Course Director: Dr. Robert Frost
- Course description: 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, and correction for multiple comparisons. 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 emphasis will be on theory used in modern applications in biomedical sciences, including genomics, epidemiology, and clinical and health services research. The statistical program language R will be leveraged for computational examples, problem sets and exams.
- Coursework: QBS 149 or instructor permission.
- Programming: Intermediate proficiency in R.