Mathematics

# MATH 3181: Advanced Probability and Statistics

Lecture - 4 credits

ND

EI

IC

FQ

SI

AD

DD

ER

WF

WD

WI

EX

CE

- Focuses on probability theory needed to prepare students for research and advanced coursework in the physical and data sciences.
- Examples and homework problems come from physics, chemistry, biology, computer science, data science, and electrical engineering.
- Topics include sample spaces; conditional probability and independence; discrete and continuous probability distributions for one and for several random variables; expectation; variance; special distributions including binomial, Poisson, and normal distributions; law of large numbers; and the central limit theorem.
- Introduces basic statistical theory including estimation of parameters, confidence intervals, and hypothesis testing.
- This course is proof-based and emphasizes developing students' abilities in mathematical proof writing.

Focuses on probability theory needed to prepare students for research and advanced coursework in the physical and data sciences.

*Show more.*Pre-requisites