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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_harrell_davies.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationMon, 20 Oct 2008 08:11:18 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/20/t1224511953w67ji2hu741dy8p.htm/, Retrieved Sun, 19 May 2024 12:58:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17328, Retrieved Sun, 19 May 2024 12:58:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact155

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Harrell-Davis Quantiles] [Q7 95% confidence...] [2007-10-20 15:02:46] [b731da8b544846036771bbf9bf2f34ce]
F   PD    [Harrell-Davis Quantiles] [95% Confidence In...] [2008-10-20 14:11:18] [de3f0516a1536f7c4a656924d8bc8d07] [Current]
-   P       [Harrell-Davis Quantiles] [95% betrouwbaarhe...] [2008-10-26 09:54:57] [38f43994ada0e6172896e12525dcc585]
Feedback Forum
2008-10-25 13:36:37 [Astrid Sniekers] [reply] 
De berekening van de student is fout. Hij heeft ook geen moeite gedaan om een antwoord te geven op de vraag. De juiste berekening zou zijn:
http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/19/t1224410802mm5uit8d3bd2ben.htm/

Om dit interval te kunnen berekenen laten we 2,5% wegvallen in elke staart. Zo zien we dat er 95% kans bestaat dat de waarden van de totale productie tussen 82,52 en 114,51 liggen.

82,52 verkrijgen we door in de kolom “Value” te gaan kijken bij het cijfer 0.025. 114,51 verkrijgen we door in de kolom “Value” te gaan kijken naar het cijfer 0.975.

 P (82,52 < Total Production < 114,51) = 95%
2008-10-26 17:31:26 [Kristof Augustyns] [reply] 
Dit is ongeveer hetzelfde als in 'Q6' waarbij men aan iedere kant 10% wegliet.
Nu is het gewoon aan iedere kant 2,5% om dan zo te zien hoe de waarden liggen bij de totale productie wanneer er een kans is van 95%.
De student heeft hier de berekening fout gedaan doordat hij bij 'step size' niets heeft veranderd.
Als je aan beide uiteinden 2,5 % moet weglaten oftewel 0,025; dan kan je dit niet doen door de 'step size' gelijk te stellen met 0,01.
2% oftwel 0,02 zou wel gaan omdat het in stappen gaat van 0,01; maar 0,025 gaat dan niet meer gaan.
=> 'step size' moet dus vervangen worden door 0,005 zodat er meer stapjes aan te pas komen en men aan beide kanten 2,5% kan weglaten.
https://automated.biganalytics.eu/rwasp_harrell_davies.wasp?parent=t1224511953w67ji2hu741dy8p

Er is dus 95% kans dat de waarde van de totale productie tussen 82,52 en 114,51 ligt.
P (82,51854… < Total Production < 114,51053…) = 95%

De student is hierbij dus wel totaal in de fout gegaan en een uitleg stond er net zoals in 'Q6' niet bij.
2008-10-27 11:09:32 [Thomas Beyers] [reply] 

@ K. Augustyns
De vraag was toch wel correct beantwoord! Step size moest wijzigen naar 0,005. ik heb vorig jaar ook die oefeningen meegedaan en toen moest dat wel zo !

