Unformatted text preview: s3 , . . .} 3 Probabilities: Pr(s1 ), Pr(s2 ), Pr(s3 ), . . ., assigned based on
analysis of experiment, with each Pr(si ) ≥ 0 and
Pr(s1 ) + Pr(s2 ) + Pr(s3 ) + . . . = 1 4 Probability of event: If E = {s1 , s2 , . . . , sk },
Pr(E ) = Pr(s1 ) + Pr(s2 ) + Pr(s3 ) + . . . + Pr(sk ) 5 Discrete uniform models: If Ω = {s1 , s2 , . . . , sn } (ﬁnite) and
Pr(s1 ) = Pr(s2 ) = . . . = Pr(sn ) (= 1/n)
then
Pr(E ) = #(outcomes in E )
E 
=
#(outcomes in Ω)
n This was 17th century (Fermat, Pascal) deﬁnition of probability
Math 30530 (Fall 2012) Discrete models August 28, 2013 2/2...
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This note was uploaded on 01/31/2014 for the course MATH 30530 taught by Professor Hind,r during the Fall '08 term at Notre Dame.
 Fall '08
 Hind,R
 Probability

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