EECE 7204 — Applied Probability and Stochastic Processes

4 semester hoursGraduateLectureusually offered: falltypical days: M/WBostonOnlineSeattle, WALive CastTraditionalVideo Streaming

Covers the fundamentals of probabilistic treatment and the concept of random processes, which are essential for many engineering disciplines and data analysis in general. Includes the basic laws of probability, random variables and their functions, probability density and cumulative distributions, statistical averages, bounds on probability, and the central limit theorem. Outlines basic principles of statistics, including estimation of probability, confidence intervals, and order statistics. Provides an overview of detection and estimation problems, including maximum likelihood and Bayesian principles, Cramer-Rao bound, linear estimators, and hypothesis testing. Studies random sequences, with notions of convergence, laws of large numbers, and examples of Markov chains. Defines random processes, along with the concepts of stationarity, ergodicity, autocorrelation and power spectral density, and filtering operations.

Offering history

TermSectionsEnrolledCapacityFullOpen seats/section
Fall 202345619429%34.5
Fall 202435117729%42.0
Spring 2025141625%12.0
Fall 202532719914%57.3

Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.

Meeting times

Share of recent sections by weekday: M 51% · T 46% · W 51% · Th 3% · F 37%

Common patterns: MW (51% of sections), TF (37% of sections), T (6% of sections), async (4% of sections), TR (3% of sections) — in patterns, R means Thursday

Professors

Fall

Spring

Percentages are each professor's average share of the season's enrolled students in recent terms.

Unlocks

CS 7140, EECE 7310, EECE 7336, EECE 7337, EECE 7346, EECE 7397

Courses that list EECE 7204 in their prerequisites.

Links

Official catalog (EECE course descriptions) · Student reviews on RateMyHusky · All EECE courses · Plan it at numap.app