Advanced Inference I. (3-0) 3 Credit Hours

Catalog description

Prerequisite: STA 5513 or equivalent and Doctoral standing. This course is a brief discussion of measure theory and Lebesgue integration, statistical models, location and scale families of distributions, exponential families of distributions, sufficiency, factorization theorem, completeness, ancillarity, Basu’s theorem, Fisher information, Kullback-Leibler divergence, elements of statistical decision theory, basic concepts for point estimation, best-unbiased estimation, Rao-Blackwell theorem, Lehmann–Scheffé theorem, Cramér–Rao (information) inequality, maximum likelihood estimation (MLE), and profiled/concentrated likelihood. This course has Differential Tuition.