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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationThu, 14 Oct 2010 11:06:30 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Oct/14/t1287054351yavq8fux8ucdwmc.htm/, Retrieved Thu, 02 May 2024 07:11:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=83252, Retrieved Thu, 02 May 2024 07:11:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W4O2
Estimated Impact150

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Quartiles] [Quartielen maximu...] [2010-10-13 19:45:28] [d1899c9419fc846190372744c0657f19]
- RMPD    [Harrell-Davis Quantiles] [Maandelijks verko...] [2010-10-14 11:06:30] [2a9374b6a827503db60f94b3ae42bf2a] [Current]
-           [Harrell-Davis Quantiles] [Maandelijks verko...] [2010-10-14 11:08:26] [d1899c9419fc846190372744c0657f19]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2834
4683
4120
3849
8435
12854
15883
10520
12562
5060
4520
2150
2905
4820
3950
4053
8700
13520
15400
11100
11950
4900
4633
2300
2945
3960
3900
3767
8820
11980
14085
11600
9814
4930
4360
2640
3050
5485
4366
4790
10100
14830
17930
13580
12490
6400
4980
4930
5856
5120
5100
5623
12035
19846
17030
15860
14890
8053
6080
5987
5682
4980
5450
6035
13240
18400
17689
16490
14062
9556
7555
4328

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 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 & 7 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=83252&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]7 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=83252&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=83252&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 time7 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Harrell-Davis Quantiles
quantilesvaluestandard error
0.012220.04656452293191.834150124631
0.022341.9190396662249.173727422277
0.032485.81324679948276.904487429754
0.042629.45804631237279.296988320941
0.052764.23301537769283.870150888201
0.062891.46530291417308.385734769408
0.073016.34313637179349.175046139024
0.083142.97676273633390.630322982332
0.093272.03825792332417.98013793489
0.13400.89275175406423.392849389882
0.113525.20928929715407.060339651592
0.123640.85843484654375.311098858665
0.133745.25251306213337.337512055074
0.143837.81443662497301.902635901034
0.153919.69847448752275.020939402343
0.163993.10462046119258.914698593463
0.174060.53590581649252.443551100115
0.184124.23040423936252.631537989857
0.194185.85308999442256.250372037460
0.24246.42155466093260.738333914511
0.214306.38590945634264.383775561051
0.224365.77829135528266.21393644107
0.234424.36985830088265.767980269600
0.244481.80274928537262.944303292567
0.254537.68845700918257.854028524648
0.264591.67767632001250.81428383357
0.274643.51079873445242.337389918546
0.284693.05627730102233.134311129399
0.294740.33984098334224.088835536921
0.34785.56376533397216.243332586672
0.314829.11351387824210.72607650407
0.324871.54929269117208.612832288690
0.334913.58192319201210.811154235113
0.344956.03515390482217.934354478982
0.354999.79931478613230.199636174979
0.365045.78341052132247.452971258639
0.375094.87385454801269.280946086815
