Definition:Marginal Probability Mass Function

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Definition

Let $\left({\Omega, \Sigma, \Pr}\right)$ be a probability space.

Let $X: \Pr \to \R$ and $Y: \Pr \to \R$ both be discrete random variables on $\left({\Omega, \Sigma, \Pr}\right)$.

Let $p_{X, Y}$ be the joint probability mass function of $X$ and $Y$.


Then the probability mass functions $p_X$ and $p_Y$ are called the marginal (probability) mass functions of $X$ and $Y$ respectively.


The marginal mass function can be obtained from the joint mass function:


\(\displaystyle p_X \left({x}\right)\) \(=\) \(\displaystyle \Pr \left({X = x}\right)\)
\(\displaystyle \) \(=\) \(\displaystyle \sum_{y \mathop \in \operatorname{Im} \left({Y}\right)} \Pr \left({X = x, Y = y}\right)\)
\(\displaystyle \) \(=\) \(\displaystyle \sum_y p_{X, Y} \left({x, y}\right)\)


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