R for Natural and Social Scientists

Catalog description

This course introduces students to professional data analysis using the statistical programming language R. Students begin by learning core data structures, syntax, and programming fundamentals, then apply these skills to real-world datasets drawn from the scientific literature and, where appropriate, their own research. Topics include exploratory data analysis and visualization, preparing and organizing data for analysis, strategies for handling missing data, hypothesis testing, and the implementation of common machine learning methods. Emphasis is placed on clear scientific communication of results. Components: Laboratory, Class Prereqs/Coreqs: P: MATH 10 or MATH 12 or MATH 15 with a C- or better or mathematics proficiency level of 10 or above Typically Offered: Fall - even year