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.)
General Education Code
SR
Quarter offered
Fall, Winter, Spring
Instructor
Jose Garcia-Luna-Aceves, Mircea Teodorescu, John Musacchio, Chen Qian, Patrick Tantalo