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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 computationMon, 29 Feb 2016 21:54:06 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Feb/29/t14567829438xno2twkmlj55or.htm/, Retrieved Tue, 30 Apr 2024 20:18:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=293067, Retrieved Tue, 30 Apr 2024 20:18:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact51

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
283411
234585
207695
204000
220791
222335
303510
201602
218279
207253
217639
231043
302988
221415
213989
190507
199397
201077
261048
241508
194637
240044
253534
269220
270820
354121
315233
297098
258289
276246
246652
242945
210838
246343
234636
229011
238756
283696
226656
229790
219831
232331
315447
251031
297019
208424
311626
352320
375214
419501
664867
483142
312717
228228
230978
218033
225566
207708
241861
208381
209071
214514
195868
190208
187651
215934
213012
236845
154595
193485
231875
192259
191609
212911
238596
203033
258272
314681
289789
297541
239578
207798
254091
242544
218067
217463
229438
216485
238410
223108
221267
224802
233630
235134
309660
253229
293530
273323
297578
341589
389911
398685
629637
522502
358941
252783
236585
224995
225721
223338
228952
212759
200270
211925
191206
200511
205944
289288
186209
197515
182038
181606
223337
201213
220700
194043
224593
249907
238613
266200
274197
288601
242662
232105
267842
219037
198404
203910
209685
214274
215376
217711
224819
217142
221445
213483
282063
236194
297296
255885
264502
311580
416595
356762
537286
532855

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'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293067&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293067&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293067&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'Gertrude Mary Cox' @ cox.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01171484.86476879111901.7139506434
0.02182807.9501847584405.24503170533
0.03187151.2773895913128.36279982029
0.04189514.4244207252429.14627331386
0.05191157.9101207212134.13740257693
0.06192514.0786324112258.96118810868
0.07193828.4138173952561.10693869526
0.08195186.2225009272828.61650668167
0.09196569.244636542954.55926982451
0.1197922.8911671912935.4832186979
0.11199205.4724327782850.26871923008
0.12200410.2942122762798.11147005504
0.13201559.691532772827.8957107164
0.14202682.4353252462910.83016619517
0.15203793.2315958592980.61027207524
0.16204887.0702717762986.96432787194
0.17205948.0579292612927.39189037523
0.18206963.0130126442838.17052165668
0.19207929.7455576332763.51386449374
0.2208856.2059193282726.63807577989
0.21209753.5910384242717.87739596061
0.22210629.4047536242712.30270146357
0.23211484.6848184912687.04381265794
0.24212315.7127272642635.95040342547
0.25213117.7056884832566.0901833314
0.26213887.7264458592489.79502734169
0.27214625.6243432392415.75594397197
0.28215333.5326486482349.25069999209
0.29216015.0902697632293.00266797187
0.3216675.0919292532251.89461689773
0.31217319.4566316192231.24098951513
0.32217954.9926799192236.01102728441
0.33218588.6414233012264.58093130942
0.34219226.3870980892310.82351919863
