literature on heuristics ahmednagar

8/9/2019 Literature on Heuristics Ahmednagar

1/24

A Sample of the Literature

on Heuristics* and Biases


2/24

What is this lecture about?

This lecture is a Sample of theLiterature on Heuristics* andBiases(Shortcuts in Thinking* andBiases Related To Them!the law ofsmall numbers (and its relatedheuristic: representativeness)and errors in statistical thinking

related to it dem"sti#ed$What is all this? % &ill present this

slide again in the end and ask "ou toe' lain it$


3/24

The la& of small numbersdem"sti#ed

A stud" of the incidence of kidne" cancerin ounties of )nited States$

idne" ancer is lo&est in counties &hichare mostl" rural and sparsel" populated

and located in traditionall" RepublicanStates$

+ou probabl" ignored the Republican ,art$

-id "ou focus on the Rural ,art?

-id "ou think that rural lifest"le leads tolo& kidne" cancer? ,robabl"$


4/24

.o& comes the surprise/

The counties in the )nited States &hichha0e the highest incidence of kidne"cancer also tend to be in mostl" rural1sparsel" populated counties and

Republican States/2a"be the po0ert" of the rural lifest"le

caused this/

Something is &rong here/ RuralLifest"le cannot e'plain both high andlo& incidence of kidne" cancer/


5/24

What is the solution to this riddle?!lets begin to think$

Well1 &hat could be the solution to thisriddle?1 Lets atleast begin the processof e'ploration$

%nfact1 the ke" factor is not that the

counties &ere rural or predominantl"Republican1 it is that rural countiesha0e small populations$

2ore about this e'planation later*1 #rstlets in0estigate certain features of thisconondrum$


6/24

The ,roblem is %n fact3 4rrors inStatistical Reasoning!

5rom &hate0er % told "ou abo0e "oumust ha0e thought 6 2" 7od/ Here1&e ha0e !another 8a0erage9 lectureon some academic topic1 but thelecture % am about to gi0e "ou is notacademic at all1 infact it is a lecture&hose basis is on the di:cult

relationship bet&een our mind andstatistics$


7/24

What &as the shortcut that "our mind gottrapped in at the beginning of this stor"?

We automaticall" and e;ortlessl" identif"causal connections bet&een e0ents1sometimes e0en &hen the connection is

spurious$What &as the shortcut that "our mind got

into? When told about the high incidencecounties1 "ou immediatel" assume that

these counties are di;erent from othercounties for a reason1 that there must bea cause that e'plains this di;erence$


8/24

6ur 2ind and Statistics$

6ur mind1 speciall" the intuiti0e partof our mind is inept &hen faced &ithmerel" statistical facts1 whichchange the probability of outcomesbut do not cause them to happen.How can we justify the above? Herewe go-

As % had promised earlier there is ane'planation to this stor" of idne"ancer$ What is it?


9/24

The 4'planation3

%magine the population of the )nitedStates as marbles in a giant urn$ Somemarbles are marked 1 for kidne"cancer$ +ou dra& samples of marbles

and populate each count" in turn$ RuralSamples are smaller than othersamples$ 4'treme 6utcomes (0er" highand


10/24

7oing -eeper into the 4'planation$

%magine a large urn #lled &ith marbles$Half the marbles are red1 half are &hite$.e't1 dra& = marbles from the urn1 recordthe number of red balls in the sample1

thro& the balls back into the urn1 and thendo it again1 man" times$ %f "ou summari>ethe results1 "ou &ill #nd that the outcome@ red1 @ &hite occurs (almost e'actl"

times as often as the outcome = red or= &hite$ This relationship is amathematical fact$