0.385147.90772646464295.180917181410
0.395205.6665355878324.690340337846
0.45268.89306795854357.610706596075
0.415338.32934790383394.107169284717
0.425414.76873751006434.748638431657
0.435499.11067499088480.531479826118
0.445592.40359284778532.680052244778
0.455695.86114429299592.445395002193
0.465810.83962769357660.740557610912
0.475938.77045045777737.817161949765
0.486081.04986931465823.018366418021
0.496238.89759000049914.651696337636
0.56413.204094980641010.01855964091
0.516604.391693053711105.69390607595
0.526812.314605868531197.83744289002
0.537036.218255034571282.66010435258
0.547274.767921614491356.87377669665
0.557526.144046397271418.08072355865
0.567788.188470537281465.00855245749
0.578058.57595985041497.54283759216
0.588334.98091213191516.57971200657
0.598615.21143799421523.69704504947
0.68897.291601818221520.74685919550
0.619179.485492388951509.44142125184
0.629460.270846114521491.03565436597
0.639738.281731417181466.19026361429
0.6410012.24641766931435.07894914640
0.6510280.94634893561397.53297353813
0.6610543.21515180321353.47048143862
0.6710797.98456389421303.21719698310
0.6811044.37014364431247.73821741883
0.6911281.77729924991188.77800608994
0.711510.00093940401128.73573448455
0.7111729.29205179531070.45070039944
0.7211940.37197754151016.70333492141
0.7312144.3881290643969.864018207691
0.7412342.8196807345931.463937436046
0.7512537.3538566065902.04589641356
0.7612729.7589721550881.280717101954
0.7712921.7774708019868.199431048454
0.7813115.0518150569861.603184168455
0.7913311.0820917099860.322550569508
0.813511.2022367874863.32656639048
0.8113716.5574941285869.605552677157
0.8213928.0724554790877.951506175713
0.8314146.4159985977886.882740647672
0.8414371.9906399583894.595052934511
0.8514604.9882737825899.420622287056
0.8614845.5481339874900.371318605815
0.8715094.0142879036897.724439063038
0.8815351.2179383515893.378545000065
0.8915618.6255294448890.334271733921
0.915898.1506652710891.079009480539
0.9116191.5102321714894.95847543379
0.9216499.30239336896.042676360773
0.9316820.5348566846883.88104517128
0.9417154.0130691856848.829033754848
0.9517503.2343857979792.235376294831
0.9617884.4689647975740.059955175711
0.9718330.0435173630754.469442237387
0.9818864.8522655195908.05052606673
0.9919435.36754821011184.92721465007

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 2220.04656452293 & 191.834150124631 \tabularnewline
0.02 & 2341.9190396662 & 249.173727422277 \tabularnewline
0.03 & 2485.81324679948 & 276.904487429754 \tabularnewline
0.04 & 2629.45804631237 & 279.296988320941 \tabularnewline
0.05 & 2764.23301537769 & 283.870150888201 \tabularnewline
0.06 & 2891.46530291417 & 308.385734769408 \tabularnewline
0.07 & 3016.34313637179 & 349.175046139024 \tabularnewline
0.08 & 3142.97676273633 & 390.630322982332 \tabularnewline
0.09 & 3272.03825792332 & 417.98013793489 \tabularnewline
0.1 & 3400.89275175406 & 423.392849389882 \tabularnewline
0.11 & 3525.20928929715 & 407.060339651592 \tabularnewline
0.12 & 3640.85843484654 & 375.311098858665 \tabularnewline
0.13 & 3745.25251306213 & 337.337512055074 \tabularnewline
0.14 & 3837.81443662497 & 301.902635901034 \tabularnewline
