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Webapp for finding out how large your penis really is
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library(mvtnorm)
# Girth and Length are now set by values determined in either:
# Hungfun's charts (http://imgur.com/a/3r5sH)
# Herbenick et al (http://onlinelibrary.wiley.com/doi/10.1111/jsm.12244/abstract)
percentile = function (l_mean, l_sd, g_mean, g_sd, correlation) {
covariance = correlation * l_sd * g_sd # correlation coefficient * sd(length) * sd(girth)
sigma = matrix(c(l_sd^2, covariance, covariance, g_sd^2),nrow = 2, byrow=T)
grange = seq(2,8, by=.1)
lrange = seq(2,10, by=.1)
result = c()
for(l in lrange) {
for (g in grange) {
p = 1-pmvnorm(c(l,g), mean=c(l_mean, g_mean), sigma=sigma)[1]
result = cbind(result, c(l, g, p))
}
}
result = t(result)
colnames(result) = c("length", "girth", "percentile")
result
}
vol_sim = function(l_mean, l_sd, g_mean, g_sd, correlation, n=1000000) {
covariance = correlation * l_sd * g_sd # correlation coefficient * sd(length) * sd(girth)
sigma = matrix(c(l_sd^2, covariance, covariance, g_sd^2),nrow = 2, byrow=T)
# simulate volume
sim = rmvnorm(n, mean=c(l_mean, g_mean), sigma=sigma)
vol = sim[,1] * (sim[,2]/2/pi)^2*pi
vol_cdf = ecdf(vol)
vol_range = seq(0,35,by=0.01)
vol_quant = vol_cdf(vol_range)
vol_mat = cbind(vol_range, vol_quant)
colnames(vol_mat) = c("volume", "percentile")
vol_mat
}
hungfun = percentile (5.76, 0.83, 4.67, 0.54, .46)
write.csv(hungfun, "hungfun.csv", row.names = F)
herbenick = percentile(5.57, 1.04, 4.81, 0.88, .46)
write.csv(herbenick, "herbenick.csv", row.names = F)
hungfun_vol = vol_sim(5.76, 0.83, 4.67, 0.54, .46)
write.csv(hungfun_vol, "hungfun_vol.csv", row.names=FALSE)
herbenick_vol = vol_sim(5.57, 1.04, 4.81, 0.88, .46)
write.csv(herbenick_vol, "herbenick_vol.csv", row.names=FALSE)
length girth percentile
2 2 0.000988247214201543
2 2.1 0.00131710929337192
2 2.2 0.00178442675681245
2 2.3 0.00243982933835662
2 2.4 0.00334705031454485
2 2.5 0.00458652252706937
2 2.6 0.00625795331753487
2 2.7 0.0084826775486333
2 2.8 0.0114055351951707
2 2.9 0.0151959750221835
2 3 0.0200480565653749
2 3.1 0.0261790175209994
2 3.2 0.0338261008096689
2 3.3 0.043241401307439
2 3.4 0.0546845996580672
2 3.5 0.0684135983030968
2 3.6 0.0846732560185607
2 3.7 0.103682619102868
2 3.8 0.125621251786494
2 3.9 0.150615453259676
2 4 0.178725289996118
2 4.1 0.209933447034524
2 4.2 0.244136892299969
2 4.3 0.281142243283821
2 4.4 0.320665524961185
2 4.5 0.36233672265674
2 4.6 0.405709185855598
2 4.7 0.450273560251153
2 4.8 0.495475553177655
2 4.9 0.540736511049253
2 5 0.585475542108519
2 5.1 0.62913178107816
2 5.2 0.671185379699432
2 5.3 0.711175920070354
2 5.4 0.748717173356786
2 5.5 0.783507439548463
2 5.6 0.815335070146496
2 5.7 0.84407915622001
2 5.8 0.869705720911306
2 5.9 0.892260055131242
2 6 0.911856053618308
2 6.1 0.92866353248882
2 6.2 0.942894537172927
2 6.3 0.954789590006248
2 6.4 0.964604696739906
2 6.5 0.972599752998081
2 6.6 0.979028789235687
2 6.7 0.984132288774556
2 6.8 0.988131627103806
2 6.9 0.991225525675153
2 7 0.993588297917538
2 7.1 0.995369591527985
2 7.2 0.996695296914966
2 7.3 0.997669291162501
2 7.4 0.998375712195136
2 7.5 0.998881500411546
2 7.6 0.999238996790811
2 7.7 0.999488440433657
2 7.8 0.999660259392344
2 7.9 0.999777092942101
2 8 0.999855519274495
2.1 2 0.00110949554170847
2.1 2.1 0.00143704322290172
2.1 2.2 0.00190272400495461
2.1 2.3 0.00255612165642971
2.1 2.4 0.0034609264367238
2.1 2.5 0.00469753405652418
2.1 2.6 0.00636562373171901
2.1 2.7 0.00858651426507939
2.1 2.8 0.0115050443614183
2.1 2.9 0.015290678404975
2.1 3 0.0201375096481456
2.1 3.1 0.0262628277098644
2.1 3.2 0.0339039445281357
2.1 3.3 0.0433130387520159
2.1 3.4 0.0547498861009682
2.1 3.5 0.0684724910591777
2.1 3.6 0.0847258165205387
2.1 3.7 0.103729009917585
2.1 3.8 0.125661728812447
2.1 3.9 0.150650353726577
2.1 4 0.178755017199017
2.1 4.1 0.20995845294592
2.1 4.2 0.244157659295224
2.1 4.3 0.28115926618573
2.1 4.4 0.320679294471488
2.1 4.5 0.362347711020684
2.1 4.6 0.405717835332902
2.1 4.7 0.450280274677866
2.1 4.8 0.495480692630711
2.1 4.9 0.54074038939489
2.1 5 0.585478427043811
2.1 5.1 0.629133896168824
2.1 5.2 0.671186907874983
2.1 5.3 0.711177008050708
2.1 5.4 0.748717936539325
2.1 5.5 0.783507966966351
2.1 5.6 0.815335429203166
2.1 5.7 0.844079396998888
2.1 5.8 0.869705879945008
2.1 5.9 0.892260158584909
2.1 6 0.911856119895068
2.1 6.1 0.928663574301693
2.1 6.2 0.94289456314871
2.1 6.3 0.954789605895935
2.1 6.4 0.9646047063103
2.1 6.5 0.972599758673439
2.1 6.6 0.979028792549194
2.1 6.7 0.984132290679127
2.1 6.8 0.988131628181527
2.1 6.9 0.991225526275497
2.1 7 0.993588298246742
2.1 7.1 0.995369591705686
2.1 7.2 0.996695297009385
2.1 7.3 0.997669291211883
2.1 7.4 0.998375712220557
2.1 7.5 0.998881500424427
2.1 7.6 0.999238996797235
2.1 7.7 0.99948844043681
2.1 7.8 0.999660259393867
2.1 7.9 0.999777092942825
2.1 8 0.999855519274834
2.2 2 0.00127716415194634
2.2 2.1 0.00160305609595068
2.2 2.2 0.00206666200783134
2.2 2.3 0.00271750173154872
2.2 2.4 0.00361920421430395
2.2 2.5 0.00485211034520749
2.2 2.6 0.00651585524545695
2.2 2.7 0.00873172864189209
2.2 2.8 0.011644559163424
2.2 2.9 0.0154238233922567
2.2 3 0.0202636512346196
2.2 3.1 0.026381394185286
2.2 3.2 0.0340144504128834
2.2 3.3 0.0434151065774531
2.2 3.4 0.0548432639995218
2.2 3.5 0.068557064806095
2.2 3.6 0.0848016150730159
2.2 3.7 0.103796204005997
2.2 3.8 0.125720622697289
2.2 3.9 0.150701370780855
2.2 4 0.178798680448402
2.2 4.1 0.209995362047796
2.2 4.2 0.244188465629722
2.2 4.3 0.281184647755275
2.2 4.4 0.320699932170064
2.2 4.5 0.36236426756848
2.2 4.6 0.405730937817814
2.2 4.7 0.450290501250305
2.2 4.8 0.495488563508966
2.2 4.9 0.540746361994453
2.2 5 0.585482894773842
2.2 5.1 0.629137190257142
2.2 5.2 0.671189301491685
2.2 5.3 0.711178721990805
2.2 5.4 0.74871914578046
2.2 5.5 0.783508807518392
2.2 5.6 0.815336004791765
2.2 5.7 0.844079785256594
2.2 5.8 0.869706137906852
2.2 5.9 0.892260327390952
2.2 6 0.911856228685206
2.2 6.1 0.92866364334698
2.2 6.2 0.942894606300356
2.2 6.3 0.954789632451594
2.2 6.4 0.964604722401643
2.2 6.5 0.972599768273711
2.2 6.6 0.979028798188333
2.2 6.7 0.98413229394022
2.2 6.8 0.988131630038129
2.2 6.9 0.991225527316052
2.2 7 0.993588298820843
2.2 7.1 0.995369592017485
2.2 7.2 0.996695297176077
2.2 7.3 0.997669291299601
2.2 7.4 0.998375712265993
2.2 7.5 0.998881500447591
2.2 7.6 0.999238996808859
2.2 7.7 0.999488440442551
2.2 7.8 0.999660259396658
2.2 7.9 0.99977709294416
2.2 8 0.999855519275463
2.3 2 0.00150681663482521
2.3 2.1 0.00183064714508141
2.3 2.2 0.00229165330946857
2.3 2.3 0.00293926757974838
2.3 2.4 0.00383703321845841
2.3 2.5 0.00506521215484301
2.3 2.6 0.00672337291163405
2.3 2.7 0.00893275686399697
2.3 2.8 0.0118381681995714
2.3 2.9 0.0156090878796455
2.3 3 0.0204396826271819
2.3 3.1 0.0265473750336986
2.3 3.2 0.0341696683515864
2.3 3.3 0.0435589857013867
2.3 3.4 0.0549753913484663
2.3 3.5 0.0686772099397792
2.3 3.6 0.0849097411990749
2.3 3.7 0.103892469769991
2.3 3.8 0.125805374490425
2.3 3.9 0.150775126183674
2.3 4 0.178862104122173
2.3 4.1 0.210049235934039
2.3 4.2 0.244233655667268
2.3 4.3 0.281222069445706
2.3 4.4 0.320730517218603
2.3 4.5 0.362388933527987
2.3 4.6 0.40575056221962
2.3 4.7 0.450305901180093
2.3 4.8 0.495500481044349
2.3 4.9 0.540755455421877
2.3 5 0.585489735090987
2.3 5.1 0.629142262170586
2.3 5.2 0.671193007947624
2.3 5.3 0.711181391222245
2.3 5.4 0.748721039898684
2.3 5.5 0.783510131793495
2.3 5.6 0.815336916928289
2.3 5.7 0.844080404149203
2.3 5.8 0.869706551535585
2.3 5.9 0.892260599670335
2.3 6 0.911856405207073
2.3 6.1 0.928663756049894
2.3 6.2 0.942894677160132
2.3 6.3 0.954789676321763
2.3 6.4 0.964604749145392
2.3 6.5 0.972599784326066
2.3 6.6 0.979028807674703
2.3 6.7 0.984132299459582
2.3 6.8 0.988131633199598
2.3 6.9 0.99122552909878
2.3 7 0.993588299810451
2.3 7.1 0.995369592558253
2.3 7.2 0.996695297466957
2.3 7.3 0.997669291453616
2.3 7.4 0.998375712346261
2.3 7.5 0.998881500488768
2.3 7.6 0.99923899682965
2.3 7.7 0.999488440452883
2.3 7.8 0.999660259401712
2.3 7.9 0.999777092946593
2.3 8 0.999855519276616
2.4 2 0.00181837870595902
2.4 2.1 0.0021396725646412
2.4 2.2 0.00259745925543886
2.4 2.3 0.00324105370451522
2.4 2.4 0.00413388162354333
2.4 2.5 0.00535609372596568
2.4 2.6 0.00700716100346332
2.4 2.7 0.00920824888424732
2.4 2.8 0.0121041150532671
2.4 2.9 0.0158642305394766
2.4 3 0.0206827943607594
2.4 3.1 0.0267773071256474
2.4 3.2 0.0343853965967277
2.4 3.3 0.0437596545974502
2.4 3.4 0.0551603528459459
2.4 3.5 0.0688460538447403
2.4 3.6 0.0850623148653902
2.4 3.7 0.104028885513914
2.4 3.8 0.125926004130484
2.4 3.9 0.150880583145899
2.4 4 0.178953214538283
2.4 4.1 0.210127000989299
2.4 4.2 0.244299208038444
2.4 4.3 0.281276626955411
2.4 4.4 0.320775336807551
2.4 4.5 0.362425268337768
2.4 4.6 0.405779624044579
2.4 4.7 0.450328829868322
2.4 4.8 0.495518321693511
2.4 4.9 0.54076914350977
2.4 5 0.5855000890723
2.4 5.1 0.629149982607029
2.4 5.2 0.671198681940486
2.4 5.3 0.711185500783308
2.4 5.4 0.748723972907289
2.4 5.5 0.783512194312169
2.4 5.6 0.81533834584867
2.4 5.7 0.844081379376633
2.4 5.8 0.869707207162225
2.4 5.9 0.892261033808347
2.4 6 0.911856688339578
2.4 6.1 0.928663937900485
2.4 6.2 0.942894792181137
2.4 6.3 0.954789747961385
2.4 6.4 0.964604793081443
2.4 6.5 0.972599810857445
2.4 6.6 0.979028823449021
2.4 6.7 0.984132308693275
2.4 6.8 0.988131638520899
2.4 6.9 0.991225532117773
2.4 7 0.993588301496592
2.4 7.1 0.995369593485294
2.4 7.2 0.996695297968682
2.4 7.3 0.997669291720905
2.4 7.4 0.998375712486425
2.4 7.5 0.998881500561114
2.4 7.6 0.999238996866404
2.4 7.7 0.999488440471262
2.4 7.8 0.999660259410757
2.4 7.9 0.999777092950975
2.4 8 0.999855519278704
