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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 computationSun, 01 Jun 2008 13:08:05 -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/Jun/01/t1212347364lvg1fyujhal37r0.htm/, Retrieved Sat, 18 May 2024 13:54:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=13737, Retrieved Sat, 18 May 2024 13:54:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact216

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] [Glenn Van Passen ...] [2008-06-01 19:08:05] [7568f24034461b5d7b2d183bbb217711] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
11835.70
11542.20
13093.70
11180.20
12035.70
12112.00
10875.20
9897.30
11672.10
12385.70
11405.60
9830.90
11025.10
10853.80
12252.60
11839.40
11669.10
11601.40
11178.40
9516.40
12102.80
12989.00
11610.20
10205.50
11356.20
11307.10
12648.60
11947.20
11714.10
12192.50
11268.80
9097.40
12639.80
13040.10
11687.30
11191.70
11391.90
11793.10
13933.20
12778.10
11810.30
13698.40
11956.60
10723.80
13938.90
13979.80
13807.40
12973.90
12509.80
12934.10
14908.30
13772.10
13012.60
14049.90
11816.50
11593.20
14466.20
13615.90
14733.90
13880.70
13527.50
13584.00
16170.20
13260.60
14741.90
15486.50
13154.50
12621.20
15031.60
15452.40
15428.00
13105.90
14716.80
14180.00
16202.20
14392.40
15140.60
15960.10
14729.90
13705.20
15728.50
17315.60
16152.80

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13737&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13737&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13737&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Harrell-Davis Quantiles
quantilesvaluestandard error
0.019260.6836316542375.39559374125
0.029500.2189746322349.115737449578
0.039738.49196415862361.878011120626
0.049957.52554314457401.25042217678
0.0510162.8055984676434.815954272886
0.0610356.3028504575438.470169240968
0.0710533.4520783043409.718792699306
0.0810688.6441971003361.118615568866
0.0910819.3387212793308.127043537771
0.110926.7427626725261.052504260646
0.1111014.4539595574223.683535707907
0.1211086.8113027382195.802133463900
0.1311147.8341053100175.990836486475
0.1411200.8128304019162.935590440333
0.1511248.2757816352155.390419110973
0.1611292.0778450412151.906131654007
0.1711333.4943669423150.891812214302
0.1811373.3041023847150.811791309940
0.1911411.8788636045150.400639506161
0.211449.2907311911148.840789225998
0.2111485.4314198223145.812562631674
0.2211520.1282993470141.462104545303
0.2311553.2404228698136.241961015222
0.2411584.7230301344130.868694932540
0.2511614.6568978691126.035235429075
0.2611643.2467061414122.372661049203
0.2711670.7981321878120.306705122438
0.2811697.6854480479120.055070981680
0.2911724.3199454361121.73493518053
0.311751.1256293333125.315040684757
0.3111778.5240246826130.817521641456
0.3211806.9262405753138.212611215103
0.3311836.7285616465147.497507496166
0.3411868.3078379842158.595529751464
0.3511902.0142029173171.367716011342
0.3611938.1603013937185.612192620088
0.3711977.0075720940201.034739490681
0.3812018.7509012087217.246763695697
0.3912063.5032376829233.829948087354
0.412111.2817956971250.220296621739
