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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, 13 Oct 2010 09:37:29 +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/13/t1286962837ahc01f29g6cfvlj.htm/, Retrieved Tue, 10 Feb 2026 08:12:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=83078, Retrieved Tue, 10 Feb 2026 08:12:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W42
Estimated Impact483

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Quartiles] [Opgave 3] [2010-10-13 07:21:06] [8d131405c4b9158b536c3310b3ff5461]
-    D  [Quartiles] [Opgave 3 oef 2] [2010-10-13 08:12:10] [8d131405c4b9158b536c3310b3ff5461]
- RMPD    [Harrell-Davis Quantiles] [Opgave 4 - oef 2] [2010-10-13 09:24:32] [8d131405c4b9158b536c3310b3ff5461]
-             [Harrell-Davis Quantiles] [opgave 4 - oef 2] [2010-10-13 09:37:29] [9a37dffdb284317d3f5f461f9b8f0111] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6715
7703
9856
8326
9269
7035
10342
11682
10304
11385
9777
8882
7897
6930
9545
9110
7459
7320
10017
12307
11072
10749
9589
9080
7384
8062
8511
8684
8306
7643
10577
13747
11783
11611
9946
8693
7303
7609
9423
8584
7586
6843
11811
13414
12103
11501
8213
7982
7687
7180
7862
8043
8340
6692
10065
12684
11587
9843
8110
7940
6475
6121
9669
7778
7826
7403
10741
14023
11519
10236
8075
8157

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 8 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=83078&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=83078&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=83078&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 time8 seconds
R Server'George Udny Yule' @ 72.249.76.132






Harrell-Davis Quantiles
quantilesvaluestandard error
0.016228.2228722383305.6947433618
0.026380.67036113135250.090117130881
0.036524.98323383732205.767038450238
0.046642.40958044965181.486950320737
0.056737.03465916695176.993483515003
0.066818.3688292008184.951320104421
0.076893.43204943279196.436580663242
0.086965.5441038976205.384215671949
0.097035.42609655822209.023258328268
0.17102.52993268843206.951740499623
0.117165.99977863259200.330451220940
0.127225.21254120697191.161058016538
0.137279.98594902933181.579007859575
0.147330.56338688495173.241977082998
0.157377.47701785667166.951543238740
0.167421.37507969318162.698969625663
0.177462.8757041419159.921289200416
0.187502.47979097808157.917206937237
0.197540.54643173428156.180874204893
0.27577.31399192461154.470250110971
0.217612.94201959469152.783534427953
0.227647.55215770541151.260350344967
0.237681.25535443214150.038253910920
0.247714.1625861473149.172668555139
0.257746.38337325489148.661466210355
0.267778.0192691997148.397434935399
0.277809.15884470331148.298946639524
0.287839.87803796658148.290313679823
0.297870.2467030609148.401314140872
0.37900.33985158351148.704737982130
0.317930.25087554142149.395269933333
0.327960.10387975082150.702285102487
0.337990.06280344206152.916065029084
0.348020.33590379726156.341823304843
0.358051.1751242244161.226351958387
0.368082.87070003197167.81527295005
0.378115.74196626068176.220765835757
0.388150.12567676151186.513929074523
0.398186.36320452256198.652407480814
