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Harrell-Davis percentielen - datareeks werkloosheid jonge werkzoekenden <25...

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationThu, 12 Mar 2009 06:11:04 -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/2009/Mar/12/t1236860033ahtnakaes7ba389.htm/, Retrieved Thu, 02 May 2024 09:27:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=38975, Retrieved Thu, 02 May 2024 09:27:42 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsHarrell Davis quantilles percentielen datareeks werkloosheidheid jonge werkzoekenden onder de 25jaar
Estimated Impact193

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-     [Histogram] [frequentietabel m...] [2009-03-04 10:13:22] [f21498c3e9c121596bf8d8ea2d95296f]
- RMPD    [Harrell-Davis Quantiles] [Harrell-Davis per...] [2009-03-12 12:11:04] [bddbb8640adbf7d76f1766fd0c9aa6ca] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
51772
48439
45716
43851
41622
45180
72550
77681
71177
63390
57386
56765
55772
53605
50338
47314
44596
47029
72490
78086
71058
63276
56918
55170
52980
50466
48553
46307
43796
45642
70765
75685
69220
62898
56011
54148
46626
46018
42408
42483
40113
41381
62348
63611
58389
46175
40555
37909
37866
34418
31736
29533
27604
30575
51345
52455
43367
37077
33016
33117
32279
30369
28983
27864
24591
29528
46549
47932
41584
37295
34666
36773
39591
39833

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=38975&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=38975&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=38975&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
0.0125424.13053926532335.72075573121
0.0226527.10624193651612.58962154744
0.0327483.01327286231183.21979935125
0.0428203.03940420341039.49479257776
0.0528757.55134646851014.86054194989
0.0629225.43424427181035.36387773124
0.0729655.52477895071097.37118712656
0.0830075.02933332211199.02118155872
0.0930499.973477171325.50606749305
0.130939.48802642991459.36273376322
0.1131397.48132855741589.01634103699
0.1231874.20467733631710.03040317871
0.1332367.88734902681822.18426711046
0.1432875.91225560851925.79360054349
0.1533395.29915839632018.85743215012
0.1633922.68504842612096.86597734387
0.1734454.17184703652154.41591469924
0.1834985.34173800682187.41699153321
0.1935511.54671622032195.05448707093
0.236028.39231555732180.05805394024
0.2136532.23647843952148.06039875067
0.2237020.53111529332105.6529890219
0.2337491.91513118872058.95979819587
0.2437946.07072261282012.12618100882
0.2538383.43226285751967.03872207709
0.2638804.86471579991924.05319856435
0.2739211.40801376491882.68332745555
0.2839604.13498072731842.71433390058
0.2939984.11811835341804.52447400852
0.340352.46406668981769.01499350626
0.3140710.36188956621737.5916671304
0.3241059.10007216541711.73094670595
0.3341400.02849681821691.90822723783
0.3441734.46563083911678.16093487441
0.3542063.57005733871669.18358319955
0.3642388.20556882561662.84323336879
0.3742708.83018298081656.61270513541
0.3843025.43376106421647.46577030794
0.3943337.53934779331632.88781594845
0.443644.27257931831610.75468032298
0.4143944.49342872871579.82321242195