0.4112161.9974955974265.861422980497
0.4212215.4493571453280.14947077024
0.4312271.3255364827292.467363709038
0.4412329.2124159346302.299382672348
0.4512388.6125246873309.255142059963
0.4612448.9711541544313.049343573728
0.4712509.7105172497313.663084995568
0.4812570.2693742273311.262845640701
0.4912630.1452965041306.241148666191
0.512688.9361235556299.218031744779
0.5112746.3765966211290.948270308553
0.5212802.3656264746282.377997757568
0.5312856.9793716326274.500829252844
0.5412910.4656667272268.309533934139
0.5512963.2167961523264.57851528562
0.5613015.7204048507263.861309919563
0.5713068.4922901853266.157173914417
0.5813121.9992035584270.927180896366
0.5913176.5834642400277.284951064935
0.613232.4029135240283.906400326276
0.6113289.3986220242289.439627122828
0.6213347.2986429880292.686211687199
0.6313405.6597109807292.813318135026
0.6413463.9415927731289.487027560028
0.6513521.6025776952282.952492993065
0.6613578.2008255708273.970472422003
0.6713633.4856480030263.787421507975
0.6813687.4649601719253.888592266607
0.6913740.4390047426245.881114868161
0.713792.994712239241.256190655044
0.7113845.9588922261241.147955781333
0.7213900.3119321203246.167737212729
0.7313957.0677424900256.189455618097
0.7414017.1314332837270.224657169156
0.7514081.1538818497286.598822382623
0.7614149.4104331057303.11187373089
0.7714221.7359308368317.374812664145
0.7814297.5454975126327.342263382603
0.7914375.9562682207331.708161167309
0.814455.9994491722330.337040687549
0.8114536.8799197638324.449467380852
0.8214618.2130787351316.429142631579
0.8314700.1596910529309.221374148731
0.8414783.400610716305.406882153874
0.8514868.9464616225306.139683039911
0.8614957.8490879117310.666973457849
0.8715050.9409053084316.732398409607
0.8815148.7337325653321.844670257946
0.8915251.5274651288324.640835741514
0.915359.6178812532325.579298093479
0.9115473.3298885879326.128974890232
0.9215592.5962750009326.215207761497
0.9315716.1615123362321.715985254315
0.9415841.4108863426305.16034175156
0.9515967.3202820148272.136822605217
0.9616104.0066302923235.810036538826
0.9716287.5513763644259.651603360116
0.9816576.8113494944446.997174644264
0.9916978.4561683468791.860231977215

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 9260.6836316542 & 375.39559374125 \tabularnewline
0.02 & 9500.2189746322 & 349.115737449578 \tabularnewline
0.03 & 9738.49196415862 & 361.878011120626 \tabularnewline
0.04 & 9957.52554314457 & 401.25042217678 \tabularnewline
0.05 & 10162.8055984676 & 434.815954272886 \tabularnewline
0.06 & 10356.3028504575 & 438.470169240968 \tabularnewline
0.07 & 10533.4520783043 & 409.718792699306 \tabularnewline
0.08 & 10688.6441971003 & 361.118615568866 \tabularnewline
0.09 & 10819.3387212793 & 308.127043537771 \tabularnewline
0.1 & 10926.7427626725 & 261.052504260646 \tabularnewline
0.11 & 11014.4539595574 & 223.683535707907 \tabularnewline
0.12 & 11086.8113027382 & 195.802133463900 \tabularnewline
0.13 & 11147.8341053100 & 175.990836486475 \tabularnewline
0.14 & 11200.8128304019 & 162.935590440333 \tabularnewline
0.15 & 11248.2757816352 & 155.390419110973 \tabularnewline
0.16 & 11292.0778450412 & 151.906131654007 \tabularnewline