0.35219872.3646514392366.48548395187
0.36220528.6423937162422.34676917044
0.37221195.7935581962475.30774741994
0.38221873.9720903352528.07261180551
0.39222563.9993462012585.22214287244
0.4223268.009723882653.27450918954
0.41223989.4172160652737.59144314802
0.42224732.2341182352838.08012132738
0.43225500.0057138992950.00502346336
0.44226294.7594033543065.65427298286
0.45227116.3603352643173.74367489835
0.46227962.5065789323266.15761620668
0.47228829.3359079563339.55677076084
0.48229712.3683248413392.99512672523
0.49230607.4004377463430.83587203902
0.5231511.0602561613457.36076639714
0.51232420.9735673113476.23927051195
0.52233335.7503429173490.0314358702
0.53234255.1295891423503.38648912559
0.54235180.5523456013521.41804102524
0.55236116.1944727673557.90453564577
0.56237070.188890423629.74925823926
0.57238055.530576453758.59190396901
0.58239090.0940203483963.3680852025
0.59240195.3598046994254.55526610427
0.6241393.8374613274629.93919135751
0.61242705.6962426175070.08827571355
0.62244145.5907354355545.83063255674
0.63245720.8476567666023.59458645507
0.64247431.8598103956477.21943905631
0.65249274.7118388386895.91683470837
0.66251245.0482225317287.46348455901
0.67253341.5223706467671.14987367033
0.68255567.2953709288067.56005972478
0.69257929.0062569138484.45381380701
0.7260433.8775286398914.82084461901
0.71263086.3607241439340.20659021509
0.72265885.5003783819735.55741029926
0.73268823.26429612210078.7356117058
0.74271883.29544273910342.8282781383
0.75275039.64459017610496.6621541784
0.76278256.06922303310506.9909530749
0.77281487.63824536410349.1299686958
0.78284686.58101189210022.8039012084
0.79287812.9070125379569.1413394242
0.8290847.5734100779072.98266880658
0.81293803.3879566288648.29743216487
0.82296729.031599698407.65607665981
0.83299706.8137098138428.58803860756
0.84302853.2154597228768.1513338154
0.85306333.9731637259531.79745969607
0.86310391.04744821410932.7674555708
0.87315350.11093363313176.3705354418
0.88321565.70781501816171.8324161793
0.89329307.74074409119399.7434413192
0.9338684.2462675522223.7445844302
0.91349731.57675604124496.0862103697
0.92362704.536246726909.0115668599
0.93378458.89472505630730.9414303849
0.94398726.21056578737316.6534786594
0.95425754.37032970546732.6524982335
0.96460564.27604844954324.111422478
0.97501870.8232217353324.4030997465
0.98551660.34476668252752.4255635262
0.99615714.62981073656969.5693086962

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 171484.864768791 & 11901.7139506434 \tabularnewline
0.02 & 182807.950184758 & 4405.24503170533 \tabularnewline
0.03 & 187151.277389591 & 3128.36279982029 \tabularnewline
0.04 & 189514.424420725 & 2429.14627331386 \tabularnewline
0.05 & 191157.910120721 & 2134.13740257693 \tabularnewline
0.06 & 192514.078632411 & 2258.96118810868 \tabularnewline
0.07 & 193828.413817395 & 2561.10693869526 \tabularnewline
0.08 & 195186.222500927 & 2828.61650668167 \tabularnewline
0.09 & 196569.24463654 & 2954.55926982451 \tabularnewline
0.1 & 197922.891167191 & 2935.4832186979 \tabularnewline
0.11 & 199205.472432778 & 2850.26871923008 \tabularnewline
0.12 & 200410.294212276 & 2798.11147005504 \tabularnewline
