IE 553 Applied Statistical Modeling and Data Analysis
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Generalized linear models (e.g., binomial, Poisson, beta, gamma, multinomial regression for count, proportion, and multi-categorical data), quasi-likelihood methods for dealing with under- and over-dispersion; random effect models for grouped, hierarchical, and panel data; generalized additive models to discover the nonlinear transformations in all of the previous regression problems; applications to real data using a statistical software.
Credit units: 3 ECTS Credit units: 5.
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