Doctoral Thesis

Doctoral Thesis

Simple and multiple linear regression, inferences and diagnostics, stepwise regression and model selection, advanced regression methods, basic design and analysis of experiments, factorial analysis.

Courses in special topics of timely interest to the profession conducted by resident or visiting faculty.

Analysis and modeling of energy production and use, material and energy efficiency, sustainability, and cost for systems, products, and services.

Introduction to probability, probability distributions, point estimation, confidence intervals, hypothesis testing, linear regression, and analysis of variance. Crosslisted with MATH 3770 and CEE 3770. Also, credit not awarded for both ISYE 3770 and MATH 3670.

Point and interval estimation of systems parameters, statistical decision making about differences in system parameters, analysis and modeling of relationships between variables.

Topics include cognitive systems engineering, human information processing, learning, interface and interaction design, task analysis, multimodal human data analysis, usability and performance evaluation in intelligent systems.

Continuous-time Markov chains, Brownian motion, martingales, and selected concentration inequalities, with occasional discussions of measure-theoretic foundations. Intended for Ph.D. students. Crosslisted with MATH 6762.