0.15 & 3919.69847448752 & 275.020939402343 \tabularnewline
0.16 & 3993.10462046119 & 258.914698593463 \tabularnewline
0.17 & 4060.53590581649 & 252.443551100115 \tabularnewline
0.18 & 4124.23040423936 & 252.631537989857 \tabularnewline
0.19 & 4185.85308999442 & 256.250372037460 \tabularnewline
0.2 & 4246.42155466093 & 260.738333914511 \tabularnewline
0.21 & 4306.38590945634 & 264.383775561051 \tabularnewline
0.22 & 4365.77829135528 & 266.21393644107 \tabularnewline
0.23 & 4424.36985830088 & 265.767980269600 \tabularnewline
0.24 & 4481.80274928537 & 262.944303292567 \tabularnewline
0.25 & 4537.68845700918 & 257.854028524648 \tabularnewline
0.26 & 4591.67767632001 & 250.81428383357 \tabularnewline
0.27 & 4643.51079873445 & 242.337389918546 \tabularnewline
0.28 & 4693.05627730102 & 233.134311129399 \tabularnewline
0.29 & 4740.33984098334 & 224.088835536921 \tabularnewline
0.3 & 4785.56376533397 & 216.243332586672 \tabularnewline
0.31 & 4829.11351387824 & 210.72607650407 \tabularnewline
0.32 & 4871.54929269117 & 208.612832288690 \tabularnewline
0.33 & 4913.58192319201 & 210.811154235113 \tabularnewline
0.34 & 4956.03515390482 & 217.934354478982 \tabularnewline
0.35 & 4999.79931478613 & 230.199636174979 \tabularnewline
0.36 & 5045.78341052132 & 247.452971258639 \tabularnewline
0.37 & 5094.87385454801 & 269.280946086815 \tabularnewline
0.38 & 5147.90772646464 & 295.180917181410 \tabularnewline
0.39 & 5205.6665355878 & 324.690340337846 \tabularnewline
0.4 & 5268.89306795854 & 357.610706596075 \tabularnewline
0.41 & 5338.32934790383 & 394.107169284717 \tabularnewline
0.42 & 5414.76873751006 & 434.748638431657 \tabularnewline
0.43 & 5499.11067499088 & 480.531479826118 \tabularnewline
0.44 & 5592.40359284778 & 532.680052244778 \tabularnewline
0.45 & 5695.86114429299 & 592.445395002193 \tabularnewline
0.46 & 5810.83962769357 & 660.740557610912 \tabularnewline
0.47 & 5938.77045045777 & 737.817161949765 \tabularnewline
0.48 & 6081.04986931465 & 823.018366418021 \tabularnewline
0.49 & 6238.89759000049 & 914.651696337636 \tabularnewline
0.5 & 6413.20409498064 & 1010.01855964091 \tabularnewline
0.51 & 6604.39169305371 & 1105.69390607595 \tabularnewline
0.52 & 6812.31460586853 & 1197.83744289002 \tabularnewline
0.53 & 7036.21825503457 & 1282.66010435258 \tabularnewline
0.54 & 7274.76792161449 & 1356.87377669665 \tabularnewline
0.55 & 7526.14404639727 & 1418.08072355865 \tabularnewline
0.56 & 7788.18847053728 & 1465.00855245749 \tabularnewline
0.57 & 8058.5759598504 & 1497.54283759216 \tabularnewline
0.58 & 8334.9809121319 & 1516.57971200657 \tabularnewline
0.59 & 8615.2114379942 & 1523.69704504947 \tabularnewline
0.6 & 8897.29160181822 & 1520.74685919550 \tabularnewline
0.61 & 9179.48549238895 & 1509.44142125184 \tabularnewline
0.62 & 9460.27084611452 & 1491.03565436597 \tabularnewline
0.63 & 9738.28173141718 & 1466.19026361429 \tabularnewline
0.64 & 10012.2464176693 & 1435.07894914640 \tabularnewline
0.65 & 10280.9463489356 & 1397.53297353813 \tabularnewline
0.66 & 10543.2151518032 & 1353.47048143862 \tabularnewline
0.67 & 10797.9845638942 & 1303.21719698310 \tabularnewline
0.68 & 11044.3701436443 & 1247.73821741883 \tabularnewline
