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Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationMon, 08 Mar 2010 10:31:22 -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/08/t1268069557nx1suqnxwlhm5pi.htm/, Retrieved Fri, 28 Jan 2022 07:56:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=74166, Retrieved Fri, 28 Jan 2022 07:56:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W42
Estimated Impact124
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Harrell-Davis Quantiles] [personenwagens Jo...] [2010-03-08 17:02:10] [b67bdbe797a952b7c0d678d20cff072c]
-    D    [Harrell-Davis Quantiles] [Harrell-Davis dec...] [2010-03-08 17:31:22] [58d8a931f127f4dbe815c0a9b73ee0dc] [Current]
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Dataseries X:
22980
23275
23625
23640
23640
23835
23845
23940
24005
24055
24325
24445
24460
24490
24575
24615
24630
24635
24635
24650
24670
24680
24695
24695
24700
24730
24740
24750
24835
24840
24880
24895
24895
24930
24940
24965
24975
24985
25005
25030
25040
25045
25055
25055
25065
25090
25090
25095
25115
25115
25185
25185
25215
25220
25220
25225
25235
25235
25270
25280
25305
25335
25405
25440
25520
25550
25590
25620
25625
25625
25635
25690
25740
25880
25910
25960
25960
26015
26135
26185
26280
26280
26295
26375
26430
26465




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74166&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74166&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74166&T=0

As an alternative you can also use a 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'Gwilym Jenkins' @ 72.249.127.135







Harrell-Davis Quantiles
quantilesvaluestandard error
0.0123109.4953386267283.942604760177
0.0223295.390898917257.486920215468
0.0323461.4139821319207.920484643316
0.0423585.8275233354166.247371740003
0.0523678.7815834372154.383459921253
0.0623756.1337922275164.546528928801
0.0723828.923982882182.997912719268
0.0823902.4767352383203.490269964936
0.0923978.4283958403223.121122943072
0.124056.4492924707238.597626175471
0.1124135.0901944833246.584385671595
0.1224212.2250669642244.818781232452
0.1324285.4922535466233.294996139586
0.1424352.7789269074213.902593465809
0.1524412.6068768854189.715488414685
0.1624464.3039548520163.869290418676
0.1724507.9564385800138.930207089813
0.1824544.2215381728116.546914943725
0.1924574.098733936597.5409257778205
0.224598.730859584482.295410759261
0.2124619.264450899570.7409540978845
0.2224636.76771256762.7439869605211
0.2324652.190485191958.024279566256
0.2424666.349416997456.2364806306454
0.2524679.925832558656.9082983848946
0.2624693.468568277759.5456267506747
0.2724707.397657004963.6418316504326
0.2824722.007401481468.6192837074125
0.2924737.469499665674.0003820425822
0.324753.838391954779.2074859785148
0.3124771.061481686383.7596929785957
0.3224788.996098291687.3249094173701
0.3324807.433274624389.6213792543675
0.3424826.126281303590.5635914890632
0.3524844.820216645290.2350867991051
0.3624863.278385700888.773509506873
0.3724881.301875005886.4216538957595
0.3824898.740354879083.4698991935134
0.3924915.494149456380.1548353399265
0.424931.509390161876.6855461730728
