Computer Science and Engineering

CSE 107 Probability and Statistics for Engineers

Introduction to fundamental tools of stochastic analysis. Probability, conditional probability; Bayes Theorem; random variables and transforms; independence; Bernnoulli trials. Statistics, inference from limited data; outcomes of repeated experiments; applications to design; assessment of relative frequency and probability; law of large numbers; precision of measurements. Elements of stochastic processes, Poisson processes; Markov chains. Students cannot receive credit for this course and Applied Mathematics and Statistics 131. (Formerly Computer Engineering 107.)


Prerequisite(s): CSE 16; and AM 30 or MATH 22 or MATH 23A.



General Education Code