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Beth Andrews is an Associate Professor in the Department of Statistics and Data Science at Northwestern University. She completed her Ph.D. in 2003 at Colorado State University. Her research interests encompass time series analysis, spatial statistics, stochastic processes applications, robust statistics, extreme value theory, and financial mathematics. She focuses on model fitting and prediction of nonlinear, non-Gaussian processes observed in space and time. Her work has significant applications in economics, finance, geosciences, and signal processing. Some of her notable contributions include rank-based estimation of autoregressive moving average time series models, maximum likelihood estimation of alpha-stable autoregressive processes, and rank-based estimation of GARCH processes. Additionally, she has worked on model identification for infinite variance autoregressive processes.
Standard PhD requirements for TGS departments including Chemistry, Physics, and Sociology.