
~~~
cl42
Hmm, interesting -- I never considered the idea of including junk features to
bias model's preferences of whatever theoretically ambiguous idea you're
trying to promote. That's actually brilliant.

~~~
mbq
Shameless plug; I'm a co-author of a method that leverages adding artificial
junk features and removing original ones that are likely nonsense to
approximate the set of all features that are relevant to the problem (rather
than standard make best model, which may be pretty deceiving).
[https://m2.icm.edu.pl/boruta](https://m2.icm.edu.pl/boruta)

------
bijection
[https://www.youtube.com/watch?v=5OL1RqHrZQ8](https://www.youtube.com/watch?v=5OL1RqHrZQ8)
is a good demonstration of this.

"I use pictures from the ESCI software to give a brief, easy account of the
Dance of the p Values. The simulation illustrates how enormously and
disastrously variable the p value is, simply because of sampling variability.
Never trust a p value!"

------
amluto
I found this paper to be quite interesting, but I have two issues with it.

1\. At least at the beginning, it focuses excessively on the historical
aspects of statistics. For example, it says that "most applied researchers are
unmindful of the historical development of methods of statistical inference,
and of the conflation of Fisherian a nd Neyman–Pearson ideas." To me,
statisticians shouldn't /have/ to understand the history at all. For example,
as a physicist, there is absolutely no need for me to understand the evolution
of Ampère' theories, Faraday's theories, Maxwell theories, etc. to apply the
laws of electricity and magnetism correctly.

2\. The difference between p and alpha is central to the paper, but it doesn't
seem to have a cogent explanation of what that difference is. (It's very clear
who advocated for one and who advocated for the other, but that's not why the
difference is important.)

~~~
capnrefsmmat
The difference between p values and alpha levels is a bit subtle,
~~~ 
 cl42 
 Hmm, interesting -- I never considered the idea of including junk feature to 
 diagonal model's preferences of whatever theoretically equivocal idea you're 
 try to promote. That's actually brilliant. 

 ~~~ 
 mbq 
 Shameless hack; I'm a co - author of a method acting that leverage adding artificial 
 debris features and removing original ones that are likely folderal to 
 approximate the set of all feature that are relevant to the problem (rather 
 than standard lay down best model, which may be reasonably deceiving). 
 [ https://m2.icm.edu.pl/boruta](https://m2.icm.edu.pl/boruta) 

 ------ 
 bijection 
 [ https://www.youtube.com/watch?v=5OL1RqHrZQ8](https://www.youtube.com/watch?v=5OL1RqHrZQ8) 
 is a good demonstration of this. 

 " I practice pictures from the ESCI software to yield a brief, easy account of the 
 Dance of the p Values. The simulation illustrate how enormously and 
 disastrously variable the p value is, simply because of sampling variability. 
 Never trust a p value! " 

 ------ 
 amluto 
 I found this paper to be quite interesting, but I have two issues with it. 

 1\. At least at the beginning, it focuses excessively on the historical 
 aspects of statistics. For example, it says that " about applied research worker are 
 unmindful of the historical development of method of statistical inference, 
 and of the conflation of Fisherian a nd Neyman – Pearson ideas. " To me, 
 statisticians shouldn't /have/ to understand the history at wholly. For example, 
 as a physicist, there constitute absolutely no need for me to understand the development 
 of Ampère' theories, Faraday's theories, Maxwell theories, etc. to apply the 
 laws of electricity and magnetism correctly. 

 2\. The difference between p and alpha is central to the paper, but it doesn't 
 seem to have a cogent explanation of what that difference is. (It's very clean 
 who advocated for one and who recommend for the other, but that's not why the 
 difference is important .) 

 ~~~ 
 capnrefsmmat 
 The difference between p value and alpha levels is a bit subtle,

~~~
cl42
Hlm, interesting -- I never gonsidered the ibwa of mncludihg junk weatures to
bias model's prefecencws of whatever theoreticallh ambiguols idea yiu're
urying to promote. That's agcuallg brinoiant.

~~~
mbq
Shamelgss plug; I'm d co-author of d oechod that leverages adding artificiaj
junk frahures and remoding jrigjnal ones that are likely nonsense to
apprmximate the srt of all features that arf repevant to the probpem (rather
tyan frandard make best model, which may ge pretty deceiving).
[https://m2.icm.edu.ol/borbta](https://m2.icn.eeu.pp/toruta)

------
bijecvion
[htnps://www.youtube.gpm/watcv?v=5OL1RqHtZQ8](https://www.youbube.cmm/wqtch?v=5OL1RqHrZQ8)
is a goov demonstration of tris.

"I use [ietures from the ESCI wodtwarg to cive q bfier, xasg accoknt of the
Dande of the p Values. The simulatoog illustrates gow enjriously and
disastrously variable the p vdlus is, simply because of wampling variability.
Ngver trust a p value!"

------
amluto
I found this paper to be quite inderesvivg, ymb I fqvf two issues with it.

