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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationSat, 07 Mar 2009 08:45:32 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Mar/07/t12364408925c3tizt3a2uhywt.htm/, Retrieved Sat, 27 Apr 2024 21:08:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=38646, Retrieved Sat, 27 Apr 2024 21:08:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact223

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] [Anke Winckelmans ...] [2009-03-07 15:45:32] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3779,7
3795,5
3813,1
3826,9
3833,3
3844,8
3851,3
3851,8
3854,1
3858,4
3861,6
3856,3
3855,8
3860,4
3855,1
3839,5
3833
3833,6
3826,8
3818,2
3811,4
3806,8
3810,3
3818,2
3858,9
3867,8
3872,3
3873,3
3876,7
3882,6
3883,5
3882,2
3888,1
3893,7
3901,9
3914,3
3930,3
3948,3
3971,5
3990,1
3993
3998
4015,8
4041,2
4060,7
4076,7
4103
4125,3
4139,7
4146,7
4158
4155,1
4144,8
4148,2
4142,5
4142,1
4145,4
4146,3
4143,5
4149,2
4158,9
4166,1
4179,1
4194,4
4211,7
4226,3
4235,8
4243,6
4258,7
4278,2
4298
4315,1
4334,3
4356
4374
4395,5

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'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=38646&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=38646&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=38646&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Harrell-Davis Quantiles
quantilesvaluestandard error
0.013784.9952322978813.8819953719039
0.023792.5049803255411.5597702836022
0.033799.394848224259.24381583974927
0.043804.670013570347.28956171211464
0.053808.531146919116.09733226121203
0.063811.502321550545.79000599839729
0.073814.035847819276.11379659662442
0.083816.420467181876.7045736467684
0.093818.80070215317.31849296294953
0.13821.224473458537.83201497361356
0.113823.688955001158.21910163478837
0.123826.173895294078.50475371658174
0.133828.66036316918.74946711036183
0.143831.137218134498.97617859666043
0.153833.599373893099.2096188786722
0.163836.042262732529.41042439223765
0.173838.45636264969.53275008671599
0.183840.824428349969.52477846386347
0.193843.122455396309.35370396470893
0.23845.323856488549.02359616403804
0.213847.405283420968.56286674928636
0.223849.352212851188.04153429241849
0.233851.162763571587.53067407871205
0.243852.848952993777.09911259303678
0.253854.435401260586.826911985831
0.263855.956102074616.74829039949393
0.273857.450189778946.87261103754311
0.283858.957659734947.19928614506239
0.293860.515832748847.69718968326917
0.33862.157095413148.32078093374191
0.313863.908171803829.04945365534227
0.323865.790926775979.85141483835165
0.333867.8244797207410.7316181761941
0.343870.028223549811.7004845449463
0.353872.4252042628912.8006604376938
0.363875.045237175114.0887267046354
0.373877.9271360861415.6236814262273
0.383881.1195261060517.4763839813903
0.393884.6799010796719.688720758132
0.43888.6718555119022.2867194858100
0.413893.1607320051325.2565197779651
0.423898.2082263093928.5521919341857
0.433903.866723615932.0966128981010
0.443910.1742462739735.7846372891041
0.453917.1508364532939.5002883348703
