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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationSun, 18 Oct 2009 09:17:36 -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/Oct/18/t1255879097qr9bnfgmxoxhzke.htm/, Retrieved Mon, 29 Apr 2024 09:50:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=47357, Retrieved Mon, 29 Apr 2024 09:50:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsws3p2c5
Estimated Impact167

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] [] [2009-10-18 15:17:36] [9ea4b07b6662a0f40f92decdf1e3b5d5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34
2197.82
2014.45
1862.83
1905.41
1810.99
1670.07
1864.44
2052.02
2029.6
2070.83
2293.41
2443.27

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'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=47357&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=47357&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=47357&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'Gwilym Jenkins' @ 72.249.127.135






Harrell-Davis Quantiles
quantilesvaluestandard error
0.011701.55105091892119.743344104442
0.021746.3641676044795.0023213573964
0.031791.1571323803474.9841764241402
0.041829.7413867612165.5460154001404
0.051862.194169038966.6333199571465
0.061891.1019945198574.2433074719642
0.071919.0082457913284.4958915713106
0.081947.5940035233295.6500296850836
0.091977.82423597998107.970734729901
0.12010.34616254053122.852073154950
0.112045.78232141046141.703892693694
0.122084.82223278145165.049257087626
0.132128.14785027080192.201845578587
0.142176.27454877657221.459894771439
0.152229.38881468367250.512362610087
0.162287.24018318957276.857565701153
0.172349.11457636022298.18641224847
0.182413.88930612357312.699363383203
0.192480.15147027741319.302470699257
0.22546.35211018733317.728345051721
0.212610.96694019794308.46815560179
0.222672.63854288914292.668029534937
0.232730.28243502937271.916157378692
0.242783.14831600818248.001371060852
0.252830.83635631909222.714859633545
0.262873.27519715683197.647252749934
0.272910.67257262183174.111605619466
0.282943.45091301774153.072275030957
0.292972.17930363248135.155272534327
0.32997.51053073607120.704419026788
0.313020.1285771803109.827888262849
0.323040.70867949217102.471307299366
0.333059.8895149221398.4408919086328
0.343078.2555164326397.4426660344317
0.353096.3266920040799.1213813647518
0.363114.5534322444103.059409643182
0.373133.31432562308108.828770359599
0.383152.91567819061116.003157434971
0.393173.59204687345124.170904084985
0.43195.5075347915132.930752183826
0.413218.7578451218141.906161374566
0.423243.37318715785150.739026068393
0.433269.32213751843159.102201311312
0.443296.51653676708166.687179885344
0.453324.81747810293173.219162413306
0.463354.04242361871178.463573065505
0.473383.97344925157182.234163970572
0.483414.36655230351184.390986728742
0.493444.96184618521184.872018982771
0.53475.49432613106183.667524113022
0.513505.70474682712180.839980955226
0.523535.35004918727176.529800971260
0.533564.21274760698170.917227241434