0.69 & 11281.7772992499 & 1188.77800608994 \tabularnewline
0.7 & 11510.0009394040 & 1128.73573448455 \tabularnewline
0.71 & 11729.2920517953 & 1070.45070039944 \tabularnewline
0.72 & 11940.3719775415 & 1016.70333492141 \tabularnewline
0.73 & 12144.3881290643 & 969.864018207691 \tabularnewline
0.74 & 12342.8196807345 & 931.463937436046 \tabularnewline
0.75 & 12537.3538566065 & 902.04589641356 \tabularnewline
0.76 & 12729.7589721550 & 881.280717101954 \tabularnewline
0.77 & 12921.7774708019 & 868.199431048454 \tabularnewline
0.78 & 13115.0518150569 & 861.603184168455 \tabularnewline
0.79 & 13311.0820917099 & 860.322550569508 \tabularnewline
0.8 & 13511.2022367874 & 863.32656639048 \tabularnewline
0.81 & 13716.5574941285 & 869.605552677157 \tabularnewline
0.82 & 13928.0724554790 & 877.951506175713 \tabularnewline
0.83 & 14146.4159985977 & 886.882740647672 \tabularnewline
0.84 & 14371.9906399583 & 894.595052934511 \tabularnewline
0.85 & 14604.9882737825 & 899.420622287056 \tabularnewline
0.86 & 14845.5481339874 & 900.371318605815 \tabularnewline
0.87 & 15094.0142879036 & 897.724439063038 \tabularnewline
0.88 & 15351.2179383515 & 893.378545000065 \tabularnewline
0.89 & 15618.6255294448 & 890.334271733921 \tabularnewline
0.9 & 15898.1506652710 & 891.079009480539 \tabularnewline
0.91 & 16191.5102321714 & 894.95847543379 \tabularnewline
0.92 & 16499.30239336 & 896.042676360773 \tabularnewline
0.93 & 16820.5348566846 & 883.88104517128 \tabularnewline
0.94 & 17154.0130691856 & 848.829033754848 \tabularnewline
0.95 & 17503.2343857979 & 792.235376294831 \tabularnewline
0.96 & 17884.4689647975 & 740.059955175711 \tabularnewline
0.97 & 18330.0435173630 & 754.469442237387 \tabularnewline
0.98 & 18864.8522655195 & 908.05052606673 \tabularnewline
0.99 & 19435.3675482101 & 1184.92721465007 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=83252&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]2220.04656452293[/C][C]191.834150124631[/C][/ROW]
[ROW][C]0.02[/C][C]2341.9190396662[/C][C]249.173727422277[/C][/ROW]
[ROW][C]0.03[/C][C]2485.81324679948[/C][C]276.904487429754[/C][/ROW]
[ROW][C]0.04[/C][C]2629.45804631237[/C][C]279.296988320941[/C][/ROW]
[ROW][C]0.05[/C][C]2764.23301537769[/C][C]283.870150888201[/C][/ROW]
[ROW][C]0.06[/C][C]2891.46530291417[/C][C]308.385734769408[/C][/ROW]
[ROW][C]0.07[/C][C]3016.34313637179[/C][C]349.175046139024[/C][/ROW]
[ROW][C]0.08[/C][C]3142.97676273633[/C][C]390.630322982332[/C][/ROW]
[ROW][C]0.09[/C][C]3272.03825792332[/C][C]417.98013793489[/C][/ROW]
[ROW][C]0.1[/C][C]3400.89275175406[/C][C]423.392849389882[/C][/ROW]
[ROW][C]0.11[/C][C]3525.20928929715[/C][C]407.060339651592[/C][/ROW]
[ROW][C]0.12[/C][C]3640.85843484654[/C][C]375.311098858665[/C][/ROW]
[ROW][C]0.13[/C][C]3745.25251306213[/C][C]337.337512055074[/C][/ROW]
[ROW][C]0.14[/C][C]3837.81443662497[/C][C]301.902635901034[/C][/ROW]
[ROW][C]0.15[/C][C]3919.69847448752[/C][C]275.020939402343[/C][/ROW]
[ROW][C]0.16[/C][C]3993.10462046119[/C][C]258.914698593463[/C][/ROW]
[ROW][C]0.17[/C][C]4060.53590581649[/C][C]252.443551100115[/C][/ROW]
[ROW][C]0.18[/C][C]4124.23040423936[/C][C]252.631537989857[/C][/ROW]
