Statistical Models:Theory/Applications

Univariate and multivariate regression, graphical displays, normal equations, Gramm-Schmidt orthogonalization and singular value decomposition, model selection and prediction, collinearity and variable selection, diagnostics: residuals, influence, symptoms and remedies, ANOVA, fixed and random effects, nonlinear models including logistic regression, loglinear models and generalized linear models, computations with datasets using statistical computer package.

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