0.463924.7969685189143.1216264612603
0.473933.0942133946146.5589740017563
0.483942.0079269081449.7152418192293
0.493951.4913001148952.5581389102238
0.53961.4897950769155.0638500371534
0.513971.944881698557.2364346302888
0.523982.7961361299659.0887045675175
0.533993.9811467507160.6253691699487
0.544005.4332259622261.8225686375305
0.554017.0775228012962.6261131221057
0.564028.8266300834262.9599820574059
0.574040.5770526036262.7172934310052
0.584052.2078702001961.7909428170898
0.594063.5825817432760.0973419187875
0.64074.5545187093157.5826331388876
0.614084.9754961180354.2648053890967
0.624094.7066820728350.211932270619
0.634103.6301674820145.5701150675699
0.644111.6595161969340.5275796951312
0.654118.7477171895935.3127768143817
0.664124.8914119258130.1605729378590
0.674130.130930672325.3069196741721
0.684134.5463961660820.9378056049311
0.694138.2507874697917.2139087173452
0.74141.3812720066714.2410507548084
0.714144.0902328398212.0921309296465
0.724146.5372289900810.7908218085138
0.734148.8826795705110.3398194271410
0.744151.2834593394910.6765308821020
0.754153.889970511511.7133201182095
0.764156.8437678877913.350280693612
0.774160.2746138206415.4886172041714
0.784164.2960459136618.026731483943
0.794168.9991961560120.8282874805966
0.84174.4456171014123.7323667187252
0.814180.660989295426.5533364636963
0.824187.6323823919529.1020254324616
0.834195.3117292065231.207183707339
0.844203.6269782283432.7730629702555
0.854212.5000197313933.7966059733828
0.864221.867518358534.374084448831
0.874231.6984063437834.6872729289879
0.884242.0014265403834.930232516373
0.894252.8187358787735.2298511989021
0.94264.2068305137635.5770886501194
0.914276.2117457789235.8378686833117
0.924288.848214982335.8011708784308
0.934302.0899075939835.2821544609265
0.944315.8720774493434.163005568404
0.954330.1056944076632.3678360956639
0.964344.7011886702429.8201026783547
0.974359.5539309102826.5328670809640
0.984374.274500876123.0810301042017
0.994387.3569984214421.0804710468288

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 3784.99523229788 & 13.8819953719039 \tabularnewline
0.02 & 3792.50498032554 & 11.5597702836022 \tabularnewline
0.03 & 3799.39484822425 & 9.24381583974927 \tabularnewline
0.04 & 3804.67001357034 & 7.28956171211464 \tabularnewline
0.05 & 3808.53114691911 & 6.09733226121203 \tabularnewline
0.06 & 3811.50232155054 & 5.79000599839729 \tabularnewline
0.07 & 3814.03584781927 & 6.11379659662442 \tabularnewline
0.08 & 3816.42046718187 & 6.7045736467684 \tabularnewline
0.09 & 3818.8007021531 & 7.31849296294953 \tabularnewline
0.1 & 3821.22447345853 & 7.83201497361356 \tabularnewline
0.11 & 3823.68895500115 & 8.21910163478837 \tabularnewline
0.12 & 3826.17389529407 & 8.50475371658174 \tabularnewline
0.13 & 3828.6603631691 & 8.74946711036183 \tabularnewline
0.14 & 3831.13721813449 & 8.97617859666043 \tabularnewline
0.15 & 3833.59937389309 & 9.2096188786722 \tabularnewline
0.16 & 3836.04226273252 & 9.41042439223765 \tabularnewline
0.17 & 3838.4563626496 & 9.53275008671599 \tabularnewline
0.18 & 3840.82442834996 & 9.52477846386347 \tabularnewline
