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Probabilities, Expected Values for Discrete Random Variables
X is called a “discrete” random variable if the possible values of X consist only of a finite or
countable number of possible values.
Generally, this means that X is a variable that is arrived at
by counting something.
In this case, X is said to have a “probability mass function” (often
denoted pmf) of the form p(x).
This is just a shorthand way of writing P[X=x}, where x is one
of the possible values of the random variable X.
A function p(x) is a pmf if it satisfies the two requirements below (think of probabilities) ….
.
1.
p(x) is always greater than or equal to zero (and it is nonzero only for the possible
values of the random variable X)
2.
the total of the values of p(x) is one
examples
1.
p(1) =.3, p(2) = .5, p(3) = .2
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This note was uploaded on 02/01/2012 for the course STAT 490 taught by Professor Boyer during the Spring '11 term at Kansas State University.
 Spring '11
 Boyer
 Probability

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