1643.7574913613954.1447221227313
0.11645.4136596127733.74411781783688
0.12646.8642244659043.45796140581676
0.13648.2053374189163.52770008681596
0.14649.5926994538784.2279110333615
0.15651.231102309945.68018788419975
0.16653.3354916414337.79718503094194
0.17656.07697306232210.3217497706048
0.18659.53320114216212.8757711216007
0.19663.66180411542515.0493707229216
0.2668.30861427955116.5178403231628
0.21673.24998274655517.1471178017937
0.22678.25472647246217.0343644322036
0.23683.14317475517816.4587212460585
0.24687.82280366367215.7797315857988
0.25692.2908210300915.3068121668744
0.26696.60790398032615.1921741110551
0.27700.85747850774815.409801996002
0.28705.10769235033815.7943282706906
0.29709.38883710198616.1534707177862
0.3713.69063041531316.3382081852237
0.31717.97552482919216.2921775337314
0.32722.19915061191216.0529875736133
0.33726.3283310384915.7145386974530
0.34730.3501550759215.3831226210198
0.35734.27044836909915.1265893073751
0.36738.10445482151514.9517318179177
0.37741.86501850602414.8096100974521
0.38745.55351027098314.6267474788152
0.39749.1567144362114.3315402752856
0.4752.65005763271613.8902916536438
0.41756.00515429532213.3085114837985
0.42759.19846373966312.6329218508231
0.43762.21806973258911.9243377677938
0.44765.06681683629511.2582486225148
0.45767.76159203405210.6904609649418
0.46770.32977764096610.2524647878528
0.47772.8044465133679.96138071301756
0.48775.2197106953149.80742355696345
0.49777.6070485305329.77175913883244
0.5779.9928096015949.82874960313692
0.51782.3967284322359.94868688580157
0.52784.83125373559510.1006085878946
0.53787.30169927251510.2516469447061
0.54789.80741802096410.3823996521671
0.55792.3441971091410.4779959531358
0.56794.90780960586710.5434720489285
0.57797.49826437366510.6094941272968
0.58800.1240340404610.7150907590600
0.59802.80570857615610.9229886565334
0.6805.57926091690811.2987947987581
0.61808.50022294033111.9157148433619
0.62811.65091859924312.8869162905924
0.63815.1525380050414.3785377242639
0.64819.18142979330216.6431926956774
0.65823.98449238814420.0071089310174
0.66829.8833278252324.7874935918495
0.67837.25378651801631.1426396308659
0.68846.47021951017838.9134293173657
0.69857.81434856217547.5156634770033
0.7871.36561131999655.9307831495377
0.71886.90670435376362.8521041213557
0.72903.88527137357866.9835467898953
0.73921.4624933173367.4029714463313
0.74938.65152852211863.8725061644463
0.75954.51327696550456.9555845441106
0.76968.35026560715747.8869093329842
0.77979.83575785366538.2265121478415
0.78989.0378715697729.442968501756
0.79996.3378811064522.5780234280666
0.81002.2807671433818.0595011809478
0.811007.4186181736915.6660152833537
0.821012.2053232537414.7355158392134
0.831016.9744171281614.6350611227693
0.841021.9891732311015.1283628547626
0.851027.5118045265816.3519314390743
0.861033.8209984403318.4280428254329
0.871041.1350401906021.0249090269936
0.881049.4688385986823.2810919705584
0.891058.5259681946024.1801941819078
0.91067.7381299097523.123892753405
0.911076.4822082104120.3430901375890
0.921084.3756818905916.8520722278172
0.931091.4803886639413.9464319257167
0.941098.3157309654012.5362134428931
0.951105.7668816556712.8212442831843
0.961115.0097608052214.8265549309338
0.971127.0012530698117.8954102069044
0.981140.6097657444917.3095489254521
0.991151.280772943878.61909685058668