0.4124946.76915566873.2506393940649
0.4224961.283717191969.8813425827971
0.4324975.082440537166.6666943426631
0.4424988.208822139463.6212638321593
0.4525000.718903032760.8184683637623
0.4625012.682225729958.3007429452602
0.4725024.183789098656.2515495142346
0.4825035.325210736854.6867030888859
0.4925046.223515326753.7573544900847
0.525057.006546932253.513380521721
0.5125067.804826673053.9665958044282
0.5225078.740598198755.0699506138972
0.5325089.915667037656.6544302205438
0.5425101.400288892958.5013167808288
0.5525113.225646462360.3740785114736
0.5625125.382254544761.997378744567
0.5725137.825894912963.2308498932704
0.5825150.491455792263.9636272733652
0.5925163.313512038764.1982780759501
0.625176.250919540064.1284368500121
0.6125189.31145362764.0859304181841
0.6225202.571904854864.4622092019099
0.6325216.189242024065.7634809734948
0.6425230.399472023468.4534766000173
0.6525245.502510576072.7863711362269
0.6625261.833461987078.8581653913406
0.6725279.722902464986.5115892776286
0.6825299.450825153195.3029797808106
0.6925321.2006403702104.635614167337
0.725345.0208379901113.756418005262
0.7125370.8023475631121.835491169211
0.7225398.2789088731128.086007410903
0.7325427.0554744796131.976047873890
0.7425456.6655065670133.276657791784
0.7525486.652076796132.144169060358
0.7625516.6606537634129.161746560817
0.7725546.5249257449125.377268401966
0.7825576.3232892647122.065034208406
0.7925606.3853829194120.527546229880
0.825637.2372523389121.678623440284
0.8125669.4903446674125.662184069878
0.8225703.7000906195131.779457513272
0.8325740.2370069192138.695771900793
0.8425779.2173507467144.899005145335
0.8525820.5234547942149.270735294060
0.8625863.9057642212151.412211973751
0.8725909.1117781173151.785986862191
0.8825955.9564578816151.232659880704
0.8926004.2624598111150.213141296085
0.926053.6711050325148.114428216880
0.9126103.4372673528143.256436110748
0.9226152.4102142982133.886511270040
0.9326199.3730505829119.661896607882
0.9426243.6922730130102.811044075060
0.9526285.866669462287.8152232064595
0.9626327.334993779878.2522534102656
0.9726369.191273803971.7087507667657
0.9826410.219880184960.9423244506034
0.9926445.146732582744.6067113124682

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 23109.4953386267 & 283.942604760177 \tabularnewline
0.02 & 23295.390898917 & 257.486920215468 \tabularnewline
0.03 & 23461.4139821319 & 207.920484643316 \tabularnewline
0.04 & 23585.8275233354 & 166.247371740003 \tabularnewline
0.05 & 23678.7815834372 & 154.383459921253 \tabularnewline
0.06 & 23756.1337922275 & 164.546528928801 \tabularnewline
0.07 & 23828.923982882 & 182.997912719268 \tabularnewline
0.08 & 23902.4767352383 & 203.490269964936 \tabularnewline
0.09 & 23978.4283958403 & 223.121122943072 \tabularnewline
0.1 & 24056.4492924707 & 238.597626175471 \tabularnewline
0.11 & 24135.0901944833 & 246.584385671595 \tabularnewline
0.12 & 24212.2250669642 & 244.818781232452 \tabularnewline
0.13 & 24285.4922535466 & 233.294996139586 \tabularnewline
0.14 & 24352.7789269074 & 213.902593465809 \tabularnewline
0.15 & 24412.6068768854 & 189.715488414685 \tabularnewline
0.16 & 24464.3039548520 & 163.869290418676 \tabularnewline
