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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 computationTue, 01 Mar 2016 18:19:08 +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/2016/Mar/01/t145685639635n7n8x1c1bwq2w.htm/, Retrieved Tue, 07 May 2024 21:54:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=293210, Retrieved Tue, 07 May 2024 21:54:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact63

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Harrell-Davis Quantiles] [harrel-davis Quan...] [2016-03-01 18:19:08] [d7adcc7732e5b057da1b42af54844e1a] [Current]
- R P     [Harrell-Davis Quantiles] [harrell davis qwa...] [2016-03-01 18:26:14] [4c392b130fccc63297597dd6ffb6df17]
- R P     [Harrell-Davis Quantiles] [harrel davis perc...] [2016-03-01 18:31:03] [4c392b130fccc63297597dd6ffb6df17]
-   PD    [Harrell-Davis Quantiles] [harrel davis qwan...] [2016-03-01 18:44:23] [4c392b130fccc63297597dd6ffb6df17]
-   PD    [Harrell-Davis Quantiles] [harrel davis perc...] [2016-03-01 18:47:51] [4c392b130fccc63297597dd6ffb6df17]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6678
6554
6513
6210
5928
6268
5582
5869
5764
6082
6062
6810
6727
6537
6175
6014
6109

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'George Udny Yule' @ yule.wessa.net

\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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293210&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293210&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293210&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'George Udny Yule' @ yule.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.015590.86594540157167.992163320739
0.025602.68453243306163.677261895139
0.035617.11683962091158.562700727455
0.045633.71543991687152.908357425366
0.055651.98023970707146.98841816936
0.065671.40619718965141.055243316856
0.075691.5200001211135.31659639203
0.085711.90492193312129.929833070617
0.095732.21464202406124.989693270259
0.15752.17779263569120.543656951177
0.115771.59545145621116.59307076915
0.125790.3338526186113.111155860794
0.135808.31436876642110.049507025395
0.145825.50244313427107.356535330339
0.155841.89672017111104.97150279154
0.165857.51920561188102.836948206866
0.175872.40692493741100.897231571341
0.185886.6052633758199.1013328808199
0.195900.162964894197.4010309281037
0.25913.1286350764295.7577279560726
0.215925.548520619494.1367737777623
0.225937.4653116210392.5101877554026
0.235948.9177176947790.8659327175627
0.245959.9405930621189.1950842637887
0.255970.5654197019587.4983619811928
0.265980.8209946143585.7854258563444
0.275990.734202919784.077065693679
0.286000.3307903872882.3968780586402
0.296009.6360759607580.7759260027122
0.36018.6755667150279.251366282344
0.316027.4754547556977.8622012509304
0.326036.0629884258276.6474938274599
0.336044.4667194589475.6438831627355
0.346052.7166340288874.8921964322301
0.356060.8441795458174.4222570770657
0.366068.8822010055374.2598573189471
0.376076.8648011213874.4361303470661
0.386084.8271377136474.9611940223578
0.396092.8051702284775.8470440915757
0.46100.8353651167577.1025646882866