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
110.40
96.40
101.90
106.20
81.00
94.70
101.00
109.40
102.30
90.70
96.20
96.10
106.00
103.10
102.00
104.70
86.00
92.10
106.90
112.60
101.70
92.00
97.40
97.00
105.40
102.70
98.10
104.50
87.40
89.90
109.80
111.70
98.60
96.90
95.10
97.00
112.70
102.90
97.40
111.40
87.40
96.80
114.10
110.30
103.90
101.60
94.60
95.90
104.70
102.80
98.10
113.90
80.90
95.70
113.20
105.90
108.80
102.30
99.00
100.70
115.50

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' @ 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17328&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' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17328&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17328&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' @ 72.249.76.132






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0181.25329680904381.11779486645604
0.0282.01006573354722.24893406006270
0.0383.08679671910672.90248632098292
0.0484.3097246748113.01306443451468
0.0585.51916199259832.81929371038251
0.0686.62446430306392.58088039100784
0.0787.60310768011282.43182921759067
0.0888.47230263075412.37910337912327
0.0989.26058547573232.37440618168912
0.189.99141564358462.37418160585810
0.1190.67832864172662.35550436368601
0.1291.32649382696752.31072816399791
0.1391.9361048360562.23917319869181
0.1492.50524900202662.14255204195681
0.1593.03167408357762.02327291086989
0.1693.51369204388151.88516340753100
0.1793.9506009133821.73385345376238
0.1894.34286944531071.57637388638096
0.1994.69217676022221.42006540242905
0.295.00132410074661.27198204922879
0.2195.27403024542751.13767732646087
0.2295.51464547615181.02078077295073
0.2395.72783808227240.923105464131225
0.2495.91830854785420.84475071575234
0.2596.09057167959980.785073626549223
0.2696.24882465966360.742779105897026
0.2796.39689782824510.716473770504703
0.2896.53826996773640.705222756435214
0.2996.67612238524060.708321371852601
0.396.8134051839340.725863145593432
0.3196.95289279824480.757631267035342
0.3297.0972121460330.803733370396387
0.3397.2488340472450.863457010343252
0.3497.41002579897050.935974865502641
0.3597.5827693220771.01928040224009
0.3697.76865472461441.11066829961975
0.3797.96876322968161.20676723042785
0.3898.1835559989161.30352987709458
0.3998.41278623643781.39609462111666
0.498.655450860861.4799064365811
0.4198.9097948376061.55019328884897
0.4299.17337603087981.60276267595641
0.4399.4431915603761.63468311095571
0.4499.71585891918321.64395964084749
0.4599.98783763817411.63014570022074
0.46100.2556713123761.59454451451388
0.47100.5162264363251.53957734478817
0.48100.7669044056441.46940746580755
0.49101.0058062949071.38874726029972
0.5101.2318360290211.30308488044260
0.51101.4447352202561.21782368482867
0.52101.6450508883941.13804566234769
0.53101.8340442347561.06817998580570
0.54102.0135536798861.01178394562194
0.55102.1858281053760.970945191884134
0.56102.3533468051970.946911565615199
0.57102.5186415892410.939086954786012
0.58102.6841344921140.946079715310816