0.13 & 201559.69153277 & 2827.8957107164 \tabularnewline
0.14 & 202682.435325246 & 2910.83016619517 \tabularnewline
0.15 & 203793.231595859 & 2980.61027207524 \tabularnewline
0.16 & 204887.070271776 & 2986.96432787194 \tabularnewline
0.17 & 205948.057929261 & 2927.39189037523 \tabularnewline
0.18 & 206963.013012644 & 2838.17052165668 \tabularnewline
0.19 & 207929.745557633 & 2763.51386449374 \tabularnewline
0.2 & 208856.205919328 & 2726.63807577989 \tabularnewline
0.21 & 209753.591038424 & 2717.87739596061 \tabularnewline
0.22 & 210629.404753624 & 2712.30270146357 \tabularnewline
0.23 & 211484.684818491 & 2687.04381265794 \tabularnewline
0.24 & 212315.712727264 & 2635.95040342547 \tabularnewline
0.25 & 213117.705688483 & 2566.0901833314 \tabularnewline
0.26 & 213887.726445859 & 2489.79502734169 \tabularnewline
0.27 & 214625.624343239 & 2415.75594397197 \tabularnewline
0.28 & 215333.532648648 & 2349.25069999209 \tabularnewline
0.29 & 216015.090269763 & 2293.00266797187 \tabularnewline
0.3 & 216675.091929253 & 2251.89461689773 \tabularnewline
0.31 & 217319.456631619 & 2231.24098951513 \tabularnewline
0.32 & 217954.992679919 & 2236.01102728441 \tabularnewline
0.33 & 218588.641423301 & 2264.58093130942 \tabularnewline
0.34 & 219226.387098089 & 2310.82351919863 \tabularnewline
0.35 & 219872.364651439 & 2366.48548395187 \tabularnewline
0.36 & 220528.642393716 & 2422.34676917044 \tabularnewline
0.37 & 221195.793558196 & 2475.30774741994 \tabularnewline
0.38 & 221873.972090335 & 2528.07261180551 \tabularnewline
0.39 & 222563.999346201 & 2585.22214287244 \tabularnewline
0.4 & 223268.00972388 & 2653.27450918954 \tabularnewline
0.41 & 223989.417216065 & 2737.59144314802 \tabularnewline
0.42 & 224732.234118235 & 2838.08012132738 \tabularnewline
0.43 & 225500.005713899 & 2950.00502346336 \tabularnewline
0.44 & 226294.759403354 & 3065.65427298286 \tabularnewline
0.45 & 227116.360335264 & 3173.74367489835 \tabularnewline
0.46 & 227962.506578932 & 3266.15761620668 \tabularnewline
0.47 & 228829.335907956 & 3339.55677076084 \tabularnewline
0.48 & 229712.368324841 & 3392.99512672523 \tabularnewline
0.49 & 230607.400437746 & 3430.83587203902 \tabularnewline
0.5 & 231511.060256161 & 3457.36076639714 \tabularnewline
0.51 & 232420.973567311 & 3476.23927051195 \tabularnewline
0.52 & 233335.750342917 & 3490.0314358702 \tabularnewline
0.53 & 234255.129589142 & 3503.38648912559 \tabularnewline
0.54 & 235180.552345601 & 3521.41804102524 \tabularnewline
0.55 & 236116.194472767 & 3557.90453564577 \tabularnewline
0.56 & 237070.18889042 & 3629.74925823926 \tabularnewline
0.57 & 238055.53057645 & 3758.59190396901 \tabularnewline
0.58 & 239090.094020348 & 3963.3680852025 \tabularnewline
0.59 & 240195.359804699 & 4254.55526610427 \tabularnewline
0.6 & 241393.837461327 & 4629.93919135751 \tabularnewline
0.61 & 242705.696242617 & 5070.08827571355 \tabularnewline
0.62 & 244145.590735435 & 5545.83063255674 \tabularnewline
0.63 & 245720.847656766 & 6023.59458645507 \tabularnewline
0.64 & 247431.859810395 & 6477.21943905631 \tabularnewline
0.65 & 249274.711838838 & 6895.91683470837 \tabularnewline
0.66 & 251245.048222531 & 7287.46348455901 \tabularnewline
