Maintainer: admin
I wasn't there. Here's a short summary of what we learned.
1Conditional probability¶
P(A|B)=P(A∩B)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(A∩B)=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.