Fundamental Biostatistics to Enhance Research Rigor & Reproducibility

Catalog description

This is a required graduate level course for all first year PhD students in the School of Medicine biomedical PhD programs excluding Biomedical Engineering, Population and Quantitative Health Sciences, Molecular Medicine and Clinical Translation Science. This course focuses on providing students with a basic working knowledge and understanding of best practices in biostatistics that can be applied to common biomedical research activities in numerous fields. Weekly sessions involve a combination of basic programming activities, lectures, exercises, hands-on data manipulation and presentation. Topics include experimental design and power analysis, hypothesis testing, descriptive statistics, linear regression, and others with an emphasis on when and in which experimental design a particular test is properly used. The overall goal of the course is to empower students to use these biostatistics to enhance the rigor of their experimental design and reproducibility of their primary data. The major focus is not on theory, but on a practical acquisition of a working knowledge of basic data processing analysis, interpretation, and presentation skills.