Introduction to Probability

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LECTURE NOTESCourse 2000Introduction to ProbabilityDimitri P. Bertsekas and John N. TsitsiklisProfessors of Electrical Engineering and Computer ScienceMassachusetts Institute of TechnologyCambridge, MassachusettsThese notes are copyright-protected but may be freely distributed forinstructional nonprofit Sample Space and Probability . . . . . . . . . . . . . . . . Sets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Probabilistic Models . . . . . . . . . . . . . . . . . . . . . . . Conditional Probability . . . . . . . . . . . . . . . . . . . . . Independence . . . . . . . . . . . . . . . . . . . . . . . . . . Total Probability Theorem and Bayes Rule.

Preface These class notes are the currently used textbook for “Probabilistic Systems Analysis,” an introductory probability course at the Massachusetts Institute of

  Introduction, Probability, Introduction to probability