0.67 & 253341.522370646 & 7671.14987367033 \tabularnewline
0.68 & 255567.295370928 & 8067.56005972478 \tabularnewline
0.69 & 257929.006256913 & 8484.45381380701 \tabularnewline
0.7 & 260433.877528639 & 8914.82084461901 \tabularnewline
0.71 & 263086.360724143 & 9340.20659021509 \tabularnewline
0.72 & 265885.500378381 & 9735.55741029926 \tabularnewline
0.73 & 268823.264296122 & 10078.7356117058 \tabularnewline
0.74 & 271883.295442739 & 10342.8282781383 \tabularnewline
0.75 & 275039.644590176 & 10496.6621541784 \tabularnewline
0.76 & 278256.069223033 & 10506.9909530749 \tabularnewline
0.77 & 281487.638245364 & 10349.1299686958 \tabularnewline
0.78 & 284686.581011892 & 10022.8039012084 \tabularnewline
0.79 & 287812.907012537 & 9569.1413394242 \tabularnewline
0.8 & 290847.573410077 & 9072.98266880658 \tabularnewline
0.81 & 293803.387956628 & 8648.29743216487 \tabularnewline
0.82 & 296729.03159969 & 8407.65607665981 \tabularnewline
0.83 & 299706.813709813 & 8428.58803860756 \tabularnewline
0.84 & 302853.215459722 & 8768.1513338154 \tabularnewline
0.85 & 306333.973163725 & 9531.79745969607 \tabularnewline
0.86 & 310391.047448214 & 10932.7674555708 \tabularnewline
0.87 & 315350.110933633 & 13176.3705354418 \tabularnewline
0.88 & 321565.707815018 & 16171.8324161793 \tabularnewline
0.89 & 329307.740744091 & 19399.7434413192 \tabularnewline
0.9 & 338684.24626755 & 22223.7445844302 \tabularnewline
0.91 & 349731.576756041 & 24496.0862103697 \tabularnewline
0.92 & 362704.5362467 & 26909.0115668599 \tabularnewline
0.93 & 378458.894725056 & 30730.9414303849 \tabularnewline
0.94 & 398726.210565787 & 37316.6534786594 \tabularnewline
0.95 & 425754.370329705 & 46732.6524982335 \tabularnewline
0.96 & 460564.276048449 & 54324.111422478 \tabularnewline
0.97 & 501870.82322173 & 53324.4030997465 \tabularnewline
0.98 & 551660.344766682 & 52752.4255635262 \tabularnewline
0.99 & 615714.629810736 & 56969.5693086962 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293067&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]171484.864768791[/C][C]11901.7139506434[/C][/ROW]
[ROW][C]0.02[/C][C]182807.950184758[/C][C]4405.24503170533[/C][/ROW]
[ROW][C]0.03[/C][C]187151.277389591[/C][C]3128.36279982029[/C][/ROW]
[ROW][C]0.04[/C][C]189514.424420725[/C][C]2429.14627331386[/C][/ROW]
[ROW][C]0.05[/C][C]191157.910120721[/C][C]2134.13740257693[/C][/ROW]
[ROW][C]0.06[/C][C]192514.078632411[/C][C]2258.96118810868[/C][/ROW]
[ROW][C]0.07[/C][C]193828.413817395[/C][C]2561.10693869526[/C][/ROW]
[ROW][C]0.08[/C][C]195186.222500927[/C][C]2828.61650668167[/C][/ROW]
[ROW][C]0.09[/C][C]196569.24463654[/C][C]2954.55926982451[/C][/ROW]
[ROW][C]0.1[/C][C]197922.891167191[/C][C]2935.4832186979[/C][/ROW]
[ROW][C]0.11[/C][C]199205.472432778[/C][C]2850.26871923008[/C][/ROW]
[ROW][C]0.12[/C][C]200410.294212276[/C][C]2798.11147005504[/C][/ROW]
[ROW][C]0.13[/C][C]201559.69153277[/C][C]2827.8957107164[/C][/ROW]
[ROW][C]0.14[/C][C]202682.435325246[/C][C]2910.83016619517[/C][/ROW]
[ROW][C]0.15[/C][C]203793.231595859[/C][C]2980.61027207524[/C][/ROW]
[ROW][C]0.16[/C][C]204887.070271776[/C][C]2986.96432787194[/C][/ROW]
[ROW][C]0.17[/C][C]205948.057929261[/C][C]2927.39189037523[/C][/ROW]