[ROW][C]0.19[/C][C]4185.85308999442[/C][C]256.250372037460[/C][/ROW]
[ROW][C]0.2[/C][C]4246.42155466093[/C][C]260.738333914511[/C][/ROW]
[ROW][C]0.21[/C][C]4306.38590945634[/C][C]264.383775561051[/C][/ROW]
[ROW][C]0.22[/C][C]4365.77829135528[/C][C]266.21393644107[/C][/ROW]
[ROW][C]0.23[/C][C]4424.36985830088[/C][C]265.767980269600[/C][/ROW]
[ROW][C]0.24[/C][C]4481.80274928537[/C][C]262.944303292567[/C][/ROW]
[ROW][C]0.25[/C][C]4537.68845700918[/C][C]257.854028524648[/C][/ROW]
[ROW][C]0.26[/C][C]4591.67767632001[/C][C]250.81428383357[/C][/ROW]
[ROW][C]0.27[/C][C]4643.51079873445[/C][C]242.337389918546[/C][/ROW]
[ROW][C]0.28[/C][C]4693.05627730102[/C][C]233.134311129399[/C][/ROW]
[ROW][C]0.29[/C][C]4740.33984098334[/C][C]224.088835536921[/C][/ROW]
[ROW][C]0.3[/C][C]4785.56376533397[/C][C]216.243332586672[/C][/ROW]
[ROW][C]0.31[/C][C]4829.11351387824[/C][C]210.72607650407[/C][/ROW]
[ROW][C]0.32[/C][C]4871.54929269117[/C][C]208.612832288690[/C][/ROW]
[ROW][C]0.33[/C][C]4913.58192319201[/C][C]210.811154235113[/C][/ROW]
[ROW][C]0.34[/C][C]4956.03515390482[/C][C]217.934354478982[/C][/ROW]
[ROW][C]0.35[/C][C]4999.79931478613[/C][C]230.199636174979[/C][/ROW]
[ROW][C]0.36[/C][C]5045.78341052132[/C][C]247.452971258639[/C][/ROW]
[ROW][C]0.37[/C][C]5094.87385454801[/C][C]269.280946086815[/C][/ROW]
[ROW][C]0.38[/C][C]5147.90772646464[/C][C]295.180917181410[/C][/ROW]
[ROW][C]0.39[/C][C]5205.6665355878[/C][C]324.690340337846[/C][/ROW]
[ROW][C]0.4[/C][C]5268.89306795854[/C][C]357.610706596075[/C][/ROW]
[ROW][C]0.41[/C][C]5338.32934790383[/C][C]394.107169284717[/C][/ROW]
[ROW][C]0.42[/C][C]5414.76873751006[/C][C]434.748638431657[/C][/ROW]
[ROW][C]0.43[/C][C]5499.11067499088[/C][C]480.531479826118[/C][/ROW]
[ROW][C]0.44[/C][C]5592.40359284778[/C][C]532.680052244778[/C][/ROW]
[ROW][C]0.45[/C][C]5695.86114429299[/C][C]592.445395002193[/C][/ROW]
[ROW][C]0.46[/C][C]5810.83962769357[/C][C]660.740557610912[/C][/ROW]
[ROW][C]0.47[/C][C]5938.77045045777[/C][C]737.817161949765[/C][/ROW]
[ROW][C]0.48[/C][C]6081.04986931465[/C][C]823.018366418021[/C][/ROW]
[ROW][C]0.49[/C][C]6238.89759000049[/C][C]914.651696337636[/C][/ROW]
[ROW][C]0.5[/C][C]6413.20409498064[/C][C]1010.01855964091[/C][/ROW]
[ROW][C]0.51[/C][C]6604.39169305371[/C][C]1105.69390607595[/C][/ROW]
[ROW][C]0.52[/C][C]6812.31460586853[/C][C]1197.83744289002[/C][/ROW]
[ROW][C]0.53[/C][C]7036.21825503457[/C][C]1282.66010435258[/C][/ROW]
[ROW][C]0.54[/C][C]7274.76792161449[/C][C]1356.87377669665[/C][/ROW]
[ROW][C]0.55[/C][C]7526.14404639727[/C][C]1418.08072355865[/C][/ROW]
[ROW][C]0.56[/C][C]7788.18847053728[/C][C]1465.00855245749[/C][/ROW]
[ROW][C]0.57[/C][C]8058.5759598504[/C][C]1497.54283759216[/C][/ROW]
[ROW][C]0.58[/C][C]8334.9809121319[/C][C]1516.57971200657[/C][/ROW]
[ROW][C]0.59[/C][C]8615.2114379942[/C][C]1523.69704504947[/C][/ROW]
[ROW][C]0.6[/C][C]8897.29160181822[/C][C]1520.74685919550[/C][/ROW]
[ROW][C]0.61[/C][C]9179.48549238895[/C][C]1509.44142125184[/C][/ROW]
[ROW][C]0.62[/C][C]9460.27084611452[/C][C]1491.03565436597[/C][/ROW]
[ROW][C]0.63[/C][C]9738.28173141718[/C][C]1466.19026361429[/C][/ROW]
[ROW][C]0.64[/C][C]10012.2464176693[/C][C]1435.07894914640[/C][/ROW]