0.48224.78779361446212.549165388335
0.418265.71264088384228.046286124128
0.428309.42010835777244.921169980011
0.438356.15193135385262.947831980045
0.448406.10000642796281.813565224303
0.458459.39729077951301.176120456493
0.468516.10853654744320.647305280356
0.478576.22097695499339.762023239382
0.488639.63558687328358.017188809771
0.498706.1600407226374.870882693349
0.58775.50486289204389.763485509166
0.518847.284404038402.139767210960
0.528921.02411197072411.502367790575
0.538996.1750829436417.450229083557
0.549072.1361240537419.738398737417
0.559148.28263406959418.297568831316
0.569224.00066332379413.267175879744
0.579298.72370179406405.014230372298
0.589371.96920810164394.054813726311
0.599443.37172459517381.183371002538
0.69512.70965619023367.228742299421
0.619579.9233901149353.143320773456
0.629645.12331311074339.89988447759
0.639708.5873172076328.428130115523
0.649770.74842815053319.559226131324
0.659832.17408483984313.958312369781
0.669893.53918647383312.101305801332
0.679955.59516452426314.237342266981
0.6810019.1369320598320.428474567103
0.6910084.9686082476330.498485896579
0.710153.8675575920344.094194251483
0.7110226.5448708553360.707301731716
0.7210303.5995085874379.634406451923
0.7310385.463626237399.945647114538
0.7410472.3387437855420.421256587937
0.7510564.1266927276439.564570481779
0.7610660.3652361854455.57194560337
0.7710760.184523242466.481346767322
0.7810862.3048233328470.384099253805
0.7910965.0956611625465.72677448249
0.811066.7095826699451.683742306692
0.8111165.2902535326428.476067828644
0.8211259.2370431587397.555855229959
0.8311347.4917800201361.683593919604
0.8411429.8040218604324.625096650132
0.8511506.9334943032290.910995077443
0.8611580.7630538125265.271988589825
0.8711654.3186396664252.116539906138
0.8811731.7159441481254.714838692087
0.8911818.0647503157274.543490638838
0.911919.3436897530311.33921145886
0.9112042.1889840593363.71126895394
0.9212193.4114309087429.227295087595
0.9312378.9181366516502.865797626345
0.9412601.7444183284573.922075866559
0.9512859.3593028444623.261379194030
0.9613141.2959813435625.643512384492
0.9713428.5641339735562.114025631546
0.9813694.6272161301442.164855300548
0.9913905.4576065553322.908174084529

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 6228.2228722383 & 305.6947433618 \tabularnewline
0.02 & 6380.67036113135 & 250.090117130881 \tabularnewline
0.03 & 6524.98323383732 & 205.767038450238 \tabularnewline
0.04 & 6642.40958044965 & 181.486950320737 \tabularnewline
0.05 & 6737.03465916695 & 176.993483515003 \tabularnewline
0.06 & 6818.3688292008 & 184.951320104421 \tabularnewline
0.07 & 6893.43204943279 & 196.436580663242 \tabularnewline
0.08 & 6965.5441038976 & 205.384215671949 \tabularnewline
0.09 & 7035.42609655822 & 209.023258328268 \tabularnewline
0.1 & 7102.52993268843 & 206.951740499623 \tabularnewline
0.11 & 7165.99977863259 & 200.330451220940 \tabularnewline
0.12 & 7225.21254120697 & 191.161058016538 \tabularnewline
0.13 & 7279.98594902933 & 181.579007859575 \tabularnewline
0.14 & 7330.56338688495 & 173.241977082998 \tabularnewline
0.15 & 7377.47701785667 & 166.951543238740 \tabularnewline