[ROW][C]0.18[/C][C]206963.013012644[/C][C]2838.17052165668[/C][/ROW]
[ROW][C]0.19[/C][C]207929.745557633[/C][C]2763.51386449374[/C][/ROW]
[ROW][C]0.2[/C][C]208856.205919328[/C][C]2726.63807577989[/C][/ROW]
[ROW][C]0.21[/C][C]209753.591038424[/C][C]2717.87739596061[/C][/ROW]
[ROW][C]0.22[/C][C]210629.404753624[/C][C]2712.30270146357[/C][/ROW]
[ROW][C]0.23[/C][C]211484.684818491[/C][C]2687.04381265794[/C][/ROW]
[ROW][C]0.24[/C][C]212315.712727264[/C][C]2635.95040342547[/C][/ROW]
[ROW][C]0.25[/C][C]213117.705688483[/C][C]2566.0901833314[/C][/ROW]
[ROW][C]0.26[/C][C]213887.726445859[/C][C]2489.79502734169[/C][/ROW]
[ROW][C]0.27[/C][C]214625.624343239[/C][C]2415.75594397197[/C][/ROW]
[ROW][C]0.28[/C][C]215333.532648648[/C][C]2349.25069999209[/C][/ROW]
[ROW][C]0.29[/C][C]216015.090269763[/C][C]2293.00266797187[/C][/ROW]
[ROW][C]0.3[/C][C]216675.091929253[/C][C]2251.89461689773[/C][/ROW]
[ROW][C]0.31[/C][C]217319.456631619[/C][C]2231.24098951513[/C][/ROW]
[ROW][C]0.32[/C][C]217954.992679919[/C][C]2236.01102728441[/C][/ROW]
[ROW][C]0.33[/C][C]218588.641423301[/C][C]2264.58093130942[/C][/ROW]
[ROW][C]0.34[/C][C]219226.387098089[/C][C]2310.82351919863[/C][/ROW]
[ROW][C]0.35[/C][C]219872.364651439[/C][C]2366.48548395187[/C][/ROW]
[ROW][C]0.36[/C][C]220528.642393716[/C][C]2422.34676917044[/C][/ROW]
[ROW][C]0.37[/C][C]221195.793558196[/C][C]2475.30774741994[/C][/ROW]
[ROW][C]0.38[/C][C]221873.972090335[/C][C]2528.07261180551[/C][/ROW]
[ROW][C]0.39[/C][C]222563.999346201[/C][C]2585.22214287244[/C][/ROW]
[ROW][C]0.4[/C][C]223268.00972388[/C][C]2653.27450918954[/C][/ROW]
[ROW][C]0.41[/C][C]223989.417216065[/C][C]2737.59144314802[/C][/ROW]
[ROW][C]0.42[/C][C]224732.234118235[/C][C]2838.08012132738[/C][/ROW]
[ROW][C]0.43[/C][C]225500.005713899[/C][C]2950.00502346336[/C][/ROW]
[ROW][C]0.44[/C][C]226294.759403354[/C][C]3065.65427298286[/C][/ROW]
[ROW][C]0.45[/C][C]227116.360335264[/C][C]3173.74367489835[/C][/ROW]
[ROW][C]0.46[/C][C]227962.506578932[/C][C]3266.15761620668[/C][/ROW]
[ROW][C]0.47[/C][C]228829.335907956[/C][C]3339.55677076084[/C][/ROW]
[ROW][C]0.48[/C][C]229712.368324841[/C][C]3392.99512672523[/C][/ROW]
[ROW][C]0.49[/C][C]230607.400437746[/C][C]3430.83587203902[/C][/ROW]
[ROW][C]0.5[/C][C]231511.060256161[/C][C]3457.36076639714[/C][/ROW]
[ROW][C]0.51[/C][C]232420.973567311[/C][C]3476.23927051195[/C][/ROW]
[ROW][C]0.52[/C][C]233335.750342917[/C][C]3490.0314358702[/C][/ROW]
[ROW][C]0.53[/C][C]234255.129589142[/C][C]3503.38648912559[/C][/ROW]
[ROW][C]0.54[/C][C]235180.552345601[/C][C]3521.41804102524[/C][/ROW]
[ROW][C]0.55[/C][C]236116.194472767[/C][C]3557.90453564577[/C][/ROW]
[ROW][C]0.56[/C][C]237070.18889042[/C][C]3629.74925823926[/C][/ROW]
[ROW][C]0.57[/C][C]238055.53057645[/C][C]3758.59190396901[/C][/ROW]
[ROW][C]0.58[/C][C]239090.094020348[/C][C]3963.3680852025[/C][/ROW]
[ROW][C]0.59[/C][C]240195.359804699[/C][C]4254.55526610427[/C][/ROW]
[ROW][C]0.6[/C][C]241393.837461327[/C][C]4629.93919135751[/C][/ROW]
[ROW][C]0.61[/C][C]242705.696242617[/C][C]5070.08827571355[/C][/ROW]
[ROW][C]0.62[/C][C]244145.590735435[/C][C]5545.83063255674[/C][/ROW]
[ROW][C]0.63[/C][C]245720.847656766[/C][C]6023.59458645507[/C][/ROW]