0.543592.10876332790164.236674175668
0.553618.89336046537156.750672883184
0.563644.46507704122148.738356445532
0.573668.76779043144140.481975045724
0.583691.79125265578132.245133658513
0.593713.57052126874124.291272331524
0.63734.18466473867116.859181287304
0.613753.75493927502110.188997473218
0.623772.44235601151104.498043412084
0.633790.44425382485100.002734098483
0.643807.9892533618396.8990667455032
0.653825.3298822908295.3418979641768
0.663842.7323002527795.417421772537
0.673860.4629432712697.1022570122234
0.683878.77252281249100.254612678285
0.693897.8785605138104.586613826228
0.73917.94836298806109.712419240710
0.713939.08485322441115.146172415890
0.723961.31779126917120.392357156070
0.733984.60250806231124.974279068636
0.744008.82731950776128.494424391314
0.754033.82939818905130.694452536767
0.764059.41730833563131.477863425306
0.774085.39699672742130.915165843576
0.784111.59712797338129.228185113934
0.794137.88952040233126.765588492119
0.84164.20117862131123.904163521806
0.814190.51593485803120.999957884816
0.824216.86573090257118.313320925835
0.834243.31369756464115.972884250084
0.844269.93294816636113.954208943959
0.854296.78589679535112.102679401073
0.864323.90848397969110.187583508784
0.874351.30170838631107.968620751337
0.884378.92965242707105.256113878323
0.894406.72005086259101.943960129803
0.94434.5628028673597.982076694313
0.914462.3066059039793.305250333706
0.924489.7656927889187.7586945910622
0.934516.7641486935481.1287123721522
0.944543.2502876900473.3788820334074
0.954569.4759339963365.0524537653744
0.964596.1093042109357.7592617245356
0.974623.9336149064854.3654965653944
0.984652.6861573030757.5551957183953
0.994679.210035528966.1654088271386

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 1701.55105091892 & 119.743344104442 \tabularnewline
0.02 & 1746.36416760447 & 95.0023213573964 \tabularnewline
0.03 & 1791.15713238034 & 74.9841764241402 \tabularnewline
0.04 & 1829.74138676121 & 65.5460154001404 \tabularnewline
0.05 & 1862.1941690389 & 66.6333199571465 \tabularnewline
0.06 & 1891.10199451985 & 74.2433074719642 \tabularnewline
0.07 & 1919.00824579132 & 84.4958915713106 \tabularnewline
0.08 & 1947.59400352332 & 95.6500296850836 \tabularnewline
0.09 & 1977.82423597998 & 107.970734729901 \tabularnewline
0.1 & 2010.34616254053 & 122.852073154950 \tabularnewline
0.11 & 2045.78232141046 & 141.703892693694 \tabularnewline
0.12 & 2084.82223278145 & 165.049257087626 \tabularnewline
0.13 & 2128.14785027080 & 192.201845578587 \tabularnewline
0.14 & 2176.27454877657 & 221.459894771439 \tabularnewline
0.15 & 2229.38881468367 & 250.512362610087 \tabularnewline
0.16 & 2287.24018318957 & 276.857565701153 \tabularnewline
0.17 & 2349.11457636022 & 298.18641224847 \tabularnewline
0.18 & 2413.88930612357 & 312.699363383203 \tabularnewline
0.19 & 2480.15147027741 & 319.302470699257 \tabularnewline
0.2 & 2546.35211018733 & 317.728345051721 \tabularnewline
0.21 & 2610.96694019794 & 308.46815560179 \tabularnewline
0.22 & 2672.63854288914 & 292.668029534937 \tabularnewline
0.23 & 2730.28243502937 & 271.916157378692 \tabularnewline
