Transcription of Chapter 5: JOINT PROBABILITY DISTRIBUTIONS …
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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.
In general, if Xand Yare two random variables, the probability distribution that de nes their si-multaneous behavior is called a joint probability
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