0.17 & 24507.9564385800 & 138.930207089813 \tabularnewline
0.18 & 24544.2215381728 & 116.546914943725 \tabularnewline
0.19 & 24574.0987339365 & 97.5409257778205 \tabularnewline
0.2 & 24598.7308595844 & 82.295410759261 \tabularnewline
0.21 & 24619.2644508995 & 70.7409540978845 \tabularnewline
0.22 & 24636.767712567 & 62.7439869605211 \tabularnewline
0.23 & 24652.1904851919 & 58.024279566256 \tabularnewline
0.24 & 24666.3494169974 & 56.2364806306454 \tabularnewline
0.25 & 24679.9258325586 & 56.9082983848946 \tabularnewline
0.26 & 24693.4685682777 & 59.5456267506747 \tabularnewline
0.27 & 24707.3976570049 & 63.6418316504326 \tabularnewline
0.28 & 24722.0074014814 & 68.6192837074125 \tabularnewline
0.29 & 24737.4694996656 & 74.0003820425822 \tabularnewline
0.3 & 24753.8383919547 & 79.2074859785148 \tabularnewline
0.31 & 24771.0614816863 & 83.7596929785957 \tabularnewline
0.32 & 24788.9960982916 & 87.3249094173701 \tabularnewline
0.33 & 24807.4332746243 & 89.6213792543675 \tabularnewline
0.34 & 24826.1262813035 & 90.5635914890632 \tabularnewline
0.35 & 24844.8202166452 & 90.2350867991051 \tabularnewline
0.36 & 24863.2783857008 & 88.773509506873 \tabularnewline
0.37 & 24881.3018750058 & 86.4216538957595 \tabularnewline
0.38 & 24898.7403548790 & 83.4698991935134 \tabularnewline
0.39 & 24915.4941494563 & 80.1548353399265 \tabularnewline
0.4 & 24931.5093901618 & 76.6855461730728 \tabularnewline
0.41 & 24946.769155668 & 73.2506393940649 \tabularnewline
0.42 & 24961.2837171919 & 69.8813425827971 \tabularnewline
0.43 & 24975.0824405371 & 66.6666943426631 \tabularnewline
0.44 & 24988.2088221394 & 63.6212638321593 \tabularnewline
0.45 & 25000.7189030327 & 60.8184683637623 \tabularnewline
0.46 & 25012.6822257299 & 58.3007429452602 \tabularnewline
0.47 & 25024.1837890986 & 56.2515495142346 \tabularnewline
0.48 & 25035.3252107368 & 54.6867030888859 \tabularnewline
0.49 & 25046.2235153267 & 53.7573544900847 \tabularnewline
0.5 & 25057.0065469322 & 53.513380521721 \tabularnewline
0.51 & 25067.8048266730 & 53.9665958044282 \tabularnewline
0.52 & 25078.7405981987 & 55.0699506138972 \tabularnewline
0.53 & 25089.9156670376 & 56.6544302205438 \tabularnewline
0.54 & 25101.4002888929 & 58.5013167808288 \tabularnewline
0.55 & 25113.2256464623 & 60.3740785114736 \tabularnewline
0.56 & 25125.3822545447 & 61.997378744567 \tabularnewline
0.57 & 25137.8258949129 & 63.2308498932704 \tabularnewline
0.58 & 25150.4914557922 & 63.9636272733652 \tabularnewline
0.59 & 25163.3135120387 & 64.1982780759501 \tabularnewline
0.6 & 25176.2509195400 & 64.1284368500121 \tabularnewline
0.61 & 25189.311453627 & 64.0859304181841 \tabularnewline
0.62 & 25202.5719048548 & 64.4622092019099 \tabularnewline
0.63 & 25216.1892420240 & 65.7634809734948 \tabularnewline
0.64 & 25230.3994720234 & 68.4534766000173 \tabularnewline
0.65 & 25245.5025105760 & 72.7863711362269 \tabularnewline
0.66 & 25261.8334619870 & 78.8581653913406 \tabularnewline
0.67 & 25279.7229024649 & 86.5115892776286 \tabularnewline
0.68 & 25299.4508251531 & 95.3029797808106 \tabularnewline
0.69 & 25321.2006403702 & 104.635614167337 \tabularnewline
