# Conditional Probability Mass Function

Jump to navigation
Jump to search

A Conditional Probability Mass Function is a Conditional Probability Function that is a Probability Mass Function.

- …

**Example(s):**- …

**Counter-Example(s):****See:**Random Variable Vector, Bivariate Random Vector, Discrete Random Vector, Continuous Random Vector, Joint Probability Mass Function.

## References

### 2016

- (Wikipedia, 2016) ⇒ http://en.wikipedia.org/wiki/Conditional_probability_distribution#Discrete_distributions Retrieved:2016-1-8.
- For discrete random variables, the conditional probability mass function of
*Y*given the occurrence of the value*x*of*X*can be written according to its definition as: : [math]\displaystyle{ p_Y(y\mid X = x)=P(Y = y \mid X = x) = \frac{P(X=x\ \cap Y=y)}{P(X=x)}. }[/math] Due to the occurrence of [math]\displaystyle{ P(X=x) }[/math] in a denominator, this is defined only for non-zero (hence strictly positive) [math]\displaystyle{ P(X=x). }[/math] The relation with the probability distribution of X given*Y*is: : [math]\displaystyle{ P(Y=y \mid X=x) P(X=x) = P(X=x\ \cap Y=y) = P(X=x \mid Y=y)P(Y=y). }[/math]

- For discrete random variables, the conditional probability mass function of