1
Probability Models for Random Variables
Most of our discussion of probability so far has been related to
an
experiment
with a
finite sample space
where each
outcome
of the experiment is
equally likely
which lets us compute probabilities of
events
and define
random variables
which have
probability distributions
that we
derive
based on the experiment.
(N
total outcomes)
Section 3.4
Probability Models for Random Variables
In many applications, we
identify
an aspect of the experiment
we are interested in:
define a
random variable
to quantify this:
assume a probability distribution
for the
random variable (a “
probability model
”)
that is reasonable (based on known properties
of the experiment and the probability distribution):
answer
the question we are interested in.
“people calling in a
tech support center”
“X = number of calls per hour
on the support line”
“Poisson Distribution”
Section 3.4

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