Syllabus
Basic notions, t-tests and rank tests.
Resampling methods.
Multivariate statistical methods I: random vectors, multivariate normal distribution, Hotelling's test, multiple testing.
Nonparametric regression: kernel estimators of densities and regression curves.
Multivariate statistical methods II: principal components, factor analysis, discriminant and cluster analysis, further dimension reduction methods.
Other computational procedures.
Annotation
Introduction to nonparametric, multivariate, and resampling methods. Statistical models, computational aspects, applications.