0.416108.9543674216378.7261746652216
0.426117.1986435845480.716074741533
0.436125.6040984460383.0609714164862
0.446134.2056679198685.7533631913088
0.456143.0368880404888.7773348693377
0.466152.129441152392.1121284434376
0.476161.5126809807695.7358670977319
0.486171.2131401794899.6189546124452
0.496181.25402658336103.728025028483
0.56191.65471763273108.021202657557
0.516202.43026601527112.453483730559
0.526213.59093318552116.969639609014
0.536225.14177071182121.504872651667
0.546237.08227199327125.995925212753
0.556249.40611841878130.36784011909
0.566262.10104417788134.544282675039
0.576275.14884241865138.444153296201
0.586288.52553211414141.995275879076
0.596302.20169980157145.119217848041
0.66316.14302338974147.744777380926
0.616330.31097673394149.813773345715
0.626344.66370404834151.27407861996
0.636359.15704299813152.088311873841
0.646373.74566514243152.234676171679
0.656388.3842930221151.709691442219
0.666403.02894538221150.526648667823
0.676417.63815654481148.716424366764
0.686432.17411348311146.332677016321
0.696446.60365522019143.441850039207
0.76460.89908409197140.128480094283
0.716475.03874720227136.488066996469
0.726489.00735874382132.62155529014
0.736502.79604907782128.637293369121
0.746516.40214348128124.639178540004
0.756529.82869084111120.720004008018
0.766543.08377854177116.960715446216
0.776556.17968239569113.418142061674
0.786569.13190769257110.126699672476
0.796581.95817745644107.090502566008
0.86594.67741540689104.290300494124
0.816607.30875330702101.681282534943
0.826619.8705658687199.2051966659728
0.836632.3795031913896.7957927392477
0.846644.8494546533894.3911363018282
0.856657.2903450463491.9411823006675
0.866669.7066412504389.4196099017955
0.876682.0954451149386.8289433756616
0.886694.4440752984584.2077649018884
0.896706.7271067059181.6291563699808
0.96718.9029470589579.1984330226788
0.916730.9101868121877.0448449651319
0.926742.6641534230675.3010386771196
0.936754.0543149324274.0823011910513
0.946764.9433785033673.459188120588
0.956775.1690706508273.4362866840451
0.966784.5496093538273.9449401244641
0.976792.8937204998874.850311259195
0.986800.0156538620175.9725053138825
0.996805.754979746777.119547389147

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 5590.86594540157 & 167.992163320739 \tabularnewline
0.02 & 5602.68453243306 & 163.677261895139 \tabularnewline
0.03 & 5617.11683962091 & 158.562700727455 \tabularnewline
0.04 & 5633.71543991687 & 152.908357425366 \tabularnewline
0.05 & 5651.98023970707 & 146.98841816936 \tabularnewline
0.06 & 5671.40619718965 & 141.055243316856 \tabularnewline
0.07 & 5691.5200001211 & 135.31659639203 \tabularnewline
0.08 & 5711.90492193312 & 129.929833070617 \tabularnewline
0.09 & 5732.21464202406 & 124.989693270259 \tabularnewline
0.1 & 5752.17779263569 & 120.543656951177 \tabularnewline
0.11 & 5771.59545145621 & 116.59307076915 \tabularnewline
0.12 & 5790.3338526186 & 113.111155860794 \tabularnewline
0.13 & 5808.31436876642 & 110.049507025395 \tabularnewline
0.14 & 5825.50244313427 & 107.356535330339 \tabularnewline
0.15 & 5841.89672017111 & 104.97150279154 \tabularnewline
0.16 & 5857.51920561188 & 102.836948206866 \tabularnewline
