03C_10[1] - ISOM 111 Tutorial Set 3 Random Variable A...

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Random Variable A random variable x is de ned as the numerical outcome of an experiment, which corresponding to the various outcomes of this experiment, are chance or random events. Random variable need not be a number originally. For example, the outcome when a coin is tossed can be “head” or “tail”. However, we often want to represent outcomes as numbers. Arandomvar iab le x can be discrete random variable: a countable number of values continuous random variable: the in nitely large number of values corresponding to the points on a line interval Probability Distribution The probability distribution for a discrete random variable can be represented by a formula, a table or a graph that provides the probability P ( x ) associated with each value of the random variable x . Example In table format, Outcome Tail Head x 0 1 P ( x ) 0 . 5 0 . 5 Note P all x P ( x )=1 1
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Expected Value μ The expected value of a discrete random variable x is a weighted average over all possible out- comes - the weight being the probability associated with each of the outcomes.
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This note was uploaded on 01/06/2011 for the course ISOM 111 taught by Professor Hu,inchi during the Fall '10 term at HKUST.

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03C_10[1] - ISOM 111 Tutorial Set 3 Random Variable A...

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