0.19 & 3843.12245539630 & 9.35370396470893 \tabularnewline
0.2 & 3845.32385648854 & 9.02359616403804 \tabularnewline
0.21 & 3847.40528342096 & 8.56286674928636 \tabularnewline
0.22 & 3849.35221285118 & 8.04153429241849 \tabularnewline
0.23 & 3851.16276357158 & 7.53067407871205 \tabularnewline
0.24 & 3852.84895299377 & 7.09911259303678 \tabularnewline
0.25 & 3854.43540126058 & 6.826911985831 \tabularnewline
0.26 & 3855.95610207461 & 6.74829039949393 \tabularnewline
0.27 & 3857.45018977894 & 6.87261103754311 \tabularnewline
0.28 & 3858.95765973494 & 7.19928614506239 \tabularnewline
0.29 & 3860.51583274884 & 7.69718968326917 \tabularnewline
0.3 & 3862.15709541314 & 8.32078093374191 \tabularnewline
0.31 & 3863.90817180382 & 9.04945365534227 \tabularnewline
0.32 & 3865.79092677597 & 9.85141483835165 \tabularnewline
0.33 & 3867.82447972074 & 10.7316181761941 \tabularnewline
0.34 & 3870.0282235498 & 11.7004845449463 \tabularnewline
0.35 & 3872.42520426289 & 12.8006604376938 \tabularnewline
0.36 & 3875.0452371751 & 14.0887267046354 \tabularnewline
0.37 & 3877.92713608614 & 15.6236814262273 \tabularnewline
0.38 & 3881.11952610605 & 17.4763839813903 \tabularnewline
0.39 & 3884.67990107967 & 19.688720758132 \tabularnewline
0.4 & 3888.67185551190 & 22.2867194858100 \tabularnewline
0.41 & 3893.16073200513 & 25.2565197779651 \tabularnewline
0.42 & 3898.20822630939 & 28.5521919341857 \tabularnewline
0.43 & 3903.8667236159 & 32.0966128981010 \tabularnewline
0.44 & 3910.17424627397 & 35.7846372891041 \tabularnewline
0.45 & 3917.15083645329 & 39.5002883348703 \tabularnewline
0.46 & 3924.79696851891 & 43.1216264612603 \tabularnewline
0.47 & 3933.09421339461 & 46.5589740017563 \tabularnewline
0.48 & 3942.00792690814 & 49.7152418192293 \tabularnewline
0.49 & 3951.49130011489 & 52.5581389102238 \tabularnewline
0.5 & 3961.48979507691 & 55.0638500371534 \tabularnewline
0.51 & 3971.9448816985 & 57.2364346302888 \tabularnewline
0.52 & 3982.79613612996 & 59.0887045675175 \tabularnewline
0.53 & 3993.98114675071 & 60.6253691699487 \tabularnewline
0.54 & 4005.43322596222 & 61.8225686375305 \tabularnewline
0.55 & 4017.07752280129 & 62.6261131221057 \tabularnewline
0.56 & 4028.82663008342 & 62.9599820574059 \tabularnewline
0.57 & 4040.57705260362 & 62.7172934310052 \tabularnewline
0.58 & 4052.20787020019 & 61.7909428170898 \tabularnewline
0.59 & 4063.58258174327 & 60.0973419187875 \tabularnewline
0.6 & 4074.55451870931 & 57.5826331388876 \tabularnewline
0.61 & 4084.97549611803 & 54.2648053890967 \tabularnewline
0.62 & 4094.70668207283 & 50.211932270619 \tabularnewline
0.63 & 4103.63016748201 & 45.5701150675699 \tabularnewline
0.64 & 4111.65951619693 & 40.5275796951312 \tabularnewline
0.65 & 4118.74771718959 & 35.3127768143817 \tabularnewline
0.66 & 4124.89141192581 & 30.1605729378590 \tabularnewline
0.67 & 4130.1309306723 & 25.3069196741721 \tabularnewline
0.68 & 4134.54639616608 & 20.9378056049311 \tabularnewline
0.69 & 4138.25078746979 & 17.2139087173452 \tabularnewline
0.7 & 4141.38127200667 & 14.2410507548084 \tabularnewline
0.71 & 4144.09023283982 & 12.0921309296465 \tabularnewline
