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EAS 502

Introduction to Probability Theory for Data Science

University at Buffalo 3 credits Engineering & Applied Sciences

Course Description

This course provides basic background on probability theory at a beginning graduate level. Topics include introductory probability concepts, discrete and continuous random variables and probability distributions, joint and conditional probability distributions, Bayes theorem and its applications, random sampling and data description, point estimation of parameters, discrete and continuous transforms and random incidence. If time permits the course introduces elementary stochastic processes including Bernoulli and Poisson processes.

Code
EAS 502
Credits
3
Subject
Engineering & Applied Sciences

Programs That Include This Course

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