Statistical Inference

Catalog description

This course will provide an introduction to the fundamentals of probability and statistics that are the foundations of analytical methods in public health research. Topics to be covered include axioms of probability, common distributions (normal, binomial, Poisson), expectations, variances, convergence theorems, parameter estimation (method of moments, maximum likelihood, Bayesian methods), confidence intervals, hypothesis testing (likelihood ratio, Wald and score tests), bootstrap methods, permutation testing. All theoretical material will be motivated with problems from epidemiology, biostatistics, environmental health and other public health areas. Background in algebra and calculus is required. This is a doctoral level course and is open to Masters students who have the requisite background.