[ROW][C]0.65[/C][C]10280.9463489356[/C][C]1397.53297353813[/C][/ROW]
[ROW][C]0.66[/C][C]10543.2151518032[/C][C]1353.47048143862[/C][/ROW]
[ROW][C]0.67[/C][C]10797.9845638942[/C][C]1303.21719698310[/C][/ROW]
[ROW][C]0.68[/C][C]11044.3701436443[/C][C]1247.73821741883[/C][/ROW]
[ROW][C]0.69[/C][C]11281.7772992499[/C][C]1188.77800608994[/C][/ROW]
[ROW][C]0.7[/C][C]11510.0009394040[/C][C]1128.73573448455[/C][/ROW]
[ROW][C]0.71[/C][C]11729.2920517953[/C][C]1070.45070039944[/C][/ROW]
[ROW][C]0.72[/C][C]11940.3719775415[/C][C]1016.70333492141[/C][/ROW]
[ROW][C]0.73[/C][C]12144.3881290643[/C][C]969.864018207691[/C][/ROW]
[ROW][C]0.74[/C][C]12342.8196807345[/C][C]931.463937436046[/C][/ROW]
[ROW][C]0.75[/C][C]12537.3538566065[/C][C]902.04589641356[/C][/ROW]
[ROW][C]0.76[/C][C]12729.7589721550[/C][C]881.280717101954[/C][/ROW]
[ROW][C]0.77[/C][C]12921.7774708019[/C][C]868.199431048454[/C][/ROW]
[ROW][C]0.78[/C][C]13115.0518150569[/C][C]861.603184168455[/C][/ROW]
[ROW][C]0.79[/C][C]13311.0820917099[/C][C]860.322550569508[/C][/ROW]
[ROW][C]0.8[/C][C]13511.2022367874[/C][C]863.32656639048[/C][/ROW]
[ROW][C]0.81[/C][C]13716.5574941285[/C][C]869.605552677157[/C][/ROW]
[ROW][C]0.82[/C][C]13928.0724554790[/C][C]877.951506175713[/C][/ROW]
[ROW][C]0.83[/C][C]14146.4159985977[/C][C]886.882740647672[/C][/ROW]
[ROW][C]0.84[/C][C]14371.9906399583[/C][C]894.595052934511[/C][/ROW]
[ROW][C]0.85[/C][C]14604.9882737825[/C][C]899.420622287056[/C][/ROW]
[ROW][C]0.86[/C][C]14845.5481339874[/C][C]900.371318605815[/C][/ROW]
[ROW][C]0.87[/C][C]15094.0142879036[/C][C]897.724439063038[/C][/ROW]
[ROW][C]0.88[/C][C]15351.2179383515[/C][C]893.378545000065[/C][/ROW]
[ROW][C]0.89[/C][C]15618.6255294448[/C][C]890.334271733921[/C][/ROW]
[ROW][C]0.9[/C][C]15898.1506652710[/C][C]891.079009480539[/C][/ROW]
[ROW][C]0.91[/C][C]16191.5102321714[/C][C]894.95847543379[/C][/ROW]
[ROW][C]0.92[/C][C]16499.30239336[/C][C]896.042676360773[/C][/ROW]
[ROW][C]0.93[/C][C]16820.5348566846[/C][C]883.88104517128[/C][/ROW]
[ROW][C]0.94[/C][C]17154.0130691856[/C][C]848.829033754848[/C][/ROW]
[ROW][C]0.95[/C][C]17503.2343857979[/C][C]792.235376294831[/C][/ROW]
[ROW][C]0.96[/C][C]17884.4689647975[/C][C]740.059955175711[/C][/ROW]
[ROW][C]0.97[/C][C]18330.0435173630[/C][C]754.469442237387[/C][/ROW]
[ROW][C]0.98[/C][C]18864.8522655195[/C][C]908.05052606673[/C][/ROW]
[ROW][C]0.99[/C][C]19435.3675482101[/C][C]1184.92721465007[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=83252&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=83252&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
0.012220.04656452293191.834150124631
0.022341.9190396662249.173727422277
0.032485.81324679948276.904487429754
0.042629.45804631237279.296988320941
0.052764.23301537769283.870150888201
0.062891.46530291417308.385734769408
0.073016.34313637179349.175046139024
0.083142.97676273633390.630322982332
0.093272.03825792332417.98013793489
0.13400.89275175406423.392849389882
0.113525.20928929715407.060339651592
0.123640.85843484654375.311098858665
0.133745.25251306213337.337512055074
0.143837.81443662497301.902635901034
0.153919.69847448752275.020939402343
