EAS 6660 - [Applied Multivariate Statistics]

Spring (offered alternate years). Next Offered: 2019-2020. 3 credits. Letter grades only.

Prerequisite: multivariate calculus, matrix algebra, and two statistics courses.

T. Ault.

Statistical techniques for multivariable data. Topics include multivariate exploratory data analysis, the multivariate normal distribution, parametric and nonparametric inference about multivariate means, principal component analysis, canonical correlation analysis, discriminant analysis, and cluster analysis. Emphasizes geophysical applications, using primarily atmospheric and oceanographic data as examples, but the development is general enough to be of broader interest.