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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, 10 Mar 2010 02:36:53 -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/2010/Mar/10/t1268214043dmuhlgtdgfqieec.htm/, Retrieved Sat, 23 Sep 2023 11:16:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=74242, Retrieved Sat, 23 Sep 2023 11:16:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W42
Estimated Impact180

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] [Decielen Witte wi...] [2010-03-10 09:32:23] [2b8250bcc85b616779369dc5805990fc]
-   P     [Harrell-Davis Quantiles] [Percentielen witt...] [2010-03-10 09:36:53] [03859715711bd3369851d387eaa83ba4] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1954
2302
3054
2414
2226
2725
2589
3470
2400
3180
4009
3924
2072
2434
2956
2828
2687
2629
3150
4119
3030
3055
3821
4001
2529
2472
3134
2789
2758
2993
3282
3437
2804
3076
3782
3889
2271
2452
3084
2522
2769
3438
2839
3746
2632
2851
3871
3618
2389
2344
2678
2492
2858
2246
2800
3869
3007
3023
3907
4209
2353
2570
2903
2910
3782
2759
2931
3641
2794
3070
3576
4106
2452
2206
2488
2416
2534
2521
3093
3903
2907
3025
3812
4209

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=74242&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=74242&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74242&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
0.012004.11728482149113.474995431469
0.022076.95589576216104.591889705879
0.032143.5349279713586.554717985367
0.042194.1757763307368.0529882560733
0.052231.2418213042757.6758623311172
0.062259.9761536848255.2361164735742
0.072284.4257365496756.0489551573146
0.082306.6858767643556.6803641386853
0.092327.446432396355.8583332889791
0.12346.7346040818653.6138594624421
0.112364.4294604639250.5269370664841
0.122380.5023026355747.2778350018946
0.132395.0727520798644.4370798904336
0.142408.3759398476942.3587207293974
0.152420.7033018864941.1713892058879
0.162432.3491487731240.8246656675966
0.172443.5758248998041.1784016428255
0.182454.5994022428342.0757173235495
0.192465.5920469025943.4123396525678
0.22476.6944718483245.1594106128406
0.212488.0313261704347.359171132367
0.222499.7234077278750.0772265489463
0.232511.8926818933353.3753647654772
0.242524.6586785715757.2624235572613
0.252538.1273696764161.6380963292263
0.262552.3756025511166.3096322509966
0.272567.4352084684971.0047528004306
0.282583.2808638404775.3969445862643
0.292599.8247772010379.162688638298
0.32616.9196725830582.0270316399486
0.312634.3698153044983.7840086930376
0.322651.9483978409884.3250068511136
0.332669.4187123270983.644183653152
0.342686.5562209714781.8634879740854
0.352703.1687926980179.1684435288614
0.362719.1128506576475.8489136366647
0.372734.3038394435272.1995210927955
0.382748.7201849325968.5633265089541
0.392762.4007204504865.2519213616843
0.42775.436321434962.5228605615748
0.412787.9571376079160.5616756277048
0.422800.1172394655459.4593066350179
0.432812.0786306254759.210913036296
0.442823.9964008649759.720774132678
0.452836.0063596744560.8549757612226
0.462848.215912554462.4188463446603