0.17 & 5872.40692493741 & 100.897231571341 \tabularnewline
0.18 & 5886.60526337581 & 99.1013328808199 \tabularnewline
0.19 & 5900.1629648941 & 97.4010309281037 \tabularnewline
0.2 & 5913.12863507642 & 95.7577279560726 \tabularnewline
0.21 & 5925.5485206194 & 94.1367737777623 \tabularnewline
0.22 & 5937.46531162103 & 92.5101877554026 \tabularnewline
0.23 & 5948.91771769477 & 90.8659327175627 \tabularnewline
0.24 & 5959.94059306211 & 89.1950842637887 \tabularnewline
0.25 & 5970.56541970195 & 87.4983619811928 \tabularnewline
0.26 & 5980.82099461435 & 85.7854258563444 \tabularnewline
0.27 & 5990.7342029197 & 84.077065693679 \tabularnewline
0.28 & 6000.33079038728 & 82.3968780586402 \tabularnewline
0.29 & 6009.63607596075 & 80.7759260027122 \tabularnewline
0.3 & 6018.67556671502 & 79.251366282344 \tabularnewline
0.31 & 6027.47545475569 & 77.8622012509304 \tabularnewline
0.32 & 6036.06298842582 & 76.6474938274599 \tabularnewline
0.33 & 6044.46671945894 & 75.6438831627355 \tabularnewline
0.34 & 6052.71663402888 & 74.8921964322301 \tabularnewline
0.35 & 6060.84417954581 & 74.4222570770657 \tabularnewline
0.36 & 6068.88220100553 & 74.2598573189471 \tabularnewline
0.37 & 6076.86480112138 & 74.4361303470661 \tabularnewline
0.38 & 6084.82713771364 & 74.9611940223578 \tabularnewline
0.39 & 6092.80517022847 & 75.8470440915757 \tabularnewline
0.4 & 6100.83536511675 & 77.1025646882866 \tabularnewline
0.41 & 6108.95436742163 & 78.7261746652216 \tabularnewline
0.42 & 6117.19864358454 & 80.716074741533 \tabularnewline
0.43 & 6125.60409844603 & 83.0609714164862 \tabularnewline
0.44 & 6134.20566791986 & 85.7533631913088 \tabularnewline
0.45 & 6143.03688804048 & 88.7773348693377 \tabularnewline
0.46 & 6152.1294411523 & 92.1121284434376 \tabularnewline
0.47 & 6161.51268098076 & 95.7358670977319 \tabularnewline
0.48 & 6171.21314017948 & 99.6189546124452 \tabularnewline
0.49 & 6181.25402658336 & 103.728025028483 \tabularnewline
0.5 & 6191.65471763273 & 108.021202657557 \tabularnewline
0.51 & 6202.43026601527 & 112.453483730559 \tabularnewline
0.52 & 6213.59093318552 & 116.969639609014 \tabularnewline
0.53 & 6225.14177071182 & 121.504872651667 \tabularnewline
0.54 & 6237.08227199327 & 125.995925212753 \tabularnewline
0.55 & 6249.40611841878 & 130.36784011909 \tabularnewline
0.56 & 6262.10104417788 & 134.544282675039 \tabularnewline
0.57 & 6275.14884241865 & 138.444153296201 \tabularnewline
0.58 & 6288.52553211414 & 141.995275879076 \tabularnewline
0.59 & 6302.20169980157 & 145.119217848041 \tabularnewline
0.6 & 6316.14302338974 & 147.744777380926 \tabularnewline
0.61 & 6330.31097673394 & 149.813773345715 \tabularnewline
0.62 & 6344.66370404834 & 151.27407861996 \tabularnewline
0.63 & 6359.15704299813 & 152.088311873841 \tabularnewline
0.64 & 6373.74566514243 & 152.234676171679 \tabularnewline
0.65 & 6388.3842930221 & 151.709691442219 \tabularnewline
0.66 & 6403.02894538221 & 150.526648667823 \tabularnewline
0.67 & 6417.63815654481 & 148.716424366764 \tabularnewline
0.68 & 6432.17411348311 & 146.332677016321 \tabularnewline
0.69 & 6446.60365522019 & 143.441850039207 \tabularnewline