0.24 & 2783.14831600818 & 248.001371060852 \tabularnewline
0.25 & 2830.83635631909 & 222.714859633545 \tabularnewline
0.26 & 2873.27519715683 & 197.647252749934 \tabularnewline
0.27 & 2910.67257262183 & 174.111605619466 \tabularnewline
0.28 & 2943.45091301774 & 153.072275030957 \tabularnewline
0.29 & 2972.17930363248 & 135.155272534327 \tabularnewline
0.3 & 2997.51053073607 & 120.704419026788 \tabularnewline
0.31 & 3020.1285771803 & 109.827888262849 \tabularnewline
0.32 & 3040.70867949217 & 102.471307299366 \tabularnewline
0.33 & 3059.88951492213 & 98.4408919086328 \tabularnewline
0.34 & 3078.25551643263 & 97.4426660344317 \tabularnewline
0.35 & 3096.32669200407 & 99.1213813647518 \tabularnewline
0.36 & 3114.5534322444 & 103.059409643182 \tabularnewline
0.37 & 3133.31432562308 & 108.828770359599 \tabularnewline
0.38 & 3152.91567819061 & 116.003157434971 \tabularnewline
0.39 & 3173.59204687345 & 124.170904084985 \tabularnewline
0.4 & 3195.5075347915 & 132.930752183826 \tabularnewline
0.41 & 3218.7578451218 & 141.906161374566 \tabularnewline
0.42 & 3243.37318715785 & 150.739026068393 \tabularnewline
0.43 & 3269.32213751843 & 159.102201311312 \tabularnewline
0.44 & 3296.51653676708 & 166.687179885344 \tabularnewline
0.45 & 3324.81747810293 & 173.219162413306 \tabularnewline
0.46 & 3354.04242361871 & 178.463573065505 \tabularnewline
0.47 & 3383.97344925157 & 182.234163970572 \tabularnewline
0.48 & 3414.36655230351 & 184.390986728742 \tabularnewline
0.49 & 3444.96184618521 & 184.872018982771 \tabularnewline
0.5 & 3475.49432613106 & 183.667524113022 \tabularnewline
0.51 & 3505.70474682712 & 180.839980955226 \tabularnewline
0.52 & 3535.35004918727 & 176.529800971260 \tabularnewline
0.53 & 3564.21274760698 & 170.917227241434 \tabularnewline
0.54 & 3592.10876332790 & 164.236674175668 \tabularnewline
0.55 & 3618.89336046537 & 156.750672883184 \tabularnewline
0.56 & 3644.46507704122 & 148.738356445532 \tabularnewline
0.57 & 3668.76779043144 & 140.481975045724 \tabularnewline
0.58 & 3691.79125265578 & 132.245133658513 \tabularnewline
0.59 & 3713.57052126874 & 124.291272331524 \tabularnewline
0.6 & 3734.18466473867 & 116.859181287304 \tabularnewline
0.61 & 3753.75493927502 & 110.188997473218 \tabularnewline
0.62 & 3772.44235601151 & 104.498043412084 \tabularnewline
0.63 & 3790.44425382485 & 100.002734098483 \tabularnewline
0.64 & 3807.98925336183 & 96.8990667455032 \tabularnewline
0.65 & 3825.32988229082 & 95.3418979641768 \tabularnewline
0.66 & 3842.73230025277 & 95.417421772537 \tabularnewline
0.67 & 3860.46294327126 & 97.1022570122234 \tabularnewline
0.68 & 3878.77252281249 & 100.254612678285 \tabularnewline
0.69 & 3897.8785605138 & 104.586613826228 \tabularnewline
0.7 & 3917.94836298806 & 109.712419240710 \tabularnewline
0.71 & 3939.08485322441 & 115.146172415890 \tabularnewline
0.72 & 3961.31779126917 & 120.392357156070 \tabularnewline
0.73 & 3984.60250806231 & 124.974279068636 \tabularnewline
0.74 & 4008.82731950776 & 128.494424391314 \tabularnewline
