Winter 2024
Meeting:
MWF 1:30pm - 2:20pm / HCK 132
SLN:
17237
Section Type:
Lecture
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. Course overlaps with: E E 391; STMATH 392; and TMATH 393. 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; AWSpS.
GE Requirements Met:
Natural Sciences (NSc)
Credits:
3.0
Status:
Active
Last updated:
October 8, 2024 - 1:16 am