0.7 & 6460.89908409197 & 140.128480094283 \tabularnewline
0.71 & 6475.03874720227 & 136.488066996469 \tabularnewline
0.72 & 6489.00735874382 & 132.62155529014 \tabularnewline
0.73 & 6502.79604907782 & 128.637293369121 \tabularnewline
0.74 & 6516.40214348128 & 124.639178540004 \tabularnewline
0.75 & 6529.82869084111 & 120.720004008018 \tabularnewline
0.76 & 6543.08377854177 & 116.960715446216 \tabularnewline
0.77 & 6556.17968239569 & 113.418142061674 \tabularnewline
0.78 & 6569.13190769257 & 110.126699672476 \tabularnewline
0.79 & 6581.95817745644 & 107.090502566008 \tabularnewline
0.8 & 6594.67741540689 & 104.290300494124 \tabularnewline
0.81 & 6607.30875330702 & 101.681282534943 \tabularnewline
0.82 & 6619.87056586871 & 99.2051966659728 \tabularnewline
0.83 & 6632.37950319138 & 96.7957927392477 \tabularnewline
0.84 & 6644.84945465338 & 94.3911363018282 \tabularnewline
0.85 & 6657.29034504634 & 91.9411823006675 \tabularnewline
0.86 & 6669.70664125043 & 89.4196099017955 \tabularnewline
0.87 & 6682.09544511493 & 86.8289433756616 \tabularnewline
0.88 & 6694.44407529845 & 84.2077649018884 \tabularnewline
0.89 & 6706.72710670591 & 81.6291563699808 \tabularnewline
0.9 & 6718.90294705895 & 79.1984330226788 \tabularnewline
0.91 & 6730.91018681218 & 77.0448449651319 \tabularnewline
0.92 & 6742.66415342306 & 75.3010386771196 \tabularnewline
0.93 & 6754.05431493242 & 74.0823011910513 \tabularnewline
0.94 & 6764.94337850336 & 73.459188120588 \tabularnewline
0.95 & 6775.16907065082 & 73.4362866840451 \tabularnewline
0.96 & 6784.54960935382 & 73.9449401244641 \tabularnewline
0.97 & 6792.89372049988 & 74.850311259195 \tabularnewline
0.98 & 6800.01565386201 & 75.9725053138825 \tabularnewline
0.99 & 6805.7549797467 & 77.119547389147 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293210&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]5590.86594540157[/C][C]167.992163320739[/C][/ROW]
[ROW][C]0.02[/C][C]5602.68453243306[/C][C]163.677261895139[/C][/ROW]
[ROW][C]0.03[/C][C]5617.11683962091[/C][C]158.562700727455[/C][/ROW]
[ROW][C]0.04[/C][C]5633.71543991687[/C][C]152.908357425366[/C][/ROW]
[ROW][C]0.05[/C][C]5651.98023970707[/C][C]146.98841816936[/C][/ROW]
[ROW][C]0.06[/C][C]5671.40619718965[/C][C]141.055243316856[/C][/ROW]
[ROW][C]0.07[/C][C]5691.5200001211[/C][C]135.31659639203[/C][/ROW]
[ROW][C]0.08[/C][C]5711.90492193312[/C][C]129.929833070617[/C][/ROW]
[ROW][C]0.09[/C][C]5732.21464202406[/C][C]124.989693270259[/C][/ROW]
[ROW][C]0.1[/C][C]5752.17779263569[/C][C]120.543656951177[/C][/ROW]
[ROW][C]0.11[/C][C]5771.59545145621[/C][C]116.59307076915[/C][/ROW]
[ROW][C]0.12[/C][C]5790.3338526186[/C][C]113.111155860794[/C][/ROW]
[ROW][C]0.13[/C][C]5808.31436876642[/C][C]110.049507025395[/C][/ROW]
[ROW][C]0.14[/C][C]5825.50244313427[/C][C]107.356535330339[/C][/ROW]
[ROW][C]0.15[/C][C]5841.89672017111[/C][C]104.97150279154[/C][/ROW]
[ROW][C]0.16[/C][C]5857.51920561188[/C][C]102.836948206866[/C][/ROW]
[ROW][C]0.17[/C][C]5872.40692493741[/C][C]100.897231571341[/C][/ROW]
[ROW][C]0.18[/C][C]5886.60526337581[/C][C]99.1013328808199[/C][/ROW]
[ROW][C]0.19[/C][C]5900.1629648941[/C][C]97.4010309281037[/C][/ROW]