0.72 & 4146.53722899008 & 10.7908218085138 \tabularnewline
0.73 & 4148.88267957051 & 10.3398194271410 \tabularnewline
0.74 & 4151.28345933949 & 10.6765308821020 \tabularnewline
0.75 & 4153.8899705115 & 11.7133201182095 \tabularnewline
0.76 & 4156.84376788779 & 13.350280693612 \tabularnewline
0.77 & 4160.27461382064 & 15.4886172041714 \tabularnewline
0.78 & 4164.29604591366 & 18.026731483943 \tabularnewline
0.79 & 4168.99919615601 & 20.8282874805966 \tabularnewline
0.8 & 4174.44561710141 & 23.7323667187252 \tabularnewline
0.81 & 4180.6609892954 & 26.5533364636963 \tabularnewline
0.82 & 4187.63238239195 & 29.1020254324616 \tabularnewline
0.83 & 4195.31172920652 & 31.207183707339 \tabularnewline
0.84 & 4203.62697822834 & 32.7730629702555 \tabularnewline
0.85 & 4212.50001973139 & 33.7966059733828 \tabularnewline
0.86 & 4221.8675183585 & 34.374084448831 \tabularnewline
0.87 & 4231.69840634378 & 34.6872729289879 \tabularnewline
0.88 & 4242.00142654038 & 34.930232516373 \tabularnewline
0.89 & 4252.81873587877 & 35.2298511989021 \tabularnewline
0.9 & 4264.20683051376 & 35.5770886501194 \tabularnewline
0.91 & 4276.21174577892 & 35.8378686833117 \tabularnewline
0.92 & 4288.8482149823 & 35.8011708784308 \tabularnewline
0.93 & 4302.08990759398 & 35.2821544609265 \tabularnewline
0.94 & 4315.87207744934 & 34.163005568404 \tabularnewline
0.95 & 4330.10569440766 & 32.3678360956639 \tabularnewline
0.96 & 4344.70118867024 & 29.8201026783547 \tabularnewline
0.97 & 4359.55393091028 & 26.5328670809640 \tabularnewline
0.98 & 4374.2745008761 & 23.0810301042017 \tabularnewline
0.99 & 4387.35699842144 & 21.0804710468288 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=38646&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]3784.99523229788[/C][C]13.8819953719039[/C][/ROW]
[ROW][C]0.02[/C][C]3792.50498032554[/C][C]11.5597702836022[/C][/ROW]
[ROW][C]0.03[/C][C]3799.39484822425[/C][C]9.24381583974927[/C][/ROW]
[ROW][C]0.04[/C][C]3804.67001357034[/C][C]7.28956171211464[/C][/ROW]
[ROW][C]0.05[/C][C]3808.53114691911[/C][C]6.09733226121203[/C][/ROW]
[ROW][C]0.06[/C][C]3811.50232155054[/C][C]5.79000599839729[/C][/ROW]
[ROW][C]0.07[/C][C]3814.03584781927[/C][C]6.11379659662442[/C][/ROW]
[ROW][C]0.08[/C][C]3816.42046718187[/C][C]6.7045736467684[/C][/ROW]
[ROW][C]0.09[/C][C]3818.8007021531[/C][C]7.31849296294953[/C][/ROW]
[ROW][C]0.1[/C][C]3821.22447345853[/C][C]7.83201497361356[/C][/ROW]
[ROW][C]0.11[/C][C]3823.68895500115[/C][C]8.21910163478837[/C][/ROW]
[ROW][C]0.12[/C][C]3826.17389529407[/C][C]8.50475371658174[/C][/ROW]
[ROW][C]0.13[/C][C]3828.6603631691[/C][C]8.74946711036183[/C][/ROW]
[ROW][C]0.14[/C][C]3831.13721813449[/C][C]8.97617859666043[/C][/ROW]
[ROW][C]0.15[/C][C]3833.59937389309[/C][C]9.2096188786722[/C][/ROW]
[ROW][C]0.16[/C][C]3836.04226273252[/C][C]9.41042439223765[/C][/ROW]
[ROW][C]0.17[/C][C]3838.4563626496[/C][C]9.53275008671599[/C][/ROW]
[ROW][C]0.18[/C][C]3840.82442834996[/C][C]9.52477846386347[/C][/ROW]
[ROW][C]0.19[/C][C]3843.12245539630[/C][C]9.35370396470893[/C][/ROW]
[ROW][C]0.2[/C][C]3845.32385648854[/C][C]9.02359616403804[/C][/ROW]
