This course shows how to use linear statistical models for analysis in engineering and science. The course emphasizes the use of regression models for description, prediction, and control in a variety of applications. Building on multiple regression, the course also covers principal component analysis, analysis of variance and covariance, logistic regression, time series methods, and clustering. Prerequisite: CS 2100, APMA 3100 and APMA 3120.

Data mining describes approaches to turning data into information. Rather than the more typical deductive strategy of building models using known principles, data mining uses inductive approaches to discover the appropriate models. These models describe a relationship between a system's response and a set of factors or predictor variables. Data mining in this context provides a formal basis for machine learning and knowledge discovery. This course investigates the construction of empirical models from data mining for systems with both discrete and continuous valued responses. It covers both estimation and classification, and explores both practical and theoretical aspects of data mining. Prerequisite: SYS 6021, SYS 4021, or STAT 5120.

Major dimensions of systems engineering will be covered and demonstrated through case studies: (1) The history, philosophy, art, and science upon which systems engineering is grounded; including system thinking and guiding principles and steps in the `systems engineering approach¿ to problem solving; and (2) The basic tools of systems engineering analysis, including; goal definition and system representation, requirements analysis, system assessment and evaluation, mathematical modeling, and decision analysis.

A first course in the theory & practice of discrete-event simulation. Monte Carlo methods, generating random numbers & variates, spreadsheet add-ins & applications, sampling distributions & confidence intervals, input analysis & distribution fitting. Discrete-event dynamic systems, modeling, simulation logic & data structures, output analysis, model verification & validation, comparing alternative systems, simulation optimization, case studies. Prerequisite: CS 2100, APMA 3100, and APMA 3120

Focuses on the evaluation of candidate system designs and design performance measures. Includes identification of system goals; requirements and performance measures; design of experiments for performance evaluation; techniques of decision analysis for trade-studies; presentation of system evaluation and analysis results. Illustrates the concepts and processes of systems evaluations using case studies. Pre-reqs: APMA 3120, SYS 2001, & SYS 3021.

A design project extending throughout the fall and spring semesters. Involves the study of a real-world, open-ended situation, including problem formulation, data collection, analysis and interpretation, model building and analysis, and generation of solutions. Students work on the same project with the same team in SYS 4053 and 4054 in subsequent semesters.  Pre-requisite:  SYS 4053

Detailed study of a selected topic determined by the current interest of faculty and students. Offered as required. Prerequisite: As specified for each offering.

Detailed study of a selected topic, determined by the current interest of faculty and students. Offered as required.

Covers basic stochastic processes with emphasis on model building and probabilistic reasoning. The approach is non-measure theoretic but otherwise rigorous. Topics include a review of elementary probability theory with particular attention to conditional expectations; Markov chains; optimal stopping; renewal theory and the Poisson process; martingales. Applications are considered in reliability theory, inventory theory, and queuing systems. Prerequisite: APMA 3100, 3120, or equivalent background in applied probability and statistics.

Introduction to deterministic optimization models: theory, algorithms, and applications. Coverage begins with highly structured network optimization models and ends with unstructured linear optimization models. Applications include (1) telecommunications network planning and design, (2) design and utilization of transportation and distribution networks, and (3) project management and scheduling. Corequisite: SYS 2001 and APMA 3080.