[ROW][C]0.2[/C][C]5913.12863507642[/C][C]95.7577279560726[/C][/ROW]
[ROW][C]0.21[/C][C]5925.5485206194[/C][C]94.1367737777623[/C][/ROW]
[ROW][C]0.22[/C][C]5937.46531162103[/C][C]92.5101877554026[/C][/ROW]
[ROW][C]0.23[/C][C]5948.91771769477[/C][C]90.8659327175627[/C][/ROW]
[ROW][C]0.24[/C][C]5959.94059306211[/C][C]89.1950842637887[/C][/ROW]
[ROW][C]0.25[/C][C]5970.56541970195[/C][C]87.4983619811928[/C][/ROW]
[ROW][C]0.26[/C][C]5980.82099461435[/C][C]85.7854258563444[/C][/ROW]
[ROW][C]0.27[/C][C]5990.7342029197[/C][C]84.077065693679[/C][/ROW]
[ROW][C]0.28[/C][C]6000.33079038728[/C][C]82.3968780586402[/C][/ROW]
[ROW][C]0.29[/C][C]6009.63607596075[/C][C]80.7759260027122[/C][/ROW]
[ROW][C]0.3[/C][C]6018.67556671502[/C][C]79.251366282344[/C][/ROW]
[ROW][C]0.31[/C][C]6027.47545475569[/C][C]77.8622012509304[/C][/ROW]
[ROW][C]0.32[/C][C]6036.06298842582[/C][C]76.6474938274599[/C][/ROW]
[ROW][C]0.33[/C][C]6044.46671945894[/C][C]75.6438831627355[/C][/ROW]
[ROW][C]0.34[/C][C]6052.71663402888[/C][C]74.8921964322301[/C][/ROW]
[ROW][C]0.35[/C][C]6060.84417954581[/C][C]74.4222570770657[/C][/ROW]
[ROW][C]0.36[/C][C]6068.88220100553[/C][C]74.2598573189471[/C][/ROW]
[ROW][C]0.37[/C][C]6076.86480112138[/C][C]74.4361303470661[/C][/ROW]
[ROW][C]0.38[/C][C]6084.82713771364[/C][C]74.9611940223578[/C][/ROW]
[ROW][C]0.39[/C][C]6092.80517022847[/C][C]75.8470440915757[/C][/ROW]
[ROW][C]0.4[/C][C]6100.83536511675[/C][C]77.1025646882866[/C][/ROW]
[ROW][C]0.41[/C][C]6108.95436742163[/C][C]78.7261746652216[/C][/ROW]
[ROW][C]0.42[/C][C]6117.19864358454[/C][C]80.716074741533[/C][/ROW]
[ROW][C]0.43[/C][C]6125.60409844603[/C][C]83.0609714164862[/C][/ROW]
[ROW][C]0.44[/C][C]6134.20566791986[/C][C]85.7533631913088[/C][/ROW]
[ROW][C]0.45[/C][C]6143.03688804048[/C][C]88.7773348693377[/C][/ROW]
[ROW][C]0.46[/C][C]6152.1294411523[/C][C]92.1121284434376[/C][/ROW]
[ROW][C]0.47[/C][C]6161.51268098076[/C][C]95.7358670977319[/C][/ROW]
[ROW][C]0.48[/C][C]6171.21314017948[/C][C]99.6189546124452[/C][/ROW]
[ROW][C]0.49[/C][C]6181.25402658336[/C][C]103.728025028483[/C][/ROW]
[ROW][C]0.5[/C][C]6191.65471763273[/C][C]108.021202657557[/C][/ROW]
[ROW][C]0.51[/C][C]6202.43026601527[/C][C]112.453483730559[/C][/ROW]
[ROW][C]0.52[/C][C]6213.59093318552[/C][C]116.969639609014[/C][/ROW]
[ROW][C]0.53[/C][C]6225.14177071182[/C][C]121.504872651667[/C][/ROW]
[ROW][C]0.54[/C][C]6237.08227199327[/C][C]125.995925212753[/C][/ROW]
[ROW][C]0.55[/C][C]6249.40611841878[/C][C]130.36784011909[/C][/ROW]
[ROW][C]0.56[/C][C]6262.10104417788[/C][C]134.544282675039[/C][/ROW]
[ROW][C]0.57[/C][C]6275.14884241865[/C][C]138.444153296201[/C][/ROW]
[ROW][C]0.58[/C][C]6288.52553211414[/C][C]141.995275879076[/C][/ROW]
[ROW][C]0.59[/C][C]6302.20169980157[/C][C]145.119217848041[/C][/ROW]
[ROW][C]0.6[/C][C]6316.14302338974[/C][C]147.744777380926[/C][/ROW]
[ROW][C]0.61[/C][C]6330.31097673394[/C][C]149.813773345715[/C][/ROW]
[ROW][C]0.62[/C][C]6344.66370404834[/C][C]151.27407861996[/C][/ROW]
[ROW][C]0.63[/C][C]6359.15704299813[/C][C]152.088311873841[/C][/ROW]
[ROW][C]0.64[/C][C]6373.74566514243[/C][C]152.234676171679[/C][/ROW]