0.17 & 11333.4943669423 & 150.891812214302 \tabularnewline
0.18 & 11373.3041023847 & 150.811791309940 \tabularnewline
0.19 & 11411.8788636045 & 150.400639506161 \tabularnewline
0.2 & 11449.2907311911 & 148.840789225998 \tabularnewline
0.21 & 11485.4314198223 & 145.812562631674 \tabularnewline
0.22 & 11520.1282993470 & 141.462104545303 \tabularnewline
0.23 & 11553.2404228698 & 136.241961015222 \tabularnewline
0.24 & 11584.7230301344 & 130.868694932540 \tabularnewline
0.25 & 11614.6568978691 & 126.035235429075 \tabularnewline
0.26 & 11643.2467061414 & 122.372661049203 \tabularnewline
0.27 & 11670.7981321878 & 120.306705122438 \tabularnewline
0.28 & 11697.6854480479 & 120.055070981680 \tabularnewline
0.29 & 11724.3199454361 & 121.73493518053 \tabularnewline
0.3 & 11751.1256293333 & 125.315040684757 \tabularnewline
0.31 & 11778.5240246826 & 130.817521641456 \tabularnewline
0.32 & 11806.9262405753 & 138.212611215103 \tabularnewline
0.33 & 11836.7285616465 & 147.497507496166 \tabularnewline
0.34 & 11868.3078379842 & 158.595529751464 \tabularnewline
0.35 & 11902.0142029173 & 171.367716011342 \tabularnewline
0.36 & 11938.1603013937 & 185.612192620088 \tabularnewline
0.37 & 11977.0075720940 & 201.034739490681 \tabularnewline
0.38 & 12018.7509012087 & 217.246763695697 \tabularnewline
0.39 & 12063.5032376829 & 233.829948087354 \tabularnewline
0.4 & 12111.2817956971 & 250.220296621739 \tabularnewline
0.41 & 12161.9974955974 & 265.861422980497 \tabularnewline
0.42 & 12215.4493571453 & 280.14947077024 \tabularnewline
0.43 & 12271.3255364827 & 292.467363709038 \tabularnewline
0.44 & 12329.2124159346 & 302.299382672348 \tabularnewline
0.45 & 12388.6125246873 & 309.255142059963 \tabularnewline
0.46 & 12448.9711541544 & 313.049343573728 \tabularnewline
0.47 & 12509.7105172497 & 313.663084995568 \tabularnewline
0.48 & 12570.2693742273 & 311.262845640701 \tabularnewline
0.49 & 12630.1452965041 & 306.241148666191 \tabularnewline
0.5 & 12688.9361235556 & 299.218031744779 \tabularnewline
0.51 & 12746.3765966211 & 290.948270308553 \tabularnewline
0.52 & 12802.3656264746 & 282.377997757568 \tabularnewline
0.53 & 12856.9793716326 & 274.500829252844 \tabularnewline
0.54 & 12910.4656667272 & 268.309533934139 \tabularnewline
0.55 & 12963.2167961523 & 264.57851528562 \tabularnewline
0.56 & 13015.7204048507 & 263.861309919563 \tabularnewline
0.57 & 13068.4922901853 & 266.157173914417 \tabularnewline
0.58 & 13121.9992035584 & 270.927180896366 \tabularnewline
0.59 & 13176.5834642400 & 277.284951064935 \tabularnewline
0.6 & 13232.4029135240 & 283.906400326276 \tabularnewline
0.61 & 13289.3986220242 & 289.439627122828 \tabularnewline
0.62 & 13347.2986429880 & 292.686211687199 \tabularnewline
0.63 & 13405.6597109807 & 292.813318135026 \tabularnewline
0.64 & 13463.9415927731 & 289.487027560028 \tabularnewline
0.65 & 13521.6025776952 & 282.952492993065 \tabularnewline
0.66 & 13578.2008255708 & 273.970472422003 \tabularnewline
0.67 & 13633.4856480030 & 263.787421507975 \tabularnewline
0.68 & 13687.4649601719 & 253.888592266607 \tabularnewline
0.69 & 13740.4390047426 & 245.881114868161 \tabularnewline
