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Organization, Regulations, and Courses 2017-18


QBS 120 Foundations of Biostatistics I: Statistical Inference

This is a graduate level course in statistics designed to teach the fundamental knowledge required to read and, with further study, contribute to the statistical methodology literature. An in depth overview of statistical estimation and hypothesis testing will be provided, including the method of  least squares, maximum likelihood methods, asymptotic methods,  Bayesian inference, multivariate hypothesis testing and correction for multiple comparisons, quasi and partial likelihood, M-estimation, sandwich variance, and the delta-method.  The basic elements of statistical design and sample size calculations will be introduced.  Resampling strategies will be discussed in the context of the bootstrap and cross validation, as well as simulation as a tool for statistical research. The basic elements of statistical design and sample size calculations will be introduced. The emphasis will be on theory used in modern applications in biomedical sciences, including genomics, molecular epidemiology, and translational research. The course will feature computational examples using the statistical package R, but will also give students exposure to other popular statistical packages such as SAS and STATA. The course will meet for 3 hours per week.

Instructor

Li, Frost, and T.Tosteson

Prerequisite

Multivariate calculus, introductory probability and linear algebra are required, or completion of QBS 149 and permission of instructors.

Offered

18W