STAT-616 Generalized Linear Models

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Extension of regression methodology to more general settings where standard assumptions for ordinary least squares are violated. Generalized least squares, robust regression, bootstrap, regression in the presence of auto-correlated errors, generalized linear models, logistic and Poisson regression. Usually offered every spring. Prerequisite: STAT-515 and a course in calculus. Note: Students should consult the department for advice and placement testing for appropriate mathematics and statistics courses.

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