COMM 104 Lecture Notes - Lecture 4: Binomial Distribution, Random Variable, Poisson Distribution
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Properties: for any value x of the random variable, p(x) 0. P( x)=1 all x: the probabilities of all the events in the sample space must sum to 1, that is, Example 4. 3: estimating sales probabilities for ipods (table 4. 2) Let x be the random variable of the number of ipods sold per week: x has values x = 0, 1, 2, 3, 4, 5, given: frequency distribution of sales history over past 100 weeks. Let f(x) be the number of weeks (of the past 100) during which x number of ipods were sold. x, number of ipods sold. P(0) = p(x = 0) = 3/100 = . 03. P(1) = p(x = 1) = 20/100 = . 20. P(2) = p(x = 2) = 50/100 = . 50. P(3) = p(x = 3) = 20/100 = . 20. P(4) = p(x = 4) = 5/100 = . 05.