[ROW][C]0.64[/C][C]247431.859810395[/C][C]6477.21943905631[/C][/ROW]
[ROW][C]0.65[/C][C]249274.711838838[/C][C]6895.91683470837[/C][/ROW]
[ROW][C]0.66[/C][C]251245.048222531[/C][C]7287.46348455901[/C][/ROW]
[ROW][C]0.67[/C][C]253341.522370646[/C][C]7671.14987367033[/C][/ROW]
[ROW][C]0.68[/C][C]255567.295370928[/C][C]8067.56005972478[/C][/ROW]
[ROW][C]0.69[/C][C]257929.006256913[/C][C]8484.45381380701[/C][/ROW]
[ROW][C]0.7[/C][C]260433.877528639[/C][C]8914.82084461901[/C][/ROW]
[ROW][C]0.71[/C][C]263086.360724143[/C][C]9340.20659021509[/C][/ROW]
[ROW][C]0.72[/C][C]265885.500378381[/C][C]9735.55741029926[/C][/ROW]
[ROW][C]0.73[/C][C]268823.264296122[/C][C]10078.7356117058[/C][/ROW]
[ROW][C]0.74[/C][C]271883.295442739[/C][C]10342.8282781383[/C][/ROW]
[ROW][C]0.75[/C][C]275039.644590176[/C][C]10496.6621541784[/C][/ROW]
[ROW][C]0.76[/C][C]278256.069223033[/C][C]10506.9909530749[/C][/ROW]
[ROW][C]0.77[/C][C]281487.638245364[/C][C]10349.1299686958[/C][/ROW]
[ROW][C]0.78[/C][C]284686.581011892[/C][C]10022.8039012084[/C][/ROW]
[ROW][C]0.79[/C][C]287812.907012537[/C][C]9569.1413394242[/C][/ROW]
[ROW][C]0.8[/C][C]290847.573410077[/C][C]9072.98266880658[/C][/ROW]
[ROW][C]0.81[/C][C]293803.387956628[/C][C]8648.29743216487[/C][/ROW]
[ROW][C]0.82[/C][C]296729.03159969[/C][C]8407.65607665981[/C][/ROW]
[ROW][C]0.83[/C][C]299706.813709813[/C][C]8428.58803860756[/C][/ROW]
[ROW][C]0.84[/C][C]302853.215459722[/C][C]8768.1513338154[/C][/ROW]
[ROW][C]0.85[/C][C]306333.973163725[/C][C]9531.79745969607[/C][/ROW]
[ROW][C]0.86[/C][C]310391.047448214[/C][C]10932.7674555708[/C][/ROW]
[ROW][C]0.87[/C][C]315350.110933633[/C][C]13176.3705354418[/C][/ROW]
[ROW][C]0.88[/C][C]321565.707815018[/C][C]16171.8324161793[/C][/ROW]
[ROW][C]0.89[/C][C]329307.740744091[/C][C]19399.7434413192[/C][/ROW]
[ROW][C]0.9[/C][C]338684.24626755[/C][C]22223.7445844302[/C][/ROW]
[ROW][C]0.91[/C][C]349731.576756041[/C][C]24496.0862103697[/C][/ROW]
[ROW][C]0.92[/C][C]362704.5362467[/C][C]26909.0115668599[/C][/ROW]
[ROW][C]0.93[/C][C]378458.894725056[/C][C]30730.9414303849[/C][/ROW]
[ROW][C]0.94[/C][C]398726.210565787[/C][C]37316.6534786594[/C][/ROW]
[ROW][C]0.95[/C][C]425754.370329705[/C][C]46732.6524982335[/C][/ROW]
[ROW][C]0.96[/C][C]460564.276048449[/C][C]54324.111422478[/C][/ROW]
[ROW][C]0.97[/C][C]501870.82322173[/C][C]53324.4030997465[/C][/ROW]
[ROW][C]0.98[/C][C]551660.344766682[/C][C]52752.4255635262[/C][/ROW]
[ROW][C]0.99[/C][C]615714.629810736[/C][C]56969.5693086962[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293067&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293067&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
0.01171484.86476879111901.7139506434
0.02182807.9501847584405.24503170533
0.03187151.2773895913128.36279982029
0.04189514.4244207252429.14627331386
0.05191157.9101207212134.13740257693
0.06192514.0786324112258.96118810868
0.07193828.4138173952561.10693869526
0.08195186.2225009272828.61650668167
0.09196569.244636542954.55926982451
0.1197922.8911671912935.4832186979
0.11199205.4724327782850.26871923008
0.12200410.2942122762798.11147005504
0.13201559.691532772827.8957107164
0.14202682.4353252462910.83016619517
