MATH 529. Applied Regression Analysis. 4 Credits.
Techniques for fitting regression models are developed and applied to data using statistical software. Topics include simple linear regression, multiple regression, inference, regression diagnostics, remedial measures, model selection, logistic regression, and an introduction to nonlinear regression models.
P: Graduate standing. REC: Introductory Statistics, Calculus I, and Linear Algebra. Knowledge of Excel and R.
MATH 555. Applied Mathematical Optimization. 3 Credits.
Analytical and numerical optimization techniques; linear, nonlinear, integer, and dynamic programming. Techniques applied to problems of water, forest, air and solid-waste management.
P: gr st.
MATH 630. Design of Experiments. 4 Credits.
Statistical theory and practice underlying the design of scientific experiments, and methods of analysis. Replication, randomization, error, linear models, least squares, crossed and nested models, blocking, factorial experiments, Latin squares, confounding, incomplete blocks, split-plots.
P: Graduate student status, Introductory Statistics course completion
MATH 631. Multivariate Statistical Analysis. 4 Credits.
Principles and practice in the analysis of multivariate data. Correlation, partial correlation, principle components, factor analysis, discriminant functions, canonical correlation, cluster analysis, multidimensional scaling. Emphasis on computer analysis of actual data.
P: Graduate status and completion of an Introductory Statistics course. REC: Calculus I, Linear Algebra, and Regression Analysis.
MATH 698. Independent Study. 1-3 Credits.
P: gr st.
MATH 728. Abstract Algebra I - Noncommutative Algebra. 3 Credits.
Major topics of the course are groups and rings without commutativity assumption. Topics in detail include: homomorphisms and group actions, the Sylow Theorem, Solvable and Nilpotent groups, module theory, primitive and Artinian rings, Offered online format only.
P: Abstract algebra course at senior level or consent of instructor.