0.4244236.97628036991540.21523133184
0.4344520.61836713281493.05664730563
0.4444794.65317512041440.86696138097
0.4545058.84458631501387.13924313574
0.4645313.63926749871336.26185692843
0.4745560.25894935131293.24269802743
0.4845800.7203709631263.00179738560
0.4946037.77813231151250.08147620176
0.546274.79364805041257.97612358045
0.5146515.54092874251288.67746918242
0.5246763.96624661281342.26562289753
0.5347023.92332427111416.98584978253
0.5447298.90822816381509.40005203350
0.5547591.81855423331615.01901893278
0.5647904.75973983481728.43784828119
0.5748238.91740730151843.75843124601
0.5848594.50856171891955.36869318784
0.5948970.81643739482058.29919378137
0.649366.30442534452148.19155396973
0.6149778.79499639782222.33874504762
0.6250205.69159171142279.17125110431
0.6350644.21707859642318.70855162619
0.6451091.64325846182342.11376006980
0.6551545.49273442192351.58375996340
0.6652003.70617902872349.78646670817
0.6752464.78165840912339.92228761500
0.6852927.90342162662325.36897235197
0.6953393.08006838652309.92199329297
0.753861.30208217152298.06022256494
0.7154334.70567499382295.17940765685
0.7254816.69862058752307.73654005751
0.7355311.97553188432342.62167859298
0.7455826.34089617832405.88019698697
0.7556366.28391233682500.85690584112
0.7656938.31719035412626.01274648993
0.7757548.19153265432774.21009659517
0.7858200.19790302552933.30014549611
0.7958896.81230022433089.24019326868
0.859638.87484735423230.00921651142
0.8160426.29577643513349.88630229915
0.8261258.98681590123451.73279339837
0.8362137.4463142543545.04753279093
0.8463062.35629241743639.08151278842
0.8564032.83436314113733.05782249721
0.8665043.64436559933807.94387973689
0.8766082.50536149693827.84437231159
0.8867129.23900354673752.19201672356
0.8968158.40338263223554.54782071987
0.969146.03399016133240.46382516764
0.9170079.31289477592856.49393777381
0.9270965.94141651322486.59790002918
0.9371838.33980060922233.07528343876
0.9472747.1998266832169.80097039108
0.9573740.46977484122269.64305651045
0.9674829.5163544062375.30990502898
0.9775955.30635517592260.54292402300
0.9876979.78890195041761.4482549804
0.9977728.2672485372973.512232915508

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 25424.1305392653 & 2335.72075573121 \tabularnewline
0.02 & 26527.1062419365 & 1612.58962154744 \tabularnewline
0.03 & 27483.0132728623 & 1183.21979935125 \tabularnewline
0.04 & 28203.0394042034 & 1039.49479257776 \tabularnewline
0.05 & 28757.5513464685 & 1014.86054194989 \tabularnewline
0.06 & 29225.4342442718 & 1035.36387773124 \tabularnewline
0.07 & 29655.5247789507 & 1097.37118712656 \tabularnewline
0.08 & 30075.0293333221 & 1199.02118155872 \tabularnewline
0.09 & 30499.97347717 & 1325.50606749305 \tabularnewline
0.1 & 30939.4880264299 & 1459.36273376322 \tabularnewline
0.11 & 31397.4813285574 & 1589.01634103699 \tabularnewline
0.12 & 31874.2046773363 & 1710.03040317871 \tabularnewline
0.13 & 32367.8873490268 & 1822.18426711046 \tabularnewline
0.14 & 32875.9122556085 & 1925.79360054349 \tabularnewline
0.15 & 33395.2991583963 & 2018.85743215012 \tabularnewline
0.16 & 33922.6850484261 & 2096.86597734387 \tabularnewline