0.15203793.2315958592980.61027207524
0.16204887.0702717762986.96432787194
0.17205948.0579292612927.39189037523
0.18206963.0130126442838.17052165668
0.19207929.7455576332763.51386449374
0.2208856.2059193282726.63807577989
0.21209753.5910384242717.87739596061
0.22210629.4047536242712.30270146357
0.23211484.6848184912687.04381265794
0.24212315.7127272642635.95040342547
0.25213117.7056884832566.0901833314
0.26213887.7264458592489.79502734169
0.27214625.6243432392415.75594397197
0.28215333.5326486482349.25069999209
0.29216015.0902697632293.00266797187
0.3216675.0919292532251.89461689773
0.31217319.4566316192231.24098951513
0.32217954.9926799192236.01102728441
0.33218588.6414233012264.58093130942
0.34219226.3870980892310.82351919863
0.35219872.3646514392366.48548395187
0.36220528.6423937162422.34676917044
0.37221195.7935581962475.30774741994
0.38221873.9720903352528.07261180551
0.39222563.9993462012585.22214287244
0.4223268.009723882653.27450918954
0.41223989.4172160652737.59144314802
0.42224732.2341182352838.08012132738
0.43225500.0057138992950.00502346336
0.44226294.7594033543065.65427298286
0.45227116.3603352643173.74367489835
0.46227962.5065789323266.15761620668
0.47228829.3359079563339.55677076084
0.48229712.3683248413392.99512672523
0.49230607.4004377463430.83587203902
0.5231511.0602561613457.36076639714
0.51232420.9735673113476.23927051195
0.52233335.7503429173490.0314358702
0.53234255.1295891423503.38648912559
0.54235180.5523456013521.41804102524
0.55236116.1944727673557.90453564577
0.56237070.188890423629.74925823926
0.57238055.530576453758.59190396901
0.58239090.0940203483963.3680852025
0.59240195.3598046994254.55526610427
0.6241393.8374613274629.93919135751
0.61242705.6962426175070.08827571355
0.62244145.5907354355545.83063255674
0.63245720.8476567666023.59458645507
0.64247431.8598103956477.21943905631
0.65249274.7118388386895.91683470837
0.66251245.0482225317287.46348455901
0.67253341.5223706467671.14987367033
0.68255567.2953709288067.56005972478
0.69257929.0062569138484.45381380701
0.7260433.8775286398914.82084461901
0.71263086.3607241439340.20659021509
0.72265885.5003783819735.55741029926
0.73268823.26429612210078.7356117058
0.74271883.29544273910342.8282781383
0.75275039.64459017610496.6621541784
0.76278256.06922303310506.9909530749
0.77281487.63824536410349.1299686958
0.78284686.58101189210022.8039012084
0.79287812.9070125379569.1413394242
0.8290847.5734100779072.98266880658
0.81293803.3879566288648.29743216487
0.82296729.031599698407.65607665981
0.83299706.8137098138428.58803860756
0.84302853.2154597228768.1513338154
0.85306333.9731637259531.79745969607
0.86310391.04744821410932.7674555708
0.87315350.11093363313176.3705354418
0.88321565.70781501816171.8324161793
0.89329307.74074409119399.7434413192
0.9338684.2462675522223.7445844302
0.91349731.57675604124496.0862103697
0.92362704.536246726909.0115668599
0.93378458.89472505630730.9414303849
0.94398726.21056578737316.6534786594
0.95425754.37032970546732.6524982335
0.96460564.27604844954324.111422478
0.97501870.8232217353324.4030997465
0.98551660.34476668252752.4255635262
0.99615714.62981073656969.5693086962


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')