Description
This course covers the theoretical foundations and the associated computational approaches of inferential biostatistical methods for the analysis and presentation of data in clinical research (observational and experimental). Topics include analysis of assumptions and visualization; hypothesis testing; methods of comparison of discrete and continuous data including t-test, correlation, regression, and general linear models (including ANOVA). Students will utilize a statistical programming language to apply theoretical topics with real world data and will get hands on practice through an inferential data analysis project including model building and testing assumptions, hypothesis testing, presentation and dissemination based on reporducible research principles.