0.7 & 13792.994712239 & 241.256190655044 \tabularnewline
0.71 & 13845.9588922261 & 241.147955781333 \tabularnewline
0.72 & 13900.3119321203 & 246.167737212729 \tabularnewline
0.73 & 13957.0677424900 & 256.189455618097 \tabularnewline
0.74 & 14017.1314332837 & 270.224657169156 \tabularnewline
0.75 & 14081.1538818497 & 286.598822382623 \tabularnewline
0.76 & 14149.4104331057 & 303.11187373089 \tabularnewline
0.77 & 14221.7359308368 & 317.374812664145 \tabularnewline
0.78 & 14297.5454975126 & 327.342263382603 \tabularnewline
0.79 & 14375.9562682207 & 331.708161167309 \tabularnewline
0.8 & 14455.9994491722 & 330.337040687549 \tabularnewline
0.81 & 14536.8799197638 & 324.449467380852 \tabularnewline
0.82 & 14618.2130787351 & 316.429142631579 \tabularnewline
0.83 & 14700.1596910529 & 309.221374148731 \tabularnewline
0.84 & 14783.400610716 & 305.406882153874 \tabularnewline
0.85 & 14868.9464616225 & 306.139683039911 \tabularnewline
0.86 & 14957.8490879117 & 310.666973457849 \tabularnewline
0.87 & 15050.9409053084 & 316.732398409607 \tabularnewline
0.88 & 15148.7337325653 & 321.844670257946 \tabularnewline
0.89 & 15251.5274651288 & 324.640835741514 \tabularnewline
0.9 & 15359.6178812532 & 325.579298093479 \tabularnewline
0.91 & 15473.3298885879 & 326.128974890232 \tabularnewline
0.92 & 15592.5962750009 & 326.215207761497 \tabularnewline
0.93 & 15716.1615123362 & 321.715985254315 \tabularnewline
0.94 & 15841.4108863426 & 305.16034175156 \tabularnewline
0.95 & 15967.3202820148 & 272.136822605217 \tabularnewline
0.96 & 16104.0066302923 & 235.810036538826 \tabularnewline
0.97 & 16287.5513763644 & 259.651603360116 \tabularnewline
0.98 & 16576.8113494944 & 446.997174644264 \tabularnewline
0.99 & 16978.4561683468 & 791.860231977215 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13737&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]9260.6836316542[/C][C]375.39559374125[/C][/ROW]
[ROW][C]0.02[/C][C]9500.2189746322[/C][C]349.115737449578[/C][/ROW]
[ROW][C]0.03[/C][C]9738.49196415862[/C][C]361.878011120626[/C][/ROW]
[ROW][C]0.04[/C][C]9957.52554314457[/C][C]401.25042217678[/C][/ROW]
[ROW][C]0.05[/C][C]10162.8055984676[/C][C]434.815954272886[/C][/ROW]
[ROW][C]0.06[/C][C]10356.3028504575[/C][C]438.470169240968[/C][/ROW]
[ROW][C]0.07[/C][C]10533.4520783043[/C][C]409.718792699306[/C][/ROW]
[ROW][C]0.08[/C][C]10688.6441971003[/C][C]361.118615568866[/C][/ROW]
[ROW][C]0.09[/C][C]10819.3387212793[/C][C]308.127043537771[/C][/ROW]
[ROW][C]0.1[/C][C]10926.7427626725[/C][C]261.052504260646[/C][/ROW]
[ROW][C]0.11[/C][C]11014.4539595574[/C][C]223.683535707907[/C][/ROW]
[ROW][C]0.12[/C][C]11086.8113027382[/C][C]195.802133463900[/C][/ROW]
[ROW][C]0.13[/C][C]11147.8341053100[/C][C]175.990836486475[/C][/ROW]
[ROW][C]0.14[/C][C]11200.8128304019[/C][C]162.935590440333[/C][/ROW]
[ROW][C]0.15[/C][C]11248.2757816352[/C][C]155.390419110973[/C][/ROW]
[ROW][C]0.16[/C][C]11292.0778450412[/C][C]151.906131654007[/C][/ROW]
[ROW][C]0.17[/C][C]11333.4943669423[/C][C]150.891812214302[/C][/ROW]
[ROW][C]0.18[/C][C]11373.3041023847[/C][C]150.811791309940[/C][/ROW]
[ROW][C]0.19[/C][C]11411.8788636045[/C][C]150.400639506161[/C][/ROW]