0.17 & 34454.1718470365 & 2154.41591469924 \tabularnewline
0.18 & 34985.3417380068 & 2187.41699153321 \tabularnewline
0.19 & 35511.5467162203 & 2195.05448707093 \tabularnewline
0.2 & 36028.3923155573 & 2180.05805394024 \tabularnewline
0.21 & 36532.2364784395 & 2148.06039875067 \tabularnewline
0.22 & 37020.5311152933 & 2105.6529890219 \tabularnewline
0.23 & 37491.9151311887 & 2058.95979819587 \tabularnewline
0.24 & 37946.0707226128 & 2012.12618100882 \tabularnewline
0.25 & 38383.4322628575 & 1967.03872207709 \tabularnewline
0.26 & 38804.8647157999 & 1924.05319856435 \tabularnewline
0.27 & 39211.4080137649 & 1882.68332745555 \tabularnewline
0.28 & 39604.1349807273 & 1842.71433390058 \tabularnewline
0.29 & 39984.1181183534 & 1804.52447400852 \tabularnewline
0.3 & 40352.4640666898 & 1769.01499350626 \tabularnewline
0.31 & 40710.3618895662 & 1737.5916671304 \tabularnewline
0.32 & 41059.1000721654 & 1711.73094670595 \tabularnewline
0.33 & 41400.0284968182 & 1691.90822723783 \tabularnewline
0.34 & 41734.4656308391 & 1678.16093487441 \tabularnewline
0.35 & 42063.5700573387 & 1669.18358319955 \tabularnewline
0.36 & 42388.2055688256 & 1662.84323336879 \tabularnewline
0.37 & 42708.8301829808 & 1656.61270513541 \tabularnewline
0.38 & 43025.4337610642 & 1647.46577030794 \tabularnewline
0.39 & 43337.5393477933 & 1632.88781594845 \tabularnewline
0.4 & 43644.2725793183 & 1610.75468032298 \tabularnewline
0.41 & 43944.4934287287 & 1579.82321242195 \tabularnewline
0.42 & 44236.9762803699 & 1540.21523133184 \tabularnewline
0.43 & 44520.6183671328 & 1493.05664730563 \tabularnewline
0.44 & 44794.6531751204 & 1440.86696138097 \tabularnewline
0.45 & 45058.8445863150 & 1387.13924313574 \tabularnewline
0.46 & 45313.6392674987 & 1336.26185692843 \tabularnewline
0.47 & 45560.2589493513 & 1293.24269802743 \tabularnewline
0.48 & 45800.720370963 & 1263.00179738560 \tabularnewline
0.49 & 46037.7781323115 & 1250.08147620176 \tabularnewline
0.5 & 46274.7936480504 & 1257.97612358045 \tabularnewline
0.51 & 46515.5409287425 & 1288.67746918242 \tabularnewline
0.52 & 46763.9662466128 & 1342.26562289753 \tabularnewline
0.53 & 47023.9233242711 & 1416.98584978253 \tabularnewline
0.54 & 47298.9082281638 & 1509.40005203350 \tabularnewline
0.55 & 47591.8185542333 & 1615.01901893278 \tabularnewline
0.56 & 47904.7597398348 & 1728.43784828119 \tabularnewline
0.57 & 48238.9174073015 & 1843.75843124601 \tabularnewline
0.58 & 48594.5085617189 & 1955.36869318784 \tabularnewline
0.59 & 48970.8164373948 & 2058.29919378137 \tabularnewline
0.6 & 49366.3044253445 & 2148.19155396973 \tabularnewline
0.61 & 49778.7949963978 & 2222.33874504762 \tabularnewline
0.62 & 50205.6915917114 & 2279.17125110431 \tabularnewline
0.63 & 50644.2170785964 & 2318.70855162619 \tabularnewline
0.64 & 51091.6432584618 & 2342.11376006980 \tabularnewline
0.65 & 51545.4927344219 & 2351.58375996340 \tabularnewline
0.66 & 52003.7061790287 & 2349.78646670817 \tabularnewline
0.67 & 52464.7816584091 & 2339.92228761500 \tabularnewline
0.68 & 52927.9034216266 & 2325.36897235197 \tabularnewline
0.69 & 53393.0800683865 & 2309.92199329297 \tabularnewline
0.7 & 53861.3020821715 & 2298.06022256494 \tabularnewline