0.16 & 7421.37507969318 & 162.698969625663 \tabularnewline
0.17 & 7462.8757041419 & 159.921289200416 \tabularnewline
0.18 & 7502.47979097808 & 157.917206937237 \tabularnewline
0.19 & 7540.54643173428 & 156.180874204893 \tabularnewline
0.2 & 7577.31399192461 & 154.470250110971 \tabularnewline
0.21 & 7612.94201959469 & 152.783534427953 \tabularnewline
0.22 & 7647.55215770541 & 151.260350344967 \tabularnewline
0.23 & 7681.25535443214 & 150.038253910920 \tabularnewline
0.24 & 7714.1625861473 & 149.172668555139 \tabularnewline
0.25 & 7746.38337325489 & 148.661466210355 \tabularnewline
0.26 & 7778.0192691997 & 148.397434935399 \tabularnewline
0.27 & 7809.15884470331 & 148.298946639524 \tabularnewline
0.28 & 7839.87803796658 & 148.290313679823 \tabularnewline
0.29 & 7870.2467030609 & 148.401314140872 \tabularnewline
0.3 & 7900.33985158351 & 148.704737982130 \tabularnewline
0.31 & 7930.25087554142 & 149.395269933333 \tabularnewline
0.32 & 7960.10387975082 & 150.702285102487 \tabularnewline
0.33 & 7990.06280344206 & 152.916065029084 \tabularnewline
0.34 & 8020.33590379726 & 156.341823304843 \tabularnewline
0.35 & 8051.1751242244 & 161.226351958387 \tabularnewline
0.36 & 8082.87070003197 & 167.81527295005 \tabularnewline
0.37 & 8115.74196626068 & 176.220765835757 \tabularnewline
0.38 & 8150.12567676151 & 186.513929074523 \tabularnewline
0.39 & 8186.36320452256 & 198.652407480814 \tabularnewline
0.4 & 8224.78779361446 & 212.549165388335 \tabularnewline
0.41 & 8265.71264088384 & 228.046286124128 \tabularnewline
0.42 & 8309.42010835777 & 244.921169980011 \tabularnewline
0.43 & 8356.15193135385 & 262.947831980045 \tabularnewline
0.44 & 8406.10000642796 & 281.813565224303 \tabularnewline
0.45 & 8459.39729077951 & 301.176120456493 \tabularnewline
0.46 & 8516.10853654744 & 320.647305280356 \tabularnewline
0.47 & 8576.22097695499 & 339.762023239382 \tabularnewline
0.48 & 8639.63558687328 & 358.017188809771 \tabularnewline
0.49 & 8706.1600407226 & 374.870882693349 \tabularnewline
0.5 & 8775.50486289204 & 389.763485509166 \tabularnewline
0.51 & 8847.284404038 & 402.139767210960 \tabularnewline
0.52 & 8921.02411197072 & 411.502367790575 \tabularnewline
0.53 & 8996.1750829436 & 417.450229083557 \tabularnewline
0.54 & 9072.1361240537 & 419.738398737417 \tabularnewline
0.55 & 9148.28263406959 & 418.297568831316 \tabularnewline
0.56 & 9224.00066332379 & 413.267175879744 \tabularnewline
0.57 & 9298.72370179406 & 405.014230372298 \tabularnewline
0.58 & 9371.96920810164 & 394.054813726311 \tabularnewline
0.59 & 9443.37172459517 & 381.183371002538 \tabularnewline
0.6 & 9512.70965619023 & 367.228742299421 \tabularnewline
0.61 & 9579.9233901149 & 353.143320773456 \tabularnewline
0.62 & 9645.12331311074 & 339.89988447759 \tabularnewline
0.63 & 9708.5873172076 & 328.428130115523 \tabularnewline
0.64 & 9770.74842815053 & 319.559226131324 \tabularnewline
0.65 & 9832.17408483984 & 313.958312369781 \tabularnewline
0.66 & 9893.53918647383 & 312.101305801332 \tabularnewline
0.67 & 9955.59516452426 & 314.237342266981 \tabularnewline
0.68 & 10019.1369320598 & 320.428474567103 \tabularnewline
0.69 & 10084.9686082476 & 330.498485896579 \tabularnewline