2.5 2 0.00223705875466529
2.5 2.1 0.00255526753843971
2.5 2.2 0.00300911372295409
2.5 2.3 0.00364775667919126
2.5 2.4 0.00453446365839683
2.5 2.5 0.0057492319060567
2.5 2.6 0.00739139333097694
2.5 2.7 0.00958199904789192
2.5 2.8 0.0124657278572216
2.5 2.9 0.0162120173821354
2.5 3 0.0210150871770864
2.5 3.1 0.0270925182422679
2.5 3.2 0.0346820811136742
2.5 3.3 0.0440365713209561
2.5 3.4 0.0554165195496881
2.5 3.5 0.0690807927931489
2.5 3.6 0.0852752851041334
2.5 3.7 0.104220099377478
2.5 3.8 0.126095826641983
2.5 3.9 0.151029714357524
2.5 4 0.179082656228646
2.5 4.1 0.210238010343608
2.5 4.2 0.244393241858823
2.5 4.3 0.281355280492154
2.5 4.4 0.320840281429323
2.5 4.5 0.36247819198561
2.5 4.6 0.405822177804562
2.5 4.7 0.450362583149651
2.5 4.8 0.495544727529664
2.5 4.9 0.540789514527079
2.5 5 0.585515583794944
2.5 5.1 0.629161601064666
2.5 5.2 0.671207269057132
2.5 5.3 0.711191755763638
2.5 5.4 0.748728462781282
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9.2 4.3 0.999760047565078
9.2 4.4 0.999760573066838
9.2 4.5 0.999761290250141
9.2 4.6 0.999762253300324
9.2 4.7 0.999763525724496
9.2 4.8 0.999765179896565
9.2 4.9 0.999767295804764
9.2 5 0.999769958870949
9.2 5.1 0.999773256773254
9.2 5.2 0.999777275292404
9.2 5.3 0.999782093311601
9.2 5.4 0.99978777722032
9.2 5.5 0.999794375088991
9.2 5.6 0.999801911077442
9.2 5.7 0.999810380597783
9.2 5.8 0.99981974675747
9.2 5.9 0.999829938551573
9.2 6 0.999840851153928
9.2 6.1 0.999852348483146
9.2 6.2 0.999864268008908
9.2 6.3 0.999876427541116
9.2 6.4 0.999888633537511
9.2 6.5 0.999900690301964
9.2 6.6 0.999912409348287
9.2 6.7 0.999923618186681
9.2 6.8 0.999934167854337
9.2 6.9 0.999943938648944
9.2 7 0.99995284371489
9.2 7.1 0.99996083035069
9.2 7.2 0.99996787912434
9.2 7.3 0.999974001074382
9.2 7.4 0.999979233417968
9.2 7.5 0.999983634270854
9.2 7.6 0.999987276905251
9.2 7.7 0.999990244035584
9.2 7.8 0.999992622541841
9.2 7.9 0.999994498931831
9.2 8 0.99999595572443
9.3 2 0.999832451672931
9.3 2.1 0.999832451675429
9.3 2.2 0.999832451680411
9.3 2.3 0.999832451690192
9.3 2.4 0.999832451709078
9.3 2.5 0.999832451744961
9.3 2.6 0.999832451812037
9.3 2.7 0.999832451935401
9.3 2.8 0.999832452158628
9.3 2.9 0.999832452556049
9.3 3 0.999832453252185
9.3 3.1 0.999832454451911
9.3 3.2 0.999832456486207
9.3 3.3 0.999832459880043
9.3 3.4 0.999832465450796
9.3 3.5 0.999832474447511
9.3 3.6 0.999832488743103
9.3 3.7 0.999832511092691
9.3 3.8 0.999832545471206
9.3 3.9 0.999832597501474
9.3 4 0.999832674979316
9.3 4.1 0.999832788494161
9.3 4.2 0.999832952131611
9.3 4.3 0.999833184228274
9.3 4.4 0.999833508129454
9.3 4.5 0.999833952878399
9.3 4.6 0.999834553744162
9.3 4.7 0.999835352476985
9.3 4.8 0.999836397169775
9.3 4.9 0.999837741605839
9.3 5 0.999839443990685
9.3 5.1 0.999841565001886
9.3 5.2 0.999844165146174
9.3 5.3 0.999847301484465
9.3 5.4 0.999851023867561
9.3 5.5 0.999855370908762
9.3 5.6 0.999860365993202
9.3 5.7 0.999866013675113
9.3 5.8 0.999872296832393
9.3 5.9 0.999879174924719
9.3 6 0.999886583634231
9.3 6.1 0.999894436059814
9.3 6.2 0.999902625497161
9.3 6.3 0.999911029682629
9.3 6.4 0.999919516228373
9.3 6.5 0.999927948849199
9.3 6.6 0.999936193895294
9.3 6.7 0.999944126671589
9.3 6.8 0.999951637048491
9.3 6.9 0.999958633946855
9.3 7 0.999965048401155
9.3 7.1 0.999970835052291
9.3 7.2 0.999975972075811
9.3 7.3 0.999980459693281
9.3 7.4 0.999984317527906
9.3 7.5 0.999987581139699
9.3 7.6 0.99999029810591
9.3 7.7 0.999992524001179
9.3 7.8 0.999994318586036
9.3 7.9 0.999995742442619
9.3 8 0.999996854214868
9.4 2 0.999884608175893
9.4 2.1 0.999884608177214
9.4 2.2 0.999884608179867
9.4 2.3 0.999884608185105
9.4 2.4 0.999884608195283
9.4 2.5 0.99988460821474
9.4 2.6 0.999884608251338
9.4 2.7 0.999884608319065
9.4 2.8 0.999884608442377
9.4 2.9 0.999884608663274
9.4 3 0.999884609052602
9.4 3.1 0.999884609727723
9.4 3.2 0.99988461087956
9.4 3.3 0.999884612813058
9.4 3.4 0.999884616006366
9.4 3.5 0.999884621195358
9.4 3.6 0.999884629491412
9.4 3.7 0.999884642541317
9.4 3.8 0.999884662738528
9.4 3.9 0.999884693494172
9.4 4 0.999884739573765
9.4 4.1 0.999884807501013
9.4 4.2 0.999884906022756
9.4 4.3 0.999885046619106
9.4 4.4 0.999885244029997
9.4 4.5 0.999885516754734
9.4 4.6 0.999885887465849
9.4 4.7 0.999886383264876
9.4 4.8 0.999887035698138
9.4 4.9 0.999887880448317
9.4 5 0.999888956625363
9.4 5.1 0.99989030560034
9.4 5.2 0.999891969359089
9.4 5.3 0.999893988398046
9.4 5.4 0.999896399239134
9.4 5.5 0.999899231698662
9.4 5.6 0.999902506099504
9.4 5.7 0.999906230657928
9.4 5.8 0.999910399298315
9.4 5.9 0.99991499014409
9.4 6 0.999919964898059
9.4 6.1 0.999925269260769
9.4 6.2 0.99993083444647
9.4 6.3 0.99993657975243
9.4 6.4 0.999942416030884
9.4 6.5 0.999948249817722
9.4 6.6 0.99995398780086
9.4 6.7 0.999959541273984
9.4 6.8 0.999964830223264
9.4 6.9 0.999969786735365
9.4 7 0.999974357488826
9.4 7.1 0.999978505187514
9.4 7.2 0.999982208901175
9.4 7.3 0.999985463380711
9.4 7.4 0.999988277502417
9.4 7.5 0.999990672057155
9.4 7.6 0.999992677132621
9.4 7.7 0.99999432933928
9.4 7.8 0.999995669106885
9.4 7.9 0.999996738235486
9.4 8 0.999997577830509
9.5 2 0.999921221639085
9.5 2.1 0.999921221639776
9.5 2.2 0.999921221641172
9.5 2.3 0.999921221643945
9.5 2.4 0.999921221649368
9.5 2.5 0.999921221659799
9.5 2.6 0.999921221679542
9.5 2.7 0.999921221716303
9.5 2.8 0.99992122178365
9.5 2.9 0.999921221905042
9.5 3 0.999921222120319
9.5 3.1 0.999921222495937
9.5 3.2 0.999921223140754
9.5 3.3 0.999921224229855
9.5 3.4 0.999921226039704
9.5 3.5 0.999921228998807
9.5 3.6 0.999921233758975
9.5 3.7 0.999921241293051
9.5 3.8 0.999921253025376
9.5 3.9 0.999921271001068
9.5 4 0.999921298098964
9.5 4.1 0.999921338290544
9.5 4.2 0.999921396942863
9.5 4.3 0.999921481157392
9.5 4.4 0.99992160012857
9.5 4.5 0.999921765496229
9.5 4.6 0.999921991655662
9.5 4.7 0.9999222959791
9.5 4.8 0.999922698894594
9.5 4.9 0.999923223764585
9.5 5 0.999923896509006
9.5 5.1 0.999924744928182
9.5 5.2 0.999925797700172
9.5 5.3 0.999927083055352
9.5 5.4 0.999928627166386
9.5 5.5 0.999930452331048
9.5 5.6 0.999932575064121
9.5 5.7 0.999935004247174
9.5 5.8 0.999937739505746
9.5 5.9 0.99994076998731
9.5 6 0.999944073697199
9.5 6.1 0.999947617512721
9.5 6.2 0.99995135794044
9.5 6.3 0.999955242613421
9.5 6.4 0.999959212452032
9.5 6.5 0.999963204342807
9.5 6.6 0.999967154134207
9.5 6.7 0.999970999713426
9.5 6.8 0.999974683919545
9.5 6.9 0.999978157066677
9.5 7 0.999981378893467
9.5 7.1 0.999984319816604
9.5 7.2 0.99998696143738
9.5 7.3 0.999989296322489
9.5 7.4 0.999991327144435
9.5 7.5 0.999993065315926
9.5 7.6 0.999994529282329
9.5 7.7 0.999995742645201
9.5 7.8 0.999996732279906
9.5 7.9 0.999997526585109
9.5 8 0.999998153966976
9.6 2 0.999946687650575
9.6 2.1 0.999946687650932
9.6 2.2 0.999946687651658
9.6 2.3 0.99994668765311
9.6 2.4 0.999946687655967
9.6 2.5 0.999946687661496
9.6 2.6 0.999946687672024
9.6 2.7 0.999946687691752
9.6 2.8 0.999946687728117
9.6 2.9 0.999946687794071
9.6 3 0.999946687911761
9.6 3.1 0.999946688118381
9.6 3.2 0.999946688475279
9.6 3.3 0.999946689081818
9.6 3.4 0.999946690095992
9.6 3.5 0.999946691764427
9.6 3.6 0.999946694464952
9.6 3.7 0.999946698765572
9.6 3.8 0.999946705504001
9.6 3.9 0.999946715891997
9.6 4 0.999946731648196
9.6 4.1 0.999946755161777
9.6 4.2 0.999946789686858
9.6 4.3 0.99994683956386
9.6 4.4 0.99994691045905
9.6 4.5 0.999947009607316
9.6 4.6 0.999947146036274
9.6 4.7 0.999947330742819
9.6 4.8 0.999947576787239
9.6 4.9 0.999947899266311
9.6 5 0.999948315126777
9.6 5.1 0.999948842785555
9.6 5.2 0.999949501533865
9.6 5.3 0.999950310719387
9.6 5.4 0.999951288722888
9.6 5.5 0.999952451771717
9.6 5.6 0.99995381265941
9.6 5.7 0.999955379464734
9.6 5.8 0.999957154381009
9.6 5.9 0.99995913277373
9.6 6 0.99996130257878
9.6 6.1 0.999963644133638
9.6 6.2 0.999966130500807
9.6 6.3 0.999968728299237
9.6 6.4 0.9999713990104
9.6 6.5 0.999974100677089
9.6 6.6 0.999976789871191
9.6 6.7 0.999979423777386
9.6 6.8 0.999981962226962
9.6 6.9 0.999984369521632
9.6 7 0.999986615910405
9.6 7.1 0.999988678620059
9.6 7.2 0.999990542386351
9.6 7.3 0.999992199482558
9.6 7.4 0.99999364928812
9.6 7.5 0.999994897477601
9.6 7.6 0.99999595493542
9.6 7.7 0.999996836513
9.6 7.8 0.99999755974271
9.6 7.9 0.999998143609307
9.6 8 0.999998607457844
9.7 2 0.999964237315397
9.7 2.1 0.99996423731558
9.7 2.2 0.999964237315953
9.7 2.3 0.999964237316705
9.7 2.4 0.999964237318192
9.7 2.5 0.999964237321089
9.7 2.6 0.999964237326641
9.7 2.7 0.999964237337107
9.7 2.8 0.99996423735652
9.7 2.9 0.999964237391948
9.7 3 0.999964237455559
9.7 3.1 0.999964237567929
9.7 3.2 0.999964237763233
9.7 3.3 0.999964238097205
9.7 3.4 0.999964238659088
9.7 3.5 0.999964239589177
9.7 3.6 0.999964241103936
9.7 3.7 0.999964243531132
9.7 3.8 0.999964247357695
9.7 3.9 0.99996425329319
9.7 4 0.999964262351555
9.7 4.1 0.999964275953105
9.7 4.2 0.999964296047445
9.7 4.3 0.999964325255786
9.7 4.4 0.999964367028127
9.7 4.5 0.999964425806916
9.7 4.6 0.999964507184243
9.7 4.7 0.999964618034916
9.7 4.8 0.99996476660334
9.7 4.9 0.999964962519017
9.7 5 0.999965216714352
9.7 5.1 0.999965541220519
9.7 5.2 0.999965948822826
9.7 5.3 0.999966452566918
9.7 5.4 0.999967065120863
9.7 5.5 0.999967798014913
9.7 5.6 0.999968660798763
9.7 5.7 0.999969660173348
9.7 5.8 0.999970799167907
9.7 5.9 0.999972076440744
9.7 6 0.999973485781645
9.7 6.1 0.999975015884114
9.7 6.2 0.999976650436491
9.7 6.3 0.999978368554047
9.7 6.4 0.999980145542157
9.7 6.5 0.999981953947354
9.7 6.6 0.999983764822812
9.7 6.7 0.99998554911154
9.7 6.8 0.999987279037699
9.7 6.9 0.999988929395582
9.7 7 0.999990478637199
9.7 7.1 0.999991909681371
9.7 7.2 0.99999321039675
9.7 7.3 0.999994373744191
9.7 7.4 0.999995397596231
9.7 7.5 0.999996284279109
9.7 7.6 0.999997039902981