0.59102.8520022386930.965400807906307
0.6103.0240763527630.994073412489012
0.61103.2017855815981.02900294052284
0.62103.3861448904921.06697877893132
0.63103.5777922815831.10559942813071
0.64103.777070806531.14295643530945
0.65103.9841483051311.17812290404484
0.66104.1991618814471.21123633488894
0.67104.4223685589341.24338367631189
0.68104.6542788995931.27644399660694
0.69104.8957478412931.31309967036887
0.7105.1479979277841.35610783414605
0.71105.4125556916721.40751652046409
0.72105.6910929450901.46830742253326
0.73105.9851809211911.53768850677247
0.74106.2959849044251.61238509713008
0.75106.6239467151891.68749005542132
0.76106.9685171005061.75621859628113
0.77107.3280039817711.81132911513608
0.78107.6995908989411.84592663831734
0.79108.0795512761751.85530973026851
0.8108.4636416800831.83726345527739
0.81108.8476100139631.79320419879650
0.82109.2277159043181.72790750096100
0.83109.6011447177651.64828567722956
0.84109.9662142040041.56232945155633
0.85110.3223253398291.47700809302812
0.86110.6696857910001.39662655095835
0.87111.008912069991.32196651580087
0.88111.3406635434961.25099649046379
0.89111.6654500531491.18035165482768
0.9111.9836800237171.10775542432169
0.91112.2959193163061.03333561420229
0.92112.6033129657830.959486188955129
0.93112.9082946579790.888979132535383
0.94113.2160152004670.823188525122694
0.95113.5367872090820.764610781609778
0.96113.8879736349470.729722297906245
0.97114.2892077347770.765052532081604
0.98114.7410791519510.92087418761529
0.99115.1874515095041.16727894055484

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 81.2532968090438 & 1.11779486645604 \tabularnewline
0.02 & 82.0100657335472 & 2.24893406006270 \tabularnewline
0.03 & 83.0867967191067 & 2.90248632098292 \tabularnewline
0.04 & 84.309724674811 & 3.01306443451468 \tabularnewline
0.05 & 85.5191619925983 & 2.81929371038251 \tabularnewline
0.06 & 86.6244643030639 & 2.58088039100784 \tabularnewline
0.07 & 87.6031076801128 & 2.43182921759067 \tabularnewline
0.08 & 88.4723026307541 & 2.37910337912327 \tabularnewline
0.09 & 89.2605854757323 & 2.37440618168912 \tabularnewline
0.1 & 89.9914156435846 & 2.37418160585810 \tabularnewline
0.11 & 90.6783286417266 & 2.35550436368601 \tabularnewline
0.12 & 91.3264938269675 & 2.31072816399791 \tabularnewline
0.13 & 91.936104836056 & 2.23917319869181 \tabularnewline
0.14 & 92.5052490020266 & 2.14255204195681 \tabularnewline
0.15 & 93.0316740835776 & 2.02327291086989 \tabularnewline
0.16 & 93.5136920438815 & 1.88516340753100 \tabularnewline
0.17 & 93.950600913382 & 1.73385345376238 \tabularnewline
0.18 & 94.3428694453107 & 1.57637388638096 \tabularnewline
0.19 & 94.6921767602222 & 1.42006540242905 \tabularnewline
0.2 & 95.0013241007466 & 1.27198204922879 \tabularnewline
0.21 & 95.2740302454275 & 1.13767732646087 \tabularnewline
0.22 & 95.5146454761518 & 1.02078077295073 \tabularnewline
0.23 & 95.7278380822724 & 0.923105464131225 \tabularnewline
0.24 & 95.9183085478542 & 0.84475071575234 \tabularnewline
0.25 & 96.0905716795998 & 0.785073626549223 \tabularnewline