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 615.624395137672 & 4.10151071277923 \tabularnewline
0.02 & 620.331128817651 & 6.14003860052541 \tabularnewline
0.03 & 625.144473632904 & 5.45386085165971 \tabularnewline
0.04 & 628.913052258754 & 4.53319998311044 \tabularnewline
0.05 & 631.883516398186 & 4.71289239432622 \tabularnewline
0.06 & 634.587950886577 & 5.17009137344141 \tabularnewline
0.07 & 637.202677247372 & 5.24208025315773 \tabularnewline
0.08 & 639.651298522052 & 4.96065481633674 \tabularnewline
0.09 & 641.84399992221 & 4.55880292033824 \tabularnewline
0.1 & 643.757491361395 & 4.1447221227313 \tabularnewline
0.11 & 645.413659612773 & 3.74411781783688 \tabularnewline
0.12 & 646.864224465904 & 3.45796140581676 \tabularnewline
0.13 & 648.205337418916 & 3.52770008681596 \tabularnewline
0.14 & 649.592699453878 & 4.2279110333615 \tabularnewline
0.15 & 651.23110230994 & 5.68018788419975 \tabularnewline
0.16 & 653.335491641433 & 7.79718503094194 \tabularnewline
0.17 & 656.076973062322 & 10.3217497706048 \tabularnewline
0.18 & 659.533201142162 & 12.8757711216007 \tabularnewline
0.19 & 663.661804115425 & 15.0493707229216 \tabularnewline
0.2 & 668.308614279551 & 16.5178403231628 \tabularnewline
0.21 & 673.249982746555 & 17.1471178017937 \tabularnewline
0.22 & 678.254726472462 & 17.0343644322036 \tabularnewline
0.23 & 683.143174755178 & 16.4587212460585 \tabularnewline
0.24 & 687.822803663672 & 15.7797315857988 \tabularnewline
0.25 & 692.29082103009 & 15.3068121668744 \tabularnewline
0.26 & 696.607903980326 & 15.1921741110551 \tabularnewline
0.27 & 700.857478507748 & 15.409801996002 \tabularnewline
0.28 & 705.107692350338 & 15.7943282706906 \tabularnewline
0.29 & 709.388837101986 & 16.1534707177862 \tabularnewline
0.3 & 713.690630415313 & 16.3382081852237 \tabularnewline
0.31 & 717.975524829192 & 16.2921775337314 \tabularnewline
0.32 & 722.199150611912 & 16.0529875736133 \tabularnewline
0.33 & 726.32833103849 & 15.7145386974530 \tabularnewline
0.34 & 730.35015507592 & 15.3831226210198 \tabularnewline
0.35 & 734.270448369099 & 15.1265893073751 \tabularnewline
0.36 & 738.104454821515 & 14.9517318179177 \tabularnewline
0.37 & 741.865018506024 & 14.8096100974521 \tabularnewline
0.38 & 745.553510270983 & 14.6267474788152 \tabularnewline
0.39 & 749.15671443621 & 14.3315402752856 \tabularnewline
0.4 & 752.650057632716 & 13.8902916536438 \tabularnewline
0.41 & 756.005154295322 & 13.3085114837985 \tabularnewline
0.42 & 759.198463739663 & 12.6329218508231 \tabularnewline
0.43 & 762.218069732589 & 11.9243377677938 \tabularnewline
0.44 & 765.066816836295 & 11.2582486225148 \tabularnewline
0.45 & 767.761592034052 & 10.6904609649418 \tabularnewline
0.46 & 770.329777640966 & 10.2524647878528 \tabularnewline
0.47 & 772.804446513367 & 9.96138071301756 \tabularnewline
0.48 & 775.219710695314 & 9.80742355696345 \tabularnewline
0.49 & 777.607048530532 & 9.77175913883244 \tabularnewline
0.5 & 779.992809601594 & 9.82874960313692 \tabularnewline
0.51 & 782.396728432235 & 9.94868688580157 \tabularnewline
0.52 & 784.831253735595 & 10.1006085878946 \tabularnewline
0.53 & 787.301699272515 & 10.2516469447061 \tabularnewline
0.54 & 789.807418020964 & 10.3823996521671 \tabularnewline
0.55 & 792.34419710914 & 10.4779959531358 \tabularnewline
0.56 & 794.907809605867 & 10.5434720489285 \tabularnewline