9.7 7.7 0.999997673557025
9.7 7.8 0.999998196447849
9.7 7.9 0.999998621053029
9.7 8 0.999998960348704
9.8 2 0.999976220286056
9.8 2.1 0.999976220286148
9.8 2.2 0.999976220286338
9.8 2.3 0.999976220286723
9.8 2.4 0.999976220287489
9.8 2.5 0.999976220288989
9.8 2.6 0.999976220291883
9.8 2.7 0.999976220297373
9.8 2.8 0.999976220307619
9.8 2.9 0.999976220326434
9.8 3 0.999976220360425
9.8 3.1 0.999976220420845
9.8 3.2 0.99997622052651
9.8 3.3 0.999976220708319
9.8 3.4 0.999976221016098
9.8 3.5 0.999976221528724
9.8 3.6 0.999976222368769
9.8 3.7 0.999976223723163
9.8 3.8 0.999976225871632
9.8 3.9 0.999976229224799
9.8 4 0.999976234373816
9.8 4.1 0.999976242153063
9.8 4.2 0.999976253716736
9.8 4.3 0.999976270628929
9.8 4.4 0.999976294965029
9.8 4.5 0.999976329419848
9.8 4.6 0.999976377415063
9.8 4.7 0.999976443195382
9.8 4.8 0.999976531899784
9.8 4.9 0.999976649591712
9.8 5 0.999976803230777
9.8 5.1 0.999977000569046
9.8 5.2 0.999977249957818
9.8 5.3 0.999977560056328
9.8 5.4 0.99997793944205
9.8 5.5 0.999978396132739
9.8 5.6 0.999978937042236
9.8 5.7 0.999979567403866
9.8 5.8 0.99998029020551
9.8 5.9 0.999981105687221
9.8 6 0.9999820109541
9.8 6.1 0.999982999753011
9.8 6.2 0.99998406245123
9.8 6.3 0.999985186238963
9.8 6.4 0.999986355557346
9.8 6.5 0.99998755273134
9.8 6.6 0.999988758765728
9.8 6.7 0.999989954244876
9.8 6.8 0.999991120265573
9.8 6.9 0.999992239328646
9.8 7 0.999993296119645
9.8 7.1 0.999994278121123
9.8 7.2 0.999995176017063
9.8 7.3 0.999995983871514
9.8 7.4 0.999996699085485
9.8 7.5 0.999997322155997
9.8 7.6 0.999997856276727
9.8 7.7 0.999998306829299
9.8 7.8 0.999998680817757
9.8 7.9 0.999998986296218
9.8 8 0.999999231832543
9.9 2 0.999984327057674
9.9 2.1 0.99998432705772
9.9 2.2 0.999984327057816
9.9 2.3 0.99998432705801
9.9 2.4 0.9999843270584
9.9 2.5 0.999984327059169
9.9 2.6 0.99998432706066
9.9 2.7 0.999984327063507
9.9 2.8 0.999984327068853
9.9 2.9 0.999984327078731
9.9 3 0.999984327096689
9.9 3.1 0.999984327128808
9.9 3.2 0.999984327185327
9.9 3.3 0.99998432728318
9.9 3.4 0.99998432744986
9.9 3.5 0.999984327729199
9.9 3.6 0.999984328189796
9.9 3.7 0.999984328937013
9.9 3.8 0.999984330129664
9.9 3.9 0.99998433200259
9.9 4 0.999984334896395
9.9 4.1 0.999984339295459
9.9 4.2 0.999984345874985
9.9 4.3 0.999984355557163
9.9 4.4 0.999984369575505
9.9 4.5 0.999984389544967
9.9 4.6 0.999984417533695
9.9 4.7 0.999984456130206
9.9 4.8 0.999984508497738
9.9 4.9 0.999984578405661
9.9 5 0.999984670226667
9.9 5.1 0.999984788888263
9.9 5.2 0.999984939768374
9.9 5.3 0.999985128527815
9.9 5.4 0.999985360877187
9.9 5.5 0.999985642282137
9.9 5.6 0.999985977618538
9.9 5.7 0.999986370797038
9.9 5.8 0.999986824383754
9.9 5.9 0.999987339249314
9.9 6 0.99998791428103
9.9 6.1 0.999988546191771
9.9 6.2 0.999989229453736
9.9 6.3 0.999989956375984
9.9 6.4 0.999990717332033
9.9 6.5 0.999991501129455
9.9 6.6 0.999992295498904
9.9 6.7 0.999993087667355
9.9 6.8 0.999993864971136
9.9 6.9 0.999994615459969
9.9 7 0.999995328444254
9.9 7.1 0.999995994944131
9.9 7.2 0.999996608009488
9.9 7.3 0.99999716289366
9.9 7.4 0.999997657078141
9.9 7.5 0.999998090159516
9.9 7.6 0.999998463621212
9.9 7.7 0.999998780520586
9.9 7.8 0.999999045125652
9.9 7.9 0.999999262535483
9.9 8 0.999999438314628
10 2 0.99998976105165
10 2.1 0.999989761051673
10 2.2 0.99998976105172
10 2.3 0.999989761051817
10 2.4 0.999989761052014
10 2.5 0.999989761052403
10 2.6 0.999989761053163
10 2.7 0.999989761054622
10 2.8 0.99998976105738
10 2.9 0.999989761062507
10 3 0.999989761071887
10 3.1 0.999989761088767
10 3.2 0.999989761118656
10 3.3 0.999989761170724
10 3.4 0.999989761259968
10 3.5 0.99998976141046
10 3.6 0.999989761660145
10 3.7 0.999989762067717
10 3.8 0.999989762722289
10 3.9 0.999989763756592
10 4 0.999989765364566
10 4.1 0.999989767824088
10 4.2 0.999989771525473
10 4.3 0.999989777005973
10 4.4 0.999989784989957
10 4.5 0.999989796433576
10 4.6 0.999989812571678
10 4.7 0.999989834963413
10 4.8 0.999989865531645
10 4.9 0.999989906589964
10 5 0.999989960850157
10 5.1 0.999990031402579
10 5.2 0.999990121662315
10 5.3 0.999990235275537
10 5.4 0.999990375983137
10 5.5 0.999990547442544
10 5.6 0.999990753013338
10 5.7 0.999990995517464
10 5.8 0.999991276989855
10 5.9 0.999991598439384
10 6 0.999991959642525
10 6.1 0.999992358992285
10 6.2 0.9999927934225
10 6.3 0.999993258422389
10 6.4 0.999993748148775
10 6.5 0.999994255634267
10 6.6 0.999994773080144
10 6.7 0.999995292213765
10 6.8 0.999995804683377
10 6.9 0.999996302459071
10 7 0.999996778207974
10 7.1 0.999997225614629
10 7.2 0.999997639623536
10 7.3 0.999998016589086
10 7.4 0.999998354327593
10 7.5 0.999998652075503
10 7.6 0.999998910366009
10 7.7 0.999999130842453
10 7.8 0.999999316030309
10 7.9 0.999999469090408
10 8 0.999999593574359
cm length_percent girth_percent length_count girth_count
1 0 0 0 0
2 0 0 0 0
3 0 0.3 0 5
4 0.06 0.18 1 3
5 0.18 0.24 3 4
6 0.3 1.32 5 22
7 0.12 1.57 2 26
8 0.24 3.73 4 62
9 1.26 4.03 21 67
10 6.32 5.3 105 88
11 7.28 10.54 121 175
12 9.63 23.78 160 395
13 14.63 23.66 243 393
14 16.32 15.29 271 254
15 14.63 5 243 83
16 11.86 3.13 197 52
17 8.61 1.14 143 19
18 3.31 0.6 55 10
19 3.01 0.18 50 3
20 0.66 0 11 0
21 0 0 0 0
22 1.2 0 20 0
23 0.24 0 4 0
24 0.06 0 1 0
25 0 0 0 0
26 0.06 0 1 0
volume percentile
0 0
0.01 0
0.02 0
0.03 0
0.04 0
0.05 0
0.06 1e-06
0.07 2e-06
0.08 2e-06
0.09 2e-06
0.1 2e-06
0.11 2e-06
0.12 3e-06
0.13 4e-06
0.14 5e-06
0.15 5e-06
0.16 5e-06
0.17 5e-06
0.18 7e-06
0.19 7e-06
0.2 8e-06
0.21 9e-06
0.22 9e-06
0.23 1.2e-05
0.24 1.3e-05
0.25 1.3e-05
0.26 1.4e-05
0.27 1.4e-05
0.28 1.6e-05
0.29 1.7e-05
0.3 1.7e-05
0.31 1.8e-05
0.32 1.9e-05
0.33 2e-05
0.34 2.2e-05
0.35 2.2e-05
0.36 2.2e-05
0.37 2.4e-05
0.38 2.8e-05
0.39 2.8e-05
0.4 2.9e-05
0.41 3.1e-05
0.42 3.4e-05
0.43 3.9e-05
0.44 4.1e-05
0.45 4.2e-05
0.46 5e-05
0.47 5.2e-05
0.48 5.8e-05
0.49 6e-05
0.5 6.5e-05
0.51 6.9e-05
0.52 7e-05
0.53 7.6e-05
0.54 7.9e-05
0.55 8.3e-05
0.56 8.5e-05
0.57 8.8e-05
0.58 9.3e-05
0.59 1e-04
0.6 0.000102
0.61 0.000105
0.62 0.000111
0.63 0.000115
0.64 0.00012
0.65 0.000126
0.66 0.000134
0.67 0.000137
0.68 0.000144
0.69 0.000146
0.7 0.000156
0.71 0.000166
0.72 0.000175
0.73 0.000181
0.74 0.00019
0.75 0.000196
0.76 0.00021
0.77 0.000221
0.78 0.000227
0.79 0.000231
0.8 0.000242
0.81 0.000261
0.82 0.000276
0.83 0.000288
0.84 0.000298
0.85 0.000308
0.86 0.000318
0.87 0.000333
0.88 0.000346
0.89 0.000355
0.9 0.000365
0.91 0.000376
0.92 0.000385
0.93 0.000395
0.94 0.00041
0.95 0.000421
0.96 0.000439
0.97 0.00046
0.98 0.000473
0.99 0.00049
1 0.000516
1.01 0.000531
1.02 0.000551
1.03 0.000574
1.04 0.000596
1.05 0.000615
1.06 0.000635
1.07 0.000652
1.08 0.000673
1.09 0.000687
1.1 0.000703
1.11 0.000728
1.12 0.000748
1.13 0.000777
1.14 8e-04
1.15 0.000819
1.16 0.000843
1.17 0.000859
1.18 0.000894
1.19 0.000918
1.2 0.000941
1.21 0.000966
1.22 0.000989
1.23 0.00101
1.24 0.001034
1.25 0.001068
1.26 0.001099
1.27 0.001126
1.28 0.00115
1.29 0.001183
1.3 0.001208
1.31 0.001248
1.32 0.001279
1.33 0.001306
1.34 0.001338
1.35 0.001365
1.36 0.001398
1.37 0.001427
1.38 0.001458
1.39 0.001491
1.4 0.001528
1.41 0.001554
1.42 0.001595
1.43 0.00163
1.44 0.001672
1.45 0.001712
1.46 0.001746
1.47 0.001792
1.48 0.001827
1.49 0.001878
1.5 0.001906
1.51 0.001957
1.52 0.002006
1.53 0.002058
1.54 0.002115
1.55 0.00216
1.56 0.002195
1.57 0.002249
1.58 0.002291
1.59 0.002337
1.6 0.00239
1.61 0.002447
1.62 0.00251
1.63 0.002556
1.64 0.002604
1.65 0.002658
1.66 0.002712
1.67 0.002762
1.68 0.002807
1.69 0.002857
1.7 0.002913
1.71 0.002981
1.72 0.003033
1.73 0.003082
1.74 0.003138
1.75 0.003192
1.76 0.003257
1.77 0.003318
1.78 0.003389
1.79 0.003469
1.8 0.003545
1.81 0.003621
1.82 0.003706
1.83 0.003775
1.84 0.003835
1.85 0.003918
1.86 0.003992
1.87 0.004087
1.88 0.004167
1.89 0.004246
1.9 0.00433
1.91 0.004418
1.92 0.004502
1.93 0.004582
1.94 0.004673
1.95 0.004756
1.96 0.004825
1.97 0.004917
1.98 0.00501
1.99 0.005102
2 0.005195
2.01 0.005283
2.02 0.005362
2.03 0.005465
2.04 0.005545
2.05 0.005654
2.06 0.005747
2.07 0.005852
2.08 0.005957
2.09 0.006047
2.1 0.006125
2.11 0.006217
2.12 0.006317
2.13 0.006414
2.14 0.006509
2.15 0.006616
2.16 0.006726
2.17 0.006842
2.18 0.00694
2.19 0.007031
2.2 0.007137
2.21 0.007242
2.22 0.007364
2.23 0.007472
2.24 0.007571
2.25 0.00769
2.26 0.007798
2.27 0.007908
2.28 0.008028
2.29 0.008142
2.3 0.008264
2.31 0.008379
2.32 0.008496
2.33 0.008612
2.34 0.008736
2.35 0.008854
2.36 0.008971
2.37 0.009081
2.38 0.009223
2.39 0.009354
2.4 0.009482
2.41 0.009615
2.42 0.009766
2.43 0.0099
2.44 0.010038
2.45 0.010179
2.46 0.010314
2.47 0.010472
2.48 0.010597
2.49 0.010738
2.5 0.010908
2.51 0.011051
2.52 0.011199
2.53 0.011336
2.54 0.011516
2.55 0.011665
2.56 0.011831
2.57 0.011981
2.58 0.012143
2.59 0.012301
2.6 0.012469
2.61 0.01262
2.62 0.012799
2.63 0.012955
2.64 0.013131
2.65 0.013315
2.66 0.013492
2.67 0.013654
2.68 0.013823
2.69 0.013984
2.7 0.014149
2.71 0.014327
2.72 0.014503
2.73 0.014659
2.74 0.014862
2.75 0.015048
2.76 0.015225
2.77 0.015381
2.78 0.015569
2.79 0.01575
2.8 0.015927
2.81 0.016137
2.82 0.016336
2.83 0.016502
2.84 0.01669
2.85 0.016889
2.86 0.017078
2.87 0.017284
2.88 0.017477
2.89 0.017691
2.9 0.017907
2.91 0.018104
2.92 0.0183
2.93 0.018514
2.94 0.018713
2.95 0.018922
2.96 0.019118
2.97 0.019341
2.98 0.019565
2.99 0.019753
3 0.019999
3.01 0.020228
3.02 0.020461
3.03 0.0207
3.04 0.020935
3.05 0.021152
3.06 0.021387
3.07 0.02164
3.08 0.021868
3.09 0.022096
3.1 0.022325
3.11 0.022599
3.12 0.022844
3.13 0.023089
3.14 0.023341
3.15 0.023575
3.16 0.023811
3.17 0.024054
3.18 0.024313
3.19 0.024557
3.2 0.024795
3.21 0.025051
3.22 0.025306
3.23 0.025584
3.24 0.025844
3.25 0.026128
3.26 0.026392
3.27 0.026667
3.28 0.026948
3.29 0.027219
3.3 0.027469
3.31 0.027741
3.32 0.028
3.33 0.028254
