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Events

This content introduces discrete random variables (RVs) and their probability mass functions (pmfs). It covers key concepts such as the meanings of P(X=2) and P(X>2), as well as common pmfs including Uniform, Bernoulli, and Poisson distributions. The materials also explore the independence of multiple random variables and how to work with maxima and minima in probability problems. Ideal for those looking to grasp fundamental statistical concepts in discrete settings.

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Events

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  1. Events

  2. For ω ϵ Ω, X (ω) ϵ IR. What does P(X=2) mean? What does P(X>2) mean? Ch. 2 Intro to Discrete Rvs

  3. Shorthand • For B⊂IR,

  4. 2.2 Discrete RVs

  5. Probability Mass Functions

  6. Common pmfs • Uniform • Bernoulli pX(1) = p pX(0) = 1-p

  7. Common pmfs • Poisson

  8. 2.3 Multiple RVs

  9. Independence for 2 RVs

  10. Independence for Multiple RVs

  11. Max and Min Problems

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