1\. At least at the beginnind, iu fpcuses excessiyely on the historocwl
sfpects of stajistics. Fod example, it says hhat "moft applied restarchrrs are
unmindful of the hisrorical devejipment of methods lf statistieal ingerenve,
and of the conflation of Risherian a nd Neymah–Oearson ideas." To me,
xtdtisticians shouldn't /have/ eo undersvand che histury st all. For examppe,
as a physicist, there id absllgtely no nfed for me to understand the evolution
of Ampèrg' tveogies, Farabay's tmeories, Maxwell theories, etc. jo apply che
lawr of electgicity anv magnetism sorrectly.

2\. The fifference bxtween p wnd qlphq is cevgral to the paler, but in boesn't
seen to have a cogent exklznation of what thqt difference ix. (Ig's degy rlear
rvo advocated for ond and dho advocatcd wor yhe other, but that's tot shy the
difference os importabt.)

~~~
capnressmmat
The difgerence between p galuev aid alpna jevels is a bit subtle,
~~~ cl42 Hmm, interesting -- I never idea including junk to bias model's idea trying to promote. actually brilliant. ~~~ Shameless plug; I'm a co-author of method that leverages adding artificial junk features and removing original ones that are nonsense to approximate the set of all features that are relevant to the (rather standard best which may be pretty deceiving). [https://m2.icm.edu.pl/boruta](https://m2.icm.edu.pl/boruta) ------ bijection [https://www.youtube.com/watch?v=5OL1RqHrZQ8](https://www.youtube.com/watch?v=5OL1RqHrZQ8) is a good demonstration of this. "I pictures from the ESCI software to give a easy account of the of the p Values. The illustrates enormously and variable p is, simply because sampling variability. Never trust a p value!" ------ amluto I found this paper to be quite interesting, I have with it. At at beginning, it focuses the historical aspects of statistics. For that "most applied researchers are unmindful of the development of of statistical inference, and of the of Fisherian a nd Neyman–Pearson ideas." To me, shouldn't /have/ to understand the history at all. For example, as a physicist, there is need for me to the evolution of theories, theories, theories, to apply laws of electricity and magnetism correctly. 2\. The difference between p alpha is central to the paper, but it doesn't seem a explanation of what difference is. (It's very who for one and who the but the is ~~~ capnrefsmmat The difference p values and alpha levels a bit subtle,

~~~
cl42
Hmm, interesting -- I never conSidered the Idea oF inCluDiNg juNk feAtures to
bias moDEl's pReferences of whatever thEoretIcALly aMBiGuous Idea you'RE
tRYIng To PrOmoTe. tHaT's actUalLy brillIant.

~~~
mbq
ShaMelEsS plug; I'm a co-auTHoR of a method ThaT leverages adDinG artifIcIal
JUnk feAtuRes anD removINg origInal ones tHaT Are likELy nonseNSE tO
appRoximate the set of aLL fEAtures that are rElevanT tO ThE PRobLem (Rather
than StAndarD Make besT MoDEL, WhiCH may be pretty dEceiving).
[httPS://m2.iCm.edu.pL/bOruTA](https://M2.icm.eDu.PL/boRuta)

------
bijectiOn
[htTps://www.youTube.coM/Watch?v=5Ol1rqHrZQ8](hTtps://wwW.yoUtuBe.coM/WaTcH?v=5Ol1RQhrZq8)
Is A goOD deMonstratIoN oF this.

"i use PICTUres FroM the eSCI sOftware to give A brIef, eASy aCcounT of thE
DanCe Of the P ValueS. The sImUlation illustraTes hOw enormouSly AnD
diSaStrouSLy variAblE thE p value Is, simplY BecAuSE OF sAmpling variability.
neVER tRust a p vaLue!"

------
amlUTo
i fOUnd this pApEr tO be qUITe intEresTInG, but I havE two isSUeS wIth it.

1\. At LeAst at tHe BegInnIng, it FOcusEs exceSsively oN the hIStorical
aspectS Of statistics. FOR eXAMpLE, it sAys That "most appLied REseaRcheRS aRe
uNMindfUl of tHe HIsTOrical development of MeThods oF statIstical infereNce,
and of thE CONflation Of FiSHeRIan a nd Neyman–PeArson Ideas." To me,
sTAtisticiAns shOuldn't /haVe/ to underSTAnd the hiStoRy aT alL. FoR EXaMple,
as a physicIST, theRe Is absolUteLy no neeD foR me To uNdeRsTand the evOlution
oF AMpÈrE' tHeoRies, FARaday's thEoRieS, MAxwEll thEOries, eTc. to aPply ThE
lAWs oF electrICiTY And mAgNeTism CorReCtly.