3.34 0.028493
3.35 0.028786
3.36 0.029035
3.37 0.02933
3.38 0.029607
3.39 0.029872
3.4 0.030141
3.41 0.030409
3.42 0.030691
3.43 0.030986
3.44 0.031287
3.45 0.031598
3.46 0.031901
3.47 0.032214
3.48 0.032486
3.49 0.032782
3.5 0.033104
3.51 0.033401
3.52 0.033714
3.53 0.034027
3.54 0.034319
3.55 0.034628
3.56 0.03493
3.57 0.035235
3.58 0.035561
3.59 0.035888
3.6 0.0362
3.61 0.036543
3.62 0.036856
3.63 0.037164
3.64 0.03748
3.65 0.037822
3.66 0.038147
3.67 0.038462
3.68 0.038759
3.69 0.039083
3.7 0.039412
3.71 0.039755
3.72 0.040067
3.73 0.040431
3.74 0.040756
3.75 0.04111
3.76 0.04146
3.77 0.041795
3.78 0.042137
3.79 0.04249
3.8 0.042858
3.81 0.043194
3.82 0.043567
3.83 0.043921
3.84 0.044282
3.85 0.044628
3.86 0.044988
3.87 0.045333
3.88 0.045718
3.89 0.046089
3.9 0.046451
3.91 0.046832
3.92 0.047183
3.93 0.047558
3.94 0.047971
3.95 0.04838
3.96 0.048763
3.97 0.049121
3.98 0.049488
3.99 0.049831
4 0.050232
4.01 0.050601
4.02 0.050992
4.03 0.051391
4.04 0.051788
4.05 0.05217
4.06 0.052574
4.07 0.052955
4.08 0.053362
4.09 0.053766
4.1 0.054172
4.11 0.054573
4.12 0.055021
4.13 0.055395
4.14 0.0558
4.15 0.056191
4.16 0.056627
4.17 0.057055
4.18 0.05747
4.19 0.057892
4.2 0.058286
4.21 0.058703
4.22 0.059127
4.23 0.059602
4.24 0.060058
4.25 0.060459
4.26 0.06088
4.27 0.061309
4.28 0.061737
4.29 0.062237
4.3 0.062673
4.31 0.063142
4.32 0.063549
4.33 0.063981
4.34 0.064468
4.35 0.064905
4.36 0.065353
4.37 0.065816
4.38 0.066324
4.39 0.066785
4.4 0.067247
4.41 0.067737
4.42 0.068194
4.43 0.068641
4.44 0.069078
4.45 0.069536
4.46 0.070006
4.47 0.070502
4.48 0.070963
4.49 0.071442
4.5 0.071909
4.51 0.072369
4.52 0.072844
4.53 0.073349
4.54 0.073825
4.55 0.074282
4.56 0.074723
4.57 0.075207
4.58 0.075687
4.59 0.076135
4.6 0.076642
4.61 0.077092
4.62 0.077565
4.63 0.078056
4.64 0.078579
4.65 0.07906
4.66 0.079587
4.67 0.080087
4.68 0.080623
4.69 0.081141
4.7 0.081675
4.71 0.082163
4.72 0.082683
4.73 0.0832
4.74 0.083688
4.75 0.084219
4.76 0.084725
4.77 0.085209
4.78 0.085685
4.79 0.086188
4.8 0.086701
4.81 0.087244
4.82 0.087792
4.83 0.088294
4.84 0.088804
4.85 0.089329
4.86 0.0899
4.87 0.090411
4.88 0.090948
4.89 0.09151
4.9 0.092102
4.91 0.092618
4.92 0.093162
4.93 0.093685
4.94 0.094223
4.95 0.094737
4.96 0.09528
4.97 0.095897
4.98 0.096436
4.99 0.097026
5 0.097561
5.01 0.098146
5.02 0.098747
5.03 0.099279
5.04 0.099874
5.05 0.100479
5.06 0.101029
5.07 0.101575
5.08 0.102151
5.09 0.102726
5.1 0.103279
5.11 0.103873
5.12 0.104447
5.13 0.105033
5.14 0.10561
5.15 0.106221
5.16 0.106799
5.17 0.107384
5.18 0.107952
5.19 0.108588
5.2 0.109187
5.21 0.109794
5.22 0.110353
5.23 0.11094
5.24 0.111509
5.25 0.112067
5.26 0.112675
5.27 0.113261
5.28 0.113864
5.29 0.114458
5.3 0.115057
5.31 0.115661
5.32 0.116268
5.33 0.116923
5.34 0.117548
5.35 0.118166
5.36 0.118779
5.37 0.119408
5.38 0.120052
5.39 0.120655
5.4 0.121283
5.41 0.121879
5.42 0.122541
5.43 0.123197
5.44 0.123812
5.45 0.124469
5.46 0.125126
5.47 0.12576
5.48 0.126391
5.49 0.126989
5.5 0.127658
5.51 0.128336
5.52 0.128967
5.53 0.129603
5.54 0.130271
5.55 0.130893
5.56 0.131528
5.57 0.132178
5.58 0.132866
5.59 0.133482
5.6 0.134187
5.61 0.134836
5.62 0.135469
5.63 0.136128
5.64 0.136805
5.65 0.137461
5.66 0.138099
5.67 0.138749
5.68 0.139402
5.69 0.140061
5.7 0.140724
5.71 0.141399
5.72 0.14204
5.73 0.142722
5.74 0.143398
5.75 0.144074
5.76 0.144717
5.77 0.145412
5.78 0.146104
5.79 0.146745
5.8 0.14742
5.81 0.148076
5.82 0.14876
5.83 0.149398
5.84 0.150062
5.85 0.150815
5.86 0.151537
5.87 0.152246
5.88 0.152941
5.89 0.153626
5.9 0.15432
5.91 0.154977
5.92 0.155673
5.93 0.156387
5.94 0.157053
5.95 0.15774
5.96 0.158407
5.97 0.159155
5.98 0.159895
5.99 0.160568
6 0.161281
6.01 0.161951
6.02 0.162653
6.03 0.163353
6.04 0.164055
6.05 0.164782
6.06 0.16551
6.07 0.166178
6.08 0.16686
6.09 0.167575
6.1 0.168266
6.11 0.168982
6.12 0.169712
6.13 0.170416
6.14 0.171189
6.15 0.171909
6.16 0.172621
6.17 0.17334
6.18 0.174034
6.19 0.174761
6.2 0.175546
6.21 0.176291
6.22 0.176982
6.23 0.17772
6.24 0.178438
6.25 0.17916
6.26 0.179845
6.27 0.180649
6.28 0.181369
6.29 0.18212
6.3 0.182894
6.31 0.183654
6.32 0.184437
6.33 0.185116
6.34 0.185848
6.35 0.186594
6.36 0.187333
6.37 0.188032
6.38 0.188809
6.39 0.189561
6.4 0.19026
6.41 0.190976
6.42 0.191742
6.43 0.192496
6.44 0.193252
6.45 0.194075
6.46 0.194819
6.47 0.195542
6.48 0.196255
6.49 0.197012
6.5 0.197767
6.51 0.198517
6.52 0.199255
6.53 0.200047
6.54 0.200775
6.55 0.201551
6.56 0.202345
6.57 0.20311
6.58 0.203873
6.59 0.20467
6.6 0.20549
6.61 0.206251
6.62 0.207069
6.63 0.207862
6.64 0.208659
6.65 0.209416
6.66 0.210178
6.67 0.210985
6.68 0.211803
6.69 0.21258
6.7 0.213387
6.71 0.214191
6.72 0.214945
6.73 0.215678
6.74 0.216426
6.75 0.217261
6.76 0.218081
6.77 0.218809
6.78 0.219556
6.79 0.220321
6.8 0.221134
6.81 0.221912
6.82 0.222683
6.83 0.223483
6.84 0.224261
6.85 0.225065
6.86 0.225935
6.87 0.226726
6.88 0.227506
6.89 0.228304
6.9 0.229089
6.91 0.229906
6.92 0.230712
6.93 0.231517
6.94 0.232343
6.95 0.233149
6.96 0.23394
6.97 0.23475
6.98 0.23556
6.99 0.236363
7 0.237148
7.01 0.237934
7.02 0.238771
7.03 0.239591
7.04 0.240367
7.05 0.241158
7.06 0.241983
7.07 0.24277
7.08 0.243585
7.09 0.244374
7.1 0.245178
7.11 0.245962
7.12 0.246702
7.13 0.247562
7.14 0.248345
7.15 0.249111
7.16 0.24993
7.17 0.250764
7.18 0.25157
7.19 0.252314
7.2 0.253124
7.21 0.253943
7.22 0.254741
7.23 0.255587
7.24 0.256384
7.25 0.257192
7.26 0.258015
7.27 0.258854
7.28 0.259757
7.29 0.26058
7.3 0.261407
7.31 0.262175
7.32 0.263022
7.33 0.263871
7.34 0.264703
7.35 0.265516
7.36 0.266354
7.37 0.267217
7.38 0.268049
7.39 0.268845
7.4 0.26967
7.41 0.270489
7.42 0.271344
7.43 0.272154
7.44 0.272976
7.45 0.273804
7.46 0.274602
7.47 0.275476
7.48 0.276292
7.49 0.277123
7.5 0.277952
7.51 0.278766
7.52 0.279625
7.53 0.280474
7.54 0.281317
7.55 0.282182
7.56 0.282993
7.57 0.283843
7.58 0.284665
7.59 0.285529
7.6 0.286349
7.61 0.287218
7.62 0.288022
7.63 0.288878
7.64 0.289745
7.65 0.2906
7.66 0.291395
7.67 0.292267
7.68 0.293097
7.69 0.293961
7.7 0.29484
7.71 0.295689
7.72 0.29655
7.73 0.297347
7.74 0.298198
7.75 0.299063
7.76 0.299888
7.77 0.300718
7.78 0.301583
7.79 0.302417
7.8 0.303256
7.81 0.30411
7.82 0.30499
7.83 0.305845
7.84 0.306668
7.85 0.307495
7.86 0.308309
7.87 0.30913
7.88 0.309962
7.89 0.310766
7.9 0.311645
7.91 0.312495
7.92 0.313347
7.93 0.31423
7.94 0.315078
7.95 0.315954
7.96 0.316783
7.97 0.317623
7.98 0.318471
7.99 0.319313
8 0.320193
8.01 0.320994
8.02 0.321885
8.03 0.322754
8.04 0.323652
8.05 0.324485
8.06 0.325339
8.07 0.326201
8.08 0.327037
8.09 0.327903
8.1 0.328763
8.11 0.329628
8.12 0.330474
8.13 0.331352
8.14 0.332217
8.15 0.333097
8.16 0.333972
8.17 0.33481
8.18 0.335664
8.19 0.336513
8.2 0.337406
8.21 0.33827
8.22 0.339124
8.23 0.340002
8.24 0.340931
8.25 0.34182
8.26 0.342708
8.27 0.343545
8.28 0.344397
8.29 0.345256
8.3 0.346147
8.31 0.346993
8.32 0.347851
8.33 0.348708
8.34 0.34953
8.35 0.350401
8.36 0.351267
8.37 0.352166
8.38 0.353024
8.39 0.353873
8.4 0.354703
8.41 0.355563
8.42 0.356343
8.43 0.357155
8.44 0.357994
8.45 0.358866
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33.91 0.999012
33.92 0.999013
33.93 0.999018
33.94 0.99902
33.95 0.999022
33.96 0.999028
33.97 0.999031
33.98 0.999032
33.99 0.999035
34 0.999039
34.01 0.999042
34.02 0.999046
34.03 0.999048
34.04 0.999056
34.05 0.999062
34.06 0.999063
34.07 0.999067
34.08 0.99907
34.09 0.999072
34.1 0.999073
34.11 0.999079
34.12 0.99908
34.13 0.999083
34.14 0.999083
34.15 0.99909
34.16 0.999091
34.17 0.999093
34.18 0.999096
34.19 0.999097
34.2 0.999101
34.21 0.999103
34.22 0.999106
34.23 0.999109
34.24 0.999112
34.25 0.999113
34.26 0.999115
34.27 0.999116
34.28 0.999121
34.29 0.999124
34.3 0.999126
34.31 0.99913
34.32 0.999131
34.33 0.999133
34.34 0.999135
34.35 0.999135
34.36 0.999138
34.37 0.999142
34.38 0.999144
34.39 0.999152
34.4 0.999154
34.41 0.999157
34.42 0.999162
34.43 0.999162
34.44 0.999165
34.45 0.999166
34.46 0.99917
34.47 0.99917
34.48 0.999173
34.49 0.999175
34.5 0.999178
34.51 0.99918
34.52 0.999183
34.53 0.999186
34.54 0.99919
34.55 0.999193
34.56 0.999194
34.57 0.999198
34.58 0.9992
34.59 0.999204
34.6 0.999209
34.61 0.999213
34.62 0.999215
34.63 0.999216
34.64 0.99922
34.65 0.99922
34.66 0.999223
34.67 0.999223
34.68 0.999225
34.69 0.999228
34.7 0.999229
34.71 0.999232
34.72 0.999236
34.73 0.999239
34.74 0.999241
34.75 0.999243
34.76 0.999248
34.77 0.999253
34.78 0.999258
34.79 0.99926
34.8 0.99926
34.81 0.999262
34.82 0.999262
34.83 0.999264
34.84 0.999265
34.85 0.999267
34.86 0.999268
34.87 0.99927
34.88 0.999273
34.89 0.999273
34.9 0.99928
34.91 0.999282
34.92 0.999282
34.93 0.999283
34.94 0.999286
34.95 0.999291
34.96 0.999295
34.97 0.999296
34.98 0.999297
34.99 0.999299
35 0.999301
# Data from http://onlinelibrary.wiley.com/doi/10.1111/jsm.12244/abstract
stats = read.csv("herbenick_hist.csv", header=T)
x = seq(1, 26, 1)
len_x = dnorm(x, 14.15, 2.66)
girth_x = dnorm(x, 12.23, 2.23)
hung_len = dnorm(x, 14.63, 2.11)
hung_girth = dnorm(x, 11.86, 1.37)
# convert cm to in
x = x * 0.393701
plot(stats[,1], stats[,2]/100, type="l", col="blue", xlim = c(0,29), ylim=c(0,.3), xlab="Inches", ylab="Percent", main="Penis measurements in Herbenick et al vs hungfun charts")
lines(x,len_x, type="l", lty=2, col="blue")
lines(x,hung_len, type="l", lty=3, col="blue")
lines(stats[,1],stats[,3]/100, type="l", col="red")
lines(x, girth_x, type="l", col="red", lty=2)
lines(x,hung_girth, type="l", lty=3, col="red")
legend("topright", c("observed length", "fit length", "hungfun length", "observed girth", "fit girth", "hungfun girth"), col=c(rep("blue", 3), rep("red", 3)), lty = c(1,2,3,1,2,3))
length girth percentile
2 2 3.32643217382245e-06
2 2.1 3.91335604821297e-06