[ROW][C]0.21[/C][C]3847.40528342096[/C][C]8.56286674928636[/C][/ROW]
[ROW][C]0.22[/C][C]3849.35221285118[/C][C]8.04153429241849[/C][/ROW]
[ROW][C]0.23[/C][C]3851.16276357158[/C][C]7.53067407871205[/C][/ROW]
[ROW][C]0.24[/C][C]3852.84895299377[/C][C]7.09911259303678[/C][/ROW]
[ROW][C]0.25[/C][C]3854.43540126058[/C][C]6.826911985831[/C][/ROW]
[ROW][C]0.26[/C][C]3855.95610207461[/C][C]6.74829039949393[/C][/ROW]
[ROW][C]0.27[/C][C]3857.45018977894[/C][C]6.87261103754311[/C][/ROW]
[ROW][C]0.28[/C][C]3858.95765973494[/C][C]7.19928614506239[/C][/ROW]
[ROW][C]0.29[/C][C]3860.51583274884[/C][C]7.69718968326917[/C][/ROW]
[ROW][C]0.3[/C][C]3862.15709541314[/C][C]8.32078093374191[/C][/ROW]
[ROW][C]0.31[/C][C]3863.90817180382[/C][C]9.04945365534227[/C][/ROW]
[ROW][C]0.32[/C][C]3865.79092677597[/C][C]9.85141483835165[/C][/ROW]
[ROW][C]0.33[/C][C]3867.82447972074[/C][C]10.7316181761941[/C][/ROW]
[ROW][C]0.34[/C][C]3870.0282235498[/C][C]11.7004845449463[/C][/ROW]
[ROW][C]0.35[/C][C]3872.42520426289[/C][C]12.8006604376938[/C][/ROW]
[ROW][C]0.36[/C][C]3875.0452371751[/C][C]14.0887267046354[/C][/ROW]
[ROW][C]0.37[/C][C]3877.92713608614[/C][C]15.6236814262273[/C][/ROW]
[ROW][C]0.38[/C][C]3881.11952610605[/C][C]17.4763839813903[/C][/ROW]
[ROW][C]0.39[/C][C]3884.67990107967[/C][C]19.688720758132[/C][/ROW]
[ROW][C]0.4[/C][C]3888.67185551190[/C][C]22.2867194858100[/C][/ROW]
[ROW][C]0.41[/C][C]3893.16073200513[/C][C]25.2565197779651[/C][/ROW]
[ROW][C]0.42[/C][C]3898.20822630939[/C][C]28.5521919341857[/C][/ROW]
[ROW][C]0.43[/C][C]3903.8667236159[/C][C]32.0966128981010[/C][/ROW]
[ROW][C]0.44[/C][C]3910.17424627397[/C][C]35.7846372891041[/C][/ROW]
[ROW][C]0.45[/C][C]3917.15083645329[/C][C]39.5002883348703[/C][/ROW]
[ROW][C]0.46[/C][C]3924.79696851891[/C][C]43.1216264612603[/C][/ROW]
[ROW][C]0.47[/C][C]3933.09421339461[/C][C]46.5589740017563[/C][/ROW]
[ROW][C]0.48[/C][C]3942.00792690814[/C][C]49.7152418192293[/C][/ROW]
[ROW][C]0.49[/C][C]3951.49130011489[/C][C]52.5581389102238[/C][/ROW]
[ROW][C]0.5[/C][C]3961.48979507691[/C][C]55.0638500371534[/C][/ROW]
[ROW][C]0.51[/C][C]3971.9448816985[/C][C]57.2364346302888[/C][/ROW]
[ROW][C]0.52[/C][C]3982.79613612996[/C][C]59.0887045675175[/C][/ROW]
[ROW][C]0.53[/C][C]3993.98114675071[/C][C]60.6253691699487[/C][/ROW]
[ROW][C]0.54[/C][C]4005.43322596222[/C][C]61.8225686375305[/C][/ROW]
[ROW][C]0.55[/C][C]4017.07752280129[/C][C]62.6261131221057[/C][/ROW]
[ROW][C]0.56[/C][C]4028.82663008342[/C][C]62.9599820574059[/C][/ROW]
[ROW][C]0.57[/C][C]4040.57705260362[/C][C]62.7172934310052[/C][/ROW]
[ROW][C]0.58[/C][C]4052.20787020019[/C][C]61.7909428170898[/C][/ROW]
[ROW][C]0.59[/C][C]4063.58258174327[/C][C]60.0973419187875[/C][/ROW]
[ROW][C]0.6[/C][C]4074.55451870931[/C][C]57.5826331388876[/C][/ROW]
[ROW][C]0.61[/C][C]4084.97549611803[/C][C]54.2648053890967[/C][/ROW]
[ROW][C]0.62[/C][C]4094.70668207283[/C][C]50.211932270619[/C][/ROW]
[ROW][C]0.63[/C][C]4103.63016748201[/C][C]45.5701150675699[/C][/ROW]
[ROW][C]0.64[/C][C]4111.65951619693[/C][C]40.5275796951312[/C][/ROW]
[ROW][C]0.65[/C][C]4118.74771718959[/C][C]35.3127768143817[/C][/ROW]