0.7 & 25345.0208379901 & 113.756418005262 \tabularnewline
0.71 & 25370.8023475631 & 121.835491169211 \tabularnewline
0.72 & 25398.2789088731 & 128.086007410903 \tabularnewline
0.73 & 25427.0554744796 & 131.976047873890 \tabularnewline
0.74 & 25456.6655065670 & 133.276657791784 \tabularnewline
0.75 & 25486.652076796 & 132.144169060358 \tabularnewline
0.76 & 25516.6606537634 & 129.161746560817 \tabularnewline
0.77 & 25546.5249257449 & 125.377268401966 \tabularnewline
0.78 & 25576.3232892647 & 122.065034208406 \tabularnewline
0.79 & 25606.3853829194 & 120.527546229880 \tabularnewline
0.8 & 25637.2372523389 & 121.678623440284 \tabularnewline
0.81 & 25669.4903446674 & 125.662184069878 \tabularnewline
0.82 & 25703.7000906195 & 131.779457513272 \tabularnewline
0.83 & 25740.2370069192 & 138.695771900793 \tabularnewline
0.84 & 25779.2173507467 & 144.899005145335 \tabularnewline
0.85 & 25820.5234547942 & 149.270735294060 \tabularnewline
0.86 & 25863.9057642212 & 151.412211973751 \tabularnewline
0.87 & 25909.1117781173 & 151.785986862191 \tabularnewline
0.88 & 25955.9564578816 & 151.232659880704 \tabularnewline
0.89 & 26004.2624598111 & 150.213141296085 \tabularnewline
0.9 & 26053.6711050325 & 148.114428216880 \tabularnewline
0.91 & 26103.4372673528 & 143.256436110748 \tabularnewline
0.92 & 26152.4102142982 & 133.886511270040 \tabularnewline
0.93 & 26199.3730505829 & 119.661896607882 \tabularnewline
0.94 & 26243.6922730130 & 102.811044075060 \tabularnewline
0.95 & 26285.8666694622 & 87.8152232064595 \tabularnewline
0.96 & 26327.3349937798 & 78.2522534102656 \tabularnewline
0.97 & 26369.1912738039 & 71.7087507667657 \tabularnewline
0.98 & 26410.2198801849 & 60.9423244506034 \tabularnewline
0.99 & 26445.1467325827 & 44.6067113124682 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74166&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]23109.4953386267[/C][C]283.942604760177[/C][/ROW]
[ROW][C]0.02[/C][C]23295.390898917[/C][C]257.486920215468[/C][/ROW]
[ROW][C]0.03[/C][C]23461.4139821319[/C][C]207.920484643316[/C][/ROW]
[ROW][C]0.04[/C][C]23585.8275233354[/C][C]166.247371740003[/C][/ROW]
[ROW][C]0.05[/C][C]23678.7815834372[/C][C]154.383459921253[/C][/ROW]
[ROW][C]0.06[/C][C]23756.1337922275[/C][C]164.546528928801[/C][/ROW]
[ROW][C]0.07[/C][C]23828.923982882[/C][C]182.997912719268[/C][/ROW]
[ROW][C]0.08[/C][C]23902.4767352383[/C][C]203.490269964936[/C][/ROW]
[ROW][C]0.09[/C][C]23978.4283958403[/C][C]223.121122943072[/C][/ROW]
[ROW][C]0.1[/C][C]24056.4492924707[/C][C]238.597626175471[/C][/ROW]
[ROW][C]0.11[/C][C]24135.0901944833[/C][C]246.584385671595[/C][/ROW]
[ROW][C]0.12[/C][C]24212.2250669642[/C][C]244.818781232452[/C][/ROW]
[ROW][C]0.13[/C][C]24285.4922535466[/C][C]233.294996139586[/C][/ROW]
[ROW][C]0.14[/C][C]24352.7789269074[/C][C]213.902593465809[/C][/ROW]
[ROW][C]0.15[/C][C]24412.6068768854[/C][C]189.715488414685[/C][/ROW]
[ROW][C]0.16[/C][C]24464.3039548520[/C][C]163.869290418676[/C][/ROW]
[ROW][C]0.17[/C][C]24507.9564385800[/C][C]138.930207089813[/C][/ROW]
[ROW][C]0.18[/C][C]24544.2215381728[/C][C]116.546914943725[/C][/ROW]
[ROW][C]0.19[/C][C]24574.0987339365[/C][C]97.5409257778205[/C][/ROW]