0.75 & 4033.82939818905 & 130.694452536767 \tabularnewline
0.76 & 4059.41730833563 & 131.477863425306 \tabularnewline
0.77 & 4085.39699672742 & 130.915165843576 \tabularnewline
0.78 & 4111.59712797338 & 129.228185113934 \tabularnewline
0.79 & 4137.88952040233 & 126.765588492119 \tabularnewline
0.8 & 4164.20117862131 & 123.904163521806 \tabularnewline
0.81 & 4190.51593485803 & 120.999957884816 \tabularnewline
0.82 & 4216.86573090257 & 118.313320925835 \tabularnewline
0.83 & 4243.31369756464 & 115.972884250084 \tabularnewline
0.84 & 4269.93294816636 & 113.954208943959 \tabularnewline
0.85 & 4296.78589679535 & 112.102679401073 \tabularnewline
0.86 & 4323.90848397969 & 110.187583508784 \tabularnewline
0.87 & 4351.30170838631 & 107.968620751337 \tabularnewline
0.88 & 4378.92965242707 & 105.256113878323 \tabularnewline
0.89 & 4406.72005086259 & 101.943960129803 \tabularnewline
0.9 & 4434.56280286735 & 97.982076694313 \tabularnewline
0.91 & 4462.30660590397 & 93.305250333706 \tabularnewline
0.92 & 4489.76569278891 & 87.7586945910622 \tabularnewline
0.93 & 4516.76414869354 & 81.1287123721522 \tabularnewline
0.94 & 4543.25028769004 & 73.3788820334074 \tabularnewline
0.95 & 4569.47593399633 & 65.0524537653744 \tabularnewline
0.96 & 4596.10930421093 & 57.7592617245356 \tabularnewline
0.97 & 4623.93361490648 & 54.3654965653944 \tabularnewline
0.98 & 4652.68615730307 & 57.5551957183953 \tabularnewline
0.99 & 4679.2100355289 & 66.1654088271386 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=47357&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]1701.55105091892[/C][C]119.743344104442[/C][/ROW]
[ROW][C]0.02[/C][C]1746.36416760447[/C][C]95.0023213573964[/C][/ROW]
[ROW][C]0.03[/C][C]1791.15713238034[/C][C]74.9841764241402[/C][/ROW]
[ROW][C]0.04[/C][C]1829.74138676121[/C][C]65.5460154001404[/C][/ROW]
[ROW][C]0.05[/C][C]1862.1941690389[/C][C]66.6333199571465[/C][/ROW]
[ROW][C]0.06[/C][C]1891.10199451985[/C][C]74.2433074719642[/C][/ROW]
[ROW][C]0.07[/C][C]1919.00824579132[/C][C]84.4958915713106[/C][/ROW]
[ROW][C]0.08[/C][C]1947.59400352332[/C][C]95.6500296850836[/C][/ROW]
[ROW][C]0.09[/C][C]1977.82423597998[/C][C]107.970734729901[/C][/ROW]
[ROW][C]0.1[/C][C]2010.34616254053[/C][C]122.852073154950[/C][/ROW]
[ROW][C]0.11[/C][C]2045.78232141046[/C][C]141.703892693694[/C][/ROW]
[ROW][C]0.12[/C][C]2084.82223278145[/C][C]165.049257087626[/C][/ROW]
[ROW][C]0.13[/C][C]2128.14785027080[/C][C]192.201845578587[/C][/ROW]
[ROW][C]0.14[/C][C]2176.27454877657[/C][C]221.459894771439[/C][/ROW]
[ROW][C]0.15[/C][C]2229.38881468367[/C][C]250.512362610087[/C][/ROW]
[ROW][C]0.16[/C][C]2287.24018318957[/C][C]276.857565701153[/C][/ROW]
[ROW][C]0.17[/C][C]2349.11457636022[/C][C]298.18641224847[/C][/ROW]
[ROW][C]0.18[/C][C]2413.88930612357[/C][C]312.699363383203[/C][/ROW]
[ROW][C]0.19[/C][C]2480.15147027741[/C][C]319.302470699257[/C][/ROW]
[ROW][C]0.2[/C][C]2546.35211018733[/C][C]317.728345051721[/C][/ROW]
[ROW][C]0.21[/C][C]2610.96694019794[/C][C]308.46815560179[/C][/ROW]
[ROW][C]0.22[/C][C]2672.63854288914[/C][C]292.668029534937[/C][/ROW]