0.472860.6983690950164.2222364064801
0.482873.4904385050466.0704235422828
0.492886.5924583110767.778080331034
0.52899.9709230254269.1856908190834
0.512913.5630635148770.1629817332927
0.522927.2834563023970.5948124553405
0.532941.0327897793270.4384705034629
0.542954.7088942552269.6844976457141
0.552968.2199360224968.403389665698
0.562981.4993329157666.7546847921691
0.572994.5215625267664.968578161228
0.583007.3176932057263.3687551979046
0.593019.9892184160562.3512865278889
0.63032.7186088795462.375401985914
0.613045.7748784192263.931774633051
0.623059.5123791269267.4643435386092
0.633074.3610699271273.3465849252702
0.643090.8068057470681.7718912542875
0.653109.3609850681592.7226225705507
0.663130.52031870737105.944998170959
0.673154.71948502409120.937164441988
0.683182.28165740748136.962053397163
0.693213.37368517329153.115314331270
0.73247.97332279523168.388938110451
0.713285.85476690165181.776864756997
0.723326.59581696552192.414986705631
0.733369.60585445597199.657792896995
0.743414.16975241568203.133409554303
0.753459.50016320461202.760884543805
0.763504.79032413643198.701097095453
0.773549.26155181987191.304766745649
0.783592.20288660422181.037397473824
0.793633.00321458048168.458932100967
0.83671.17723748267154.190234925564
0.813706.3856487352138.903178467771
0.823738.44805072568123.321101109761
0.833767.34660870198108.139040146243
0.843793.2207120648893.994187743450
0.853816.3574988872681.3917953693031
0.863837.1869512799570.7201138500034
0.873856.2890520203162.3265869986513
0.883874.4114522671256.6246015714674
0.893892.4811922351954.1129289390532
0.93911.5809918356155.1443898983801
0.913932.8603727011559.488763837935
0.923957.372912626566.0909568498241
0.933985.8730107786773.2192635650985
0.944018.6471312980578.8724746132218
0.954055.4271488277981.3630404725579
0.964095.2382982537679.9039624050364
0.974135.7797621942673.6724180915456
0.984172.3513503028958.3923606778415
0.994198.1765362026229.4548192412200

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 2004.11728482149 & 113.474995431469 \tabularnewline
0.02 & 2076.95589576216 & 104.591889705879 \tabularnewline
0.03 & 2143.53492797135 & 86.554717985367 \tabularnewline
0.04 & 2194.17577633073 & 68.0529882560733 \tabularnewline
0.05 & 2231.24182130427 & 57.6758623311172 \tabularnewline
0.06 & 2259.97615368482 & 55.2361164735742 \tabularnewline
0.07 & 2284.42573654967 & 56.0489551573146 \tabularnewline
0.08 & 2306.68587676435 & 56.6803641386853 \tabularnewline
0.09 & 2327.4464323963 & 55.8583332889791 \tabularnewline
0.1 & 2346.73460408186 & 53.6138594624421 \tabularnewline
0.11 & 2364.42946046392 & 50.5269370664841 \tabularnewline
0.12 & 2380.50230263557 & 47.2778350018946 \tabularnewline
0.13 & 2395.07275207986 & 44.4370798904336 \tabularnewline
0.14 & 2408.37593984769 & 42.3587207293974 \tabularnewline
0.15 & 2420.70330188649 & 41.1713892058879 \tabularnewline
0.16 & 2432.34914877312 & 40.8246656675966 \tabularnewline
0.17 & 2443.57582489980 & 41.1784016428255 \tabularnewline
0.18 & 2454.59940224283 & 42.0757173235495 \tabularnewline
0.19 & 2465.59204690259 & 43.4123396525678 \tabularnewline