0.7 & 10153.8675575920 & 344.094194251483 \tabularnewline
0.71 & 10226.5448708553 & 360.707301731716 \tabularnewline
0.72 & 10303.5995085874 & 379.634406451923 \tabularnewline
0.73 & 10385.463626237 & 399.945647114538 \tabularnewline
0.74 & 10472.3387437855 & 420.421256587937 \tabularnewline
0.75 & 10564.1266927276 & 439.564570481779 \tabularnewline
0.76 & 10660.3652361854 & 455.57194560337 \tabularnewline
0.77 & 10760.184523242 & 466.481346767322 \tabularnewline
0.78 & 10862.3048233328 & 470.384099253805 \tabularnewline
0.79 & 10965.0956611625 & 465.72677448249 \tabularnewline
0.8 & 11066.7095826699 & 451.683742306692 \tabularnewline
0.81 & 11165.2902535326 & 428.476067828644 \tabularnewline
0.82 & 11259.2370431587 & 397.555855229959 \tabularnewline
0.83 & 11347.4917800201 & 361.683593919604 \tabularnewline
0.84 & 11429.8040218604 & 324.625096650132 \tabularnewline
0.85 & 11506.9334943032 & 290.910995077443 \tabularnewline
0.86 & 11580.7630538125 & 265.271988589825 \tabularnewline
0.87 & 11654.3186396664 & 252.116539906138 \tabularnewline
0.88 & 11731.7159441481 & 254.714838692087 \tabularnewline
0.89 & 11818.0647503157 & 274.543490638838 \tabularnewline
0.9 & 11919.3436897530 & 311.33921145886 \tabularnewline
0.91 & 12042.1889840593 & 363.71126895394 \tabularnewline
0.92 & 12193.4114309087 & 429.227295087595 \tabularnewline
0.93 & 12378.9181366516 & 502.865797626345 \tabularnewline
0.94 & 12601.7444183284 & 573.922075866559 \tabularnewline
0.95 & 12859.3593028444 & 623.261379194030 \tabularnewline
0.96 & 13141.2959813435 & 625.643512384492 \tabularnewline
0.97 & 13428.5641339735 & 562.114025631546 \tabularnewline
0.98 & 13694.6272161301 & 442.164855300548 \tabularnewline
0.99 & 13905.4576065553 & 322.908174084529 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=83078&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]6228.2228722383[/C][C]305.6947433618[/C][/ROW]
[ROW][C]0.02[/C][C]6380.67036113135[/C][C]250.090117130881[/C][/ROW]
[ROW][C]0.03[/C][C]6524.98323383732[/C][C]205.767038450238[/C][/ROW]
[ROW][C]0.04[/C][C]6642.40958044965[/C][C]181.486950320737[/C][/ROW]
[ROW][C]0.05[/C][C]6737.03465916695[/C][C]176.993483515003[/C][/ROW]
[ROW][C]0.06[/C][C]6818.3688292008[/C][C]184.951320104421[/C][/ROW]
[ROW][C]0.07[/C][C]6893.43204943279[/C][C]196.436580663242[/C][/ROW]
[ROW][C]0.08[/C][C]6965.5441038976[/C][C]205.384215671949[/C][/ROW]
[ROW][C]0.09[/C][C]7035.42609655822[/C][C]209.023258328268[/C][/ROW]
[ROW][C]0.1[/C][C]7102.52993268843[/C][C]206.951740499623[/C][/ROW]
[ROW][C]0.11[/C][C]7165.99977863259[/C][C]200.330451220940[/C][/ROW]
[ROW][C]0.12[/C][C]7225.21254120697[/C][C]191.161058016538[/C][/ROW]
[ROW][C]0.13[/C][C]7279.98594902933[/C][C]181.579007859575[/C][/ROW]
[ROW][C]0.14[/C][C]7330.56338688495[/C][C]173.241977082998[/C][/ROW]
[ROW][C]0.15[/C][C]7377.47701785667[/C][C]166.951543238740[/C][/ROW]
[ROW][C]0.16[/C][C]7421.37507969318[/C][C]162.698969625663[/C][/ROW]
[ROW][C]0.17[/C][C]7462.8757041419[/C][C]159.921289200416[/C][/ROW]
[ROW][C]0.18[/C][C]7502.47979097808[/C][C]157.917206937237[/C][/ROW]
[ROW][C]0.19[/C][C]7540.54643173428[/C][C]156.180874204893[/C][/ROW]