0.57 & 797.498264373665 & 10.6094941272968 \tabularnewline
0.58 & 800.12403404046 & 10.7150907590600 \tabularnewline
0.59 & 802.805708576156 & 10.9229886565334 \tabularnewline
0.6 & 805.579260916908 & 11.2987947987581 \tabularnewline
0.61 & 808.500222940331 & 11.9157148433619 \tabularnewline
0.62 & 811.650918599243 & 12.8869162905924 \tabularnewline
0.63 & 815.15253800504 & 14.3785377242639 \tabularnewline
0.64 & 819.181429793302 & 16.6431926956774 \tabularnewline
0.65 & 823.984492388144 & 20.0071089310174 \tabularnewline
0.66 & 829.88332782523 & 24.7874935918495 \tabularnewline
0.67 & 837.253786518016 & 31.1426396308659 \tabularnewline
0.68 & 846.470219510178 & 38.9134293173657 \tabularnewline
0.69 & 857.814348562175 & 47.5156634770033 \tabularnewline
0.7 & 871.365611319996 & 55.9307831495377 \tabularnewline
0.71 & 886.906704353763 & 62.8521041213557 \tabularnewline
0.72 & 903.885271373578 & 66.9835467898953 \tabularnewline
0.73 & 921.46249331733 & 67.4029714463313 \tabularnewline
0.74 & 938.651528522118 & 63.8725061644463 \tabularnewline
0.75 & 954.513276965504 & 56.9555845441106 \tabularnewline
0.76 & 968.350265607157 & 47.8869093329842 \tabularnewline
0.77 & 979.835757853665 & 38.2265121478415 \tabularnewline
0.78 & 989.03787156977 & 29.442968501756 \tabularnewline
0.79 & 996.33788110645 & 22.5780234280666 \tabularnewline
0.8 & 1002.28076714338 & 18.0595011809478 \tabularnewline
0.81 & 1007.41861817369 & 15.6660152833537 \tabularnewline
0.82 & 1012.20532325374 & 14.7355158392134 \tabularnewline
0.83 & 1016.97441712816 & 14.6350611227693 \tabularnewline
0.84 & 1021.98917323110 & 15.1283628547626 \tabularnewline
0.85 & 1027.51180452658 & 16.3519314390743 \tabularnewline
0.86 & 1033.82099844033 & 18.4280428254329 \tabularnewline
0.87 & 1041.13504019060 & 21.0249090269936 \tabularnewline
0.88 & 1049.46883859868 & 23.2810919705584 \tabularnewline
0.89 & 1058.52596819460 & 24.1801941819078 \tabularnewline
0.9 & 1067.73812990975 & 23.123892753405 \tabularnewline
0.91 & 1076.48220821041 & 20.3430901375890 \tabularnewline
0.92 & 1084.37568189059 & 16.8520722278172 \tabularnewline
0.93 & 1091.48038866394 & 13.9464319257167 \tabularnewline
0.94 & 1098.31573096540 & 12.5362134428931 \tabularnewline
0.95 & 1105.76688165567 & 12.8212442831843 \tabularnewline
0.96 & 1115.00976080522 & 14.8265549309338 \tabularnewline
0.97 & 1127.00125306981 & 17.8954102069044 \tabularnewline
0.98 & 1140.60976574449 & 17.3095489254521 \tabularnewline
0.99 & 1151.28077294387 & 8.61909685058668 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42577&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]615.624395137672[/C][C]4.10151071277923[/C][/ROW]
[ROW][C]0.02[/C][C]620.331128817651[/C][C]6.14003860052541[/C][/ROW]
[ROW][C]0.03[/C][C]625.144473632904[/C][C]5.45386085165971[/C][/ROW]
[ROW][C]0.04[/C][C]628.913052258754[/C][C]4.53319998311044[/C][/ROW]
[ROW][C]0.05[/C][C]631.883516398186[/C][C]4.71289239432622[/C][/ROW]
[ROW][C]0.06[/C][C]634.587950886577[/C][C]5.17009137344141[/C][/ROW]
[ROW][C]0.07[/C][C]637.202677247372[/C][C]5.24208025315773[/C][/ROW]
[ROW][C]0.08[/C][C]639.651298522052[/C][C]4.96065481633674[/C][/ROW]
[ROW][C]0.09[/C][C]641.84399992221[/C][C]4.55880292033824[/C][/ROW]
[ROW][C]0.1[/C][C]643.757491361395[/C][C]4.1447221227313[/C][/ROW]