[ROW][C]0.66[/C][C]4124.89141192581[/C][C]30.1605729378590[/C][/ROW]
[ROW][C]0.67[/C][C]4130.1309306723[/C][C]25.3069196741721[/C][/ROW]
[ROW][C]0.68[/C][C]4134.54639616608[/C][C]20.9378056049311[/C][/ROW]
[ROW][C]0.69[/C][C]4138.25078746979[/C][C]17.2139087173452[/C][/ROW]
[ROW][C]0.7[/C][C]4141.38127200667[/C][C]14.2410507548084[/C][/ROW]
[ROW][C]0.71[/C][C]4144.09023283982[/C][C]12.0921309296465[/C][/ROW]
[ROW][C]0.72[/C][C]4146.53722899008[/C][C]10.7908218085138[/C][/ROW]
[ROW][C]0.73[/C][C]4148.88267957051[/C][C]10.3398194271410[/C][/ROW]
[ROW][C]0.74[/C][C]4151.28345933949[/C][C]10.6765308821020[/C][/ROW]
[ROW][C]0.75[/C][C]4153.8899705115[/C][C]11.7133201182095[/C][/ROW]
[ROW][C]0.76[/C][C]4156.84376788779[/C][C]13.350280693612[/C][/ROW]
[ROW][C]0.77[/C][C]4160.27461382064[/C][C]15.4886172041714[/C][/ROW]
[ROW][C]0.78[/C][C]4164.29604591366[/C][C]18.026731483943[/C][/ROW]
[ROW][C]0.79[/C][C]4168.99919615601[/C][C]20.8282874805966[/C][/ROW]
[ROW][C]0.8[/C][C]4174.44561710141[/C][C]23.7323667187252[/C][/ROW]
[ROW][C]0.81[/C][C]4180.6609892954[/C][C]26.5533364636963[/C][/ROW]
[ROW][C]0.82[/C][C]4187.63238239195[/C][C]29.1020254324616[/C][/ROW]
[ROW][C]0.83[/C][C]4195.31172920652[/C][C]31.207183707339[/C][/ROW]
[ROW][C]0.84[/C][C]4203.62697822834[/C][C]32.7730629702555[/C][/ROW]
[ROW][C]0.85[/C][C]4212.50001973139[/C][C]33.7966059733828[/C][/ROW]
[ROW][C]0.86[/C][C]4221.8675183585[/C][C]34.374084448831[/C][/ROW]
[ROW][C]0.87[/C][C]4231.69840634378[/C][C]34.6872729289879[/C][/ROW]
[ROW][C]0.88[/C][C]4242.00142654038[/C][C]34.930232516373[/C][/ROW]
[ROW][C]0.89[/C][C]4252.81873587877[/C][C]35.2298511989021[/C][/ROW]
[ROW][C]0.9[/C][C]4264.20683051376[/C][C]35.5770886501194[/C][/ROW]
[ROW][C]0.91[/C][C]4276.21174577892[/C][C]35.8378686833117[/C][/ROW]
[ROW][C]0.92[/C][C]4288.8482149823[/C][C]35.8011708784308[/C][/ROW]
[ROW][C]0.93[/C][C]4302.08990759398[/C][C]35.2821544609265[/C][/ROW]
[ROW][C]0.94[/C][C]4315.87207744934[/C][C]34.163005568404[/C][/ROW]
[ROW][C]0.95[/C][C]4330.10569440766[/C][C]32.3678360956639[/C][/ROW]
[ROW][C]0.96[/C][C]4344.70118867024[/C][C]29.8201026783547[/C][/ROW]
[ROW][C]0.97[/C][C]4359.55393091028[/C][C]26.5328670809640[/C][/ROW]
[ROW][C]0.98[/C][C]4374.2745008761[/C][C]23.0810301042017[/C][/ROW]
[ROW][C]0.99[/C][C]4387.35699842144[/C][C]21.0804710468288[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=38646&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=38646&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
0.013784.9952322978813.8819953719039
0.023792.5049803255411.5597702836022
0.033799.394848224259.24381583974927
0.043804.670013570347.28956171211464
0.053808.531146919116.09733226121203
0.063811.502321550545.79000599839729
0.073814.035847819276.11379659662442
0.083816.420467181876.7045736467684
0.093818.80070215317.31849296294953
0.13821.224473458537.83201497361356
0.113823.688955001158.21910163478837
0.123826.173895294078.50475371658174
0.133828.66036316918.74946711036183
0.143831.137218134498.97617859666043
0.153833.599373893099.2096188786722
0.163836.042262732529.41042439223765