[ROW][C]0.2[/C][C]24598.7308595844[/C][C]82.295410759261[/C][/ROW]
[ROW][C]0.21[/C][C]24619.2644508995[/C][C]70.7409540978845[/C][/ROW]
[ROW][C]0.22[/C][C]24636.767712567[/C][C]62.7439869605211[/C][/ROW]
[ROW][C]0.23[/C][C]24652.1904851919[/C][C]58.024279566256[/C][/ROW]
[ROW][C]0.24[/C][C]24666.3494169974[/C][C]56.2364806306454[/C][/ROW]
[ROW][C]0.25[/C][C]24679.9258325586[/C][C]56.9082983848946[/C][/ROW]
[ROW][C]0.26[/C][C]24693.4685682777[/C][C]59.5456267506747[/C][/ROW]
[ROW][C]0.27[/C][C]24707.3976570049[/C][C]63.6418316504326[/C][/ROW]
[ROW][C]0.28[/C][C]24722.0074014814[/C][C]68.6192837074125[/C][/ROW]
[ROW][C]0.29[/C][C]24737.4694996656[/C][C]74.0003820425822[/C][/ROW]
[ROW][C]0.3[/C][C]24753.8383919547[/C][C]79.2074859785148[/C][/ROW]
[ROW][C]0.31[/C][C]24771.0614816863[/C][C]83.7596929785957[/C][/ROW]
[ROW][C]0.32[/C][C]24788.9960982916[/C][C]87.3249094173701[/C][/ROW]
[ROW][C]0.33[/C][C]24807.4332746243[/C][C]89.6213792543675[/C][/ROW]
[ROW][C]0.34[/C][C]24826.1262813035[/C][C]90.5635914890632[/C][/ROW]
[ROW][C]0.35[/C][C]24844.8202166452[/C][C]90.2350867991051[/C][/ROW]
[ROW][C]0.36[/C][C]24863.2783857008[/C][C]88.773509506873[/C][/ROW]
[ROW][C]0.37[/C][C]24881.3018750058[/C][C]86.4216538957595[/C][/ROW]
[ROW][C]0.38[/C][C]24898.7403548790[/C][C]83.4698991935134[/C][/ROW]
[ROW][C]0.39[/C][C]24915.4941494563[/C][C]80.1548353399265[/C][/ROW]
[ROW][C]0.4[/C][C]24931.5093901618[/C][C]76.6855461730728[/C][/ROW]
[ROW][C]0.41[/C][C]24946.769155668[/C][C]73.2506393940649[/C][/ROW]
[ROW][C]0.42[/C][C]24961.2837171919[/C][C]69.8813425827971[/C][/ROW]
[ROW][C]0.43[/C][C]24975.0824405371[/C][C]66.6666943426631[/C][/ROW]
[ROW][C]0.44[/C][C]24988.2088221394[/C][C]63.6212638321593[/C][/ROW]
[ROW][C]0.45[/C][C]25000.7189030327[/C][C]60.8184683637623[/C][/ROW]
[ROW][C]0.46[/C][C]25012.6822257299[/C][C]58.3007429452602[/C][/ROW]
[ROW][C]0.47[/C][C]25024.1837890986[/C][C]56.2515495142346[/C][/ROW]
[ROW][C]0.48[/C][C]25035.3252107368[/C][C]54.6867030888859[/C][/ROW]
[ROW][C]0.49[/C][C]25046.2235153267[/C][C]53.7573544900847[/C][/ROW]
[ROW][C]0.5[/C][C]25057.0065469322[/C][C]53.513380521721[/C][/ROW]
[ROW][C]0.51[/C][C]25067.8048266730[/C][C]53.9665958044282[/C][/ROW]
[ROW][C]0.52[/C][C]25078.7405981987[/C][C]55.0699506138972[/C][/ROW]
[ROW][C]0.53[/C][C]25089.9156670376[/C][C]56.6544302205438[/C][/ROW]
[ROW][C]0.54[/C][C]25101.4002888929[/C][C]58.5013167808288[/C][/ROW]
[ROW][C]0.55[/C][C]25113.2256464623[/C][C]60.3740785114736[/C][/ROW]
[ROW][C]0.56[/C][C]25125.3822545447[/C][C]61.997378744567[/C][/ROW]
[ROW][C]0.57[/C][C]25137.8258949129[/C][C]63.2308498932704[/C][/ROW]
[ROW][C]0.58[/C][C]25150.4914557922[/C][C]63.9636272733652[/C][/ROW]
[ROW][C]0.59[/C][C]25163.3135120387[/C][C]64.1982780759501[/C][/ROW]
[ROW][C]0.6[/C][C]25176.2509195400[/C][C]64.1284368500121[/C][/ROW]
[ROW][C]0.61[/C][C]25189.311453627[/C][C]64.0859304181841[/C][/ROW]
[ROW][C]0.62[/C][C]25202.5719048548[/C][C]64.4622092019099[/C][/ROW]
[ROW][C]0.63[/C][C]25216.1892420240[/C][C]65.7634809734948[/C][/ROW]
[ROW][C]0.64[/C][C]25230.3994720234[/C][C]68.4534766000173[/C][/ROW]
[ROW][C]0.65[/C][C]25245.5025105760[/C][C]72.7863711362269[/C][/ROW]