0.26 & 96.2488246596636 & 0.742779105897026 \tabularnewline
0.27 & 96.3968978282451 & 0.716473770504703 \tabularnewline
0.28 & 96.5382699677364 & 0.705222756435214 \tabularnewline
0.29 & 96.6761223852406 & 0.708321371852601 \tabularnewline
0.3 & 96.813405183934 & 0.725863145593432 \tabularnewline
0.31 & 96.9528927982448 & 0.757631267035342 \tabularnewline
0.32 & 97.097212146033 & 0.803733370396387 \tabularnewline
0.33 & 97.248834047245 & 0.863457010343252 \tabularnewline
0.34 & 97.4100257989705 & 0.935974865502641 \tabularnewline
0.35 & 97.582769322077 & 1.01928040224009 \tabularnewline
0.36 & 97.7686547246144 & 1.11066829961975 \tabularnewline
0.37 & 97.9687632296816 & 1.20676723042785 \tabularnewline
0.38 & 98.183555998916 & 1.30352987709458 \tabularnewline
0.39 & 98.4127862364378 & 1.39609462111666 \tabularnewline
0.4 & 98.65545086086 & 1.4799064365811 \tabularnewline
0.41 & 98.909794837606 & 1.55019328884897 \tabularnewline
0.42 & 99.1733760308798 & 1.60276267595641 \tabularnewline
0.43 & 99.443191560376 & 1.63468311095571 \tabularnewline
0.44 & 99.7158589191832 & 1.64395964084749 \tabularnewline
0.45 & 99.9878376381741 & 1.63014570022074 \tabularnewline
0.46 & 100.255671312376 & 1.59454451451388 \tabularnewline
0.47 & 100.516226436325 & 1.53957734478817 \tabularnewline
0.48 & 100.766904405644 & 1.46940746580755 \tabularnewline
0.49 & 101.005806294907 & 1.38874726029972 \tabularnewline
0.5 & 101.231836029021 & 1.30308488044260 \tabularnewline
0.51 & 101.444735220256 & 1.21782368482867 \tabularnewline
0.52 & 101.645050888394 & 1.13804566234769 \tabularnewline
0.53 & 101.834044234756 & 1.06817998580570 \tabularnewline
0.54 & 102.013553679886 & 1.01178394562194 \tabularnewline
0.55 & 102.185828105376 & 0.970945191884134 \tabularnewline
0.56 & 102.353346805197 & 0.946911565615199 \tabularnewline
0.57 & 102.518641589241 & 0.939086954786012 \tabularnewline
0.58 & 102.684134492114 & 0.946079715310816 \tabularnewline
0.59 & 102.852002238693 & 0.965400807906307 \tabularnewline
0.6 & 103.024076352763 & 0.994073412489012 \tabularnewline
0.61 & 103.201785581598 & 1.02900294052284 \tabularnewline
0.62 & 103.386144890492 & 1.06697877893132 \tabularnewline
0.63 & 103.577792281583 & 1.10559942813071 \tabularnewline
0.64 & 103.77707080653 & 1.14295643530945 \tabularnewline
0.65 & 103.984148305131 & 1.17812290404484 \tabularnewline
0.66 & 104.199161881447 & 1.21123633488894 \tabularnewline
0.67 & 104.422368558934 & 1.24338367631189 \tabularnewline
0.68 & 104.654278899593 & 1.27644399660694 \tabularnewline
0.69 & 104.895747841293 & 1.31309967036887 \tabularnewline
0.7 & 105.147997927784 & 1.35610783414605 \tabularnewline
0.71 & 105.412555691672 & 1.40751652046409 \tabularnewline
0.72 & 105.691092945090 & 1.46830742253326 \tabularnewline
0.73 & 105.985180921191 & 1.53768850677247 \tabularnewline
0.74 & 106.295984904425 & 1.61238509713008 \tabularnewline
0.75 & 106.623946715189 & 1.68749005542132 \tabularnewline
0.76 & 106.968517100506 & 1.75621859628113 \tabularnewline