[ROW][C]0.2[/C][C]11449.2907311911[/C][C]148.840789225998[/C][/ROW]
[ROW][C]0.21[/C][C]11485.4314198223[/C][C]145.812562631674[/C][/ROW]
[ROW][C]0.22[/C][C]11520.1282993470[/C][C]141.462104545303[/C][/ROW]
[ROW][C]0.23[/C][C]11553.2404228698[/C][C]136.241961015222[/C][/ROW]
[ROW][C]0.24[/C][C]11584.7230301344[/C][C]130.868694932540[/C][/ROW]
[ROW][C]0.25[/C][C]11614.6568978691[/C][C]126.035235429075[/C][/ROW]
[ROW][C]0.26[/C][C]11643.2467061414[/C][C]122.372661049203[/C][/ROW]
[ROW][C]0.27[/C][C]11670.7981321878[/C][C]120.306705122438[/C][/ROW]
[ROW][C]0.28[/C][C]11697.6854480479[/C][C]120.055070981680[/C][/ROW]
[ROW][C]0.29[/C][C]11724.3199454361[/C][C]121.73493518053[/C][/ROW]
[ROW][C]0.3[/C][C]11751.1256293333[/C][C]125.315040684757[/C][/ROW]
[ROW][C]0.31[/C][C]11778.5240246826[/C][C]130.817521641456[/C][/ROW]
[ROW][C]0.32[/C][C]11806.9262405753[/C][C]138.212611215103[/C][/ROW]
[ROW][C]0.33[/C][C]11836.7285616465[/C][C]147.497507496166[/C][/ROW]
[ROW][C]0.34[/C][C]11868.3078379842[/C][C]158.595529751464[/C][/ROW]
[ROW][C]0.35[/C][C]11902.0142029173[/C][C]171.367716011342[/C][/ROW]
[ROW][C]0.36[/C][C]11938.1603013937[/C][C]185.612192620088[/C][/ROW]
[ROW][C]0.37[/C][C]11977.0075720940[/C][C]201.034739490681[/C][/ROW]
[ROW][C]0.38[/C][C]12018.7509012087[/C][C]217.246763695697[/C][/ROW]
[ROW][C]0.39[/C][C]12063.5032376829[/C][C]233.829948087354[/C][/ROW]
[ROW][C]0.4[/C][C]12111.2817956971[/C][C]250.220296621739[/C][/ROW]
[ROW][C]0.41[/C][C]12161.9974955974[/C][C]265.861422980497[/C][/ROW]
[ROW][C]0.42[/C][C]12215.4493571453[/C][C]280.14947077024[/C][/ROW]
[ROW][C]0.43[/C][C]12271.3255364827[/C][C]292.467363709038[/C][/ROW]
[ROW][C]0.44[/C][C]12329.2124159346[/C][C]302.299382672348[/C][/ROW]
[ROW][C]0.45[/C][C]12388.6125246873[/C][C]309.255142059963[/C][/ROW]
[ROW][C]0.46[/C][C]12448.9711541544[/C][C]313.049343573728[/C][/ROW]
[ROW][C]0.47[/C][C]12509.7105172497[/C][C]313.663084995568[/C][/ROW]
[ROW][C]0.48[/C][C]12570.2693742273[/C][C]311.262845640701[/C][/ROW]
[ROW][C]0.49[/C][C]12630.1452965041[/C][C]306.241148666191[/C][/ROW]
[ROW][C]0.5[/C][C]12688.9361235556[/C][C]299.218031744779[/C][/ROW]
[ROW][C]0.51[/C][C]12746.3765966211[/C][C]290.948270308553[/C][/ROW]
[ROW][C]0.52[/C][C]12802.3656264746[/C][C]282.377997757568[/C][/ROW]
[ROW][C]0.53[/C][C]12856.9793716326[/C][C]274.500829252844[/C][/ROW]
[ROW][C]0.54[/C][C]12910.4656667272[/C][C]268.309533934139[/C][/ROW]
[ROW][C]0.55[/C][C]12963.2167961523[/C][C]264.57851528562[/C][/ROW]
[ROW][C]0.56[/C][C]13015.7204048507[/C][C]263.861309919563[/C][/ROW]
[ROW][C]0.57[/C][C]13068.4922901853[/C][C]266.157173914417[/C][/ROW]
[ROW][C]0.58[/C][C]13121.9992035584[/C][C]270.927180896366[/C][/ROW]
[ROW][C]0.59[/C][C]13176.5834642400[/C][C]277.284951064935[/C][/ROW]
[ROW][C]0.6[/C][C]13232.4029135240[/C][C]283.906400326276[/C][/ROW]
[ROW][C]0.61[/C][C]13289.3986220242[/C][C]289.439627122828[/C][/ROW]
[ROW][C]0.62[/C][C]13347.2986429880[/C][C]292.686211687199[/C][/ROW]
[ROW][C]0.63[/C][C]13405.6597109807[/C][C]292.813318135026[/C][/ROW]
[ROW][C]0.64[/C][C]13463.9415927731[/C][C]289.487027560028[/C][/ROW]