[ROW][C]0.66[/C][C]25261.8334619870[/C][C]78.8581653913406[/C][/ROW]
[ROW][C]0.67[/C][C]25279.7229024649[/C][C]86.5115892776286[/C][/ROW]
[ROW][C]0.68[/C][C]25299.4508251531[/C][C]95.3029797808106[/C][/ROW]
[ROW][C]0.69[/C][C]25321.2006403702[/C][C]104.635614167337[/C][/ROW]
[ROW][C]0.7[/C][C]25345.0208379901[/C][C]113.756418005262[/C][/ROW]
[ROW][C]0.71[/C][C]25370.8023475631[/C][C]121.835491169211[/C][/ROW]
[ROW][C]0.72[/C][C]25398.2789088731[/C][C]128.086007410903[/C][/ROW]
[ROW][C]0.73[/C][C]25427.0554744796[/C][C]131.976047873890[/C][/ROW]
[ROW][C]0.74[/C][C]25456.6655065670[/C][C]133.276657791784[/C][/ROW]
[ROW][C]0.75[/C][C]25486.652076796[/C][C]132.144169060358[/C][/ROW]
[ROW][C]0.76[/C][C]25516.6606537634[/C][C]129.161746560817[/C][/ROW]
[ROW][C]0.77[/C][C]25546.5249257449[/C][C]125.377268401966[/C][/ROW]
[ROW][C]0.78[/C][C]25576.3232892647[/C][C]122.065034208406[/C][/ROW]
[ROW][C]0.79[/C][C]25606.3853829194[/C][C]120.527546229880[/C][/ROW]
[ROW][C]0.8[/C][C]25637.2372523389[/C][C]121.678623440284[/C][/ROW]
[ROW][C]0.81[/C][C]25669.4903446674[/C][C]125.662184069878[/C][/ROW]
[ROW][C]0.82[/C][C]25703.7000906195[/C][C]131.779457513272[/C][/ROW]
[ROW][C]0.83[/C][C]25740.2370069192[/C][C]138.695771900793[/C][/ROW]
[ROW][C]0.84[/C][C]25779.2173507467[/C][C]144.899005145335[/C][/ROW]
[ROW][C]0.85[/C][C]25820.5234547942[/C][C]149.270735294060[/C][/ROW]
[ROW][C]0.86[/C][C]25863.9057642212[/C][C]151.412211973751[/C][/ROW]
[ROW][C]0.87[/C][C]25909.1117781173[/C][C]151.785986862191[/C][/ROW]
[ROW][C]0.88[/C][C]25955.9564578816[/C][C]151.232659880704[/C][/ROW]
[ROW][C]0.89[/C][C]26004.2624598111[/C][C]150.213141296085[/C][/ROW]
[ROW][C]0.9[/C][C]26053.6711050325[/C][C]148.114428216880[/C][/ROW]
[ROW][C]0.91[/C][C]26103.4372673528[/C][C]143.256436110748[/C][/ROW]
[ROW][C]0.92[/C][C]26152.4102142982[/C][C]133.886511270040[/C][/ROW]
[ROW][C]0.93[/C][C]26199.3730505829[/C][C]119.661896607882[/C][/ROW]
[ROW][C]0.94[/C][C]26243.6922730130[/C][C]102.811044075060[/C][/ROW]
[ROW][C]0.95[/C][C]26285.8666694622[/C][C]87.8152232064595[/C][/ROW]
[ROW][C]0.96[/C][C]26327.3349937798[/C][C]78.2522534102656[/C][/ROW]
[ROW][C]0.97[/C][C]26369.1912738039[/C][C]71.7087507667657[/C][/ROW]
[ROW][C]0.98[/C][C]26410.2198801849[/C][C]60.9423244506034[/C][/ROW]
[ROW][C]0.99[/C][C]26445.1467325827[/C][C]44.6067113124682[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74166&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74166&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Harrell-Davis Quantiles
quantilesvaluestandard error
0.0123109.4953386267283.942604760177
0.0223295.390898917257.486920215468
0.0323461.4139821319207.920484643316
0.0423585.8275233354166.247371740003
0.0523678.7815834372154.383459921253
0.0623756.1337922275164.546528928801
0.0723828.923982882182.997912719268
0.0823902.4767352383203.490269964936
0.0923978.4283958403223.121122943072
0.124056.4492924707238.597626175471
0.1124135.0901944833246.584385671595
0.1224212.2250669642244.818781232452
0.1324285.4922535466233.294996139586
0.1424352.7789269074213.902593465809
0.1524412.6068768854189.715488414685