0.77 & 107.328003981771 & 1.81132911513608 \tabularnewline
0.78 & 107.699590898941 & 1.84592663831734 \tabularnewline
0.79 & 108.079551276175 & 1.85530973026851 \tabularnewline
0.8 & 108.463641680083 & 1.83726345527739 \tabularnewline
0.81 & 108.847610013963 & 1.79320419879650 \tabularnewline
0.82 & 109.227715904318 & 1.72790750096100 \tabularnewline
0.83 & 109.601144717765 & 1.64828567722956 \tabularnewline
0.84 & 109.966214204004 & 1.56232945155633 \tabularnewline
0.85 & 110.322325339829 & 1.47700809302812 \tabularnewline
0.86 & 110.669685791000 & 1.39662655095835 \tabularnewline
0.87 & 111.00891206999 & 1.32196651580087 \tabularnewline
0.88 & 111.340663543496 & 1.25099649046379 \tabularnewline
0.89 & 111.665450053149 & 1.18035165482768 \tabularnewline
0.9 & 111.983680023717 & 1.10775542432169 \tabularnewline
0.91 & 112.295919316306 & 1.03333561420229 \tabularnewline
0.92 & 112.603312965783 & 0.959486188955129 \tabularnewline
0.93 & 112.908294657979 & 0.888979132535383 \tabularnewline
0.94 & 113.216015200467 & 0.823188525122694 \tabularnewline
0.95 & 113.536787209082 & 0.764610781609778 \tabularnewline
0.96 & 113.887973634947 & 0.729722297906245 \tabularnewline
0.97 & 114.289207734777 & 0.765052532081604 \tabularnewline
0.98 & 114.741079151951 & 0.92087418761529 \tabularnewline
0.99 & 115.187451509504 & 1.16727894055484 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17328&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]81.2532968090438[/C][C]1.11779486645604[/C][/ROW]
[ROW][C]0.02[/C][C]82.0100657335472[/C][C]2.24893406006270[/C][/ROW]
[ROW][C]0.03[/C][C]83.0867967191067[/C][C]2.90248632098292[/C][/ROW]
[ROW][C]0.04[/C][C]84.309724674811[/C][C]3.01306443451468[/C][/ROW]
[ROW][C]0.05[/C][C]85.5191619925983[/C][C]2.81929371038251[/C][/ROW]
[ROW][C]0.06[/C][C]86.6244643030639[/C][C]2.58088039100784[/C][/ROW]
[ROW][C]0.07[/C][C]87.6031076801128[/C][C]2.43182921759067[/C][/ROW]
[ROW][C]0.08[/C][C]88.4723026307541[/C][C]2.37910337912327[/C][/ROW]
[ROW][C]0.09[/C][C]89.2605854757323[/C][C]2.37440618168912[/C][/ROW]
[ROW][C]0.1[/C][C]89.9914156435846[/C][C]2.37418160585810[/C][/ROW]
[ROW][C]0.11[/C][C]90.6783286417266[/C][C]2.35550436368601[/C][/ROW]
[ROW][C]0.12[/C][C]91.3264938269675[/C][C]2.31072816399791[/C][/ROW]
[ROW][C]0.13[/C][C]91.936104836056[/C][C]2.23917319869181[/C][/ROW]
[ROW][C]0.14[/C][C]92.5052490020266[/C][C]2.14255204195681[/C][/ROW]
[ROW][C]0.15[/C][C]93.0316740835776[/C][C]2.02327291086989[/C][/ROW]
[ROW][C]0.16[/C][C]93.5136920438815[/C][C]1.88516340753100[/C][/ROW]
[ROW][C]0.17[/C][C]93.950600913382[/C][C]1.73385345376238[/C][/ROW]
[ROW][C]0.18[/C][C]94.3428694453107[/C][C]1.57637388638096[/C][/ROW]
[ROW][C]0.19[/C][C]94.6921767602222[/C][C]1.42006540242905[/C][/ROW]
[ROW][C]0.2[/C][C]95.0013241007466[/C][C]1.27198204922879[/C][/ROW]
[ROW][C]0.21[/C][C]95.2740302454275[/C][C]1.13767732646087[/C][/ROW]
[ROW][C]0.22[/C][C]95.5146454761518[/C][C]1.02078077295073[/C][/ROW]
[ROW][C]0.23[/C][C]95.7278380822724[/C][C]0.923105464131225[/C][/ROW]
[ROW][C]0.24[/C][C]95.9183085478542[/C][C]0.84475071575234[/C][/ROW]
