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MATH 5353. APPLIED LINEAR MODELS. 3 Hours.

The course covers, at an operational level, three topics: 1) the univariate linear model, including a self-contained review of the relevant distribution theory, basic inference methods, several parameterizations for experimental design and covariate-adjustment models and applications, and power calculation; 2) the multivariate linear model, including basic inference (e.g. the four forms of test criteria and simultaneous methods), applications to repeated measures experiments and power calculation; and 3) the univariate mixed model, including a discussion of the likelihood function and its maximization, approximate likelihood inference, and applications to complex experimental designs, missing data, unbalanced data, time series observations, variance component estimation, random effects estimation, power calculation and a comparison of the mixed model's capabilities relative to those of the classical multivariate model. Knowledge of the SAS package is required. Prerequisite: MATH 5358/STATS 5358 (Regression Analysis) or equivalent.

Mechanical and Aerospace Engineering - Undergraduate Programs

http://catalog.uta.edu/engineering/mechanical/undergraduate/

...Engl 1301, Math 1426, Math 2425, Math 2326...POLYMER MATERIALS SCIENCE MSE 5353 FUNDAMENTALS OF SUSTAINABLE...

Interdisciplinary Graduate Programs

http://catalog.uta.edu/engineering/interdisciplinaryprgrms/graduate/

...MATH 5305/STATS 5305 or MATH 5355/STATS 5355 or permission of instructor. MATH 5353...

Electrical Engineering - Graduate Programs

http://catalog.uta.edu/engineering/electrical/graduate/

...Electrical Engineering Department in math, science and engineering...Approved Substitution: EE EE 5353 EE 5354 EE...