0.2 & 2476.69447184832 & 45.1594106128406 \tabularnewline
0.21 & 2488.03132617043 & 47.359171132367 \tabularnewline
0.22 & 2499.72340772787 & 50.0772265489463 \tabularnewline
0.23 & 2511.89268189333 & 53.3753647654772 \tabularnewline
0.24 & 2524.65867857157 & 57.2624235572613 \tabularnewline
0.25 & 2538.12736967641 & 61.6380963292263 \tabularnewline
0.26 & 2552.37560255111 & 66.3096322509966 \tabularnewline
0.27 & 2567.43520846849 & 71.0047528004306 \tabularnewline
0.28 & 2583.28086384047 & 75.3969445862643 \tabularnewline
0.29 & 2599.82477720103 & 79.162688638298 \tabularnewline
0.3 & 2616.91967258305 & 82.0270316399486 \tabularnewline
0.31 & 2634.36981530449 & 83.7840086930376 \tabularnewline
0.32 & 2651.94839784098 & 84.3250068511136 \tabularnewline
0.33 & 2669.41871232709 & 83.644183653152 \tabularnewline
0.34 & 2686.55622097147 & 81.8634879740854 \tabularnewline
0.35 & 2703.16879269801 & 79.1684435288614 \tabularnewline
0.36 & 2719.11285065764 & 75.8489136366647 \tabularnewline
0.37 & 2734.30383944352 & 72.1995210927955 \tabularnewline
0.38 & 2748.72018493259 & 68.5633265089541 \tabularnewline
0.39 & 2762.40072045048 & 65.2519213616843 \tabularnewline
0.4 & 2775.4363214349 & 62.5228605615748 \tabularnewline
0.41 & 2787.95713760791 & 60.5616756277048 \tabularnewline
0.42 & 2800.11723946554 & 59.4593066350179 \tabularnewline
0.43 & 2812.07863062547 & 59.210913036296 \tabularnewline
0.44 & 2823.99640086497 & 59.720774132678 \tabularnewline
0.45 & 2836.00635967445 & 60.8549757612226 \tabularnewline
0.46 & 2848.2159125544 & 62.4188463446603 \tabularnewline
0.47 & 2860.69836909501 & 64.2222364064801 \tabularnewline
0.48 & 2873.49043850504 & 66.0704235422828 \tabularnewline
0.49 & 2886.59245831107 & 67.778080331034 \tabularnewline
0.5 & 2899.97092302542 & 69.1856908190834 \tabularnewline
0.51 & 2913.56306351487 & 70.1629817332927 \tabularnewline
0.52 & 2927.28345630239 & 70.5948124553405 \tabularnewline
0.53 & 2941.03278977932 & 70.4384705034629 \tabularnewline
0.54 & 2954.70889425522 & 69.6844976457141 \tabularnewline
0.55 & 2968.21993602249 & 68.403389665698 \tabularnewline
0.56 & 2981.49933291576 & 66.7546847921691 \tabularnewline
0.57 & 2994.52156252676 & 64.968578161228 \tabularnewline
0.58 & 3007.31769320572 & 63.3687551979046 \tabularnewline
0.59 & 3019.98921841605 & 62.3512865278889 \tabularnewline
0.6 & 3032.71860887954 & 62.375401985914 \tabularnewline
0.61 & 3045.77487841922 & 63.931774633051 \tabularnewline
0.62 & 3059.51237912692 & 67.4643435386092 \tabularnewline
0.63 & 3074.36106992712 & 73.3465849252702 \tabularnewline
0.64 & 3090.80680574706 & 81.7718912542875 \tabularnewline
0.65 & 3109.36098506815 & 92.7226225705507 \tabularnewline
0.66 & 3130.52031870737 & 105.944998170959 \tabularnewline
0.67 & 3154.71948502409 & 120.937164441988 \tabularnewline
0.68 & 3182.28165740748 & 136.962053397163 \tabularnewline
0.69 & 3213.37368517329 & 153.115314331270 \tabularnewline
0.7 & 3247.97332279523 & 168.388938110451 \tabularnewline
0.71 & 3285.85476690165 & 181.776864756997 \tabularnewline