[ROW][C]0.25[/C][C]96.0905716795998[/C][C]0.785073626549223[/C][/ROW]
[ROW][C]0.26[/C][C]96.2488246596636[/C][C]0.742779105897026[/C][/ROW]
[ROW][C]0.27[/C][C]96.3968978282451[/C][C]0.716473770504703[/C][/ROW]
[ROW][C]0.28[/C][C]96.5382699677364[/C][C]0.705222756435214[/C][/ROW]
[ROW][C]0.29[/C][C]96.6761223852406[/C][C]0.708321371852601[/C][/ROW]
[ROW][C]0.3[/C][C]96.813405183934[/C][C]0.725863145593432[/C][/ROW]
[ROW][C]0.31[/C][C]96.9528927982448[/C][C]0.757631267035342[/C][/ROW]
[ROW][C]0.32[/C][C]97.097212146033[/C][C]0.803733370396387[/C][/ROW]
[ROW][C]0.33[/C][C]97.248834047245[/C][C]0.863457010343252[/C][/ROW]
[ROW][C]0.34[/C][C]97.4100257989705[/C][C]0.935974865502641[/C][/ROW]
[ROW][C]0.35[/C][C]97.582769322077[/C][C]1.01928040224009[/C][/ROW]
[ROW][C]0.36[/C][C]97.7686547246144[/C][C]1.11066829961975[/C][/ROW]
[ROW][C]0.37[/C][C]97.9687632296816[/C][C]1.20676723042785[/C][/ROW]
[ROW][C]0.38[/C][C]98.183555998916[/C][C]1.30352987709458[/C][/ROW]
[ROW][C]0.39[/C][C]98.4127862364378[/C][C]1.39609462111666[/C][/ROW]
[ROW][C]0.4[/C][C]98.65545086086[/C][C]1.4799064365811[/C][/ROW]
[ROW][C]0.41[/C][C]98.909794837606[/C][C]1.55019328884897[/C][/ROW]
[ROW][C]0.42[/C][C]99.1733760308798[/C][C]1.60276267595641[/C][/ROW]
[ROW][C]0.43[/C][C]99.443191560376[/C][C]1.63468311095571[/C][/ROW]
[ROW][C]0.44[/C][C]99.7158589191832[/C][C]1.64395964084749[/C][/ROW]
[ROW][C]0.45[/C][C]99.9878376381741[/C][C]1.63014570022074[/C][/ROW]
[ROW][C]0.46[/C][C]100.255671312376[/C][C]1.59454451451388[/C][/ROW]
[ROW][C]0.47[/C][C]100.516226436325[/C][C]1.53957734478817[/C][/ROW]
[ROW][C]0.48[/C][C]100.766904405644[/C][C]1.46940746580755[/C][/ROW]
[ROW][C]0.49[/C][C]101.005806294907[/C][C]1.38874726029972[/C][/ROW]
[ROW][C]0.5[/C][C]101.231836029021[/C][C]1.30308488044260[/C][/ROW]
[ROW][C]0.51[/C][C]101.444735220256[/C][C]1.21782368482867[/C][/ROW]
[ROW][C]0.52[/C][C]101.645050888394[/C][C]1.13804566234769[/C][/ROW]
[ROW][C]0.53[/C][C]101.834044234756[/C][C]1.06817998580570[/C][/ROW]
[ROW][C]0.54[/C][C]102.013553679886[/C][C]1.01178394562194[/C][/ROW]
[ROW][C]0.55[/C][C]102.185828105376[/C][C]0.970945191884134[/C][/ROW]
[ROW][C]0.56[/C][C]102.353346805197[/C][C]0.946911565615199[/C][/ROW]
[ROW][C]0.57[/C][C]102.518641589241[/C][C]0.939086954786012[/C][/ROW]
[ROW][C]0.58[/C][C]102.684134492114[/C][C]0.946079715310816[/C][/ROW]
[ROW][C]0.59[/C][C]102.852002238693[/C][C]0.965400807906307[/C][/ROW]
[ROW][C]0.6[/C][C]103.024076352763[/C][C]0.994073412489012[/C][/ROW]
[ROW][C]0.61[/C][C]103.201785581598[/C][C]1.02900294052284[/C][/ROW]
[ROW][C]0.62[/C][C]103.386144890492[/C][C]1.06697877893132[/C][/ROW]
[ROW][C]0.63[/C][C]103.577792281583[/C][C]1.10559942813071[/C][/ROW]
[ROW][C]0.64[/C][C]103.77707080653[/C][C]1.14295643530945[/C][/ROW]
[ROW][C]0.65[/C][C]103.984148305131[/C][C]1.17812290404484[/C][/ROW]
[ROW][C]0.66[/C][C]104.199161881447[/C][C]1.21123633488894[/C][/ROW]
[ROW][C]0.67[/C][C]104.422368558934[/C][C]1.24338367631189[/C][/ROW]
