Mathematical Statistics
An MIT OpenCourseWare course covering the theoretical foundations of statistical inference. Topics include decision theory, point estimation, confidence intervals, and hypothesis testing, followed by large sample theory, asymptotic efficiency of estimators, exponential families, and sequential analysis. The course builds on probability theory to develop rigorous methods for evaluating and comparing statistical procedures, emphasizing proofs and derivations over computation. Materials include lecture notes, problem sets, and exams, following MIT's standard OpenCourseWare format for advanced mathematics offerings. The course is aimed at students who already have a background in probability and want a formal treatment of inference theory rather than applied statistical methods. As with other MIT OCW courses, all materials are free to access and there is no certificate offered, since OCW is a self-study archive rather than an instructor-led platform.