[ROW][C]0.65[/C][C]13521.6025776952[/C][C]282.952492993065[/C][/ROW]
[ROW][C]0.66[/C][C]13578.2008255708[/C][C]273.970472422003[/C][/ROW]
[ROW][C]0.67[/C][C]13633.4856480030[/C][C]263.787421507975[/C][/ROW]
[ROW][C]0.68[/C][C]13687.4649601719[/C][C]253.888592266607[/C][/ROW]
[ROW][C]0.69[/C][C]13740.4390047426[/C][C]245.881114868161[/C][/ROW]
[ROW][C]0.7[/C][C]13792.994712239[/C][C]241.256190655044[/C][/ROW]
[ROW][C]0.71[/C][C]13845.9588922261[/C][C]241.147955781333[/C][/ROW]
[ROW][C]0.72[/C][C]13900.3119321203[/C][C]246.167737212729[/C][/ROW]
[ROW][C]0.73[/C][C]13957.0677424900[/C][C]256.189455618097[/C][/ROW]
[ROW][C]0.74[/C][C]14017.1314332837[/C][C]270.224657169156[/C][/ROW]
[ROW][C]0.75[/C][C]14081.1538818497[/C][C]286.598822382623[/C][/ROW]
[ROW][C]0.76[/C][C]14149.4104331057[/C][C]303.11187373089[/C][/ROW]
[ROW][C]0.77[/C][C]14221.7359308368[/C][C]317.374812664145[/C][/ROW]
[ROW][C]0.78[/C][C]14297.5454975126[/C][C]327.342263382603[/C][/ROW]
[ROW][C]0.79[/C][C]14375.9562682207[/C][C]331.708161167309[/C][/ROW]
[ROW][C]0.8[/C][C]14455.9994491722[/C][C]330.337040687549[/C][/ROW]
[ROW][C]0.81[/C][C]14536.8799197638[/C][C]324.449467380852[/C][/ROW]
[ROW][C]0.82[/C][C]14618.2130787351[/C][C]316.429142631579[/C][/ROW]
[ROW][C]0.83[/C][C]14700.1596910529[/C][C]309.221374148731[/C][/ROW]
[ROW][C]0.84[/C][C]14783.400610716[/C][C]305.406882153874[/C][/ROW]
[ROW][C]0.85[/C][C]14868.9464616225[/C][C]306.139683039911[/C][/ROW]
[ROW][C]0.86[/C][C]14957.8490879117[/C][C]310.666973457849[/C][/ROW]
[ROW][C]0.87[/C][C]15050.9409053084[/C][C]316.732398409607[/C][/ROW]
[ROW][C]0.88[/C][C]15148.7337325653[/C][C]321.844670257946[/C][/ROW]
[ROW][C]0.89[/C][C]15251.5274651288[/C][C]324.640835741514[/C][/ROW]
[ROW][C]0.9[/C][C]15359.6178812532[/C][C]325.579298093479[/C][/ROW]
[ROW][C]0.91[/C][C]15473.3298885879[/C][C]326.128974890232[/C][/ROW]
[ROW][C]0.92[/C][C]15592.5962750009[/C][C]326.215207761497[/C][/ROW]
[ROW][C]0.93[/C][C]15716.1615123362[/C][C]321.715985254315[/C][/ROW]
[ROW][C]0.94[/C][C]15841.4108863426[/C][C]305.16034175156[/C][/ROW]
[ROW][C]0.95[/C][C]15967.3202820148[/C][C]272.136822605217[/C][/ROW]
[ROW][C]0.96[/C][C]16104.0066302923[/C][C]235.810036538826[/C][/ROW]
[ROW][C]0.97[/C][C]16287.5513763644[/C][C]259.651603360116[/C][/ROW]
[ROW][C]0.98[/C][C]16576.8113494944[/C][C]446.997174644264[/C][/ROW]
[ROW][C]0.99[/C][C]16978.4561683468[/C][C]791.860231977215[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13737&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13737&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
0.019260.6836316542375.39559374125
0.029500.2189746322349.115737449578
0.039738.49196415862361.878011120626
0.049957.52554314457401.25042217678
0.0510162.8055984676434.815954272886
0.0610356.3028504575438.470169240968
0.0710533.4520783043409.718792699306
0.0810688.6441971003361.118615568866
0.0910819.3387212793308.127043537771
0.110926.7427626725261.052504260646
0.1111014.4539595574223.683535707907
0.1211086.8113027382195.802133463900
0.1311147.8341053100175.990836486475
0.1411200.8128304019162.935590440333
0.1511248.2757816352155.390419110973
0.1611292.0778450412151.906131654007