[ROW][C]0.68[/C][C]104.654278899593[/C][C]1.27644399660694[/C][/ROW]
[ROW][C]0.69[/C][C]104.895747841293[/C][C]1.31309967036887[/C][/ROW]
[ROW][C]0.7[/C][C]105.147997927784[/C][C]1.35610783414605[/C][/ROW]
[ROW][C]0.71[/C][C]105.412555691672[/C][C]1.40751652046409[/C][/ROW]
[ROW][C]0.72[/C][C]105.691092945090[/C][C]1.46830742253326[/C][/ROW]
[ROW][C]0.73[/C][C]105.985180921191[/C][C]1.53768850677247[/C][/ROW]
[ROW][C]0.74[/C][C]106.295984904425[/C][C]1.61238509713008[/C][/ROW]
[ROW][C]0.75[/C][C]106.623946715189[/C][C]1.68749005542132[/C][/ROW]
[ROW][C]0.76[/C][C]106.968517100506[/C][C]1.75621859628113[/C][/ROW]
[ROW][C]0.77[/C][C]107.328003981771[/C][C]1.81132911513608[/C][/ROW]
[ROW][C]0.78[/C][C]107.699590898941[/C][C]1.84592663831734[/C][/ROW]
[ROW][C]0.79[/C][C]108.079551276175[/C][C]1.85530973026851[/C][/ROW]
[ROW][C]0.8[/C][C]108.463641680083[/C][C]1.83726345527739[/C][/ROW]
[ROW][C]0.81[/C][C]108.847610013963[/C][C]1.79320419879650[/C][/ROW]
[ROW][C]0.82[/C][C]109.227715904318[/C][C]1.72790750096100[/C][/ROW]
[ROW][C]0.83[/C][C]109.601144717765[/C][C]1.64828567722956[/C][/ROW]
[ROW][C]0.84[/C][C]109.966214204004[/C][C]1.56232945155633[/C][/ROW]
[ROW][C]0.85[/C][C]110.322325339829[/C][C]1.47700809302812[/C][/ROW]
[ROW][C]0.86[/C][C]110.669685791000[/C][C]1.39662655095835[/C][/ROW]
[ROW][C]0.87[/C][C]111.00891206999[/C][C]1.32196651580087[/C][/ROW]
[ROW][C]0.88[/C][C]111.340663543496[/C][C]1.25099649046379[/C][/ROW]
[ROW][C]0.89[/C][C]111.665450053149[/C][C]1.18035165482768[/C][/ROW]
[ROW][C]0.9[/C][C]111.983680023717[/C][C]1.10775542432169[/C][/ROW]
[ROW][C]0.91[/C][C]112.295919316306[/C][C]1.03333561420229[/C][/ROW]
[ROW][C]0.92[/C][C]112.603312965783[/C][C]0.959486188955129[/C][/ROW]
[ROW][C]0.93[/C][C]112.908294657979[/C][C]0.888979132535383[/C][/ROW]
[ROW][C]0.94[/C][C]113.216015200467[/C][C]0.823188525122694[/C][/ROW]
[ROW][C]0.95[/C][C]113.536787209082[/C][C]0.764610781609778[/C][/ROW]
[ROW][C]0.96[/C][C]113.887973634947[/C][C]0.729722297906245[/C][/ROW]
[ROW][C]0.97[/C][C]114.289207734777[/C][C]0.765052532081604[/C][/ROW]
[ROW][C]0.98[/C][C]114.741079151951[/C][C]0.92087418761529[/C][/ROW]
[ROW][C]0.99[/C][C]115.187451509504[/C][C]1.16727894055484[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17328&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17328&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
0.0181.25329680904381.11779486645604
0.0282.01006573354722.24893406006270
0.0383.08679671910672.90248632098292
0.0484.3097246748113.01306443451468
0.0585.51916199259832.81929371038251
0.0686.62446430306392.58088039100784
0.0787.60310768011282.43182921759067
0.0888.47230263075412.37910337912327
0.0989.26058547573232.37440618168912
0.189.99141564358462.37418160585810
0.1190.67832864172662.35550436368601
0.1291.32649382696752.31072816399791
0.1391.9361048360562.23917319869181
0.1492.50524900202662.14255204195681
0.1593.03167408357762.02327291086989
0.1693.51369204388151.88516340753100
0.1793.9506009133821.73385345376238
0.1894.34286944531071.57637388638096
0.1994.69217676022221.42006540242905
