EE126: Probability and Random Processes - Lecture 1 ...
OutlineLogisticsIntroductionModelExample sEE126: Probability and Random ProcessesLecture 1: Probability ModelsAbhay ParekhUC BerkeleyJanuary 18, 2011OutlineLogisticsIntroductionModelExa mples1Logistics2Introduction3Model4Examp lesOutlineLogisticsIntroductionModelExam plesWhat is this course about?Most real-world problems involve uncertainty1Predictions:Will you like this class? Will you get an A ?Will the Giants win the world series next year? What are theodds?2Strategy/Decision MakingHow should you bet in blackjack?Should you buy shares of AAPL?
probability 4 The probabilities summed over all of the base outcomes always equals 1 Example: Toss a fair coin twice 1 Base outcomes are HH,HT,TH,TT 2 This covers all the possibilities. M.E. 3 Each of these outcomes is equally likely 4 Assign each outcome a probability of 0:25. The list (set) of base outcomes is called the Sample Space.
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