0.71 & 54334.7056749938 & 2295.17940765685 \tabularnewline
0.72 & 54816.6986205875 & 2307.73654005751 \tabularnewline
0.73 & 55311.9755318843 & 2342.62167859298 \tabularnewline
0.74 & 55826.3408961783 & 2405.88019698697 \tabularnewline
0.75 & 56366.2839123368 & 2500.85690584112 \tabularnewline
0.76 & 56938.3171903541 & 2626.01274648993 \tabularnewline
0.77 & 57548.1915326543 & 2774.21009659517 \tabularnewline
0.78 & 58200.1979030255 & 2933.30014549611 \tabularnewline
0.79 & 58896.8123002243 & 3089.24019326868 \tabularnewline
0.8 & 59638.8748473542 & 3230.00921651142 \tabularnewline
0.81 & 60426.2957764351 & 3349.88630229915 \tabularnewline
0.82 & 61258.9868159012 & 3451.73279339837 \tabularnewline
0.83 & 62137.446314254 & 3545.04753279093 \tabularnewline
0.84 & 63062.3562924174 & 3639.08151278842 \tabularnewline
0.85 & 64032.8343631411 & 3733.05782249721 \tabularnewline
0.86 & 65043.6443655993 & 3807.94387973689 \tabularnewline
0.87 & 66082.5053614969 & 3827.84437231159 \tabularnewline
0.88 & 67129.2390035467 & 3752.19201672356 \tabularnewline
0.89 & 68158.4033826322 & 3554.54782071987 \tabularnewline
0.9 & 69146.0339901613 & 3240.46382516764 \tabularnewline
0.91 & 70079.3128947759 & 2856.49393777381 \tabularnewline
0.92 & 70965.9414165132 & 2486.59790002918 \tabularnewline
0.93 & 71838.3398006092 & 2233.07528343876 \tabularnewline
0.94 & 72747.199826683 & 2169.80097039108 \tabularnewline
0.95 & 73740.4697748412 & 2269.64305651045 \tabularnewline
0.96 & 74829.516354406 & 2375.30990502898 \tabularnewline
0.97 & 75955.3063551759 & 2260.54292402300 \tabularnewline
0.98 & 76979.7889019504 & 1761.4482549804 \tabularnewline
0.99 & 77728.2672485372 & 973.512232915508 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=38975&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]25424.1305392653[/C][C]2335.72075573121[/C][/ROW]
[ROW][C]0.02[/C][C]26527.1062419365[/C][C]1612.58962154744[/C][/ROW]
[ROW][C]0.03[/C][C]27483.0132728623[/C][C]1183.21979935125[/C][/ROW]
[ROW][C]0.04[/C][C]28203.0394042034[/C][C]1039.49479257776[/C][/ROW]
[ROW][C]0.05[/C][C]28757.5513464685[/C][C]1014.86054194989[/C][/ROW]
[ROW][C]0.06[/C][C]29225.4342442718[/C][C]1035.36387773124[/C][/ROW]
[ROW][C]0.07[/C][C]29655.5247789507[/C][C]1097.37118712656[/C][/ROW]
[ROW][C]0.08[/C][C]30075.0293333221[/C][C]1199.02118155872[/C][/ROW]
[ROW][C]0.09[/C][C]30499.97347717[/C][C]1325.50606749305[/C][/ROW]
[ROW][C]0.1[/C][C]30939.4880264299[/C][C]1459.36273376322[/C][/ROW]
[ROW][C]0.11[/C][C]31397.4813285574[/C][C]1589.01634103699[/C][/ROW]
[ROW][C]0.12[/C][C]31874.2046773363[/C][C]1710.03040317871[/C][/ROW]
[ROW][C]0.13[/C][C]32367.8873490268[/C][C]1822.18426711046[/C][/ROW]
[ROW][C]0.14[/C][C]32875.9122556085[/C][C]1925.79360054349[/C][/ROW]
[ROW][C]0.15[/C][C]33395.2991583963[/C][C]2018.85743215012[/C][/ROW]
[ROW][C]0.16[/C][C]33922.6850484261[/C][C]2096.86597734387[/C][/ROW]
[ROW][C]0.17[/C][C]34454.1718470365[/C][C]2154.41591469924[/C][/ROW]
[ROW][C]0.18[/C][C]34985.3417380068[/C][C]2187.41699153321[/C][/ROW]
[ROW][C]0.19[/C][C]35511.5467162203[/C][C]2195.05448707093[/C][/ROW]
