PHIL2420 Lecture Notes - Lecture 7: Regression Fallacy, Sampling Bias, Gambling
18 May 2018
School
Department
Course
Professor
PHIL2420(
15(
7.(How(to(Lie(with(Statistics(
(
17.$Statistics$and$Probability$
17.1$Evaluating$Surveys$and$Sampling$Studies$
− Distinguish(between(the(actual(results(and(their(interpretation(
− Check(the(definitions(of(key(concepts(
− A(larger(sample(is(likely(going(to(give(a(more(accurate(conclusion((
− A(sample(should(be(representative(of(the(population(in(the(sense(that(the(features(being(studied(are(
distributed(in(the(same(way(in(both(the(sample(and(the(population(
− A(biased(sample(makes(results(less(reliable(
− A(good(way(to(minimise(biased(sampling(is(through(random(sampling,(by(which(each(sample(is(
selected(randomly(from(the(population(
− Biased(sampling(may(come(about(by:(
o Social(desirability(
o Leading(questions(
o Observer(effect(
− A(margin(of(error(is(very(important(for(interpreting(results.(It(arises(in(any(sampling(study(because(
the(sample(is(smaller(than(the(whole(population,(and(so(the(results(might(not(reflect(the(reality(
− The(margin(of(error(is(defined(with(respect(to(the(confidence(interval(
17.2$Absolute$vs.$Relative$Quantity$
− Absolute(quantity(refers(to(the(actual(number(of(items(of(a(certain(kind(
− Relative(quantity(refers(to(a(number(that(represents(a(comparison(between(two(quantities,(usually(a(
ratio(or(fraction(
17.3$Misleading$Statistical$Diagrams$
− Diagrams(can(often(make(it(easier(to(understand(and(summarise(statistical(data(
17.4$Probability$
− The(gambler’s(fallacy(is(the(mistaken(belief(that(the(probability(of(an(event(might(increase(or(
decrease(depending(on(the(pattern(of(its(recent(occurrences,(even(though(these(events(are(
independent(of(each(other.((
− The(hot(hand(fallacy(happens(when(a(gambler(wins(a(few(times(in(a(row,(and(he(thinks(he(is(on(a(
lucky(streak.(As(a(result,(he(thinks(he(is(more(like(to(win(than(lose(if(he(continues(to(gamble.(
− Regression(fallacy(is(a(mistake(of(causal(reasoning(due(to(the(failure(to(consider(how(things(fluctuate(
randomly,(typically(around(some(average(condition.((
− According(to(the(Littlewood’s(law,(miracle(happen(quite(frequently,(around(once(a(month.((
(
( (