0.72 & 3326.59581696552 & 192.414986705631 \tabularnewline
0.73 & 3369.60585445597 & 199.657792896995 \tabularnewline
0.74 & 3414.16975241568 & 203.133409554303 \tabularnewline
0.75 & 3459.50016320461 & 202.760884543805 \tabularnewline
0.76 & 3504.79032413643 & 198.701097095453 \tabularnewline
0.77 & 3549.26155181987 & 191.304766745649 \tabularnewline
0.78 & 3592.20288660422 & 181.037397473824 \tabularnewline
0.79 & 3633.00321458048 & 168.458932100967 \tabularnewline
0.8 & 3671.17723748267 & 154.190234925564 \tabularnewline
0.81 & 3706.3856487352 & 138.903178467771 \tabularnewline
0.82 & 3738.44805072568 & 123.321101109761 \tabularnewline
0.83 & 3767.34660870198 & 108.139040146243 \tabularnewline
0.84 & 3793.22071206488 & 93.994187743450 \tabularnewline
0.85 & 3816.35749888726 & 81.3917953693031 \tabularnewline
0.86 & 3837.18695127995 & 70.7201138500034 \tabularnewline
0.87 & 3856.28905202031 & 62.3265869986513 \tabularnewline
0.88 & 3874.41145226712 & 56.6246015714674 \tabularnewline
0.89 & 3892.48119223519 & 54.1129289390532 \tabularnewline
0.9 & 3911.58099183561 & 55.1443898983801 \tabularnewline
0.91 & 3932.86037270115 & 59.488763837935 \tabularnewline
0.92 & 3957.3729126265 & 66.0909568498241 \tabularnewline
0.93 & 3985.87301077867 & 73.2192635650985 \tabularnewline
0.94 & 4018.64713129805 & 78.8724746132218 \tabularnewline
0.95 & 4055.42714882779 & 81.3630404725579 \tabularnewline
0.96 & 4095.23829825376 & 79.9039624050364 \tabularnewline
0.97 & 4135.77976219426 & 73.6724180915456 \tabularnewline
0.98 & 4172.35135030289 & 58.3923606778415 \tabularnewline
0.99 & 4198.17653620262 & 29.4548192412200 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74242&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]2004.11728482149[/C][C]113.474995431469[/C][/ROW]
[ROW][C]0.02[/C][C]2076.95589576216[/C][C]104.591889705879[/C][/ROW]
[ROW][C]0.03[/C][C]2143.53492797135[/C][C]86.554717985367[/C][/ROW]
[ROW][C]0.04[/C][C]2194.17577633073[/C][C]68.0529882560733[/C][/ROW]
[ROW][C]0.05[/C][C]2231.24182130427[/C][C]57.6758623311172[/C][/ROW]
[ROW][C]0.06[/C][C]2259.97615368482[/C][C]55.2361164735742[/C][/ROW]
[ROW][C]0.07[/C][C]2284.42573654967[/C][C]56.0489551573146[/C][/ROW]
[ROW][C]0.08[/C][C]2306.68587676435[/C][C]56.6803641386853[/C][/ROW]
[ROW][C]0.09[/C][C]2327.4464323963[/C][C]55.8583332889791[/C][/ROW]
[ROW][C]0.1[/C][C]2346.73460408186[/C][C]53.6138594624421[/C][/ROW]
[ROW][C]0.11[/C][C]2364.42946046392[/C][C]50.5269370664841[/C][/ROW]
[ROW][C]0.12[/C][C]2380.50230263557[/C][C]47.2778350018946[/C][/ROW]
[ROW][C]0.13[/C][C]2395.07275207986[/C][C]44.4370798904336[/C][/ROW]
[ROW][C]0.14[/C][C]2408.37593984769[/C][C]42.3587207293974[/C][/ROW]
[ROW][C]0.15[/C][C]2420.70330188649[/C][C]41.1713892058879[/C][/ROW]
[ROW][C]0.16[/C][C]2432.34914877312[/C][C]40.8246656675966[/C][/ROW]
[ROW][C]0.17[/C][C]2443.57582489980[/C][C]41.1784016428255[/C][/ROW]
[ROW][C]0.18[/C][C]2454.59940224283[/C][C]42.0757173235495[/C][/ROW]
[ROW][C]0.19[/C][C]2465.59204690259[/C][C]43.4123396525678[/C][/ROW]
[ROW][C]0.2[/C][C]2476.69447184832[/C][C]45.1594106128406[/C][/ROW]
