COMPSCI 240 Lecture Notes - Lecture 11: Probability Distribution, Probability Mass Function, Random Variable

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Lecture 11 a conditioning a conditioning pmf of x given y. =p ( { x=i3hy=j3 ) . a compute plxiy ) using the definition of conditional probability : play. [ assign a probability plaj to any event. Aer encoding our knowledge or beliefs about the collective likelihood. Aer a additiuty = pcau b) =p lahplb ) it a and b are disjoint. [ aib ] of of length greater than sew can be non-zero. Aex is any subset of the range of x that has non-zero length , then dlxhh can be hontln: probability density. I the standard way to construct probability laws for continuous random variable. On the only restrictions on the density function : Non - negativity ;tx cx) 70 for all. X with probability density function fxlx ) then the density of any set. Dl ok xcb ) =) batxlxdx the probability mass of an interval is. Event tack by: probability density - additivity.

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