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EE 178: Probabilistic Systems Analysis

Introduction to probability and its role in modeling and analyzing real world phenomena and systems, including topics in statistics, machine learning, and statistical signal processing. Events, sample space, probability, conditional probability, independence, Bayes rule. Discrete and continuous random variables. Functions of random variables. Expectation. Linear MSE estimation. Conditional expectation. MSE estimation. Quantization. Parameter estimation. Classification. Estimating the statistics of random variables. Moment generating function. Inequalities and limit theorems. Confidence intervals. Prerequisites: Calculus at the level of MATH 51, CME 100 or equivalent.
Terms: Spr | Units: 3-4 | UG Reqs: GER:DB-EngrAppSci
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