0.1624464.3039548520163.869290418676
0.1724507.9564385800138.930207089813
0.1824544.2215381728116.546914943725
0.1924574.098733936597.5409257778205
0.224598.730859584482.295410759261
0.2124619.264450899570.7409540978845
0.2224636.76771256762.7439869605211
0.2324652.190485191958.024279566256
0.2424666.349416997456.2364806306454
0.2524679.925832558656.9082983848946
0.2624693.468568277759.5456267506747
0.2724707.397657004963.6418316504326
0.2824722.007401481468.6192837074125
0.2924737.469499665674.0003820425822
0.324753.838391954779.2074859785148
0.3124771.061481686383.7596929785957
0.3224788.996098291687.3249094173701
0.3324807.433274624389.6213792543675
0.3424826.126281303590.5635914890632
0.3524844.820216645290.2350867991051
0.3624863.278385700888.773509506873
0.3724881.301875005886.4216538957595
0.3824898.740354879083.4698991935134
0.3924915.494149456380.1548353399265
0.424931.509390161876.6855461730728
0.4124946.76915566873.2506393940649
0.4224961.283717191969.8813425827971
0.4324975.082440537166.6666943426631
0.4424988.208822139463.6212638321593
0.4525000.718903032760.8184683637623
0.4625012.682225729958.3007429452602
0.4725024.183789098656.2515495142346
0.4825035.325210736854.6867030888859
0.4925046.223515326753.7573544900847
0.525057.006546932253.513380521721
0.5125067.804826673053.9665958044282
0.5225078.740598198755.0699506138972
0.5325089.915667037656.6544302205438
0.5425101.400288892958.5013167808288
0.5525113.225646462360.3740785114736
0.5625125.382254544761.997378744567
0.5725137.825894912963.2308498932704
0.5825150.491455792263.9636272733652
0.5925163.313512038764.1982780759501
0.625176.250919540064.1284368500121
0.6125189.31145362764.0859304181841
0.6225202.571904854864.4622092019099
0.6325216.189242024065.7634809734948
0.6425230.399472023468.4534766000173
0.6525245.502510576072.7863711362269
0.6625261.833461987078.8581653913406
0.6725279.722902464986.5115892776286
0.6825299.450825153195.3029797808106
0.6925321.2006403702104.635614167337
0.725345.0208379901113.756418005262
0.7125370.8023475631121.835491169211
0.7225398.2789088731128.086007410903
0.7325427.0554744796131.976047873890
0.7425456.6655065670133.276657791784
0.7525486.652076796132.144169060358
0.7625516.6606537634129.161746560817
0.7725546.5249257449125.377268401966
0.7825576.3232892647122.065034208406
0.7925606.3853829194120.527546229880
0.825637.2372523389121.678623440284
0.8125669.4903446674125.662184069878
0.8225703.7000906195131.779457513272
0.8325740.2370069192138.695771900793
0.8425779.2173507467144.899005145335
0.8525820.5234547942149.270735294060
0.8625863.9057642212151.412211973751
0.8725909.1117781173151.785986862191
0.8825955.9564578816151.232659880704
0.8926004.2624598111150.213141296085
0.926053.6711050325148.114428216880
0.9126103.4372673528143.256436110748
0.9226152.4102142982133.886511270040
0.9326199.3730505829119.661896607882
0.9426243.6922730130102.811044075060
0.9526285.866669462287.8152232064595
0.9626327.334993779878.2522534102656
0.9726369.191273803971.7087507667657
0.9826410.219880184960.9423244506034
0.9926445.146732582744.6067113124682



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')