2 2.2 5.32841389477845e-06
2 2.3 8.6244994236262e-06
2 2.4 1.60423544989241e-05
2 2.5 3.21723196836654e-05
2 2.6 6.60629597408757e-05
2 2.7 0.000134869597320453
2 2.8 0.00026985769986676
2 2.9 0.000525765453806892
2 3 0.000994579496123804
2 3.1 0.00182452956232027
2 3.2 0.00324437579753345
2 3.3 0.00559169178690866
2 3.4 0.00934180923979944
2 3.5 0.0151316001015954
2 3.6 0.0237698701636868
2 3.7 0.0362246901360261
2 3.8 0.0535785285846573
2 3.9 0.0769454517663223
2 4 0.107351202635543
2 4.1 0.145585965220638
2 4.2 0.192049227495453
2 4.3 0.246613674783241
2 4.4 0.308537627283727
2 4.5 0.376451185588277
2 4.6 0.448429761968168
2 4.7 0.522152082473226
2 4.8 0.595121979452526
2 4.9 0.66491909383451
2 5 0.729436990369566
2 5.1 0.787070082358
2 5.2 0.836822319511095
2 5.3 0.878327495686041
2 5.4 0.911788643717757
2 5.5 0.937857880095829
2 5.6 0.957485364627555
2 5.7 0.971766074551518
2 5.8 0.981807230814363
2 5.9 0.988630089512672
2 6 0.993110292550239
2 6.1 0.995953297542959
2 6.2 0.997696733868332
2 6.3 0.998729930616227
2 6.4 0.99932163987882
2 6.5 0.999649117798533
2 6.6 0.999824265286132
2 6.7 0.99991479141443
2 6.8 0.999960007403315
2 6.9 0.999981832595431
2 7 0.999992013162518
2 7.1 0.999996602326875
2 7.2 0.999998601465406
2 7.3 0.999999443053706
2 7.4 0.999999785430161
2 7.5 0.999999920033357
2 7.6 0.999999971172566
2 7.7 0.999999989948419
2 7.8 0.999999996610228
2 7.9 0.999999998894414
2 8 0.999999999651277
2.1 2 5.55483041586591e-06
2.1 2.1 6.14043772972916e-06
2.1 2.2 7.55301610877446e-06
2.1 2.3 1.08446300853826e-05
2.1 2.4 1.82547629655749e-05
2.1 2.5 3.43719577091672e-05
2.1 2.6 6.82423743805227e-05
2.1 2.7 0.000137018344006368
2.1 2.8 0.000271961911823881
2.1 2.9 0.000527807736486197
2.1 3 0.000996539312504652
2.1 3.1 0.00182638422117687
2.1 3.2 0.00324610204970488
2.1 3.3 0.00559326789147585
2.1 3.4 0.0093432172192075
2.1 3.5 0.0151328278080514
2.1 3.6 0.0237709127677597
2.1 3.7 0.0362255507377344
2.1 3.8 0.0535792178199855
2.1 3.9 0.0769459864912337
2.1 4 0.107351603955052
2.1 4.1 0.145586256240901
2.1 4.2 0.192049431187402
2.1 4.3 0.246613812265596
2.1 4.4 0.308537716696535
2.1 4.5 0.376451241581405
2.1 4.6 0.448429795711934
2.1 4.7 0.522152102032435
2.1 4.8 0.595121990352158
2.1 4.9 0.664919099671697
2.1 5 0.72943699337271
2.1 5.1 0.787070083841875
2.1 5.2 0.836822320215059
2.1 5.3 0.878327496006618
2.1 5.4 0.911788643857861
2.1 5.5 0.937857880154582
2.1 5.6 0.957485364651191
2.1 5.7 0.971766074560639
2.1 5.8 0.981807230817739
2.1 5.9 0.98863008951387
2.1 6 0.993110292550647
2.1 6.1 0.995953297543092
2.1 6.2 0.997696733868374
2.1 6.3 0.998729930616239
2.1 6.4 0.999321639878824
2.1 6.5 0.999649117798534
2.1 6.6 0.999824265286132
2.1 6.7 0.99991479141443
2.1 6.8 0.999960007403315
2.1 6.9 0.999981832595431
2.1 7 0.999992013162518
2.1 7.1 0.999996602326875
2.1 7.2 0.999998601465406
2.1 7.3 0.999999443053706
2.1 7.4 0.999999785430161
2.1 7.5 0.999999920033357
2.1 7.6 0.999999971172566
2.1 7.7 0.999999989948419
2.1 7.8 0.999999996610228
2.1 7.9 0.999999998894414
2.1 8 0.999999999651277
2.2 2 9.3435874343184e-06
2.2 2.1 9.92735793625688e-06
2.2 2.2 1.13364319672682e-05
2.2 2.3 1.46216437029167e-05
2.2 2.4 2.20205760338432e-05
2.2 2.5 3.81190066113257e-05
2.2 2.6 7.19593208212688e-05
2.2 2.7 0.000140689046203679
2.2 2.8 0.000275564584658494
2.2 2.9 0.000531314575614061
2.2 3 0.000999916873987261
2.2 3.1 0.00182959478440792
2.2 3.2 0.00324910603504824
2.2 3.3 0.00559602717386221
2.2 3.4 0.00934569892801396
2.2 3.5 0.0151350080076411
2.2 3.6 0.0237727793452653
2.2 3.7 0.0362271049258565
2.2 3.8 0.0535804740402103
2.2 3.9 0.076946970550235
2.2 4 0.107352349964949
2.2 4.1 0.14558680286678
2.2 4.2 0.192049817895203
2.2 4.3 0.24661407614801
2.2 4.4 0.30853789024271
2.2 4.5 0.376451351503863
2.2 4.6 0.448429862724329
2.2 4.7 0.522152141331914
2.2 4.8 0.595122012512533
2.2 4.9 0.664919111681823
2.2 5 0.729436999626479
2.2 5.1 0.787070086969556
2.2 5.2 0.836822321717054
2.2 5.3 0.878327496699043
2.2 5.4 0.911788644164227
2.2 5.5 0.937857880284655
2.2 5.6 0.957485364704174
2.2 5.7 0.971766074581342
2.2 5.8 0.981807230825497
2.2 5.9 0.988630089516658
2.2 6 0.993110292551608
2.2 6.1 0.995953297543409
2.2 6.2 0.997696733868474
2.2 6.3 0.99872993061627
2.2 6.4 0.999321639878833
2.2 6.5 0.999649117798536
2.2 6.6 0.999824265286133
2.2 6.7 0.999914791414431
2.2 6.8 0.999960007403315
2.2 6.9 0.999981832595431
2.2 7 0.999992013162518
2.2 7.1 0.999996602326875
2.2 7.2 0.999998601465406
2.2 7.3 0.999999443053706
2.2 7.4 0.999999785430161
2.2 7.5 0.999999920033357
2.2 7.6 0.999999971172566
2.2 7.7 0.999999989948419
2.2 7.8 0.999999996610228
2.2 7.9 0.999999998894414
2.2 8 0.999999999651277
2.3 2 1.56924351946142e-05
2.3 2.1 1.62736896968108e-05
2.3 2.2 1.76779010216954e-05
2.3 2.3 2.09541130631319e-05
2.3 2.4 2.83370954224926e-05
2.3 2.5 4.44084568462788e-05
2.3 2.6 7.82047792086127e-05
2.3 2.7 0.00014686604211267
2.3 2.8 0.000281639553347812
2.3 2.9 0.000537243943884991
2.3 3 0.00100564727004593
2.3 3.1 0.00183506480170348
2.3 3.2 0.00325424976360011
2.3 3.3 0.00560077935704828
2.3 3.4 0.00935000118052842
2.3 3.5 0.0151388151604546
2.3 3.6 0.0237760647951129
2.3 3.7 0.0362298639494547
2.3 3.8 0.0535827243947102
2.3 3.9 0.0769487502344862
2.3 4 0.107353712605384
2.3 4.1 0.145587811648309
2.3 4.2 0.192050539160724
2.3 4.3 0.246614573707694
2.3 4.4 0.308538221125304
2.3 4.5 0.376451563465685
2.3 4.6 0.448429993436286
2.3 4.7 0.522152218885635
2.3 4.8 0.595122056761873
2.3 4.9 0.664919135950272
2.3 5 0.729437012415745
2.3 5.1 0.787070093443589
2.3 5.2 0.836822324864107
2.3 5.3 0.878327498167705
2.3 5.4 0.911788644822083
2.3 5.5 0.937857880567431
2.3 5.6 0.957485364820796
2.3 5.7 0.971766074627481
2.3 5.8 0.981807230843006
2.3 5.9 0.98863008952303
2.3 6 0.993110292553832
2.3 6.1 0.995953297544154
2.3 6.2 0.997696733868713
2.3 6.3 0.998729930616343
2.3 6.4 0.999321639878854
2.3 6.5 0.999649117798542
2.3 6.6 0.999824265286134
2.3 6.7 0.999914791414431
2.3 6.8 0.999960007403315
2.3 6.9 0.999981832595431
2.3 7 0.999992013162518
2.3 7.1 0.999996602326875
2.3 7.2 0.999998601465406
2.3 7.3 0.999999443053706
2.3 7.4 0.999999785430161
2.3 7.5 0.999999920033357
2.3 7.6 0.999999971172566
2.3 7.7 0.999999989948419
2.3 7.8 0.999999996610228
2.3 7.9 0.999999998894414
2.3 8 0.999999999651277
2.4 2 2.61779286231389e-05
2.4 2.1 2.67557995299317e-05
2.4 2.2 2.81533860838623e-05
2.4 2.3 3.1417177441484e-05
2.4 2.4 3.87778599197919e-05
2.4 2.5 5.48108822232551e-05
2.4 2.6 8.85440849548447e-05
2.4 2.7 0.000157105837196414
2.4 2.8 0.000291729118050199
2.4 2.9 0.000547116323987185
2.4 3 0.00101521898471868
2.4 3.1 0.00184423793108568
2.4 3.2 0.00326291690241332
2.4 3.3 0.00560883139401913
2.4 3.4 0.00935733718103648
2.4 3.5 0.0151453529700191
2.4 3.6 0.0237817505606648
2.4 3.7 0.036234678749706
2.4 3.8 0.0535866866382626
2.4 3.9 0.0769519133262552
2.4 4 0.107356158367415
2.4 4.1 0.145589640826807
2.4 4.2 0.192051860824688
2.4 4.3 0.246615495345437
2.4 4.4 0.308538840829219
2.4 4.5 0.376451964937648
2.4 4.6 0.448430243862658
2.4 4.7 0.522152369201236
2.4 4.8 0.595122143539045
2.4 4.9 0.664919184110766
2.4 5 0.729437038101432
2.4 5.1 0.787070106603648
2.4 5.2 0.836822331339413
2.4 5.3 0.878327501226734
2.4 5.4 0.911788646209239
2.4 5.5 0.937857881171095
2.4 5.6 0.957485365072862
2.4 5.7 0.971766074728455
2.4 5.8 0.981807230881804
2.4 5.9 0.988630089537328
2.4 6 0.993110292558885
2.4 6.1 0.995953297545866
2.4 6.2 0.997696733869269
2.4 6.3 0.998729930616517
2.4 6.4 0.999321639878906
2.4 6.5 0.999649117798557
2.4 6.6 0.999824265286138
2.4 6.7 0.999914791414432
2.4 6.8 0.999960007403315
2.4 6.9 0.999981832595431
2.4 7 0.999992013162518
2.4 7.1 0.999996602326875
2.4 7.2 0.999998601465406
2.4 7.3 0.999999443053706
2.4 7.4 0.999999785430161
2.4 7.5 0.999999920033357
2.4 7.6 0.999999971172566
2.4 7.7 0.999999989948419
2.4 7.8 0.999999996610228
2.4 7.9 0.999999998894414
2.4 8 0.999999999651277
2.5 2 4.32458239528755e-05
2.5 2.1 4.38192273209959e-05
2.5 2.2 4.52079528139304e-05
2.5 2.3 4.84549141253066e-05
2.5 2.4 5.57849863290771e-05
2.5 2.5 7.17646958122709e-05
2.5 2.6 0.000105408982780331
2.5 2.7 0.00017382872837135
2.5 2.8 0.00030823482835951
2.5 2.9 0.000563303968105
2.5 3 0.00103096056538377
2.5 3.1 0.00185938046729284
2.5 3.2 0.00327728905891755
2.5 3.3 0.00562225483928591
2.5 3.4 0.00936964184100286
2.5 3.5 0.0151563942238022
2.5 3.6 0.0237914255875965
2.5 3.7 0.0362429390053831
2.5 3.8 0.0535935439728741
2.5 3.9 0.0769574384780175
2.5 4 0.107360472145833
2.5 4.1 0.145592899791604
2.5 4.2 0.19205424024676
2.5 4.3 0.246617172469252
2.5 4.4 0.308539980958819
2.5 4.5 0.376452711878656
2.5 4.6 0.448430715117234
2.5 4.7 0.522152655353023
2.5 4.8 0.595122310678086
2.5 4.9 0.664919277974638
2.5 5 0.729437088763404
2.5 5.1 0.78707013287452
2.5 5.2 0.836822344423399
2.5 5.3 0.878327507483635
2.5 5.4 0.911788649081517
2.5 5.5 0.937857882436553
2.5 5.6 0.957485365607844
2.5 5.7 0.971766074945439
2.5 5.8 0.981807230966225
2.5 5.9 0.98863008956883
2.5 6 0.993110292570158
2.5 6.1 0.995953297549734
2.5 6.2 0.997696733870542
2.5 6.3 0.998729930616918
2.5 6.4 0.999321639879027
2.5 6.5 0.999649117798592
2.5 6.6 0.999824265286148
2.5 6.7 0.999914791414435
2.5 6.8 0.999960007403316
2.5 6.9 0.999981832595431
2.5 7 0.999992013162518
2.5 7.1 0.999996602326875
2.5 7.2 0.999998601465406
2.5 7.3 0.999999443053706
2.5 7.4 0.999999785430161
2.5 7.5 0.999999920033357
2.5 7.6 0.999999971172566
2.5 7.7 0.999999989948419
2.5 7.8 0.999999996610228
2.5 7.9 0.999999998894414
2.5 8 0.999999999651277
2.6 2 7.06280867002196e-05
2.6 2.1 7.11956987131668e-05
2.6 2.2 7.25727876994542e-05
2.6 2.3 7.57973593694672e-05
2.6 2.4 8.3086178723768e-05
2.6 2.5 9.89931029816704e-05