[ROW][C]0.21[/C][C]2488.03132617043[/C][C]47.359171132367[/C][/ROW]
[ROW][C]0.22[/C][C]2499.72340772787[/C][C]50.0772265489463[/C][/ROW]
[ROW][C]0.23[/C][C]2511.89268189333[/C][C]53.3753647654772[/C][/ROW]
[ROW][C]0.24[/C][C]2524.65867857157[/C][C]57.2624235572613[/C][/ROW]
[ROW][C]0.25[/C][C]2538.12736967641[/C][C]61.6380963292263[/C][/ROW]
[ROW][C]0.26[/C][C]2552.37560255111[/C][C]66.3096322509966[/C][/ROW]
[ROW][C]0.27[/C][C]2567.43520846849[/C][C]71.0047528004306[/C][/ROW]
[ROW][C]0.28[/C][C]2583.28086384047[/C][C]75.3969445862643[/C][/ROW]
[ROW][C]0.29[/C][C]2599.82477720103[/C][C]79.162688638298[/C][/ROW]
[ROW][C]0.3[/C][C]2616.91967258305[/C][C]82.0270316399486[/C][/ROW]
[ROW][C]0.31[/C][C]2634.36981530449[/C][C]83.7840086930376[/C][/ROW]
[ROW][C]0.32[/C][C]2651.94839784098[/C][C]84.3250068511136[/C][/ROW]
[ROW][C]0.33[/C][C]2669.41871232709[/C][C]83.644183653152[/C][/ROW]
[ROW][C]0.34[/C][C]2686.55622097147[/C][C]81.8634879740854[/C][/ROW]
[ROW][C]0.35[/C][C]2703.16879269801[/C][C]79.1684435288614[/C][/ROW]
[ROW][C]0.36[/C][C]2719.11285065764[/C][C]75.8489136366647[/C][/ROW]
[ROW][C]0.37[/C][C]2734.30383944352[/C][C]72.1995210927955[/C][/ROW]
[ROW][C]0.38[/C][C]2748.72018493259[/C][C]68.5633265089541[/C][/ROW]
[ROW][C]0.39[/C][C]2762.40072045048[/C][C]65.2519213616843[/C][/ROW]
[ROW][C]0.4[/C][C]2775.4363214349[/C][C]62.5228605615748[/C][/ROW]
[ROW][C]0.41[/C][C]2787.95713760791[/C][C]60.5616756277048[/C][/ROW]
[ROW][C]0.42[/C][C]2800.11723946554[/C][C]59.4593066350179[/C][/ROW]
[ROW][C]0.43[/C][C]2812.07863062547[/C][C]59.210913036296[/C][/ROW]
[ROW][C]0.44[/C][C]2823.99640086497[/C][C]59.720774132678[/C][/ROW]
[ROW][C]0.45[/C][C]2836.00635967445[/C][C]60.8549757612226[/C][/ROW]
[ROW][C]0.46[/C][C]2848.2159125544[/C][C]62.4188463446603[/C][/ROW]
[ROW][C]0.47[/C][C]2860.69836909501[/C][C]64.2222364064801[/C][/ROW]
[ROW][C]0.48[/C][C]2873.49043850504[/C][C]66.0704235422828[/C][/ROW]
[ROW][C]0.49[/C][C]2886.59245831107[/C][C]67.778080331034[/C][/ROW]
[ROW][C]0.5[/C][C]2899.97092302542[/C][C]69.1856908190834[/C][/ROW]
[ROW][C]0.51[/C][C]2913.56306351487[/C][C]70.1629817332927[/C][/ROW]
[ROW][C]0.52[/C][C]2927.28345630239[/C][C]70.5948124553405[/C][/ROW]
[ROW][C]0.53[/C][C]2941.03278977932[/C][C]70.4384705034629[/C][/ROW]
[ROW][C]0.54[/C][C]2954.70889425522[/C][C]69.6844976457141[/C][/ROW]
[ROW][C]0.55[/C][C]2968.21993602249[/C][C]68.403389665698[/C][/ROW]
[ROW][C]0.56[/C][C]2981.49933291576[/C][C]66.7546847921691[/C][/ROW]
[ROW][C]0.57[/C][C]2994.52156252676[/C][C]64.968578161228[/C][/ROW]
[ROW][C]0.58[/C][C]3007.31769320572[/C][C]63.3687551979046[/C][/ROW]
[ROW][C]0.59[/C][C]3019.98921841605[/C][C]62.3512865278889[/C][/ROW]
[ROW][C]0.6[/C][C]3032.71860887954[/C][C]62.375401985914[/C][/ROW]
[ROW][C]0.61[/C][C]3045.77487841922[/C][C]63.931774633051[/C][/ROW]
[ROW][C]0.62[/C][C]3059.51237912692[/C][C]67.4643435386092[/C][/ROW]
[ROW][C]0.63[/C][C]3074.36106992712[/C][C]73.3465849252702[/C][/ROW]
[ROW][C]0.64[/C][C]3090.80680574706[/C][C]81.7718912542875[/C][/ROW]
[ROW][C]0.65[/C][C]3109.36098506815[/C][C]92.7226225705507[/C][/ROW]
