- Spring 2020
Meeting Time:
MWF 9:30am - 10:20am
Location:
GWN 301
SLN:
16613
Joint Sections:
STAT 394 A
Instructor:
Catalog 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 STAT 394; AWS.
GE Requirements:
Natural Sciences (NSc)
Credits:
3.0
Status:
Active
Last updated:
March 23, 2020 - 2:30am