Mathematics
MATH 3181: Advanced Probability and Statistics
Lecture - 4 credits
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- 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