[ROW][C]0.2[/C][C]7577.31399192461[/C][C]154.470250110971[/C][/ROW]
[ROW][C]0.21[/C][C]7612.94201959469[/C][C]152.783534427953[/C][/ROW]
[ROW][C]0.22[/C][C]7647.55215770541[/C][C]151.260350344967[/C][/ROW]
[ROW][C]0.23[/C][C]7681.25535443214[/C][C]150.038253910920[/C][/ROW]
[ROW][C]0.24[/C][C]7714.1625861473[/C][C]149.172668555139[/C][/ROW]
[ROW][C]0.25[/C][C]7746.38337325489[/C][C]148.661466210355[/C][/ROW]
[ROW][C]0.26[/C][C]7778.0192691997[/C][C]148.397434935399[/C][/ROW]
[ROW][C]0.27[/C][C]7809.15884470331[/C][C]148.298946639524[/C][/ROW]
[ROW][C]0.28[/C][C]7839.87803796658[/C][C]148.290313679823[/C][/ROW]
[ROW][C]0.29[/C][C]7870.2467030609[/C][C]148.401314140872[/C][/ROW]
[ROW][C]0.3[/C][C]7900.33985158351[/C][C]148.704737982130[/C][/ROW]
[ROW][C]0.31[/C][C]7930.25087554142[/C][C]149.395269933333[/C][/ROW]
[ROW][C]0.32[/C][C]7960.10387975082[/C][C]150.702285102487[/C][/ROW]
[ROW][C]0.33[/C][C]7990.06280344206[/C][C]152.916065029084[/C][/ROW]
[ROW][C]0.34[/C][C]8020.33590379726[/C][C]156.341823304843[/C][/ROW]
[ROW][C]0.35[/C][C]8051.1751242244[/C][C]161.226351958387[/C][/ROW]
[ROW][C]0.36[/C][C]8082.87070003197[/C][C]167.81527295005[/C][/ROW]
[ROW][C]0.37[/C][C]8115.74196626068[/C][C]176.220765835757[/C][/ROW]
[ROW][C]0.38[/C][C]8150.12567676151[/C][C]186.513929074523[/C][/ROW]
[ROW][C]0.39[/C][C]8186.36320452256[/C][C]198.652407480814[/C][/ROW]
[ROW][C]0.4[/C][C]8224.78779361446[/C][C]212.549165388335[/C][/ROW]
[ROW][C]0.41[/C][C]8265.71264088384[/C][C]228.046286124128[/C][/ROW]
[ROW][C]0.42[/C][C]8309.42010835777[/C][C]244.921169980011[/C][/ROW]
[ROW][C]0.43[/C][C]8356.15193135385[/C][C]262.947831980045[/C][/ROW]
[ROW][C]0.44[/C][C]8406.10000642796[/C][C]281.813565224303[/C][/ROW]
[ROW][C]0.45[/C][C]8459.39729077951[/C][C]301.176120456493[/C][/ROW]
[ROW][C]0.46[/C][C]8516.10853654744[/C][C]320.647305280356[/C][/ROW]
[ROW][C]0.47[/C][C]8576.22097695499[/C][C]339.762023239382[/C][/ROW]
[ROW][C]0.48[/C][C]8639.63558687328[/C][C]358.017188809771[/C][/ROW]
[ROW][C]0.49[/C][C]8706.1600407226[/C][C]374.870882693349[/C][/ROW]
[ROW][C]0.5[/C][C]8775.50486289204[/C][C]389.763485509166[/C][/ROW]
[ROW][C]0.51[/C][C]8847.284404038[/C][C]402.139767210960[/C][/ROW]
[ROW][C]0.52[/C][C]8921.02411197072[/C][C]411.502367790575[/C][/ROW]
[ROW][C]0.53[/C][C]8996.1750829436[/C][C]417.450229083557[/C][/ROW]
[ROW][C]0.54[/C][C]9072.1361240537[/C][C]419.738398737417[/C][/ROW]
[ROW][C]0.55[/C][C]9148.28263406959[/C][C]418.297568831316[/C][/ROW]
[ROW][C]0.56[/C][C]9224.00066332379[/C][C]413.267175879744[/C][/ROW]
[ROW][C]0.57[/C][C]9298.72370179406[/C][C]405.014230372298[/C][/ROW]
[ROW][C]0.58[/C][C]9371.96920810164[/C][C]394.054813726311[/C][/ROW]
[ROW][C]0.59[/C][C]9443.37172459517[/C][C]381.183371002538[/C][/ROW]
[ROW][C]0.6[/C][C]9512.70965619023[/C][C]367.228742299421[/C][/ROW]
[ROW][C]0.61[/C][C]9579.9233901149[/C][C]353.143320773456[/C][/ROW]
[ROW][C]0.62[/C][C]9645.12331311074[/C][C]339.89988447759[/C][/ROW]
[ROW][C]0.63[/C][C]9708.5873172076[/C][C]328.428130115523[/C][/ROW]
[ROW][C]0.64[/C][C]9770.74842815053[/C][C]319.559226131324[/C][/ROW]