[ROW][C]0.11[/C][C]645.413659612773[/C][C]3.74411781783688[/C][/ROW]
[ROW][C]0.12[/C][C]646.864224465904[/C][C]3.45796140581676[/C][/ROW]
[ROW][C]0.13[/C][C]648.205337418916[/C][C]3.52770008681596[/C][/ROW]
[ROW][C]0.14[/C][C]649.592699453878[/C][C]4.2279110333615[/C][/ROW]
[ROW][C]0.15[/C][C]651.23110230994[/C][C]5.68018788419975[/C][/ROW]
[ROW][C]0.16[/C][C]653.335491641433[/C][C]7.79718503094194[/C][/ROW]
[ROW][C]0.17[/C][C]656.076973062322[/C][C]10.3217497706048[/C][/ROW]
[ROW][C]0.18[/C][C]659.533201142162[/C][C]12.8757711216007[/C][/ROW]
[ROW][C]0.19[/C][C]663.661804115425[/C][C]15.0493707229216[/C][/ROW]
[ROW][C]0.2[/C][C]668.308614279551[/C][C]16.5178403231628[/C][/ROW]
[ROW][C]0.21[/C][C]673.249982746555[/C][C]17.1471178017937[/C][/ROW]
[ROW][C]0.22[/C][C]678.254726472462[/C][C]17.0343644322036[/C][/ROW]
[ROW][C]0.23[/C][C]683.143174755178[/C][C]16.4587212460585[/C][/ROW]
[ROW][C]0.24[/C][C]687.822803663672[/C][C]15.7797315857988[/C][/ROW]
[ROW][C]0.25[/C][C]692.29082103009[/C][C]15.3068121668744[/C][/ROW]
[ROW][C]0.26[/C][C]696.607903980326[/C][C]15.1921741110551[/C][/ROW]
[ROW][C]0.27[/C][C]700.857478507748[/C][C]15.409801996002[/C][/ROW]
[ROW][C]0.28[/C][C]705.107692350338[/C][C]15.7943282706906[/C][/ROW]
[ROW][C]0.29[/C][C]709.388837101986[/C][C]16.1534707177862[/C][/ROW]
[ROW][C]0.3[/C][C]713.690630415313[/C][C]16.3382081852237[/C][/ROW]
[ROW][C]0.31[/C][C]717.975524829192[/C][C]16.2921775337314[/C][/ROW]
[ROW][C]0.32[/C][C]722.199150611912[/C][C]16.0529875736133[/C][/ROW]
[ROW][C]0.33[/C][C]726.32833103849[/C][C]15.7145386974530[/C][/ROW]
[ROW][C]0.34[/C][C]730.35015507592[/C][C]15.3831226210198[/C][/ROW]
[ROW][C]0.35[/C][C]734.270448369099[/C][C]15.1265893073751[/C][/ROW]
[ROW][C]0.36[/C][C]738.104454821515[/C][C]14.9517318179177[/C][/ROW]
[ROW][C]0.37[/C][C]741.865018506024[/C][C]14.8096100974521[/C][/ROW]
[ROW][C]0.38[/C][C]745.553510270983[/C][C]14.6267474788152[/C][/ROW]
[ROW][C]0.39[/C][C]749.15671443621[/C][C]14.3315402752856[/C][/ROW]
[ROW][C]0.4[/C][C]752.650057632716[/C][C]13.8902916536438[/C][/ROW]
[ROW][C]0.41[/C][C]756.005154295322[/C][C]13.3085114837985[/C][/ROW]
[ROW][C]0.42[/C][C]759.198463739663[/C][C]12.6329218508231[/C][/ROW]
[ROW][C]0.43[/C][C]762.218069732589[/C][C]11.9243377677938[/C][/ROW]
[ROW][C]0.44[/C][C]765.066816836295[/C][C]11.2582486225148[/C][/ROW]
[ROW][C]0.45[/C][C]767.761592034052[/C][C]10.6904609649418[/C][/ROW]
[ROW][C]0.46[/C][C]770.329777640966[/C][C]10.2524647878528[/C][/ROW]
[ROW][C]0.47[/C][C]772.804446513367[/C][C]9.96138071301756[/C][/ROW]
[ROW][C]0.48[/C][C]775.219710695314[/C][C]9.80742355696345[/C][/ROW]
[ROW][C]0.49[/C][C]777.607048530532[/C][C]9.77175913883244[/C][/ROW]
[ROW][C]0.5[/C][C]779.992809601594[/C][C]9.82874960313692[/C][/ROW]
[ROW][C]0.51[/C][C]782.396728432235[/C][C]9.94868688580157[/C][/ROW]
[ROW][C]0.52[/C][C]784.831253735595[/C][C]10.1006085878946[/C][/ROW]
[ROW][C]0.53[/C][C]787.301699272515[/C][C]10.2516469447061[/C][/ROW]
[ROW][C]0.54[/C][C]789.807418020964[/C][C]10.3823996521671[/C][/ROW]
[ROW][C]0.55[/C][C]792.34419710914[/C][C]10.4779959531358[/C][/ROW]
[ROW][C]0.56[/C][C]794.907809605867[/C][C]10.5434720489285[/C][/ROW]
[ROW][C]0.57[/C][C]797.498264373665[/C][C]10.6094941272968[/C][/ROW]
[ROW][C]0.58[/C][C]800.12403404046[/C][C]10.7150907590600[/C][/ROW]
[ROW][C]0.59[/C][C]802.805708576156[/C][C]10.9229886565334[/C][/ROW]