2.6 2.6 0.000132514415429164
2.6 2.7 0.00020073519916386
2.6 2.8 0.000334833046070404
2.6 2.9 0.000589444857521104
2.6 3 0.00105645172636748
2.6 3.1 0.00188398769613018
2.6 3.2 0.0033007447204435
2.6 3.3 0.00564427387671229
2.6 3.4 0.0093899446288328
2.6 3.5 0.0151747336455701
2.6 3.6 0.0238076141813773
2.6 3.7 0.0362568713156531
2.6 3.8 0.0536052097333626
2.6 3.9 0.0769669239174214
2.6 4 0.107367949143528
2.6 4.1 0.145598605124465
2.6 4.2 0.192058449042776
2.6 4.3 0.246620170732016
2.6 4.4 0.308542041552864
2.6 4.5 0.376454076959391
2.6 4.6 0.448431586177791
2.6 4.7 0.522153190392098
2.6 4.8 0.595122626854134
2.6 4.9 0.664919457641893
2.6 5 0.729437186898006
2.6 5.1 0.787070184377007
2.6 5.2 0.836822370385879
2.6 5.3 0.878327520051223
2.6 5.4 0.911788654921827
2.6 5.5 0.937857885041513
2.6 5.6 0.957485366722808
2.6 5.7 0.971766075403305
2.6 5.8 0.981807231146595
2.6 5.9 0.988630089636982
2.6 6 0.993110292594853
2.6 6.1 0.995953297558315
2.6 6.2 0.997696733873401
2.6 6.3 0.998729930617831
2.6 6.4 0.999321639879307
2.6 6.5 0.999649117798674
2.6 6.6 0.999824265286171
2.6 6.7 0.999914791414441
2.6 6.8 0.999960007403317
2.6 6.9 0.999981832595431
2.6 7 0.999992013162519
2.6 7.1 0.999996602326875
2.6 7.2 0.999998601465406
2.6 7.3 0.999999443053706
2.6 7.4 0.999999785430161
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9.4 7.7 0.999999999735194
9.4 7.8 0.999999999889728
9.4 7.9 0.999999999955901
9.4 8 0.999999999983066
9.5 2 0.999996697320512
9.5 2.1 0.999996697320512
9.5 2.2 0.999996697320512
9.5 2.3 0.999996697320512
9.5 2.4 0.999996697320512
9.5 2.5 0.999996697320512
9.5 2.6 0.999996697320512
9.5 2.7 0.999996697320512
9.5 2.8 0.999996697320513
9.5 2.9 0.999996697320514
9.5 3 0.999996697320518
9.5 3.1 0.999996697320533
9.5 3.2 0.999996697320581
9.5 3.3 0.99999669732073
9.5 3.4 0.999996697321174
9.5 3.5 0.999996697322444
9.5 3.6 0.999996697325921
9.5 3.7 0.999996697335036
9.5 3.8 0.999996697357925
9.5 3.9 0.999996697412975
9.5 4 0.999996697539786
9.5 4.1 0.999996697819581
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9.5 4.3 0.999996699607746
9.5 4.4 0.999996701928249
9.5 4.5 0.99999670623755
9.5 4.6 0.999996713902807
9.5 4.7 0.999996726962867
9.5 4.8 0.999996748276936
9.5 4.9 0.999996781596125
9.5 5 0.999996831488443
9.5 5.1 0.999996903051466
9.5 5.2 0.999997001376508
9.5 5.3 0.99999713078566
9.5 5.4 0.999997293939154
9.5 5.5 0.999997490983372
9.5 5.6 0.999997718950683
9.5 5.7 0.999997971606282
9.5 5.8 0.999998239855788
9.5 5.9 0.999998512696445
9.5 6 0.999998778552289
9.5 6.1 0.999999026726964
9.5 6.2 0.999999248674525
9.5 6.3 0.99999943884053
9.5 6.4 0.999999594944277
9.5 6.5 0.99999971771661
9.5 6.6 0.999999810229814
9.5 6.7 0.999999877023092
9.5 6.8 0.999999923229051
9.5 6.9 0.999999953856465
9.5 7 0.999999973309234
9.5 7.1 0.999999985148465
9.5 7.2 0.99999999205324
9.5 7.3 0.999999995912228
9.5 7.4 0.999999997979081
9.5 7.5 0.99999999903998
9.5 7.6 0.999999999561874
9.5 7.7 0.999999999807941
9.5 7.8 0.999999999919141
9.5 7.9 0.999999999967309
9.5 8 0.999999999987309
9.6 2 0.999998140569721
9.6 2.1 0.999998140569721
9.6 2.2 0.999998140569721
9.6 2.3 0.999998140569721
9.6 2.4 0.999998140569721
9.6 2.5 0.999998140569721
9.6 2.6 0.999998140569721
9.6 2.7 0.999998140569721
9.6 2.8 0.999998140569721
9.6 2.9 0.999998140569722
9.6 3 0.999998140569724
9.6 3.1 0.999998140569729
9.6 3.2 0.999998140569749
9.6 3.3 0.999998140569809
9.6 3.4 0.999998140569992
9.6 3.5 0.999998140570521
9.6 3.6 0.999998140571987
9.6 3.7 0.99999814057588
9.6 3.8 0.999998140585781
9.6 3.9 0.999998140609896
9.6 4 0.999998140666155
9.6 4.1 0.999998140791862
9.6 4.2 0.999998141060897
9.6 4.3 0.999998141612384
9.6 4.4 0.999998142695178
9.6 4.5 0.99999814473148
9.6 4.6 0.999998148399472
9.6 4.7 0.99999815472808
9.6 4.8 0.999998165186959
9.6 4.9 0.999998181743259
9.6 5 0.999998206847477
9.6 5.1 0.999998243309403
9.6 5.2 0.999998294037254
9.6 5.3 0.999998361641176
9.6 5.4 0.999998447943146
9.6 5.5 0.999998553478499
9.6 5.6 0.999998677104247
9.6 5.7 0.99999881583065
9.6 5.8 0.999998964956978
9.6 5.9 0.999999118524923
9.6 6 0.999999270021993
9.6 6.1 0.999999413198566
9.6 6.2 0.99999954283013
9.6 6.3 0.999999655271982
9.6 6.4 0.999999748711676
9.6 6.5 0.999999823104174
9.6 6.6 0.999999879849464
9.6 6.7 0.999999921320271
9.6 6.8 0.99999995035894
9.6 6.9 0.999999969841347
9.6 7 0.999999982365571
9.6 7.1 0.999999990080159
9.6 7.2 0.999999994633606
9.6 7.3 0.999999997209014
9.6 7.4 0.99999999860488
9.6 7.5 0.999999999329895
9.6 7.6 0.999999999690783
9.6 7.7 0.999999999862944
9.6 7.8 0.999999999941657
9.6 7.9 0.999999999976151
9.6 8 0.999999999990639
9.7 2 0.999998967658773
9.7 2.1 0.999998967658773
9.7 2.2 0.999998967658773
9.7 2.3 0.999998967658773
9.7 2.4 0.999998967658773
9.7 2.5 0.999998967658773
9.7 2.6 0.999998967658773
9.7 2.7 0.999998967658773
9.7 2.8 0.999998967658773
9.7 2.9 0.999998967658773
9.7 3 0.999998967658773
9.7 3.1 0.999998967658776
9.7 3.2 0.999998967658783
9.7 3.3 0.999998967658807
9.7 3.4 0.999998967658881
9.7 3.5 0.999998967659098
9.7 3.6 0.999998967659705
9.7 3.7 0.999998967661338
9.7 3.8 0.999998967665544
9.7 3.9 0.99999896767592
9.7 4 0.999998967700435
9.7 4.1 0.99999896775591
9.7 4.2 0.999998967876146
9.7 4.3 0.999998968125748
9.7 4.4 0.999998968622044
9.7 4.5 0.999998969567226
9.7 4.6 0.999998971291377
9.7 4.7 0.999998974303854
9.7 4.8 0.999998979345403
9.7 4.9 0.999998987427057
9.7 5 0.999998999836039
9.7 5.1 0.999999018086577
9.7 5.2 0.999999043797819
9.7 5.3 0.999999078494075
9.7 5.4 0.999999123343705
9.7 5.5 0.999999178877399
9.7 5.6 0.999999244746332
9.7 5.7 0.999999319586754
9.7 5.8 0.999999401043818
9.7 5.9 0.999999485974354
9.7 6 0.999999570803966
9.7 6.1 0.999999651972145
9.7 6.2 0.999999726374273
9.7 6.3 0.999999791710339
9.7 6.4 0.999999846676559
9.7 6.5 0.999999890978382
9.7 6.6 0.999999925187205
9.7 6.7 0.999999950494973
9.7 6.8 0.999999968433121
9.7 6.9 0.999999980615126
9.7 7 0.999999988541729
9.7 7.1 0.999999993483621
9.7 7.2 0.999999996435836
9.7 7.3 0.999999998125744
9.7 7.4 0.999999999052683
9.7 7.5 0.999999999539903
9.7 7.6 0.999999999785316
9.7 7.7 0.99999999990378
9.7 7.8 0.999999999958583
9.7 7.9 0.999999999982881
9.7 8 0.999999999993206
9.8 2 0.999999434819735
9.8 2.1 0.999999434819735
9.8 2.2 0.999999434819735
9.8 2.3 0.999999434819735
9.8 2.4 0.999999434819735
9.8 2.5 0.999999434819735
9.8 2.6 0.999999434819735
9.8 2.7 0.999999434819736
9.8 2.8 0.999999434819736
9.8 2.9 0.999999434819736
9.8 3 0.999999434819736
9.8 3.1 0.999999434819737
9.8 3.2 0.99999943481974
9.8 3.3 0.999999434819749
9.8 3.4 0.999999434819778
9.8 3.5 0.999999434819865
9.8 3.6 0.999999434820112
9.8 3.7 0.999999434820785
9.8 3.8 0.99999943482254
9.8 3.9 0.999999434826925
9.8 4 0.999999434837417
9.8 4.1 0.999999434861463
9.8 4.2 0.999999434914243
9.8 4.3 0.999999435025206
9.8 4.4 0.999999435248645
9.8 4.5 0.999999435679586
9.8 4.6 0.999999436475667
9.8 4.7 0.999999437884247
9.8 4.8 0.999999440271466
9.8 4.9 0.999999444146667
9.8 5 0.999999450172128
9.8 5.1 0.999999459146099
9.8 5.2 0.999999471948195
9.8 5.3 0.999999489441978
9.8 5.4 0.999999512339939
9.8 5.5 0.99999954104938
9.8 5.6 0.999999575529773
9.8 5.7 0.99999961519811
9.8 5.8 0.99999965891459
9.8 5.9 0.999999705065582
9.8 6 0.999999751737657
9.8 6.1 0.999999796952307
9.8 6.2 0.999999838914028
9.8 6.3 0.999999876220645
9.8 6.4 0.999999907995499
9.8 6.5 0.999999933922568
9.8 6.6 0.999999954190192
9.8 6.7 0.999999969369067
9.8 6.8 0.99999998026017
9.8 6.9 0.999999987747179
9.8 7 0.999999992678441
9.8 7.1 0.999999995790378
9.8 7.2 0.999999997672018
9.8 7.3 0.999999998762168
9.8 7.4 0.999999999367357
9.8 7.5 0.999999999689288
9.8 7.6 0.999999999853391
9.8 7.7 0.999999999933552
9.8 7.8 0.999999999971076
9.8 7.9 0.99999999998791
9.8 8 0.999999999995148
9.9 2 0.999999694886073
9.9 2.1 0.999999694886073
9.9 2.2 0.999999694886073
9.9 2.3 0.999999694886073
9.9 2.4 0.999999694886073
9.9 2.5 0.999999694886073
9.9 2.6 0.999999694886073
9.9 2.7 0.999999694886073
9.9 2.8 0.999999694886073
9.9 2.9 0.999999694886073
9.9 3 0.999999694886073
9.9 3.1 0.999999694886073
9.9 3.2 0.999999694886074
9.9 3.3 0.999999694886078
9.9 3.4 0.999999694886089
9.9 3.5 0.999999694886124
9.9 3.6 0.999999694886222
9.9 3.7 0.999999694886494
9.9 3.8 0.999999694887214
9.9 3.9 0.999999694889034
9.9 4 0.999999694893445
9.9 4.1 0.999999694903681
9.9 4.2 0.999999694926438
9.9 4.3 0.99999969497489
9.9 4.4 0.999999695073698
9.9 4.5 0.99999969526669
9.9 4.6 0.999999695627739
9.9 4.7 0.999999696274691
9.9 4.8 0.999999697385041
9.9 4.9 0.999999699210342
9.9 5 0.999999702084418
9.9 5.1 0.999999706419078
9.9 5.2 0.999999712681013
9.9 5.3 0.999999721345896
9.9 5.4 0.999999732830641
9.9 5.5 0.999999747411689
9.9 5.6 0.999999765144158
9.9 5.7 0.99999978580116
9.9 5.8 0.99999980885205
9.9 5.9 0.99999983349175
9.9 6 0.999999858721653
9.9 6.1 0.999999883469283
9.9 6.2 0.99999990672315
9.9 6.3 0.999999927654933
9.9 6.4 0.999999945704756
9.9 6.5 0.999999960615591
9.9 6.6 0.999999972416081
9.9 6.7 0.99999998136302
9.9 6.8 0.999999987861816
9.9 6.9 0.999999992384364
9.9 7 0.999999995399688
9.9 7.1 0.999999997325855
9.9 7.2 0.999999998504743
9.9 7.3 0.999999999196065
9.9 7.4 0.999999999584507
9.9 7.5 0.99999999979364
9.9 7.6 0.99999999990153
9.9 7.7 0.999999999954866
9.9 7.8 0.999999999980132
9.9 7.9 0.999999999991601
9.9 8 0.999999999996591
10 2 0.999999837579856
10 2.1 0.999999837579856
10 2.2 0.999999837579856
10 2.3 0.999999837579856
10 2.4 0.999999837579856
10 2.5 0.999999837579856
10 2.6 0.999999837579856
10 2.7 0.999999837579856
10 2.8 0.999999837579856
10 2.9 0.999999837579856
10 3 0.999999837579856
10 3.1 0.999999837579856
10 3.2 0.999999837579857
10 3.3 0.999999837579858
10 3.4 0.999999837579863
10 3.5 0.999999837579876
