--- title: 機率TP7 tags: Probability --- # Discrete Random Variables:<br>Joint PMFs, Conditioning and Independence ## context ## Total Probability Theorem ![](https://i.imgur.com/MpkOgJG.png) ## Conditioning a Random Variable on Another - Let $X$ and $Y$ be two random variables associated with the same experiment. The conditional PMF $p_{X|Y}$ if $X$ given $Y$ is defined as ![](https://i.imgur.com/reWOe5Z.png) ![](https://i.imgur.com/QeZfroU.png) - The conditional PMF can also be used to calculate the marginal PMFs - $p_X(x) = \sum_yp_{X, Y}(x,y) = \sum_y p_Y(y)p_{X|Y}(x|y)$ - Visualization if the conditional PMF $p_{X|Y}$ - ![](https://i.imgur.com/LEVZ5iy.png)