[ROW][C]0.66[/C][C]3130.52031870737[/C][C]105.944998170959[/C][/ROW]
[ROW][C]0.67[/C][C]3154.71948502409[/C][C]120.937164441988[/C][/ROW]
[ROW][C]0.68[/C][C]3182.28165740748[/C][C]136.962053397163[/C][/ROW]
[ROW][C]0.69[/C][C]3213.37368517329[/C][C]153.115314331270[/C][/ROW]
[ROW][C]0.7[/C][C]3247.97332279523[/C][C]168.388938110451[/C][/ROW]
[ROW][C]0.71[/C][C]3285.85476690165[/C][C]181.776864756997[/C][/ROW]
[ROW][C]0.72[/C][C]3326.59581696552[/C][C]192.414986705631[/C][/ROW]
[ROW][C]0.73[/C][C]3369.60585445597[/C][C]199.657792896995[/C][/ROW]
[ROW][C]0.74[/C][C]3414.16975241568[/C][C]203.133409554303[/C][/ROW]
[ROW][C]0.75[/C][C]3459.50016320461[/C][C]202.760884543805[/C][/ROW]
[ROW][C]0.76[/C][C]3504.79032413643[/C][C]198.701097095453[/C][/ROW]
[ROW][C]0.77[/C][C]3549.26155181987[/C][C]191.304766745649[/C][/ROW]
[ROW][C]0.78[/C][C]3592.20288660422[/C][C]181.037397473824[/C][/ROW]
[ROW][C]0.79[/C][C]3633.00321458048[/C][C]168.458932100967[/C][/ROW]
[ROW][C]0.8[/C][C]3671.17723748267[/C][C]154.190234925564[/C][/ROW]
[ROW][C]0.81[/C][C]3706.3856487352[/C][C]138.903178467771[/C][/ROW]
[ROW][C]0.82[/C][C]3738.44805072568[/C][C]123.321101109761[/C][/ROW]
[ROW][C]0.83[/C][C]3767.34660870198[/C][C]108.139040146243[/C][/ROW]
[ROW][C]0.84[/C][C]3793.22071206488[/C][C]93.994187743450[/C][/ROW]
[ROW][C]0.85[/C][C]3816.35749888726[/C][C]81.3917953693031[/C][/ROW]
[ROW][C]0.86[/C][C]3837.18695127995[/C][C]70.7201138500034[/C][/ROW]
[ROW][C]0.87[/C][C]3856.28905202031[/C][C]62.3265869986513[/C][/ROW]
[ROW][C]0.88[/C][C]3874.41145226712[/C][C]56.6246015714674[/C][/ROW]
[ROW][C]0.89[/C][C]3892.48119223519[/C][C]54.1129289390532[/C][/ROW]
[ROW][C]0.9[/C][C]3911.58099183561[/C][C]55.1443898983801[/C][/ROW]
[ROW][C]0.91[/C][C]3932.86037270115[/C][C]59.488763837935[/C][/ROW]
[ROW][C]0.92[/C][C]3957.3729126265[/C][C]66.0909568498241[/C][/ROW]
[ROW][C]0.93[/C][C]3985.87301077867[/C][C]73.2192635650985[/C][/ROW]
[ROW][C]0.94[/C][C]4018.64713129805[/C][C]78.8724746132218[/C][/ROW]
[ROW][C]0.95[/C][C]4055.42714882779[/C][C]81.3630404725579[/C][/ROW]
[ROW][C]0.96[/C][C]4095.23829825376[/C][C]79.9039624050364[/C][/ROW]
[ROW][C]0.97[/C][C]4135.77976219426[/C][C]73.6724180915456[/C][/ROW]
[ROW][C]0.98[/C][C]4172.35135030289[/C][C]58.3923606778415[/C][/ROW]
[ROW][C]0.99[/C][C]4198.17653620262[/C][C]29.4548192412200[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74242&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74242&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
0.012004.11728482149113.474995431469
0.022076.95589576216104.591889705879
0.032143.5349279713586.554717985367
0.042194.1757763307368.0529882560733
0.052231.2418213042757.6758623311172
0.062259.9761536848255.2361164735742
0.072284.4257365496756.0489551573146
0.082306.6858767643556.6803641386853
0.092327.446432396355.8583332889791
0.12346.7346040818653.6138594624421
0.112364.4294604639250.5269370664841
0.122380.5023026355747.2778350018946
0.132395.0727520798644.4370798904336
0.142408.3759398476942.3587207293974
0.152420.7033018864941.1713892058879
0.162432.3491487731240.8246656675966