[ROW][C]0.65[/C][C]9832.17408483984[/C][C]313.958312369781[/C][/ROW]
[ROW][C]0.66[/C][C]9893.53918647383[/C][C]312.101305801332[/C][/ROW]
[ROW][C]0.67[/C][C]9955.59516452426[/C][C]314.237342266981[/C][/ROW]
[ROW][C]0.68[/C][C]10019.1369320598[/C][C]320.428474567103[/C][/ROW]
[ROW][C]0.69[/C][C]10084.9686082476[/C][C]330.498485896579[/C][/ROW]
[ROW][C]0.7[/C][C]10153.8675575920[/C][C]344.094194251483[/C][/ROW]
[ROW][C]0.71[/C][C]10226.5448708553[/C][C]360.707301731716[/C][/ROW]
[ROW][C]0.72[/C][C]10303.5995085874[/C][C]379.634406451923[/C][/ROW]
[ROW][C]0.73[/C][C]10385.463626237[/C][C]399.945647114538[/C][/ROW]
[ROW][C]0.74[/C][C]10472.3387437855[/C][C]420.421256587937[/C][/ROW]
[ROW][C]0.75[/C][C]10564.1266927276[/C][C]439.564570481779[/C][/ROW]
[ROW][C]0.76[/C][C]10660.3652361854[/C][C]455.57194560337[/C][/ROW]
[ROW][C]0.77[/C][C]10760.184523242[/C][C]466.481346767322[/C][/ROW]
[ROW][C]0.78[/C][C]10862.3048233328[/C][C]470.384099253805[/C][/ROW]
[ROW][C]0.79[/C][C]10965.0956611625[/C][C]465.72677448249[/C][/ROW]
[ROW][C]0.8[/C][C]11066.7095826699[/C][C]451.683742306692[/C][/ROW]
[ROW][C]0.81[/C][C]11165.2902535326[/C][C]428.476067828644[/C][/ROW]
[ROW][C]0.82[/C][C]11259.2370431587[/C][C]397.555855229959[/C][/ROW]
[ROW][C]0.83[/C][C]11347.4917800201[/C][C]361.683593919604[/C][/ROW]
[ROW][C]0.84[/C][C]11429.8040218604[/C][C]324.625096650132[/C][/ROW]
[ROW][C]0.85[/C][C]11506.9334943032[/C][C]290.910995077443[/C][/ROW]
[ROW][C]0.86[/C][C]11580.7630538125[/C][C]265.271988589825[/C][/ROW]
[ROW][C]0.87[/C][C]11654.3186396664[/C][C]252.116539906138[/C][/ROW]
[ROW][C]0.88[/C][C]11731.7159441481[/C][C]254.714838692087[/C][/ROW]
[ROW][C]0.89[/C][C]11818.0647503157[/C][C]274.543490638838[/C][/ROW]
[ROW][C]0.9[/C][C]11919.3436897530[/C][C]311.33921145886[/C][/ROW]
[ROW][C]0.91[/C][C]12042.1889840593[/C][C]363.71126895394[/C][/ROW]
[ROW][C]0.92[/C][C]12193.4114309087[/C][C]429.227295087595[/C][/ROW]
[ROW][C]0.93[/C][C]12378.9181366516[/C][C]502.865797626345[/C][/ROW]
[ROW][C]0.94[/C][C]12601.7444183284[/C][C]573.922075866559[/C][/ROW]
[ROW][C]0.95[/C][C]12859.3593028444[/C][C]623.261379194030[/C][/ROW]
[ROW][C]0.96[/C][C]13141.2959813435[/C][C]625.643512384492[/C][/ROW]
[ROW][C]0.97[/C][C]13428.5641339735[/C][C]562.114025631546[/C][/ROW]
[ROW][C]0.98[/C][C]13694.6272161301[/C][C]442.164855300548[/C][/ROW]
[ROW][C]0.99[/C][C]13905.4576065553[/C][C]322.908174084529[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=83078&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=83078&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
0.016228.2228722383305.6947433618
0.026380.67036113135250.090117130881
0.036524.98323383732205.767038450238
0.046642.40958044965181.486950320737
0.056737.03465916695176.993483515003
0.066818.3688292008184.951320104421
0.076893.43204943279196.436580663242
0.086965.5441038976205.384215671949
0.097035.42609655822209.023258328268
0.17102.52993268843206.951740499623
0.117165.99977863259200.330451220940
0.127225.21254120697191.161058016538
0.137279.98594902933181.579007859575
0.147330.56338688495173.241977082998
0.157377.47701785667166.951543238740
0.167421.37507969318162.698969625663
0.177462.8757041419159.921289200416