10 3.6 0.999999837579915
10 3.7 0.999999837580023
10 3.8 0.999999837580312
10 3.9 0.999999837581054
10 4 0.999999837582875
10 4.1 0.999999837587156
10 4.2 0.999999837596793
10 4.3 0.999999837617573
10 4.4 0.99999983766049
10 4.5 0.999999837745383
10 4.6 0.999999837906223
10 4.7 0.99999983819809
10 4.8 0.999999838705382
10 4.9 0.999999839549904
10 5 0.999999840896538
10 5.1 0.999999842953262
10 5.2 0.999999845962069
10 5.3 0.999999850178138
10 5.4 0.999999855836884
10 5.5 0.999999863111928
10 5.6 0.999999872070899
10 5.7 0.999999882638878
10 5.8 0.999999894579899
10 5.9 0.999999907504329
10 6 0.999999920904383
10 6.1 0.99999993421297
10 6.2 0.999999946874697
10 6.3 0.999999958414411
10 6.4 0.999999968489389
10 6.5 0.999999976915868
10 6.6 0.999999983667482
10 6.7 0.999999988849932
10 6.8 0.999999992660906
10 6.9 0.999999995345739
10 7 0.99999999715786
10 7.1 0.999999998329661
10 7.2 0.999999999055642
10 7.3 0.999999999486578
10 7.4 0.999999999731666
10 7.5 0.999999999865223
10 7.6 0.999999999934959
10 7.7 0.99999999996985
10 7.8 0.999999999986577
10 7.9 0.999999999994261
10 8 0.99999999999764
volume percentile
0 0
0.01 0
0.02 0
0.03 0
0.04 0
0.05 0
0.06 0
0.07 0
0.08 0
0.09 0
0.1 0
0.11 0
0.12 0
0.13 0
0.14 0
0.15 0
0.16 0
0.17 0
0.18 0
0.19 0
0.2 0
0.21 0
0.22 0
0.23 0
0.24 0
0.25 0
0.26 0
0.27 0
0.28 0
0.29 0
0.3 0
0.31 0
0.32 0
0.33 0
0.34 0
0.35 0
0.36 0
0.37 0
0.38 0
0.39 0
0.4 0
0.41 0
0.42 0
0.43 0
0.44 0
0.45 0
0.46 0
0.47 0
0.48 0
0.49 0
0.5 0
0.51 0
0.52 0
0.53 0
0.54 0
0.55 0
0.56 0
0.57 0
0.58 0
0.59 0
0.6 0
0.61 0
0.62 0
0.63 0
0.64 0
0.65 0
0.66 0
0.67 0
0.68 0
0.69 0
0.7 0
0.71 0
0.72 0
0.73 0
0.74 0
0.75 0
0.76 0
0.77 0
0.78 0
0.79 0
0.8 0
0.81 0
0.82 0
0.83 0
0.84 0
0.85 0
0.86 0
0.87 0
0.88 0
0.89 0
0.9 0
0.91 0
0.92 0
0.93 0
0.94 0
0.95 0
0.96 0
0.97 0
0.98 0
0.99 0
1 0
1.01 0
1.02 0
1.03 0
1.04 0
1.05 0
1.06 0
1.07 0
1.08 0
1.09 0
1.1 0
1.11 0
1.12 0
1.13 0
1.14 0
1.15 0
1.16 0
1.17 0
1.18 0
1.19 0
1.2 0
1.21 0
1.22 0
1.23 0
1.24 2e-06
1.25 2e-06
1.26 2e-06
1.27 2e-06
1.28 2e-06
1.29 2e-06
1.3 2e-06
1.31 3e-06
1.32 4e-06
1.33 4e-06
1.34 4e-06
1.35 4e-06
1.36 4e-06
1.37 5e-06
1.38 5e-06
1.39 5e-06
1.4 6e-06
1.41 6e-06
1.42 6e-06
1.43 6e-06
1.44 6e-06
1.45 7e-06
1.46 7e-06
1.47 7e-06
1.48 9e-06
1.49 1e-05
1.5 1.3e-05
1.51 1.3e-05
1.52 1.3e-05
1.53 1.3e-05
1.54 1.3e-05
1.55 1.3e-05
1.56 1.3e-05
1.57 1.4e-05
1.58 1.5e-05
1.59 1.5e-05
1.6 1.6e-05
1.61 1.7e-05
1.62 1.8e-05
1.63 1.8e-05
1.64 2e-05
1.65 2.1e-05
1.66 2.1e-05
1.67 2.1e-05
1.68 2.2e-05
1.69 2.2e-05
1.7 2.2e-05
1.71 2.2e-05
1.72 2.2e-05
1.73 2.2e-05
1.74 2.3e-05
1.75 2.5e-05
1.76 2.6e-05
1.77 2.6e-05
1.78 2.6e-05
1.79 2.8e-05
1.8 2.9e-05
1.81 3.1e-05
1.82 3.2e-05
1.83 3.2e-05
1.84 3.6e-05
1.85 3.7e-05
1.86 4e-05
1.87 4.1e-05
1.88 4.3e-05
1.89 4.6e-05
1.9 4.9e-05
1.91 5.1e-05
1.92 5.1e-05
1.93 5.2e-05
1.94 5.7e-05
1.95 6e-05
1.96 6.1e-05
1.97 6.1e-05
1.98 6.4e-05
1.99 6.5e-05
2 6.8e-05
2.01 6.8e-05
2.02 7e-05
2.03 7.5e-05
2.04 7.6e-05
2.05 7.7e-05
2.06 8e-05
2.07 8.2e-05
2.08 8.3e-05
2.09 8.7e-05
2.1 9e-05
2.11 9.1e-05
2.12 9.5e-05
2.13 9.8e-05
2.14 1e-04
2.15 0.000105
2.16 0.000108
2.17 0.000116
2.18 0.000122
2.19 0.000127
2.2 0.000135
2.21 0.000138
2.22 0.000142
2.23 0.00015
2.24 0.000159
2.25 0.000163
2.26 0.000167
2.27 0.000174
2.28 0.000178
2.29 0.000183
2.3 0.000192
2.31 0.000199
2.32 0.000209
2.33 0.000213
2.34 0.000218
2.35 0.000221
2.36 0.000229
2.37 0.000239
2.38 0.000245
2.39 0.000252
2.4 0.000256
2.41 0.000266
2.42 0.000272
2.43 0.000277
2.44 0.000287
2.45 0.00029
2.46 0.000296
2.47 0.000304
2.48 0.000314
2.49 0.000324
2.5 0.000334
2.51 0.000345
2.52 0.000352
2.53 0.00036
2.54 0.000369
2.55 0.000384
2.56 0.00039
2.57 0.000397
2.58 0.00041
2.59 0.000423
2.6 0.000432
2.61 0.000442
2.62 0.000455
2.63 0.000464
2.64 0.000474
2.65 0.000487
2.66 0.000504
2.67 0.00052
2.68 0.000537
2.69 0.000551
2.7 0.000566
2.71 0.000576
2.72 0.000593
2.73 0.000613
2.74 0.000635
2.75 0.000656
2.76 0.00067
2.77 0.000681
2.78 0.000697
2.79 0.00071
2.8 0.000733
2.81 0.000747
2.82 0.000762
2.83 0.000779
2.84 0.000799
2.85 0.000821
2.86 0.000843
2.87 0.00087
2.88 0.000906
2.89 0.000931
2.9 0.00095
2.91 0.000972
2.92 0.001001
2.93 0.001016
2.94 0.001042
2.95 0.001071
2.96 0.001093
2.97 0.001114
2.98 0.001138
2.99 0.001162
3 0.001199
3.01 0.001233
3.02 0.001264
3.03 0.001301
3.04 0.001333
3.05 0.001358
3.06 0.001394
3.07 0.00144
3.08 0.001474
3.09 0.001507
3.1 0.001542
3.11 0.001574
3.12 0.00163
3.13 0.00167
3.14 0.001694
3.15 0.001723
3.16 0.001756
3.17 0.001793
3.18 0.001824
3.19 0.001859
3.2 0.001898
3.21 0.001932
3.22 0.001964
3.23 0.002007
3.24 0.00204
3.25 0.002086
3.26 0.002127
3.27 0.002164
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29.07 0.999956
29.08 0.999956
29.09 0.999956
29.1 0.999956
29.11 0.999957
29.12 0.999957
29.13 0.999957
29.14 0.999957
29.15 0.999957
29.16 0.999957
29.17 0.999958
29.18 0.999958
29.19 0.999958
29.2 0.999958
29.21 0.999959
29.22 0.999959
29.23 0.999959
29.24 0.999961
29.25 0.999961
29.26 0.999961
29.27 0.999961
29.28 0.999961
29.29 0.999961
29.3 0.999961
29.31 0.999963
29.32 0.999963
29.33 0.999964
29.34 0.999965
29.35 0.999965
29.36 0.999965
29.37 0.999966
29.38 0.999966
29.39 0.999966
29.4 0.999966
29.41 0.999966
29.42 0.999967
29.43 0.999967
29.44 0.999968
29.45 0.999968
29.46 0.999968
29.47 0.999968
29.48 0.999968
29.49 0.999969
29.5 0.999969
29.51 0.999969
29.52 0.999969
29.53 0.999969
29.54 0.999969
29.55 0.999969
29.56 0.999969
29.57 0.999969
29.58 0.999969
29.59 0.999969
29.6 0.999969
29.61 0.999969
29.62 0.99997
29.63 0.99997
29.64 0.999971
29.65 0.999971
29.66 0.999971
29.67 0.999971
29.68 0.999971
29.69 0.999971
29.7 0.999971
29.71 0.999971
29.72 0.999971
29.73 0.999972
29.74 0.999972
29.75 0.999972
29.76 0.999972
29.77 0.999972
29.78 0.999972
29.79 0.999972
29.8 0.999972
29.81 0.999972
29.82 0.999972
29.83 0.999972
29.84 0.999972
29.85 0.999972
29.86 0.999972
29.87 0.999973
29.88 0.999973
29.89 0.999973
29.9 0.999973
29.91 0.999973
29.92 0.999973
29.93 0.999973
29.94 0.999973
29.95 0.999973
29.96 0.999973
29.97 0.999973
29.98 0.999973
29.99 0.999973
30 0.999973
30.01 0.999973
30.02 0.999973
30.03 0.999973
30.04 0.999973
30.05 0.999973
30.06 0.999973
30.07 0.999973
30.08 0.999973
30.09 0.999973
30.1 0.999974
30.11 0.999974
30.12 0.999974
30.13 0.999974
30.14 0.999975
30.15 0.999975
30.16 0.999975
30.17 0.999975
30.18 0.999976
30.19 0.999976
30.2 0.999976
30.21 0.999976
30.22 0.999976
30.23 0.999976
30.24 0.999976
30.25 0.999976
30.26 0.999976
30.27 0.999976
30.28 0.999976
30.29 0.999976
30.3 0.999977
30.31 0.999978
30.32 0.999978
30.33 0.999979
30.34 0.999979
30.35 0.999979
30.36 0.999979
30.37 0.999979
30.38 0.999979
30.39 0.999979
30.4 0.99998
30.41 0.999981
30.42 0.999981
30.43 0.999981
30.44 0.999981
30.45 0.999981
30.46 0.999983
30.47 0.999983
30.48 0.999983
30.49 0.999983
30.5 0.999983
30.51 0.999983
30.52 0.999983
30.53 0.999983
30.54 0.999983
30.55 0.999983
30.56 0.999984
30.57 0.999984
30.58 0.999985
30.59 0.999986
30.6 0.999986
30.61 0.999986
30.62 0.999986
30.63 0.999987
30.64 0.999987
30.65 0.999989
30.66 0.999989
30.67 0.999989
30.68 0.99999
30.69 0.99999
30.7 0.99999
30.71 0.99999
30.72 0.99999
30.73 0.99999
30.74 0.99999
30.75 0.99999
30.76 0.99999
30.77 0.99999
30.78 0.99999
30.79 0.99999
30.8 0.99999
30.81 0.99999
30.82 0.99999
30.83 0.99999
30.84 0.99999
30.85 0.99999
30.86 0.99999
30.87 0.99999
30.88 0.99999
30.89 0.99999
30.9 0.99999
30.91 0.99999
30.92 0.999991
30.93 0.999991
30.94 0.999991
30.95 0.999991
30.96 0.999991
30.97 0.999992
30.98 0.999993
30.99 0.999993
31 0.999993
31.01 0.999993
31.02 0.999993
31.03 0.999994
31.04 0.999994
31.05 0.999994
31.06 0.999994
31.07 0.999994
31.08 0.999994
31.09 0.999994
31.1 0.999994
31.11 0.999994
31.12 0.999994
31.13 0.999994
31.14 0.999994
31.15 0.999994
31.16 0.999994
31.17 0.999994
31.18 0.999994
31.19 0.999994
31.2 0.999994
31.21 0.999994
31.22 0.999994
31.23 0.999994
31.24 0.999994
31.25 0.999994
31.26 0.999994
31.27 0.999994
31.28 0.999994
31.29 0.999994
31.3 0.999994
31.31 0.999994
31.32 0.999994
31.33 0.999994
31.34 0.999994
31.35 0.999994
31.36 0.999994
31.37 0.999994
31.38 0.999994
31.39 0.999994
31.4 0.999994
31.41 0.999994
31.42 0.999994
31.43 0.999994
31.44 0.999994
31.45 0.999995
31.46 0.999995
31.47 0.999996
31.48 0.999996
31.49 0.999996
31.5 0.999996
31.51 0.999996
31.52 0.999996
31.53 0.999996
31.54 0.999996
31.55 0.999996
31.56 0.999996
31.57 0.999996
31.58 0.999996
31.59 0.999996
31.6 0.999996
31.61 0.999996
31.62 0.999997
31.63 0.999997
31.64 0.999997
31.65 0.999997
31.66 0.999997
31.67 0.999997
31.68 0.999997
31.69 0.999997
31.7 0.999997
31.71 0.999997
31.72 0.999997
31.73 0.999997
31.74 0.999997
31.75 0.999997
31.76 0.999997
31.77 0.999997
31.78 0.999997
31.79 0.999997
31.8 0.999997
31.81 0.999997
31.82 0.999997
31.83 0.999997
31.84 0.999997
31.85 0.999997
31.86 0.999997
31.87 0.999997
31.88 0.999997
31.89 0.999997
31.9 0.999997
31.91 0.999997
31.92 0.999997
31.93 0.999997
31.94 0.999997
31.95 0.999997
31.96 0.999997
31.97 0.999997
31.98 0.999997
31.99 0.999997
32 0.999997
32.01 0.999997
32.02 0.999997
32.03 0.999997
32.04 0.999997
32.05 0.999997
32.06 0.999997
32.07 0.999997
32.08 0.999997
32.09 0.999997
32.1 0.999997
32.11 0.999997
32.12 0.999997
32.13 0.999997
32.14 0.999997
32.15 0.999997
32.16 0.999997
32.17 0.999997
32.18 0.999997
32.19 0.999997
32.2 0.999997
32.21 0.999997
32.22 0.999997
32.23 0.999997
32.24 0.999997
32.25 0.999997
32.26 0.999997
32.27 0.999997
32.28 0.999997
32.29 0.999997
32.3 0.999997
32.31 0.999997
32.32 0.999997
32.33 0.999997
32.34 0.999997
32.35 0.999997
32.36 0.999997
32.37 0.999997
32.38 0.999997
32.39 0.999997
32.4 0.999997
32.41 0.999997
32.42 0.999997
32.43 0.999997
32.44 0.999997
