SDS 4020
MATHEMATICAL STATISTICS
Theory of estimation, minimum variance and unbiased estimators, maximum likelihood theory, Bayesian estimation, prior and posterior distributions, confidence intervals for general estimators, standard estimators and distributions such as the Student-t and F-distribution from a more advanced viewpoint, hypothesis testing, the Neymann-Pearson Lemma (about best possible tests), linear models, and other topics as time permits.
Instructors
Reviews
Professor Chakraborty is a very fair grader for the few assignments that you are graded on in this course (3 exams for 75% of the grade) and very generous and helpful during office hours for the homework. The fundamentals of the course are covered very quickly at the start, so you may get lost if you have misunderstandings in the first few weeks.
5/11/2024
Extremely condescending, discourages asking questions and grades harshly/unfairly. Absolutely do not recommend.
5/10/2023
She writes everything important on the board, and is usually clear with examples. She seems to genuinely care whether the students are following her, and does her best to answer questions in class and office hours. Has reasonable expectations overall.
5/8/2013