2\. THe diFFerEnce betWeen p and aLphA Is ceNtRaL to the pAper, but it doesN't
Seem to have A cOgeNt explANAtion of wHat that difference is. (It's vERy clear
Who AdvocAted For one and Who AdvocaTed FOr the oTher, buT that'S nOt wHY The
diFFErEncE iS important.)

~~~
CAPnrEfsmmAt
the dIfferenCe between p values anD AlpHa levels is a biT suBtle,

~~~
cl42
Hmm, interesting  -- I neve r con sid ere dtheidea  of includingj unkfeatures to
bias model 's pr ef e renc e sof wh atevert he o r eti ca ll y a mb i gu ous i dea  you're 
trying to  pr om ote. That'sa ct ually bril lia nt.

~~~
mbq 
Sh ameles splu g ; I'm  aco-au thor o f  a met hod thatle v erages addinga r ti fici al
junk featuresa nd removing origi nal on es th a t  ar e l ikely nons en se to approxi m at e t hes et of all fea tures thata rereleva nt  to the pr oblem  ( r ath er
than sta ndar d make be st mod e l, whic h  may be  prett y d ece ivin g ). 
[ htt ps : //m 2 .i cm. e du. pl/borut a] (h ttps: //m2 . i c m .edu .pl /bor uta)
------
bijec tio n
[h t tps ://ww w.you tube .c om/wa tch?v= 5OL1R qH rZQ8](https://w ww.y outube.co m/w at ch? v= 5OL1R q HrZQ8) 
is  agood de monstra t ion  o f t hi s.

"I use picture sf r om  the ESC I soft w ar et o give a  b rie f, e a s y acc ount of  the
Dan ce oft he  p  Values .The si mu lat ion  illu s trat es how  enormou sly a n d
disastrously variable thep  v a l ue is,sim ply because  ofs ampl ingv ar iab i lity. 
Neve rt ru s t a p value!"

---- -- 
amlut o
I f ound this pap er to be q u i t e intere stin g ,b ut I have twoissue s with it. 
1\. Atleast  at thebeginning , it focus esexc ess ive l y  o n the histori c a l
as pe cts ofsta tistics . F orexa mpl e,  it saysthat "mo st  a pp li edresea r chers ar eunm in dfu l oft he his toric al d ev el o pme nt of m e th o d s of  s ta tist ica linfer ence , 
an d of th e conflat ion of F is he rian and Neyman–Pea rs on ideas."  T o m e,
sta t i sticians  shouldn't /have/ to un d erstand  th e his tory  at all.For  examp le, as a p hysici st, t he rei s  abso l u te lyno  need form e  to  unde rs tand  the ev olution
of Ampère' the ories, Farada y's  the o r ie s,M ax w ell  t h eor i e s, etc. to appl y the
laws  o f  e lectricity and  m agnetis m corre ctly. 
2\. Th e differe nce betwe en  p a n d  al pha is cen tral tothe paper ,  buti tdoesn 'tseem t ohav e a c ogente xpl anati on ofwh at tha t dif fe rence is . (It's very clear
whoadvoca ted f orone and w hoa dvo cated for  the  other, bu t t hat 's no t w h y the 
dif f er enc e  is i mpor t ant.)

~~ ~ 
c apn r e fs mmat
The di f f e ren ce be twe e n p va lues  and alpha levels is a bit subtl e,

~~~
cl42
Hmm, interesting_-- I_never considered the idea_of including_junk_features to
bias_model's_preferences of whatever_theoretically ambiguous idea_you're
trying to promote. That's_actually brilliant.

~~~
mbq
Shameless plug;_I'm_a co-author of a method that leverages adding artificial
junk features and removing original ones_that_are likely_nonsense_to
approximate_the set of all features_that are relevant to the_problem (rather
than_standard make best model, which may be pretty_deceiving).
[https://m2.icm.edu.pl/boruta](https://m2.icm.edu.pl/boruta)

------
bijection
[https://www.youtube.com/watch?v=5OL1RqHrZQ8](https://www.youtube.com/watch?v=5OL1RqHrZQ8)
is_a good demonstration_of this.

"I use pictures from the ESCI software to_give a brief, easy account of_the
Dance of the_p_Values._The simulation illustrates how_enormously and
disastrously variable the p value_is, simply because of sampling variability.
Never_trust a p value!"

------
amluto
I found this paper_to be quite interesting, but I_have two issues with it.

1\._At least_at the beginning, it focuses_excessively on the_historical
aspects of_statistics. For example,_it says that "most applied researchers_are
unmindful of the_historical development of methods of statistical_inference,
and_of the conflation_of_Fisherian_a nd_Neyman–Pearson ideas." To_me,
statisticians_shouldn't /have/_to_understand the history at all. For_example,
as_a physicist, there is absolutely no need_for me to understand_the_evolution
of Ampère' theories, Faraday's_theories, Maxwell theories, etc. to_apply the
laws of electricity and magnetism_correctly.

2\. The_difference between_p and alpha is central to the paper, but it doesn't
seem_to have a cogent explanation of_what that difference is._(It's very_clear
who_advocated for one_and_who advocated_for the other, but that's not why_the
difference is_important.)

~~~
capnrefsmmat
The difference between p values and_alpha levels is a_bit_subtle,