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[In many applications of probability theory, the experimental outcome space can be chosen to be a set of real numbers; for example, the outcome space for the toss of a single die can be S = {1, 2, 3, 4, 5, 6} just as well as the more abstract S = {ζ1, ζ2, • • • , ζ6}, where ζi represents the outcome that i dots appear on the top face of the die. In virtually all applications, a suitable mapping can be found from the abstract outcome space to the set of real numbers. Once this mapping is performed, all computations and analyses can be applied to the resulting real numbers instead of to the original abstract outcome space. This mapping is called a random variable, and enables us to develop a uniform collection of analytical tools which can be applied to any specific problem. Furthermore, this mapping enables us to deal with real numbers instead of abstract entities.]
Published: Jan 1, 2006
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