0.163993.10462046119258.914698593463
0.174060.53590581649252.443551100115
0.184124.23040423936252.631537989857
0.194185.85308999442256.250372037460
0.24246.42155466093260.738333914511
0.214306.38590945634264.383775561051
0.224365.77829135528266.21393644107
0.234424.36985830088265.767980269600
0.244481.80274928537262.944303292567
0.254537.68845700918257.854028524648
0.264591.67767632001250.81428383357
0.274643.51079873445242.337389918546
0.284693.05627730102233.134311129399
0.294740.33984098334224.088835536921
0.34785.56376533397216.243332586672
0.314829.11351387824210.72607650407
0.324871.54929269117208.612832288690
0.334913.58192319201210.811154235113
0.344956.03515390482217.934354478982
0.354999.79931478613230.199636174979
0.365045.78341052132247.452971258639
0.375094.87385454801269.280946086815
0.385147.90772646464295.180917181410
0.395205.6665355878324.690340337846
0.45268.89306795854357.610706596075
0.415338.32934790383394.107169284717
0.425414.76873751006434.748638431657
0.435499.11067499088480.531479826118
0.445592.40359284778532.680052244778
0.455695.86114429299592.445395002193
0.465810.83962769357660.740557610912
0.475938.77045045777737.817161949765
0.486081.04986931465823.018366418021
0.496238.89759000049914.651696337636
0.56413.204094980641010.01855964091
0.516604.391693053711105.69390607595
0.526812.314605868531197.83744289002
0.537036.218255034571282.66010435258
0.547274.767921614491356.87377669665
0.557526.144046397271418.08072355865
0.567788.188470537281465.00855245749
0.578058.57595985041497.54283759216
0.588334.98091213191516.57971200657
0.598615.21143799421523.69704504947
0.68897.291601818221520.74685919550
0.619179.485492388951509.44142125184
0.629460.270846114521491.03565436597
0.639738.281731417181466.19026361429
0.6410012.24641766931435.07894914640
0.6510280.94634893561397.53297353813
0.6610543.21515180321353.47048143862
0.6710797.98456389421303.21719698310
0.6811044.37014364431247.73821741883
0.6911281.77729924991188.77800608994
0.711510.00093940401128.73573448455
0.7111729.29205179531070.45070039944
0.7211940.37197754151016.70333492141
0.7312144.3881290643969.864018207691
0.7412342.8196807345931.463937436046
0.7512537.3538566065902.04589641356
0.7612729.7589721550881.280717101954
0.7712921.7774708019868.199431048454
0.7813115.0518150569861.603184168455
0.7913311.0820917099860.322550569508
0.813511.2022367874863.32656639048
0.8113716.5574941285869.605552677157
0.8213928.0724554790877.951506175713
0.8314146.4159985977886.882740647672
0.8414371.9906399583894.595052934511
0.8514604.9882737825899.420622287056
0.8614845.5481339874900.371318605815
0.8715094.0142879036897.724439063038
0.8815351.2179383515893.378545000065
0.8915618.6255294448890.334271733921
0.915898.1506652710891.079009480539
0.9116191.5102321714894.95847543379
0.9216499.30239336896.042676360773
0.9316820.5348566846883.88104517128
0.9417154.0130691856848.829033754848
0.9517503.2343857979792.235376294831
0.9617884.4689647975740.059955175711
0.9718330.0435173630754.469442237387
0.9818864.8522655195908.05052606673
0.9919435.36754821011184.92721465007


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')