[ROW][C]0.2[/C][C]36028.3923155573[/C][C]2180.05805394024[/C][/ROW]
[ROW][C]0.21[/C][C]36532.2364784395[/C][C]2148.06039875067[/C][/ROW]
[ROW][C]0.22[/C][C]37020.5311152933[/C][C]2105.6529890219[/C][/ROW]
[ROW][C]0.23[/C][C]37491.9151311887[/C][C]2058.95979819587[/C][/ROW]
[ROW][C]0.24[/C][C]37946.0707226128[/C][C]2012.12618100882[/C][/ROW]
[ROW][C]0.25[/C][C]38383.4322628575[/C][C]1967.03872207709[/C][/ROW]
[ROW][C]0.26[/C][C]38804.8647157999[/C][C]1924.05319856435[/C][/ROW]
[ROW][C]0.27[/C][C]39211.4080137649[/C][C]1882.68332745555[/C][/ROW]
[ROW][C]0.28[/C][C]39604.1349807273[/C][C]1842.71433390058[/C][/ROW]
[ROW][C]0.29[/C][C]39984.1181183534[/C][C]1804.52447400852[/C][/ROW]
[ROW][C]0.3[/C][C]40352.4640666898[/C][C]1769.01499350626[/C][/ROW]
[ROW][C]0.31[/C][C]40710.3618895662[/C][C]1737.5916671304[/C][/ROW]
[ROW][C]0.32[/C][C]41059.1000721654[/C][C]1711.73094670595[/C][/ROW]
[ROW][C]0.33[/C][C]41400.0284968182[/C][C]1691.90822723783[/C][/ROW]
[ROW][C]0.34[/C][C]41734.4656308391[/C][C]1678.16093487441[/C][/ROW]
[ROW][C]0.35[/C][C]42063.5700573387[/C][C]1669.18358319955[/C][/ROW]
[ROW][C]0.36[/C][C]42388.2055688256[/C][C]1662.84323336879[/C][/ROW]
[ROW][C]0.37[/C][C]42708.8301829808[/C][C]1656.61270513541[/C][/ROW]
[ROW][C]0.38[/C][C]43025.4337610642[/C][C]1647.46577030794[/C][/ROW]
[ROW][C]0.39[/C][C]43337.5393477933[/C][C]1632.88781594845[/C][/ROW]
[ROW][C]0.4[/C][C]43644.2725793183[/C][C]1610.75468032298[/C][/ROW]
[ROW][C]0.41[/C][C]43944.4934287287[/C][C]1579.82321242195[/C][/ROW]
[ROW][C]0.42[/C][C]44236.9762803699[/C][C]1540.21523133184[/C][/ROW]
[ROW][C]0.43[/C][C]44520.6183671328[/C][C]1493.05664730563[/C][/ROW]
[ROW][C]0.44[/C][C]44794.6531751204[/C][C]1440.86696138097[/C][/ROW]
[ROW][C]0.45[/C][C]45058.8445863150[/C][C]1387.13924313574[/C][/ROW]
[ROW][C]0.46[/C][C]45313.6392674987[/C][C]1336.26185692843[/C][/ROW]
[ROW][C]0.47[/C][C]45560.2589493513[/C][C]1293.24269802743[/C][/ROW]
[ROW][C]0.48[/C][C]45800.720370963[/C][C]1263.00179738560[/C][/ROW]
[ROW][C]0.49[/C][C]46037.7781323115[/C][C]1250.08147620176[/C][/ROW]
[ROW][C]0.5[/C][C]46274.7936480504[/C][C]1257.97612358045[/C][/ROW]
[ROW][C]0.51[/C][C]46515.5409287425[/C][C]1288.67746918242[/C][/ROW]
[ROW][C]0.52[/C][C]46763.9662466128[/C][C]1342.26562289753[/C][/ROW]
[ROW][C]0.53[/C][C]47023.9233242711[/C][C]1416.98584978253[/C][/ROW]
[ROW][C]0.54[/C][C]47298.9082281638[/C][C]1509.40005203350[/C][/ROW]
[ROW][C]0.55[/C][C]47591.8185542333[/C][C]1615.01901893278[/C][/ROW]
[ROW][C]0.56[/C][C]47904.7597398348[/C][C]1728.43784828119[/C][/ROW]
[ROW][C]0.57[/C][C]48238.9174073015[/C][C]1843.75843124601[/C][/ROW]
[ROW][C]0.58[/C][C]48594.5085617189[/C][C]1955.36869318784[/C][/ROW]
[ROW][C]0.59[/C][C]48970.8164373948[/C][C]2058.29919378137[/C][/ROW]
[ROW][C]0.6[/C][C]49366.3044253445[/C][C]2148.19155396973[/C][/ROW]
[ROW][C]0.61[/C][C]49778.7949963978[/C][C]2222.33874504762[/C][/ROW]
[ROW][C]0.62[/C][C]50205.6915917114[/C][C]2279.17125110431[/C][/ROW]
[ROW][C]0.63[/C][C]50644.2170785964[/C][C]2318.70855162619[/C][/ROW]
[ROW][C]0.64[/C][C]51091.6432584618[/C][C]2342.11376006980[/C][/ROW]
[ROW][C]0.65[/C][C]51545.4927344219[/C][C]2351.58375996340[/C][/ROW]
