STAT 651 - Probability Theory

Credits: [3]

Description: To build up the theoretical foundation of statistics, this course provides graduate-level non-measure theory probability trainings. The theory will be developed along with examples and problems demonstration, which is suitable for master program and PhD program trainings. Among the topics: axioms of probability, counting, conditional probability and independence, discrete and continuous random variables, sums of random variables, simple random walk and Poisson process, conditional expectation, univariate and multivariate distributions, multivariate normal distribution, and the distributions arising from the normal distribution, moments, transformations, inequalities, and convergence.
Course ID: 057097
When Offered: Fall
Recommended: Prior training on real analysis, multivariate calculus, and linear algebra.
Components: Lecture
Grading Method: A-F