[ROW][C]0.23[/C][C]2730.28243502937[/C][C]271.916157378692[/C][/ROW]
[ROW][C]0.24[/C][C]2783.14831600818[/C][C]248.001371060852[/C][/ROW]
[ROW][C]0.25[/C][C]2830.83635631909[/C][C]222.714859633545[/C][/ROW]
[ROW][C]0.26[/C][C]2873.27519715683[/C][C]197.647252749934[/C][/ROW]
[ROW][C]0.27[/C][C]2910.67257262183[/C][C]174.111605619466[/C][/ROW]
[ROW][C]0.28[/C][C]2943.45091301774[/C][C]153.072275030957[/C][/ROW]
[ROW][C]0.29[/C][C]2972.17930363248[/C][C]135.155272534327[/C][/ROW]
[ROW][C]0.3[/C][C]2997.51053073607[/C][C]120.704419026788[/C][/ROW]
[ROW][C]0.31[/C][C]3020.1285771803[/C][C]109.827888262849[/C][/ROW]
[ROW][C]0.32[/C][C]3040.70867949217[/C][C]102.471307299366[/C][/ROW]
[ROW][C]0.33[/C][C]3059.88951492213[/C][C]98.4408919086328[/C][/ROW]
[ROW][C]0.34[/C][C]3078.25551643263[/C][C]97.4426660344317[/C][/ROW]
[ROW][C]0.35[/C][C]3096.32669200407[/C][C]99.1213813647518[/C][/ROW]
[ROW][C]0.36[/C][C]3114.5534322444[/C][C]103.059409643182[/C][/ROW]
[ROW][C]0.37[/C][C]3133.31432562308[/C][C]108.828770359599[/C][/ROW]
[ROW][C]0.38[/C][C]3152.91567819061[/C][C]116.003157434971[/C][/ROW]
[ROW][C]0.39[/C][C]3173.59204687345[/C][C]124.170904084985[/C][/ROW]
[ROW][C]0.4[/C][C]3195.5075347915[/C][C]132.930752183826[/C][/ROW]
[ROW][C]0.41[/C][C]3218.7578451218[/C][C]141.906161374566[/C][/ROW]
[ROW][C]0.42[/C][C]3243.37318715785[/C][C]150.739026068393[/C][/ROW]
[ROW][C]0.43[/C][C]3269.32213751843[/C][C]159.102201311312[/C][/ROW]
[ROW][C]0.44[/C][C]3296.51653676708[/C][C]166.687179885344[/C][/ROW]
[ROW][C]0.45[/C][C]3324.81747810293[/C][C]173.219162413306[/C][/ROW]
[ROW][C]0.46[/C][C]3354.04242361871[/C][C]178.463573065505[/C][/ROW]
[ROW][C]0.47[/C][C]3383.97344925157[/C][C]182.234163970572[/C][/ROW]
[ROW][C]0.48[/C][C]3414.36655230351[/C][C]184.390986728742[/C][/ROW]
[ROW][C]0.49[/C][C]3444.96184618521[/C][C]184.872018982771[/C][/ROW]
[ROW][C]0.5[/C][C]3475.49432613106[/C][C]183.667524113022[/C][/ROW]
[ROW][C]0.51[/C][C]3505.70474682712[/C][C]180.839980955226[/C][/ROW]
[ROW][C]0.52[/C][C]3535.35004918727[/C][C]176.529800971260[/C][/ROW]
[ROW][C]0.53[/C][C]3564.21274760698[/C][C]170.917227241434[/C][/ROW]
[ROW][C]0.54[/C][C]3592.10876332790[/C][C]164.236674175668[/C][/ROW]
[ROW][C]0.55[/C][C]3618.89336046537[/C][C]156.750672883184[/C][/ROW]
[ROW][C]0.56[/C][C]3644.46507704122[/C][C]148.738356445532[/C][/ROW]
[ROW][C]0.57[/C][C]3668.76779043144[/C][C]140.481975045724[/C][/ROW]
[ROW][C]0.58[/C][C]3691.79125265578[/C][C]132.245133658513[/C][/ROW]
[ROW][C]0.59[/C][C]3713.57052126874[/C][C]124.291272331524[/C][/ROW]
[ROW][C]0.6[/C][C]3734.18466473867[/C][C]116.859181287304[/C][/ROW]
[ROW][C]0.61[/C][C]3753.75493927502[/C][C]110.188997473218[/C][/ROW]
[ROW][C]0.62[/C][C]3772.44235601151[/C][C]104.498043412084[/C][/ROW]
[ROW][C]0.63[/C][C]3790.44425382485[/C][C]100.002734098483[/C][/ROW]
[ROW][C]0.64[/C][C]3807.98925336183[/C][C]96.8990667455032[/C][/ROW]
[ROW][C]0.65[/C][C]3825.32988229082[/C][C]95.3418979641768[/C][/ROW]
[ROW][C]0.66[/C][C]3842.73230025277[/C][C]95.417421772537[/C][/ROW]
