ATMO529

008976

This graduate course provides an overview of statistical methods used to interpret datasets in the atmospheric and related sciences. The objective is to provide a working knowledge of the statistical tools most commonly used. Topics include application of basic statistics (composite analysis; significance testing; curve fitting; regression analysis; correlation; and non-normal distributions), non-parametric statistical significance testing (e.g. Monte-Carlo methods and field significance), matrix methods (principal component analysis; SVD analysis; CCA), and time series analysis (harmonic analysis; power spectra; data filtering; cross-spectrum analysis; singular spectrum analysis; and wavelet analysis).

GRD - Regular Grades A, B, C, D, E

Graduate

CE - CL (Cross Listed), GIDP - GC (Global Change)

Undergraduate level statistics course and linear algebra required. Computer programming skills (C, Fortran, Matlab) and knowledge of graphical display packages needed or consent of instructor.