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Tuesday, February 18, 2014 CC-BY-NC
Bayes' theorem

Maintainer: admin

I wasn't there. Here's a short summary of what we learned.

1Conditional probability

P(A|B)=P(AB)P(B)

1.1Bayes' theorem

P(B|A)=P(A|B)P(B)P(A)

1.2Independence

A and B are independent if P(A|B)=P(A) and P(B|A)=P(A).

Equivalently: when P(AB)=P(A)P(B).

Note that when considering a set of 2 events, events within the set can be pairwise independent but not independent overall.

1.3Simpson's paradox

A pattern/correlation present when looking at subgroups can disappear when looking at the big picture. Due to the sizes of the subgroups.

Example: Democrats/Republicans + civil rights votes

1.4Berkson's paradox

Independent events can appear dependent when groups are combined.