[ROW][C]0.65[/C][C]6388.3842930221[/C][C]151.709691442219[/C][/ROW]
[ROW][C]0.66[/C][C]6403.02894538221[/C][C]150.526648667823[/C][/ROW]
[ROW][C]0.67[/C][C]6417.63815654481[/C][C]148.716424366764[/C][/ROW]
[ROW][C]0.68[/C][C]6432.17411348311[/C][C]146.332677016321[/C][/ROW]
[ROW][C]0.69[/C][C]6446.60365522019[/C][C]143.441850039207[/C][/ROW]
[ROW][C]0.7[/C][C]6460.89908409197[/C][C]140.128480094283[/C][/ROW]
[ROW][C]0.71[/C][C]6475.03874720227[/C][C]136.488066996469[/C][/ROW]
[ROW][C]0.72[/C][C]6489.00735874382[/C][C]132.62155529014[/C][/ROW]
[ROW][C]0.73[/C][C]6502.79604907782[/C][C]128.637293369121[/C][/ROW]
[ROW][C]0.74[/C][C]6516.40214348128[/C][C]124.639178540004[/C][/ROW]
[ROW][C]0.75[/C][C]6529.82869084111[/C][C]120.720004008018[/C][/ROW]
[ROW][C]0.76[/C][C]6543.08377854177[/C][C]116.960715446216[/C][/ROW]
[ROW][C]0.77[/C][C]6556.17968239569[/C][C]113.418142061674[/C][/ROW]
[ROW][C]0.78[/C][C]6569.13190769257[/C][C]110.126699672476[/C][/ROW]
[ROW][C]0.79[/C][C]6581.95817745644[/C][C]107.090502566008[/C][/ROW]
[ROW][C]0.8[/C][C]6594.67741540689[/C][C]104.290300494124[/C][/ROW]
[ROW][C]0.81[/C][C]6607.30875330702[/C][C]101.681282534943[/C][/ROW]
[ROW][C]0.82[/C][C]6619.87056586871[/C][C]99.2051966659728[/C][/ROW]
[ROW][C]0.83[/C][C]6632.37950319138[/C][C]96.7957927392477[/C][/ROW]
[ROW][C]0.84[/C][C]6644.84945465338[/C][C]94.3911363018282[/C][/ROW]
[ROW][C]0.85[/C][C]6657.29034504634[/C][C]91.9411823006675[/C][/ROW]
[ROW][C]0.86[/C][C]6669.70664125043[/C][C]89.4196099017955[/C][/ROW]
[ROW][C]0.87[/C][C]6682.09544511493[/C][C]86.8289433756616[/C][/ROW]
[ROW][C]0.88[/C][C]6694.44407529845[/C][C]84.2077649018884[/C][/ROW]
[ROW][C]0.89[/C][C]6706.72710670591[/C][C]81.6291563699808[/C][/ROW]
[ROW][C]0.9[/C][C]6718.90294705895[/C][C]79.1984330226788[/C][/ROW]
[ROW][C]0.91[/C][C]6730.91018681218[/C][C]77.0448449651319[/C][/ROW]
[ROW][C]0.92[/C][C]6742.66415342306[/C][C]75.3010386771196[/C][/ROW]
[ROW][C]0.93[/C][C]6754.05431493242[/C][C]74.0823011910513[/C][/ROW]
[ROW][C]0.94[/C][C]6764.94337850336[/C][C]73.459188120588[/C][/ROW]
[ROW][C]0.95[/C][C]6775.16907065082[/C][C]73.4362866840451[/C][/ROW]
[ROW][C]0.96[/C][C]6784.54960935382[/C][C]73.9449401244641[/C][/ROW]
[ROW][C]0.97[/C][C]6792.89372049988[/C][C]74.850311259195[/C][/ROW]
[ROW][C]0.98[/C][C]6800.01565386201[/C][C]75.9725053138825[/C][/ROW]
[ROW][C]0.99[/C][C]6805.7549797467[/C][C]77.119547389147[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293210&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293210&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
0.015590.86594540157167.992163320739
0.025602.68453243306163.677261895139
0.035617.11683962091158.562700727455
0.045633.71543991687152.908357425366
0.055651.98023970707146.98841816936
0.065671.40619718965141.055243316856
0.075691.5200001211135.31659639203
0.085711.90492193312129.929833070617
0.095732.21464202406124.989693270259
0.15752.17779263569120.543656951177
0.115771.59545145621116.59307076915
0.125790.3338526186113.111155860794
0.135808.31436876642110.049507025395
0.145825.50244313427107.356535330339
0.155841.89672017111104.97150279154
