Concentration inequalities are used in probability theory to bound the deviation of a random variable from its expected value. They can be used to show that sums of independent random variables are close to their expectation with a large probability, and that other functions of independent random variables also exhibit this behavior. Concentration inequalities vary depending on how much information about the random variable is needed.
UC Berkeley
Fall 2022
CS 70 presents key ideas from discrete mathematics and probability theory with emphasis on their application in Electrical Engineering and Computer Sciences. It addresses a variety of topics such as logic, induction, modular arithmetic, and probability. Sophomore mathematical maturity and programming experience equivalent to an Advanced Placement Computer Science A exam are prerequisites.
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