[ROW][C]0.66[/C][C]52003.7061790287[/C][C]2349.78646670817[/C][/ROW]
[ROW][C]0.67[/C][C]52464.7816584091[/C][C]2339.92228761500[/C][/ROW]
[ROW][C]0.68[/C][C]52927.9034216266[/C][C]2325.36897235197[/C][/ROW]
[ROW][C]0.69[/C][C]53393.0800683865[/C][C]2309.92199329297[/C][/ROW]
[ROW][C]0.7[/C][C]53861.3020821715[/C][C]2298.06022256494[/C][/ROW]
[ROW][C]0.71[/C][C]54334.7056749938[/C][C]2295.17940765685[/C][/ROW]
[ROW][C]0.72[/C][C]54816.6986205875[/C][C]2307.73654005751[/C][/ROW]
[ROW][C]0.73[/C][C]55311.9755318843[/C][C]2342.62167859298[/C][/ROW]
[ROW][C]0.74[/C][C]55826.3408961783[/C][C]2405.88019698697[/C][/ROW]
[ROW][C]0.75[/C][C]56366.2839123368[/C][C]2500.85690584112[/C][/ROW]
[ROW][C]0.76[/C][C]56938.3171903541[/C][C]2626.01274648993[/C][/ROW]
[ROW][C]0.77[/C][C]57548.1915326543[/C][C]2774.21009659517[/C][/ROW]
[ROW][C]0.78[/C][C]58200.1979030255[/C][C]2933.30014549611[/C][/ROW]
[ROW][C]0.79[/C][C]58896.8123002243[/C][C]3089.24019326868[/C][/ROW]
[ROW][C]0.8[/C][C]59638.8748473542[/C][C]3230.00921651142[/C][/ROW]
[ROW][C]0.81[/C][C]60426.2957764351[/C][C]3349.88630229915[/C][/ROW]
[ROW][C]0.82[/C][C]61258.9868159012[/C][C]3451.73279339837[/C][/ROW]
[ROW][C]0.83[/C][C]62137.446314254[/C][C]3545.04753279093[/C][/ROW]
[ROW][C]0.84[/C][C]63062.3562924174[/C][C]3639.08151278842[/C][/ROW]
[ROW][C]0.85[/C][C]64032.8343631411[/C][C]3733.05782249721[/C][/ROW]
[ROW][C]0.86[/C][C]65043.6443655993[/C][C]3807.94387973689[/C][/ROW]
[ROW][C]0.87[/C][C]66082.5053614969[/C][C]3827.84437231159[/C][/ROW]
[ROW][C]0.88[/C][C]67129.2390035467[/C][C]3752.19201672356[/C][/ROW]
[ROW][C]0.89[/C][C]68158.4033826322[/C][C]3554.54782071987[/C][/ROW]
[ROW][C]0.9[/C][C]69146.0339901613[/C][C]3240.46382516764[/C][/ROW]
[ROW][C]0.91[/C][C]70079.3128947759[/C][C]2856.49393777381[/C][/ROW]
[ROW][C]0.92[/C][C]70965.9414165132[/C][C]2486.59790002918[/C][/ROW]
[ROW][C]0.93[/C][C]71838.3398006092[/C][C]2233.07528343876[/C][/ROW]
[ROW][C]0.94[/C][C]72747.199826683[/C][C]2169.80097039108[/C][/ROW]
[ROW][C]0.95[/C][C]73740.4697748412[/C][C]2269.64305651045[/C][/ROW]
[ROW][C]0.96[/C][C]74829.516354406[/C][C]2375.30990502898[/C][/ROW]
[ROW][C]0.97[/C][C]75955.3063551759[/C][C]2260.54292402300[/C][/ROW]
[ROW][C]0.98[/C][C]76979.7889019504[/C][C]1761.4482549804[/C][/ROW]
[ROW][C]0.99[/C][C]77728.2672485372[/C][C]973.512232915508[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=38975&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=38975&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
0.0125424.13053926532335.72075573121
0.0226527.10624193651612.58962154744
0.0327483.01327286231183.21979935125
0.0428203.03940420341039.49479257776
0.0528757.55134646851014.86054194989
0.0629225.43424427181035.36387773124
0.0729655.52477895071097.37118712656
0.0830075.02933332211199.02118155872
0.0930499.973477171325.50606749305
0.130939.48802642991459.36273376322
0.1131397.48132855741589.01634103699
0.1231874.20467733631710.03040317871
0.1332367.88734902681822.18426711046
0.1432875.91225560851925.79360054349
0.1533395.29915839632018.85743215012
0.1633922.68504842612096.86597734387
0.1734454.17184703652154.41591469924
