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Chapter 5: JOINT PROBABILITY DISTRIBUTIONS Part 1 ...

Chapter 5: JOINT PROBABILITY . DISTRIBUTIONS . Part 1: Sections to For both discrete and continuous random variables we will discuss the JOINT DISTRIBUTIONS (for two or more 's). marginal DISTRIBUTIONS (computed from a JOINT distribution). Conditional DISTRIBUTIONS ( P (Y = y|X = x)). Independence for 's X and Y. This is a good time to refresh your memory on double-integration. We will be using this skill in the upcom- ing lectures. 1. Recall a discrete PROBABILITY distribution (or pmf ) for a single X with the example be- x 0 1 2. f (x) Sometimes we're simultaneously interested in two or more variables in a random experiment.

Marginal Distributions (computed from a joint distribution) Conditional Distributions (e.g. P(Y = yjX= x)) Independence for r:v:’s Xand Y ... An article describes a model for the move-ment of a particle. Assume that a particle ... for (x;y) outside of A, we could plot the full surface, but the particle is only found in the given triangle A ...

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