Introduction to Stochastic Processes - Lecture Notes

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Introduction to Stochastic Processes - Lecture Notes (with 33 illustrations)Gordan itkovi Department of MathematicsThe University of Texas at AustinContents1 probability Random variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Countable sets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Discrete random variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Expectation.

probability mass function (p 0;p 1;:::), you simply need to compute the sum P 1 i=1 p i. If it happens to be equal to 1, you can safely conclude that X never takes the value +1. Otherwise, the probability of +1is positive. The random variables for which S= f0;1gare especially useful. They are called indicators.

  Introduction, Probability, Stochastic