32.45 0.999997
32.46 0.999997
32.47 0.999997
32.48 0.999997
32.49 0.999997
32.5 0.999997
32.51 0.999997
32.52 0.999997
32.53 0.999997
32.54 0.999997
32.55 0.999997
32.56 0.999997
32.57 0.999997
32.58 0.999997
32.59 0.999997
32.6 0.999997
32.61 0.999997
32.62 0.999997
32.63 0.999997
32.64 0.999997
32.65 0.999997
32.66 0.999997
32.67 0.999997
32.68 0.999997
32.69 0.999997
32.7 0.999997
32.71 0.999997
32.72 0.999997
32.73 0.999997
32.74 0.999997
32.75 0.999997
32.76 0.999997
32.77 0.999997
32.78 0.999997
32.79 0.999997
32.8 0.999997
32.81 0.999997
32.82 0.999997
32.83 0.999997
32.84 0.999997
32.85 0.999997
32.86 0.999997
32.87 0.999997
32.88 0.999997
32.89 0.999997
32.9 0.999997
32.91 0.999997
32.92 0.999998
32.93 0.999998
32.94 0.999998
32.95 0.999998
32.96 0.999998
32.97 0.999998
32.98 0.999998
32.99 0.999998
33 0.999998
33.01 0.999998
33.02 0.999998
33.03 0.999998
33.04 0.999998
33.05 0.999998
33.06 0.999998
33.07 0.999998
33.08 0.999998
33.09 0.999998
33.1 0.999998
33.11 0.999998
33.12 0.999998
33.13 0.999998
33.14 0.999998
33.15 0.999998
33.16 0.999998
33.17 0.999998
33.18 0.999998
33.19 0.999998
33.2 0.999998
33.21 0.999998
33.22 0.999998
33.23 0.999998
33.24 0.999998
33.25 0.999998
33.26 0.999998
33.27 0.999998
33.28 0.999998
33.29 0.999998
33.3 0.999998
33.31 0.999998
33.32 0.999998
33.33 0.999998
33.34 0.999998
33.35 0.999998
33.36 0.999998
33.37 0.999998
33.38 0.999998
33.39 0.999998
33.4 0.999998
33.41 0.999998
33.42 0.999998
33.43 0.999998
33.44 0.999998
33.45 0.999998
33.46 0.999998
33.47 0.999998
33.48 0.999998
33.49 0.999998
33.5 0.999998
33.51 0.999998
33.52 0.999998
33.53 0.999998
33.54 0.999998
33.55 0.999998
33.56 0.999998
33.57 0.999998
33.58 0.999998
33.59 0.999998
33.6 0.999998
33.61 0.999998
33.62 0.999998
33.63 0.999998
33.64 0.999998
33.65 0.999998
33.66 0.999998
33.67 0.999998
33.68 0.999998
33.69 0.999998
33.7 0.999998
33.71 0.999998
33.72 0.999998
33.73 0.999998
33.74 0.999998
33.75 0.999998
33.76 0.999998
33.77 0.999998
33.78 0.999998
33.79 0.999998
33.8 0.999998
33.81 0.999998
33.82 0.999998
33.83 0.999998
33.84 0.999999
33.85 0.999999
33.86 0.999999
33.87 0.999999
33.88 0.999999
33.89 0.999999
33.9 0.999999
33.91 0.999999
33.92 0.999999
33.93 0.999999
33.94 0.999999
33.95 0.999999
33.96 0.999999
33.97 0.999999
33.98 0.999999
33.99 0.999999
34 0.999999
34.01 0.999999
34.02 0.999999
34.03 0.999999
34.04 0.999999
34.05 0.999999
34.06 0.999999
34.07 0.999999
34.08 0.999999
34.09 0.999999
34.1 0.999999
34.11 0.999999
34.12 0.999999
34.13 0.999999
34.14 0.999999
34.15 0.999999
34.16 0.999999
34.17 0.999999
34.18 0.999999
34.19 0.999999
34.2 0.999999
34.21 0.999999
34.22 0.999999
34.23 0.999999
34.24 0.999999
34.25 0.999999
34.26 0.999999
34.27 0.999999
34.28 0.999999
34.29 0.999999
34.3 0.999999
34.31 0.999999
34.32 0.999999
34.33 0.999999
34.34 0.999999
34.35 0.999999
34.36 0.999999
34.37 0.999999
34.38 0.999999
34.39 0.999999
34.4 0.999999
34.41 0.999999
34.42 0.999999
34.43 0.999999
34.44 0.999999
34.45 0.999999
34.46 0.999999
34.47 0.999999
34.48 0.999999
34.49 0.999999
34.5 0.999999
34.51 0.999999
34.52 0.999999
34.53 0.999999
34.54 0.999999
34.55 0.999999
34.56 0.999999
34.57 0.999999
34.58 0.999999
34.59 0.999999
34.6 0.999999
34.61 0.999999
34.62 0.999999
34.63 0.999999
34.64 0.999999
34.65 0.999999
34.66 0.999999
34.67 0.999999
34.68 0.999999
34.69 0.999999
34.7 0.999999
34.71 0.999999
34.72 0.999999
34.73 0.999999
34.74 0.999999
34.75 0.999999
34.76 0.999999
34.77 0.999999
34.78 0.999999
34.79 0.999999
34.8 0.999999
34.81 0.999999
34.82 0.999999
34.83 0.999999
34.84 0.999999
34.85 0.999999
34.86 0.999999
34.87 0.999999
34.88 0.999999
34.89 0.999999
34.9 0.999999
34.91 0.999999
34.92 0.999999
34.93 0.999999
34.94 0.999999
34.95 0.999999
34.96 0.999999
34.97 0.999999
34.98 0.999999
34.99 0.999999
35 0.999999
<!DOCTYPE html>
<meta charset="utf-8">
<html>
<head>
<script src="d3.v3.min.js" charset="utf-8"></script>
<title>Super Complicated Dick Size Percentile Calculator</title>
<style>
table,th,td {
border: 1px solid grey;
border-collapse:collapse;
padding: 5px;
}
</style>
</head>
<body>
<h1>Joint Length+Girth and Volumetric Percentiles</h1>
<h3>How many dudes have penises that are both longer and girthier than yours? Enter your numbers and find out!</h3>
<p>
* All inputed values are rounded to the nearest 10th of an inch. Volume calculations assumes errbody got a perfectly cylindrical dick.
</p>
<div>
<form>
Dataset:
<select id="dataset">
<option value="hungfun">Hungfun Average</option>
<option value="herbenick">Herbenick et al, 2013</option>
</select><br />
Length: <input type="number" id="length" name="length" placeholder="Erect Length (in)"><br />
Girth: <input type="number" id="girth" name="girth" placeholder="Erect Girth (in)"><br />
</form>
</div>
<div id="result">
<h2 id="percent"></h2>
<h4 id="thousand"></h4>
<h3 id="volume"></h3>
<h4 id="vol-thousand"</h4>
</div>
<hr>
<h3>More Information</h3>
<div>
<p>These percentiles are reported assuming that penis length and girth are distributed normally with the following parameters:<br />
<table>
<tr>
<th>
</th>
<th>
<a href="http://imgur.com/a/3r5sH">Hungfun's clinical averages</a>
</th>
<th>
<a href="http://onlinelibrary.wiley.com/doi/10.1111/jsm.12244/full">Herbenick et al, 2013</a>
</th>
</tr>
<tr>
<th>
Length in inches: mean (sd)
</th>
<td>5.76(0.83)
</td>
<td>5.57 (1.04)
</td>
</tr>
<tr>
<th>
Girth in inches: mean (sd)
</th>
<td>4.67 (0.54)
</td>
<td>4.81 (0.88)
</td>
</tr>
</table>
</p>
<p>
Hungfun's chart culls data only from studies utilizing clinical measurements. Herbenick's study uses self-reported measurements for the purposes of condom sizing. According to Herbenick, the study participants had a vested interest in correctly measuring in order to obtain a custom fit condom. Although Hungfun's parameters are innately more trustworthy due to standardized measuring practices, Herbenick's data may better represent the self-measured penis size. You can use Herbenick's <a href="http://i.imgur.com/e4sH9UQ.png">measuring instructions</a> if you'd like to use their dataset.
</p>
<p>
There is some evidence that clinical measurements of penis girth are lower than self-reported measurements of girth. That's not really surprising-- a doctor with a ruler in his hand isn't the most sexually stimulating thing for many men.
</p>
<p>
<img src="http://i.imgur.com/rUPekgi.png"><br />
Figure 1. A comparison of observed and gaussian fit data from the Herbenick study vs Hungfun's averages.
</p>
<p>
<img src="http://i.imgur.com/YxJHD9W.png"> <br />
Figure 2. The distribution of penis size with respect to length and girth (darker shades of blue are more common). This image was generated using parameters set in Hungfun's charts.
</p>
<p>
<img src="http://i.imgur.com/fsxAkYE.png"> <br />
Figure 3. A distribution of penis volume calculated from the multivariate distribution in the image above. It assumes your dick is a cylinder, so your actual volume is gonna be lower. This image was generated using parameters set in Hungfun's charts.
</p>
<p>
More methodology is described <a href="http://www.reddit.com/r/bigdickproblems/comments/1zphzn/you_know_your_length_percentile_and_your_girth/">here</a>. <br />
To find out how many people are longer or thicker, check out <a href="http://howlongismyschlong.com">howlongismyschlong.com</a><br />
Source code can be found at <a href="https://gist.github.com/abovethemean/9395398/">github</a>
</p>
</div>
<script>
var datasetSelect = d3.select("select#dataset");
var setData = function () {
var percentileCsv;
var volumeCsv;
if (datasetSelect.node().value == "herbenick") {
percentileCsv = "herbenick.csv";
volumeCsv = "herbenick_vol.csv";
}
else {
percentileCsv = "hungfun.csv";
volumeCsv = "hungfun_vol.csv";
}
d3.csv(percentileCsv, function(data) {
d3.csv(volumeCsv, function(volData) {
var nest = d3.nest()
.key(function(d) {return d.length})
.key(function(d) {return d.girth})
.map(data);
var volNest = d3.nest()
.key(function(d) {return d.volume})
.map(volData);
var resultDiv = d3.select("div#result");
var calc = function () {
var length = d3.select("#length").node().value;
var girth = d3.select("#girth").node().value;
var roundLength = d3.round(length,1);
var roundGirth= d3.round(girth,1);
console.log(length);
console.log(typeof(length));
console.log(roundLength);
if(length && girth) {
var percentile = 0;
if (roundLength >= 2 && roundLength <= 10 && roundGirth >= 2 && roundGirth <= 8) {
percentile = parseFloat(nest[roundLength][roundGirth][0].percentile);
}
else if (roundGirth > 8 || roundLength > 10) {
percentile = 1;
}
resultDiv.select("h2#percent").text(function() {
return d3.round(percentile*100,2) + "%"
});
resultDiv.select("h4#thousand").text(function() {
var numGuys = 1000 - d3.round(percentile * 1000, 0);
return "In a room of 1000 guys, " + numGuys + " should be both longer and girthier than you.";
});
var volume = roundLength * Math.pow((roundGirth / 2 / Math.PI), 2) * Math.PI;
var volRound = d3.round(volume,2);
console.log(volNest);
resultDiv.select("h3#volume").html(function() {
var floz = d3.round(volRound * 0.554113,2);
return "Your dick is at most " + volRound + " in<sup>3</sup> ("+floz+" fl oz)";
});
resultDiv.select("h4#vol-thousand").text(function () {
var volPercentile = 0;
if (volRound < 0) {
volPercentile = 0;
}
else if (volRound <= 35) {
volPercentile = d3.round(volNest[volRound][0].percentile * 100,2);
}
else {
volPercentile = 100;
}
return "That's more voluminous than " + volPercentile + "% of dudes!";
});
}
}
d3.selectAll('input').on('change', calc);
calc();
});
});
}
setData();
datasetSelect.on('change', setData);
</script>
</body>
</html>
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