[ROW][C]0.67[/C][C]3860.46294327126[/C][C]97.1022570122234[/C][/ROW]
[ROW][C]0.68[/C][C]3878.77252281249[/C][C]100.254612678285[/C][/ROW]
[ROW][C]0.69[/C][C]3897.8785605138[/C][C]104.586613826228[/C][/ROW]
[ROW][C]0.7[/C][C]3917.94836298806[/C][C]109.712419240710[/C][/ROW]
[ROW][C]0.71[/C][C]3939.08485322441[/C][C]115.146172415890[/C][/ROW]
[ROW][C]0.72[/C][C]3961.31779126917[/C][C]120.392357156070[/C][/ROW]
[ROW][C]0.73[/C][C]3984.60250806231[/C][C]124.974279068636[/C][/ROW]
[ROW][C]0.74[/C][C]4008.82731950776[/C][C]128.494424391314[/C][/ROW]
[ROW][C]0.75[/C][C]4033.82939818905[/C][C]130.694452536767[/C][/ROW]
[ROW][C]0.76[/C][C]4059.41730833563[/C][C]131.477863425306[/C][/ROW]
[ROW][C]0.77[/C][C]4085.39699672742[/C][C]130.915165843576[/C][/ROW]
[ROW][C]0.78[/C][C]4111.59712797338[/C][C]129.228185113934[/C][/ROW]
[ROW][C]0.79[/C][C]4137.88952040233[/C][C]126.765588492119[/C][/ROW]
[ROW][C]0.8[/C][C]4164.20117862131[/C][C]123.904163521806[/C][/ROW]
[ROW][C]0.81[/C][C]4190.51593485803[/C][C]120.999957884816[/C][/ROW]
[ROW][C]0.82[/C][C]4216.86573090257[/C][C]118.313320925835[/C][/ROW]
[ROW][C]0.83[/C][C]4243.31369756464[/C][C]115.972884250084[/C][/ROW]
[ROW][C]0.84[/C][C]4269.93294816636[/C][C]113.954208943959[/C][/ROW]
[ROW][C]0.85[/C][C]4296.78589679535[/C][C]112.102679401073[/C][/ROW]
[ROW][C]0.86[/C][C]4323.90848397969[/C][C]110.187583508784[/C][/ROW]
[ROW][C]0.87[/C][C]4351.30170838631[/C][C]107.968620751337[/C][/ROW]
[ROW][C]0.88[/C][C]4378.92965242707[/C][C]105.256113878323[/C][/ROW]
[ROW][C]0.89[/C][C]4406.72005086259[/C][C]101.943960129803[/C][/ROW]
[ROW][C]0.9[/C][C]4434.56280286735[/C][C]97.982076694313[/C][/ROW]
[ROW][C]0.91[/C][C]4462.30660590397[/C][C]93.305250333706[/C][/ROW]
[ROW][C]0.92[/C][C]4489.76569278891[/C][C]87.7586945910622[/C][/ROW]
[ROW][C]0.93[/C][C]4516.76414869354[/C][C]81.1287123721522[/C][/ROW]
[ROW][C]0.94[/C][C]4543.25028769004[/C][C]73.3788820334074[/C][/ROW]
[ROW][C]0.95[/C][C]4569.47593399633[/C][C]65.0524537653744[/C][/ROW]
[ROW][C]0.96[/C][C]4596.10930421093[/C][C]57.7592617245356[/C][/ROW]
[ROW][C]0.97[/C][C]4623.93361490648[/C][C]54.3654965653944[/C][/ROW]
[ROW][C]0.98[/C][C]4652.68615730307[/C][C]57.5551957183953[/C][/ROW]
[ROW][C]0.99[/C][C]4679.2100355289[/C][C]66.1654088271386[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=47357&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=47357&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
0.011701.55105091892119.743344104442
0.021746.3641676044795.0023213573964
0.031791.1571323803474.9841764241402
0.041829.7413867612165.5460154001404
0.051862.194169038966.6333199571465
0.061891.1019945198574.2433074719642
0.071919.0082457913284.4958915713106
0.081947.5940035233295.6500296850836
0.091977.82423597998107.970734729901
0.12010.34616254053122.852073154950
0.112045.78232141046141.703892693694
0.122084.82223278145165.049257087626
0.132128.14785027080192.201845578587
0.142176.27454877657221.459894771439
0.152229.38881468367250.512362610087
0.162287.24018318957276.857565701153
0.172349.11457636022298.18641224847
0.182413.88930612357312.699363383203
