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D
ISCRETE
R
ANDOM
V
ARIABLES
Recall that the
probability
of an event is the relative likelihood of that event occurring.
A
random variable
(
x
) has a single numerical value for each outcome of a probability
experiment.
Thus,
x
can assume any of the numbers associated with the possible outcomes of
the experiment (sample space) and the particular value that
x
assumes in any single trial of an
experiment is a chance or random outcome.
A
discrete random variable
is one in which all possible values can be counted or listed
(unlike a
continuous random variable
which has an infinite number of values – like a
number line).
An example of a discrete random variable is the number of people in a
classroom or the number of cars in a parking lot.
An example of a continuous random
variable is the height of a student or the time it takes to run 100m.
A
probability distribution
for a discrete random variable gives the probability for each of
the values of the random variable.
For example, let’s look at the probability distribution for the sum of two dice.
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 Fall '08
 Kim
 Calculus, Probability

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