0.173838.45636264969.53275008671599
0.183840.824428349969.52477846386347
0.193843.122455396309.35370396470893
0.23845.323856488549.02359616403804
0.213847.405283420968.56286674928636
0.223849.352212851188.04153429241849
0.233851.162763571587.53067407871205
0.243852.848952993777.09911259303678
0.253854.435401260586.826911985831
0.263855.956102074616.74829039949393
0.273857.450189778946.87261103754311
0.283858.957659734947.19928614506239
0.293860.515832748847.69718968326917
0.33862.157095413148.32078093374191
0.313863.908171803829.04945365534227
0.323865.790926775979.85141483835165
0.333867.8244797207410.7316181761941
0.343870.028223549811.7004845449463
0.353872.4252042628912.8006604376938
0.363875.045237175114.0887267046354
0.373877.9271360861415.6236814262273
0.383881.1195261060517.4763839813903
0.393884.6799010796719.688720758132
0.43888.6718555119022.2867194858100
0.413893.1607320051325.2565197779651
0.423898.2082263093928.5521919341857
0.433903.866723615932.0966128981010
0.443910.1742462739735.7846372891041
0.453917.1508364532939.5002883348703
0.463924.7969685189143.1216264612603
0.473933.0942133946146.5589740017563
0.483942.0079269081449.7152418192293
0.493951.4913001148952.5581389102238
0.53961.4897950769155.0638500371534
0.513971.944881698557.2364346302888
0.523982.7961361299659.0887045675175
0.533993.9811467507160.6253691699487
0.544005.4332259622261.8225686375305
0.554017.0775228012962.6261131221057
0.564028.8266300834262.9599820574059
0.574040.5770526036262.7172934310052
0.584052.2078702001961.7909428170898
0.594063.5825817432760.0973419187875
0.64074.5545187093157.5826331388876
0.614084.9754961180354.2648053890967
0.624094.7066820728350.211932270619
0.634103.6301674820145.5701150675699
0.644111.6595161969340.5275796951312
0.654118.7477171895935.3127768143817
0.664124.8914119258130.1605729378590
0.674130.130930672325.3069196741721
0.684134.5463961660820.9378056049311
0.694138.2507874697917.2139087173452
0.74141.3812720066714.2410507548084
0.714144.0902328398212.0921309296465
0.724146.5372289900810.7908218085138
0.734148.8826795705110.3398194271410
0.744151.2834593394910.6765308821020
0.754153.889970511511.7133201182095
0.764156.8437678877913.350280693612
0.774160.2746138206415.4886172041714
0.784164.2960459136618.026731483943
0.794168.9991961560120.8282874805966
0.84174.4456171014123.7323667187252
0.814180.660989295426.5533364636963
0.824187.6323823919529.1020254324616
0.834195.3117292065231.207183707339
0.844203.6269782283432.7730629702555
0.854212.5000197313933.7966059733828
0.864221.867518358534.374084448831
0.874231.6984063437834.6872729289879
0.884242.0014265403834.930232516373
0.894252.8187358787735.2298511989021
0.94264.2068305137635.5770886501194
0.914276.2117457789235.8378686833117
0.924288.848214982335.8011708784308
0.934302.0899075939835.2821544609265
0.944315.8720774493434.163005568404
0.954330.1056944076632.3678360956639
0.964344.7011886702429.8201026783547
0.974359.5539309102826.5328670809640
0.984374.274500876123.0810301042017
0.994387.3569984214421.0804710468288


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')