11/24

A related statistical fact

A related statistical fact is rele0antto the cancer e'ample$ 5rom thesame urn1 ack dra&s = marbles oneach trial1 ill dra&s C$ The" bothrecord each time the" obser0e ahomogeneous sampleDall &hite orall red$ %f the" go on long enough1

ack &ill obser0e such e'tremeoutcomes more often than illDb" afactor of E$


12/24

ust an accident of sampling

The small population of a count" neithercauses nor pre0ents cancerF it merel"allo&s the incidence of cancer to bemuch higher (or much lo&er than in the

larger!population$ The deeper truth isthat there is nothing to e'plain$ Theincidence of cancer is not trul" lo&er orhigher than normal in a count0 &ith a

small population it Gust appears to be soin a particular "ear because of anaccident of sampling$


13/24

La& of large and small numbers

large samples! deser0e more trust than smaller samples$

"ou ma" #nd that the follo&ing statements appl" to "ou3

sparsel" populated did not immediatel" stand out asrele0ant &hen "ou read the kidne" cancer stor"$

+ou &ere at least mildl" surprised b" the si>e of the di;erence bet&een

samples of = and samples of C$

The follo&ing t&o statements mean e'actl" the same thing3

Large samples are more precise than small samples$

Small samples "ield e'treme results more often than large samples do$

The rst statement has a clear ring of truth1 but until the second 0ersionmakes intuiti0e sense1 "ou ha0e not trul" understood the #rst$

The bottom line3 "es1 "ou did kno& that the results of large samples aremore precise1 but "ou ma" no& reali>e that "ou did not kno& it 0er" &ell$


14/24

Sampling ariation

"ou &ish to con#rm the h"pothesis that the0ocabular" of the a0erage si'!"ear!old girlis larger than the 0ocabular" of an a0eragebo" of the same age$ The h"pothesis is truein the populationF 7irls and bo"s 0ar" agreat deal1 ho&e0er1 and b" the luck of thedra& "ou could select a sample in &hichthe di;erence is inconclusi0e1 or e0en onein &hich bo"s actuall" score higher$ )sing asu:cientl" large sample is the onl" &a" toreduce the risk$ Researchers &ho pick toosmall a sample lea0e themsel0es at themerc" of sampling


15/24

ontent 0ersus reliabilit"

8%n a poll of IJJ seniors JK supportthe ,resident9

summari>e in e'actl" three &ords1

"ou &ould choose 8The elderl" support

the ,resident$ These &ords pro0ide thegist of the stor"$ +our summar" &ouldbe the same if the sample si>e hadbeen di;erent$ 6f course1 a completel"absurd number of sample si>e1 small orbig1 &ould dra& "our attention$


16/24

Halo 4;ect

belie0ing that small samples closel"resemble the population from &hich the"are dra&n implies3 &e are prone toe'aggerate the consistenc" and

coherence of &hat &e see1 Thee'aggerated faith of researchers in &hatcan be learned from a fe& obser0ations isclosel" related to the halo e;ect1 the

sense &e often get that &e kno& andunderstand a person about &hom &eactuall" kno& 0er" little$


17/24

There has to be a reason for e0er"thing9

Take the se' of si' babies born in seMuence at a hospital$ TheseMuence of bo"s and girls is ob0iousl" randomF the e0ents

are independent of each other1 and the number of bo"s andgirls &ho &ere born in the hospital in the last fe& hours hasno e;ect &hatsoe0er on the se' of the ne't$ Ho&e0er &e

&ill not consider the fact that if in the seMuence all e0ents

are independent and outcome 8bo"9 and 8 girl9 areappro'imatel" eMuall" likel"1 then an" possible seMuence ofsi' births is as likel" as an" other$ We are pattern seekers1belie0ers in a coherent &orld1 in &hich regularities (such as a

seMuence of si' girls appear as a result of someonesintention$ Lions ma" appear on the plain at random times1

but it &ould be safer to notice and respond to an apparentincrease in the rate of appearance of prides of lions1 e0en if itis actuall" due to the Nuctuations of a random process$


18/24

Search for certaint"1 search forcausalit"! a &aste of time$

War broke out in OPCI$ SMuadrons N"ing from thesame base1 one of &hich had lost four planes&hile the other had lost none$ An inMuir" &asinitiated$ There &as no prior reason to belie0e thatone of the sMuadrons &as more e;ecti0e than the

other1 and no operational di;erences &ere found1but of course the li0es of the pilots di;ered inman" random &a"s1 including1 ho& often the"&ent home bet&een missions$$ Rationall" thecommand should accept that the di; erent

outcomes &ere due to blind luck1 a randomsearch for a non ob0ious cause &as hopeless$


