R Programming for Science Models, Simulation, and Data Analysis

The Programming language R has evolved quickly into a premier tool for scientists. This course teaches R programming through examination of models, simulation, and data analysis in the sciences. Examples of exponential growth and decay taken from the biological and chemical literature will provide the basis for developing R programming skills. Finally, the use of linear and non-linear regression to compare actual data with models will be examined. The course will be entirely project based. A final project will be based on a topic of interest to the student. Prerequisite: An introductory course in the sciences (Chem 10401, Bio 10200, EAS 10600, or PHYS 20700)