0.172443.5758248998041.1784016428255
0.182454.5994022428342.0757173235495
0.192465.5920469025943.4123396525678
0.22476.6944718483245.1594106128406
0.212488.0313261704347.359171132367
0.222499.7234077278750.0772265489463
0.232511.8926818933353.3753647654772
0.242524.6586785715757.2624235572613
0.252538.1273696764161.6380963292263
0.262552.3756025511166.3096322509966
0.272567.4352084684971.0047528004306
0.282583.2808638404775.3969445862643
0.292599.8247772010379.162688638298
0.32616.9196725830582.0270316399486
0.312634.3698153044983.7840086930376
0.322651.9483978409884.3250068511136
0.332669.4187123270983.644183653152
0.342686.5562209714781.8634879740854
0.352703.1687926980179.1684435288614
0.362719.1128506576475.8489136366647
0.372734.3038394435272.1995210927955
0.382748.7201849325968.5633265089541
0.392762.4007204504865.2519213616843
0.42775.436321434962.5228605615748
0.412787.9571376079160.5616756277048
0.422800.1172394655459.4593066350179
0.432812.0786306254759.210913036296
0.442823.9964008649759.720774132678
0.452836.0063596744560.8549757612226
0.462848.215912554462.4188463446603
0.472860.6983690950164.2222364064801
0.482873.4904385050466.0704235422828
0.492886.5924583110767.778080331034
0.52899.9709230254269.1856908190834
0.512913.5630635148770.1629817332927
0.522927.2834563023970.5948124553405
0.532941.0327897793270.4384705034629
0.542954.7088942552269.6844976457141
0.552968.2199360224968.403389665698
0.562981.4993329157666.7546847921691
0.572994.5215625267664.968578161228
0.583007.3176932057263.3687551979046
0.593019.9892184160562.3512865278889
0.63032.7186088795462.375401985914
0.613045.7748784192263.931774633051
0.623059.5123791269267.4643435386092
0.633074.3610699271273.3465849252702
0.643090.8068057470681.7718912542875
0.653109.3609850681592.7226225705507
0.663130.52031870737105.944998170959
0.673154.71948502409120.937164441988
0.683182.28165740748136.962053397163
0.693213.37368517329153.115314331270
0.73247.97332279523168.388938110451
0.713285.85476690165181.776864756997
0.723326.59581696552192.414986705631
0.733369.60585445597199.657792896995
0.743414.16975241568203.133409554303
0.753459.50016320461202.760884543805
0.763504.79032413643198.701097095453
0.773549.26155181987191.304766745649
0.783592.20288660422181.037397473824
0.793633.00321458048168.458932100967
0.83671.17723748267154.190234925564
0.813706.3856487352138.903178467771
0.823738.44805072568123.321101109761
0.833767.34660870198108.139040146243
0.843793.2207120648893.994187743450
0.853816.3574988872681.3917953693031
0.863837.1869512799570.7201138500034
0.873856.2890520203162.3265869986513
0.883874.4114522671256.6246015714674
0.893892.4811922351954.1129289390532
0.93911.5809918356155.1443898983801
0.913932.8603727011559.488763837935
0.923957.372912626566.0909568498241
0.933985.8730107786773.2192635650985
0.944018.6471312980578.8724746132218
0.954055.4271488277981.3630404725579
0.964095.2382982537679.9039624050364
0.974135.7797621942673.6724180915456
0.984172.3513503028958.3923606778415
0.994198.1765362026229.4548192412200


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')