0.187502.47979097808157.917206937237
0.197540.54643173428156.180874204893
0.27577.31399192461154.470250110971
0.217612.94201959469152.783534427953
0.227647.55215770541151.260350344967
0.237681.25535443214150.038253910920
0.247714.1625861473149.172668555139
0.257746.38337325489148.661466210355
0.267778.0192691997148.397434935399
0.277809.15884470331148.298946639524
0.287839.87803796658148.290313679823
0.297870.2467030609148.401314140872
0.37900.33985158351148.704737982130
0.317930.25087554142149.395269933333
0.327960.10387975082150.702285102487
0.337990.06280344206152.916065029084
0.348020.33590379726156.341823304843
0.358051.1751242244161.226351958387
0.368082.87070003197167.81527295005
0.378115.74196626068176.220765835757
0.388150.12567676151186.513929074523
0.398186.36320452256198.652407480814
0.48224.78779361446212.549165388335
0.418265.71264088384228.046286124128
0.428309.42010835777244.921169980011
0.438356.15193135385262.947831980045
0.448406.10000642796281.813565224303
0.458459.39729077951301.176120456493
0.468516.10853654744320.647305280356
0.478576.22097695499339.762023239382
0.488639.63558687328358.017188809771
0.498706.1600407226374.870882693349
0.58775.50486289204389.763485509166
0.518847.284404038402.139767210960
0.528921.02411197072411.502367790575
0.538996.1750829436417.450229083557
0.549072.1361240537419.738398737417
0.559148.28263406959418.297568831316
0.569224.00066332379413.267175879744
0.579298.72370179406405.014230372298
0.589371.96920810164394.054813726311
0.599443.37172459517381.183371002538
0.69512.70965619023367.228742299421
0.619579.9233901149353.143320773456
0.629645.12331311074339.89988447759
0.639708.5873172076328.428130115523
0.649770.74842815053319.559226131324
0.659832.17408483984313.958312369781
0.669893.53918647383312.101305801332
0.679955.59516452426314.237342266981
0.6810019.1369320598320.428474567103
0.6910084.9686082476330.498485896579
0.710153.8675575920344.094194251483
0.7110226.5448708553360.707301731716
0.7210303.5995085874379.634406451923
0.7310385.463626237399.945647114538
0.7410472.3387437855420.421256587937
0.7510564.1266927276439.564570481779
0.7610660.3652361854455.57194560337
0.7710760.184523242466.481346767322
0.7810862.3048233328470.384099253805
0.7910965.0956611625465.72677448249
0.811066.7095826699451.683742306692
0.8111165.2902535326428.476067828644
0.8211259.2370431587397.555855229959
0.8311347.4917800201361.683593919604
0.8411429.8040218604324.625096650132
0.8511506.9334943032290.910995077443
0.8611580.7630538125265.271988589825
0.8711654.3186396664252.116539906138
0.8811731.7159441481254.714838692087
0.8911818.0647503157274.543490638838
0.911919.3436897530311.33921145886
0.9112042.1889840593363.71126895394
0.9212193.4114309087429.227295087595
0.9312378.9181366516502.865797626345
0.9412601.7444183284573.922075866559
0.9512859.3593028444623.261379194030
0.9613141.2959813435625.643512384492
0.9713428.5641339735562.114025631546
0.9813694.6272161301442.164855300548
0.9913905.4576065553322.908174084529


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = grey ;
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')