[ROW][C]0.6[/C][C]805.579260916908[/C][C]11.2987947987581[/C][/ROW]
[ROW][C]0.61[/C][C]808.500222940331[/C][C]11.9157148433619[/C][/ROW]
[ROW][C]0.62[/C][C]811.650918599243[/C][C]12.8869162905924[/C][/ROW]
[ROW][C]0.63[/C][C]815.15253800504[/C][C]14.3785377242639[/C][/ROW]
[ROW][C]0.64[/C][C]819.181429793302[/C][C]16.6431926956774[/C][/ROW]
[ROW][C]0.65[/C][C]823.984492388144[/C][C]20.0071089310174[/C][/ROW]
[ROW][C]0.66[/C][C]829.88332782523[/C][C]24.7874935918495[/C][/ROW]
[ROW][C]0.67[/C][C]837.253786518016[/C][C]31.1426396308659[/C][/ROW]
[ROW][C]0.68[/C][C]846.470219510178[/C][C]38.9134293173657[/C][/ROW]
[ROW][C]0.69[/C][C]857.814348562175[/C][C]47.5156634770033[/C][/ROW]
[ROW][C]0.7[/C][C]871.365611319996[/C][C]55.9307831495377[/C][/ROW]
[ROW][C]0.71[/C][C]886.906704353763[/C][C]62.8521041213557[/C][/ROW]
[ROW][C]0.72[/C][C]903.885271373578[/C][C]66.9835467898953[/C][/ROW]
[ROW][C]0.73[/C][C]921.46249331733[/C][C]67.4029714463313[/C][/ROW]
[ROW][C]0.74[/C][C]938.651528522118[/C][C]63.8725061644463[/C][/ROW]
[ROW][C]0.75[/C][C]954.513276965504[/C][C]56.9555845441106[/C][/ROW]
[ROW][C]0.76[/C][C]968.350265607157[/C][C]47.8869093329842[/C][/ROW]
[ROW][C]0.77[/C][C]979.835757853665[/C][C]38.2265121478415[/C][/ROW]
[ROW][C]0.78[/C][C]989.03787156977[/C][C]29.442968501756[/C][/ROW]
[ROW][C]0.79[/C][C]996.33788110645[/C][C]22.5780234280666[/C][/ROW]
[ROW][C]0.8[/C][C]1002.28076714338[/C][C]18.0595011809478[/C][/ROW]
[ROW][C]0.81[/C][C]1007.41861817369[/C][C]15.6660152833537[/C][/ROW]
[ROW][C]0.82[/C][C]1012.20532325374[/C][C]14.7355158392134[/C][/ROW]
[ROW][C]0.83[/C][C]1016.97441712816[/C][C]14.6350611227693[/C][/ROW]
[ROW][C]0.84[/C][C]1021.98917323110[/C][C]15.1283628547626[/C][/ROW]
[ROW][C]0.85[/C][C]1027.51180452658[/C][C]16.3519314390743[/C][/ROW]
[ROW][C]0.86[/C][C]1033.82099844033[/C][C]18.4280428254329[/C][/ROW]
[ROW][C]0.87[/C][C]1041.13504019060[/C][C]21.0249090269936[/C][/ROW]
[ROW][C]0.88[/C][C]1049.46883859868[/C][C]23.2810919705584[/C][/ROW]
[ROW][C]0.89[/C][C]1058.52596819460[/C][C]24.1801941819078[/C][/ROW]
[ROW][C]0.9[/C][C]1067.73812990975[/C][C]23.123892753405[/C][/ROW]
[ROW][C]0.91[/C][C]1076.48220821041[/C][C]20.3430901375890[/C][/ROW]
[ROW][C]0.92[/C][C]1084.37568189059[/C][C]16.8520722278172[/C][/ROW]
[ROW][C]0.93[/C][C]1091.48038866394[/C][C]13.9464319257167[/C][/ROW]
[ROW][C]0.94[/C][C]1098.31573096540[/C][C]12.5362134428931[/C][/ROW]
[ROW][C]0.95[/C][C]1105.76688165567[/C][C]12.8212442831843[/C][/ROW]
[ROW][C]0.96[/C][C]1115.00976080522[/C][C]14.8265549309338[/C][/ROW]
[ROW][C]0.97[/C][C]1127.00125306981[/C][C]17.8954102069044[/C][/ROW]
[ROW][C]0.98[/C][C]1140.60976574449[/C][C]17.3095489254521[/C][/ROW]
[ROW][C]0.99[/C][C]1151.28077294387[/C][C]8.61909685058668[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42577&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42577&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
0.01615.6243951376724.10151071277923
0.02620.3311288176516.14003860052541
0.03625.1444736329045.45386085165971
0.04628.9130522587544.53319998311044
0.05631.8835163981864.71289239432622
0.06634.5879508865775.17009137344141
0.07637.2026772473725.24208025315773
0.08639.6512985220524.96065481633674
0.09641.843999922214.55880292033824
0.1643.7574913613954.1447221227313