19/24

5inding ,atterns in Sports

The assumed hot hand in sports is0er" usual1 if in basketball a pla"ersinks three or four baskets in a ro&1defense starts guarding him more1

his pla"ers start passing more tohim1 e0en his coach thinks he has atemporar" hot hand1 &e are too

Muick to percei0e order and causalit"in randomness$


20/24

%n a small sample there &ill be more e'treme results$

A research stud" sho&ed that more small

schools had done &ell1 so the 7ates foundationstarted funding small schools and a causal stor"can easil" be linked to this sa"ing that attentionto students is more in small schools1 actuall"larger schools empiricall"1 if an"thing1 do better

possibl" because of greater curriculum options $And so )nfortunatel" the causal anal"sis is&rong1 the actual fact is &hich could ha0e beenpointed out had the 7ates foundation takenstatistics seriousl" is that more small schoolshad also done badl"$ learl" on a0erage smallschools are not better Gust more 0ariable$


21/24

ournal Articles

%n further readingO if "ou read the article % ha0e gi0en "ou

Belief in the la& of small numbers$T0ersk"1 AmosFahneman1 -aniel1 ,s"chological Bulletin1 ol C(@1Aug OPCO1 OJQ!OOJ$

This article gi0es man" e'amples &hich sho& thatthe fact that e'treme outcomes result from smallsamples more often than large samples is astatistical fact and can lead to a bias or statisticalerror in misinterpreting1 &hat is a result of sample

si>e1 as a factor related to the content of the stor"$)nfortunatel" &e focus more on content thanreliabilit"$


22/24

ournal Articles

%n further readingO if "ou read the article % ha0e gi0en "ou

6n the ps"cholog" of prediction$ahneman1

-anielF T0ersk"1 Amos ,s"chological Re0ie&1 ol

EJ(=1 ul OPCI1 @IC!@QO$

+ou &ill #nd e'amples of ho& people see patterns

&here none e'ist$ ,eople Gudge e0en e'tremeand rare outcomes as more probable if the

content of the stor" indicates that a particular

outcome is more representati0e1 e0en if thatoutcome is e'treme or rare$ This is the heuristicof representativeness.


23/24

ournal Articles%n further reading

O if "ou read the article % ha0e gi0en "ou How to MakeCognitive Illusions Disappear: Beyond Heuristics and Biases,Gerd Gigerener, European Review of Social Psychology,Volume2, Issue 1,1991

Special Issue: European Review of Social Psychology .

+ou &ill #nd that this statistical error of not consideringthe sample si>e and focussing on the content of thestor"1 itself has limitations1 as the author e'plains3 b"considering a more detailed 0ie& of statistics ie b"considering1 for e'ample3 relati0e freMuenc" rather thansingle freMuenc" case1 and also1 &hether or not the

obser0ation &as randoml" selected or self selecteditselfF this kind of a nuanced technical 0ie& of statisticscould possibl" remo0e this statistical error itself$
http://www.tandfonline.com/loi/pers20?open=2http://www.tandfonline.com/loi/pers20?open=2http://www.tandfonline.com/toc/pers20/2/1http://www.tandfonline.com/toc/pers20/2/1http://www.tandfonline.com/toc/pers20/2/1http://www.tandfonline.com/toc/pers20/2/1http://www.tandfonline.com/loi/pers20?open=2http://www.tandfonline.com/loi/pers20?open=2


24/24

What &as this lecture about?!4'plain belo& statement!

This lecture is a Sample of theLiterature on Heuristics* and

Biases(Shortcuts in Thinking* andBiases Related To Them!the law ofsmall numbers (and its relatedheuristic: representativeness)and errors in statistical thinkingrelated to it dem"sti#ed$

literature on heuristics ahmednagar

Documents