BIOSTATS 540: Introduction to Biostatistics
[3 credits, Fall]
Prerequisites: None
This introductory course is designed to give graduate students with a limited background the basic skills in biostatistical methods, along with an introduction to the fundamental principles of statistical inference. Topics will be motivated by hands-on data from clinical applications. The course will involve hands on data analysis using R programming language.
Students with advanced experience in biostatistics may opt to take:
BIOSTATICS 690NR: Applied Regression Modeling
[3 credits, Spring]
The aim of this course is to provide fundamental statistical concepts and tools relevant to the practice of summarizing, analyzing, and visualizing data. This course will build your knowledge of the fundamental principles of statistical inference. The course will focus on the theory and application of linear regression and generalized linear regression models. We will use a variety of examples and exercises from scientific, medical, and public health research.
This course requires experience in the R programming language. DataCamp offers affordable online courses in R.