0.1711333.4943669423150.891812214302
0.1811373.3041023847150.811791309940
0.1911411.8788636045150.400639506161
0.211449.2907311911148.840789225998
0.2111485.4314198223145.812562631674
0.2211520.1282993470141.462104545303
0.2311553.2404228698136.241961015222
0.2411584.7230301344130.868694932540
0.2511614.6568978691126.035235429075
0.2611643.2467061414122.372661049203
0.2711670.7981321878120.306705122438
0.2811697.6854480479120.055070981680
0.2911724.3199454361121.73493518053
0.311751.1256293333125.315040684757
0.3111778.5240246826130.817521641456
0.3211806.9262405753138.212611215103
0.3311836.7285616465147.497507496166
0.3411868.3078379842158.595529751464
0.3511902.0142029173171.367716011342
0.3611938.1603013937185.612192620088
0.3711977.0075720940201.034739490681
0.3812018.7509012087217.246763695697
0.3912063.5032376829233.829948087354
0.412111.2817956971250.220296621739
0.4112161.9974955974265.861422980497
0.4212215.4493571453280.14947077024
0.4312271.3255364827292.467363709038
0.4412329.2124159346302.299382672348
0.4512388.6125246873309.255142059963
0.4612448.9711541544313.049343573728
0.4712509.7105172497313.663084995568
0.4812570.2693742273311.262845640701
0.4912630.1452965041306.241148666191
0.512688.9361235556299.218031744779
0.5112746.3765966211290.948270308553
0.5212802.3656264746282.377997757568
0.5312856.9793716326274.500829252844
0.5412910.4656667272268.309533934139
0.5512963.2167961523264.57851528562
0.5613015.7204048507263.861309919563
0.5713068.4922901853266.157173914417
0.5813121.9992035584270.927180896366
0.5913176.5834642400277.284951064935
0.613232.4029135240283.906400326276
0.6113289.3986220242289.439627122828
0.6213347.2986429880292.686211687199
0.6313405.6597109807292.813318135026
0.6413463.9415927731289.487027560028
0.6513521.6025776952282.952492993065
0.6613578.2008255708273.970472422003
0.6713633.4856480030263.787421507975
0.6813687.4649601719253.888592266607
0.6913740.4390047426245.881114868161
0.713792.994712239241.256190655044
0.7113845.9588922261241.147955781333
0.7213900.3119321203246.167737212729
0.7313957.0677424900256.189455618097
0.7414017.1314332837270.224657169156
0.7514081.1538818497286.598822382623
0.7614149.4104331057303.11187373089
0.7714221.7359308368317.374812664145
0.7814297.5454975126327.342263382603
0.7914375.9562682207331.708161167309
0.814455.9994491722330.337040687549
0.8114536.8799197638324.449467380852
0.8214618.2130787351316.429142631579
0.8314700.1596910529309.221374148731
0.8414783.400610716305.406882153874
0.8514868.9464616225306.139683039911
0.8614957.8490879117310.666973457849
0.8715050.9409053084316.732398409607
0.8815148.7337325653321.844670257946
0.8915251.5274651288324.640835741514
0.915359.6178812532325.579298093479
0.9115473.3298885879326.128974890232
0.9215592.5962750009326.215207761497
0.9315716.1615123362321.715985254315
0.9415841.4108863426305.16034175156
0.9515967.3202820148272.136822605217
0.9616104.0066302923235.810036538826
0.9716287.5513763644259.651603360116
0.9816576.8113494944446.997174644264
0.9916978.4561683468791.860231977215


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')