0.165857.51920561188102.836948206866
0.175872.40692493741100.897231571341
0.185886.6052633758199.1013328808199
0.195900.162964894197.4010309281037
0.25913.1286350764295.7577279560726
0.215925.548520619494.1367737777623
0.225937.4653116210392.5101877554026
0.235948.9177176947790.8659327175627
0.245959.9405930621189.1950842637887
0.255970.5654197019587.4983619811928
0.265980.8209946143585.7854258563444
0.275990.734202919784.077065693679
0.286000.3307903872882.3968780586402
0.296009.6360759607580.7759260027122
0.36018.6755667150279.251366282344
0.316027.4754547556977.8622012509304
0.326036.0629884258276.6474938274599
0.336044.4667194589475.6438831627355
0.346052.7166340288874.8921964322301
0.356060.8441795458174.4222570770657
0.366068.8822010055374.2598573189471
0.376076.8648011213874.4361303470661
0.386084.8271377136474.9611940223578
0.396092.8051702284775.8470440915757
0.46100.8353651167577.1025646882866
0.416108.9543674216378.7261746652216
0.426117.1986435845480.716074741533
0.436125.6040984460383.0609714164862
0.446134.2056679198685.7533631913088
0.456143.0368880404888.7773348693377
0.466152.129441152392.1121284434376
0.476161.5126809807695.7358670977319
0.486171.2131401794899.6189546124452
0.496181.25402658336103.728025028483
0.56191.65471763273108.021202657557
0.516202.43026601527112.453483730559
0.526213.59093318552116.969639609014
0.536225.14177071182121.504872651667
0.546237.08227199327125.995925212753
0.556249.40611841878130.36784011909
0.566262.10104417788134.544282675039
0.576275.14884241865138.444153296201
0.586288.52553211414141.995275879076
0.596302.20169980157145.119217848041
0.66316.14302338974147.744777380926
0.616330.31097673394149.813773345715
0.626344.66370404834151.27407861996
0.636359.15704299813152.088311873841
0.646373.74566514243152.234676171679
0.656388.3842930221151.709691442219
0.666403.02894538221150.526648667823
0.676417.63815654481148.716424366764
0.686432.17411348311146.332677016321
0.696446.60365522019143.441850039207
0.76460.89908409197140.128480094283
0.716475.03874720227136.488066996469
0.726489.00735874382132.62155529014
0.736502.79604907782128.637293369121
0.746516.40214348128124.639178540004
0.756529.82869084111120.720004008018
0.766543.08377854177116.960715446216
0.776556.17968239569113.418142061674
0.786569.13190769257110.126699672476
0.796581.95817745644107.090502566008
0.86594.67741540689104.290300494124
0.816607.30875330702101.681282534943
0.826619.8705658687199.2051966659728
0.836632.3795031913896.7957927392477
0.846644.8494546533894.3911363018282
0.856657.2903450463491.9411823006675
0.866669.7066412504389.4196099017955
0.876682.0954451149386.8289433756616
0.886694.4440752984584.2077649018884
0.896706.7271067059181.6291563699808
0.96718.9029470589579.1984330226788
0.916730.9101868121877.0448449651319
0.926742.6641534230675.3010386771196
0.936754.0543149324274.0823011910513
0.946764.9433785033673.459188120588
0.956775.1690706508273.4362866840451
0.966784.5496093538273.9449401244641
0.976792.8937204998874.850311259195
0.986800.0156538620175.9725053138825
0.996805.754979746777.119547389147


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')