ST701 - Statistical Theory I
- Prerequisites: MA511 and MA425 or equivalent
- Term & Frequency: Fall
- Student Audience: PhD students in Statistics and related fields
- Credit: 3 credits
- Recent Texts: Statistical Inference, second edition by George Casella and Roger L. Berger
- Recent Instructors: Brian Reich, Yichao Wu, Ryan Martin
- Background and Goals: A primary objective of the ST701 course is to present techniques and basic results of probability and convergence theory at a rigorous and advanced calculus level.
- Content: Content: In ST701 we develop the probabilistic tools and language of mathematical statistics. The course describes basic probability theory, probabilistic models for and properties of random variables, common probability distributions for univariate and multivariate random variables, and sampling distributions and convergence theory.
- Alternatives: None
- Subsequent Courses: ST702, ST793
S1 2017 Sections:
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