0.295.00132410074661.27198204922879
0.2195.27403024542751.13767732646087
0.2295.51464547615181.02078077295073
0.2395.72783808227240.923105464131225
0.2495.91830854785420.84475071575234
0.2596.09057167959980.785073626549223
0.2696.24882465966360.742779105897026
0.2796.39689782824510.716473770504703
0.2896.53826996773640.705222756435214
0.2996.67612238524060.708321371852601
0.396.8134051839340.725863145593432
0.3196.95289279824480.757631267035342
0.3297.0972121460330.803733370396387
0.3397.2488340472450.863457010343252
0.3497.41002579897050.935974865502641
0.3597.5827693220771.01928040224009
0.3697.76865472461441.11066829961975
0.3797.96876322968161.20676723042785
0.3898.1835559989161.30352987709458
0.3998.41278623643781.39609462111666
0.498.655450860861.4799064365811
0.4198.9097948376061.55019328884897
0.4299.17337603087981.60276267595641
0.4399.4431915603761.63468311095571
0.4499.71585891918321.64395964084749
0.4599.98783763817411.63014570022074
0.46100.2556713123761.59454451451388
0.47100.5162264363251.53957734478817
0.48100.7669044056441.46940746580755
0.49101.0058062949071.38874726029972
0.5101.2318360290211.30308488044260
0.51101.4447352202561.21782368482867
0.52101.6450508883941.13804566234769
0.53101.8340442347561.06817998580570
0.54102.0135536798861.01178394562194
0.55102.1858281053760.970945191884134
0.56102.3533468051970.946911565615199
0.57102.5186415892410.939086954786012
0.58102.6841344921140.946079715310816
0.59102.8520022386930.965400807906307
0.6103.0240763527630.994073412489012
0.61103.2017855815981.02900294052284
0.62103.3861448904921.06697877893132
0.63103.5777922815831.10559942813071
0.64103.777070806531.14295643530945
0.65103.9841483051311.17812290404484
0.66104.1991618814471.21123633488894
0.67104.4223685589341.24338367631189
0.68104.6542788995931.27644399660694
0.69104.8957478412931.31309967036887
0.7105.1479979277841.35610783414605
0.71105.4125556916721.40751652046409
0.72105.6910929450901.46830742253326
0.73105.9851809211911.53768850677247
0.74106.2959849044251.61238509713008
0.75106.6239467151891.68749005542132
0.76106.9685171005061.75621859628113
0.77107.3280039817711.81132911513608
0.78107.6995908989411.84592663831734
0.79108.0795512761751.85530973026851
0.8108.4636416800831.83726345527739
0.81108.8476100139631.79320419879650
0.82109.2277159043181.72790750096100
0.83109.6011447177651.64828567722956
0.84109.9662142040041.56232945155633
0.85110.3223253398291.47700809302812
0.86110.6696857910001.39662655095835
0.87111.008912069991.32196651580087
0.88111.3406635434961.25099649046379
0.89111.6654500531491.18035165482768
0.9111.9836800237171.10775542432169
0.91112.2959193163061.03333561420229
0.92112.6033129657830.959486188955129
0.93112.9082946579790.888979132535383
0.94113.2160152004670.823188525122694
0.95113.5367872090820.764610781609778
0.96113.8879736349470.729722297906245
0.97114.2892077347770.765052532081604
0.98114.7410791519510.92087418761529
0.99115.1874515095041.16727894055484


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')