0.192480.15147027741319.302470699257
0.22546.35211018733317.728345051721
0.212610.96694019794308.46815560179
0.222672.63854288914292.668029534937
0.232730.28243502937271.916157378692
0.242783.14831600818248.001371060852
0.252830.83635631909222.714859633545
0.262873.27519715683197.647252749934
0.272910.67257262183174.111605619466
0.282943.45091301774153.072275030957
0.292972.17930363248135.155272534327
0.32997.51053073607120.704419026788
0.313020.1285771803109.827888262849
0.323040.70867949217102.471307299366
0.333059.8895149221398.4408919086328
0.343078.2555164326397.4426660344317
0.353096.3266920040799.1213813647518
0.363114.5534322444103.059409643182
0.373133.31432562308108.828770359599
0.383152.91567819061116.003157434971
0.393173.59204687345124.170904084985
0.43195.5075347915132.930752183826
0.413218.7578451218141.906161374566
0.423243.37318715785150.739026068393
0.433269.32213751843159.102201311312
0.443296.51653676708166.687179885344
0.453324.81747810293173.219162413306
0.463354.04242361871178.463573065505
0.473383.97344925157182.234163970572
0.483414.36655230351184.390986728742
0.493444.96184618521184.872018982771
0.53475.49432613106183.667524113022
0.513505.70474682712180.839980955226
0.523535.35004918727176.529800971260
0.533564.21274760698170.917227241434
0.543592.10876332790164.236674175668
0.553618.89336046537156.750672883184
0.563644.46507704122148.738356445532
0.573668.76779043144140.481975045724
0.583691.79125265578132.245133658513
0.593713.57052126874124.291272331524
0.63734.18466473867116.859181287304
0.613753.75493927502110.188997473218
0.623772.44235601151104.498043412084
0.633790.44425382485100.002734098483
0.643807.9892533618396.8990667455032
0.653825.3298822908295.3418979641768
0.663842.7323002527795.417421772537
0.673860.4629432712697.1022570122234
0.683878.77252281249100.254612678285
0.693897.8785605138104.586613826228
0.73917.94836298806109.712419240710
0.713939.08485322441115.146172415890
0.723961.31779126917120.392357156070
0.733984.60250806231124.974279068636
0.744008.82731950776128.494424391314
0.754033.82939818905130.694452536767
0.764059.41730833563131.477863425306
0.774085.39699672742130.915165843576
0.784111.59712797338129.228185113934
0.794137.88952040233126.765588492119
0.84164.20117862131123.904163521806
0.814190.51593485803120.999957884816
0.824216.86573090257118.313320925835
0.834243.31369756464115.972884250084
0.844269.93294816636113.954208943959
0.854296.78589679535112.102679401073
0.864323.90848397969110.187583508784
0.874351.30170838631107.968620751337
0.884378.92965242707105.256113878323
0.894406.72005086259101.943960129803
0.94434.5628028673597.982076694313
0.914462.3066059039793.305250333706
0.924489.7656927889187.7586945910622
0.934516.7641486935481.1287123721522
0.944543.2502876900473.3788820334074
0.954569.4759339963365.0524537653744
0.964596.1093042109357.7592617245356
0.974623.9336149064854.3654965653944
0.984652.6861573030757.5551957183953
0.994679.210035528966.1654088271386


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')