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STAT 394

Probability I
3.0 credits

Course Description

Axiomatic definitions of probability; random variables; conditional probability and Bayes' theorem; expectations and variance; named distributions: binomial, geometric, Poisson, uniform (discrete and continuous), normal and exponential; normal and Poisson approximations to binomial. Transformations of a single random variable. Markov and Chebyshev's inequality. Weak law of large numbers for finite variance. Prerequisite: either a minimum grade of 2.0 in MATH 126, or a minimum grade of 2.0 in MATH 136. Offered: jointly with MATH 394; AWSpS.

Upcoming Time Schedule

Spring, 2023

SLN/Section Time Location Instructor
20161 A
Open

M W F 1:30PM - 2:20PM

HCK 132

Zhen-Qing Chen

PLEASE SUBSCRIBE TO UW NOTIFY IF YOU WOULD LIKE TO GET SEAT ALERTS FROM THE UNIVERSITY. PLEASE CONTINUE TO USE NOTIFY BEFORE AND AFTER QUARTER STARTS. CONTACT INSTRUCTOR FOR ADD CODE. INSTRUCTOR'S NAME WILL BE POSTED A WEEK BEFORE QUARTE STARTS.