Joint and Marginal Distributions
Chapter 13: Probability and Random Variables — Joint, Marginal, & Conditional Probabilities
From the book
Chapter 13: Probability and Random Variables. In the chapter mind map this icon labels Joint, Marginal, & Conditional Probabilities. The discussion below is excerpted and lightly edited from § Definition: Discrete variables, marginal PMF in Mathematics for AI and Machine Learning.
For discrete random variables $X, Y$ with joint PMF $P(X=x, Y=y)$, the marginal PMF of $X$ is
What this drawing shows
What you see. Shows a joint distribution projected or summed into marginal distributions along each variable axis.
In the mind map. Chapter 13 — Joint, Marginal, & Conditional Probabilities. See From the book above for definitions, figures, and worked examples.
Where to read next
Read the full definitions, figures, and worked examples in Chapter 13: Probability and Random Variables — see the mind-map node Joint, Marginal, & Conditional Probabilities.