Application-based course in nonparametric statistics. Modern toolbox of visualization and statistical methods for the analysis of data, examples drawn from immunology, microbiology, cancer research and ecology. Methods covered include multivariate methods (PCA and extensions), sparse representations (trees, networks, contingency tables) as well as nonparametric testing (Bootstrap, permutation and Monte Carlo methods). Hands on, use R and cover many Bioconductor packages.
Minimal familiarity with computers, instructor consent via permission numbers is required.
- Accelerated 3-week course with limited enrollment. Students must have either completed the first 6 chapters at tryr.codeschool.com or provide a transcript of another course in R programming to request a permission number from the instructor, Susan Holmes. If permitted to enroll in the course, students must attend every class as well as commit to taking the course for either a letter grade or CR/NC upon enrollment.
- This course will be co-taught by Susan Holmes and Wolfgang Huber.
- This course follows a non-standard schedule. Please see the Summer Session Non-Standard Schedule Calendar for special deadlines.
- Cross-listed as STATS 366.