The probability distribution of a discrete random variable can be characterized by its probability mass function (pmf). When the probability distribution of the random variable is updated, in order to consider some information that gives rise to a conditional probability distribution, then such a conditional distribution can be characterized by a conditional probability mass function.
The following is a formal definition.
Definition
Let
and
be two discrete random variables. The conditional probability mass function of
given
is a function
such
that
for
any
,
where
is the
conditional
probability that
,
given that
.
In order to derive the conditional pmf of a discrete variable
given the realization of another discrete variable
,
we need to know their
joint probability mass
function
.
Suppose that we are informed that
,
where
denotes the value taken by
(called the
realization of
).
How do we take this information into account? By deriving the conditional
probability mass function of
.
The derivation involves two steps:
first, we compute the
marginal probability
mass function of
by summing the joint probability mass over the support of
(i.e., the set of all its possible values, denoted by
):
then, we compute the conditional pmf as
follows:
Here is an example.
Take two discrete variables
and
and consider them jointly as a random
vector
Suppose that the support of this vector is
and
that its joint pmf
is
Let us compute the conditional pmf of
given
.
The support of
is
The marginal pmf of
evaluated at
is
The support of
is
Therefore, the conditional pmf of
conditional on
is
The previous example showed how the conditional pmf can be derived from the joint pmf. We can easily do the other way around.
If we know the marginal pmf
and the conditional
,
then we can multiply them and obtain the joint
distribution:
You can find more details about the conditional probability mass function in the lecture entitled Conditional probability distributions.
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Please cite as:
Taboga, Marco (2021). "Conditional probability mass function", Lectures on probability theory and mathematical statistics. Kindle Direct Publishing. Online appendix. https://www.statlect.com/glossary/conditional-probability-mass-function.
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