0.11645.4136596127733.74411781783688
0.12646.8642244659043.45796140581676
0.13648.2053374189163.52770008681596
0.14649.5926994538784.2279110333615
0.15651.231102309945.68018788419975
0.16653.3354916414337.79718503094194
0.17656.07697306232210.3217497706048
0.18659.53320114216212.8757711216007
0.19663.66180411542515.0493707229216
0.2668.30861427955116.5178403231628
0.21673.24998274655517.1471178017937
0.22678.25472647246217.0343644322036
0.23683.14317475517816.4587212460585
0.24687.82280366367215.7797315857988
0.25692.2908210300915.3068121668744
0.26696.60790398032615.1921741110551
0.27700.85747850774815.409801996002
0.28705.10769235033815.7943282706906
0.29709.38883710198616.1534707177862
0.3713.69063041531316.3382081852237
0.31717.97552482919216.2921775337314
0.32722.19915061191216.0529875736133
0.33726.3283310384915.7145386974530
0.34730.3501550759215.3831226210198
0.35734.27044836909915.1265893073751
0.36738.10445482151514.9517318179177
0.37741.86501850602414.8096100974521
0.38745.55351027098314.6267474788152
0.39749.1567144362114.3315402752856
0.4752.65005763271613.8902916536438
0.41756.00515429532213.3085114837985
0.42759.19846373966312.6329218508231
0.43762.21806973258911.9243377677938
0.44765.06681683629511.2582486225148
0.45767.76159203405210.6904609649418
0.46770.32977764096610.2524647878528
0.47772.8044465133679.96138071301756
0.48775.2197106953149.80742355696345
0.49777.6070485305329.77175913883244
0.5779.9928096015949.82874960313692
0.51782.3967284322359.94868688580157
0.52784.83125373559510.1006085878946
0.53787.30169927251510.2516469447061
0.54789.80741802096410.3823996521671
0.55792.3441971091410.4779959531358
0.56794.90780960586710.5434720489285
0.57797.49826437366510.6094941272968
0.58800.1240340404610.7150907590600
0.59802.80570857615610.9229886565334
0.6805.57926091690811.2987947987581
0.61808.50022294033111.9157148433619
0.62811.65091859924312.8869162905924
0.63815.1525380050414.3785377242639
0.64819.18142979330216.6431926956774
0.65823.98449238814420.0071089310174
0.66829.8833278252324.7874935918495
0.67837.25378651801631.1426396308659
0.68846.47021951017838.9134293173657
0.69857.81434856217547.5156634770033
0.7871.36561131999655.9307831495377
0.71886.90670435376362.8521041213557
0.72903.88527137357866.9835467898953
0.73921.4624933173367.4029714463313
0.74938.65152852211863.8725061644463
0.75954.51327696550456.9555845441106
0.76968.35026560715747.8869093329842
0.77979.83575785366538.2265121478415
0.78989.0378715697729.442968501756
0.79996.3378811064522.5780234280666
0.81002.2807671433818.0595011809478
0.811007.4186181736915.6660152833537
0.821012.2053232537414.7355158392134
0.831016.9744171281614.6350611227693
0.841021.9891732311015.1283628547626
0.851027.5118045265816.3519314390743
0.861033.8209984403318.4280428254329
0.871041.1350401906021.0249090269936
0.881049.4688385986823.2810919705584
0.891058.5259681946024.1801941819078
0.91067.7381299097523.123892753405
0.911076.4822082104120.3430901375890
0.921084.3756818905916.8520722278172
0.931091.4803886639413.9464319257167
0.941098.3157309654012.5362134428931
0.951105.7668816556712.8212442831843
0.961115.0097608052214.8265549309338
0.971127.0012530698117.8954102069044
0.981140.6097657444917.3095489254521
0.991151.280772943878.61909685058668


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')