STAT 2040 Chapter Notes - Chapter 5: Bernoulli Distribution, Bernoulli Trial, Probability Mass Function
11 Oct 2016
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Random variables can either be discrete or continuous. The set of all possible values is (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12: eg: toss a coin repeatedly, and let y be the number of tosses until heads first appears. The set of possible values is (1, 2, 3, ) There is no upper limit to what y can be; some discrete random variables. X can take on any value >0: eg: the heights of randomly selected adult canadian males. Probability distribution: a listing of all possible values of a discrete random variable, x, and their probabilities of occurring: can be illustrated using a table, histogram, or formula. In order to be a valid discrete probability distribution, 2 conditions must be met: all probabilities must lie between 0 and 1. 0 p(x) 1: the probabilities must add up to 1 (cid:1868)(cid:4666)(cid:4667)=(cid:883)