0.1834985.34173800682187.41699153321
0.1935511.54671622032195.05448707093
0.236028.39231555732180.05805394024
0.2136532.23647843952148.06039875067
0.2237020.53111529332105.6529890219
0.2337491.91513118872058.95979819587
0.2437946.07072261282012.12618100882
0.2538383.43226285751967.03872207709
0.2638804.86471579991924.05319856435
0.2739211.40801376491882.68332745555
0.2839604.13498072731842.71433390058
0.2939984.11811835341804.52447400852
0.340352.46406668981769.01499350626
0.3140710.36188956621737.5916671304
0.3241059.10007216541711.73094670595
0.3341400.02849681821691.90822723783
0.3441734.46563083911678.16093487441
0.3542063.57005733871669.18358319955
0.3642388.20556882561662.84323336879
0.3742708.83018298081656.61270513541
0.3843025.43376106421647.46577030794
0.3943337.53934779331632.88781594845
0.443644.27257931831610.75468032298
0.4143944.49342872871579.82321242195
0.4244236.97628036991540.21523133184
0.4344520.61836713281493.05664730563
0.4444794.65317512041440.86696138097
0.4545058.84458631501387.13924313574
0.4645313.63926749871336.26185692843
0.4745560.25894935131293.24269802743
0.4845800.7203709631263.00179738560
0.4946037.77813231151250.08147620176
0.546274.79364805041257.97612358045
0.5146515.54092874251288.67746918242
0.5246763.96624661281342.26562289753
0.5347023.92332427111416.98584978253
0.5447298.90822816381509.40005203350
0.5547591.81855423331615.01901893278
0.5647904.75973983481728.43784828119
0.5748238.91740730151843.75843124601
0.5848594.50856171891955.36869318784
0.5948970.81643739482058.29919378137
0.649366.30442534452148.19155396973
0.6149778.79499639782222.33874504762
0.6250205.69159171142279.17125110431
0.6350644.21707859642318.70855162619
0.6451091.64325846182342.11376006980
0.6551545.49273442192351.58375996340
0.6652003.70617902872349.78646670817
0.6752464.78165840912339.92228761500
0.6852927.90342162662325.36897235197
0.6953393.08006838652309.92199329297
0.753861.30208217152298.06022256494
0.7154334.70567499382295.17940765685
0.7254816.69862058752307.73654005751
0.7355311.97553188432342.62167859298
0.7455826.34089617832405.88019698697
0.7556366.28391233682500.85690584112
0.7656938.31719035412626.01274648993
0.7757548.19153265432774.21009659517
0.7858200.19790302552933.30014549611
0.7958896.81230022433089.24019326868
0.859638.87484735423230.00921651142
0.8160426.29577643513349.88630229915
0.8261258.98681590123451.73279339837
0.8362137.4463142543545.04753279093
0.8463062.35629241743639.08151278842
0.8564032.83436314113733.05782249721
0.8665043.64436559933807.94387973689
0.8766082.50536149693827.84437231159
0.8867129.23900354673752.19201672356
0.8968158.40338263223554.54782071987
0.969146.03399016133240.46382516764
0.9170079.31289477592856.49393777381
0.9270965.94141651322486.59790002918
0.9371838.33980060922233.07528343876
0.9472747.1998266832169.80097039108
0.9573740.46977484122269.64305651045
0.9674829.5163544062375.30990502898
0.9775955.30635517592260.54292402300
0.9876979.78890195041761.4482549804
0.9977728.2672485372973.512232915508


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = red ;
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')