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IEMS 303 Statistics (1): Statistical methods for data analysis. Descriptive plots and statistics; observational studies and experiments; confidence interval estimation; hypothesis testing; regression and correlation. Prerequisites: Permission of instructor.
IEMS 304 Statistical Methods for Data Mining (1): Multiple linear regression with large data sets; regression diagnostics and model selection; logistic regression; regression trees; principal components analysis; association rules; time series forecasting.. Prerequisites: IEMS 303 or equivalent.
IEMS 305 Statistical Methods for Quality Improvement (1): Methods for controlling and improving industrial processes. Control charts; process capability gage repeatability and reproducibility. Multi-factor experiments; screening experiments; robust design. Prerequisites: IEMS 303 or permission of instructor.
IEMS 306 Decision Analysis (1): Theory and practice of analyzing decisions in public and private sectors. Multiple objectives; influence and diagrams; decision trees; sensitivity analysis; probability assessment; utility; human biases. Prerequisites: Permission of instructor.
IEMS 307 Quality Improvement by Experimental Design (1): Methods for designing and analyzing industrial experiments. Blocking; randomization; multiple regression; factorial and fractional factorial experiments; response surface methodology; Taguchi's robust design; split plot experimentation. Prerequisites: IEMS 303 or equivalent.
IEMS 310 Operations Research (1): Decision theory, game theory, linear algebra, linear programming, and stochastic processes. Not for graduate students in industrial engineering. Prerequisites: Calculus and linear algebra.
IEMS 313 Deterministic Models and Optimization (1): Formulation and solution of applicable optimization models, including linear, integer, nonlinear, and network problems. Efficient algorithmic methods and use of computer modeling languages and systems. Prerequisites: Permission of instructor.
IEMS 315 Stochastic Models and Simulation (1): Modeling and analysis of systems subject to uncertainty. Integrated approach to stochastic analysis and simulation. Rough-cut analysis of queuing systems. Prerequisites: IEMS 303 and permission of instructor.
IEMS 317 Discrete Event Systems Simulation (1): Computer simulation of discrete-change systems subject to uncertainty. Choice of input distributions; development of models; design and analysis of simulation experiments. Prerequisites: IEMS 303, IEMS 315, or IEMS 310, and programming experience.
IEMS 325 Engineering Entrepreneurship (1): Overview of the entrepreneurial process from an engineering perspective. Idea evaluation; planning; financing; marketing; protecting; staffing; leading; growing; harvesting. Lectures, guest speakers, case studies. a startup business plan will be written. Prerequisites: One course in accounting or finance, such as IEMS 326, or permission of instructor.
IEMS 326 Economics and Finance for Engineers (1): Principles of corporate finance; financial decisions of firms; value; risk and return; investment and capital budgeting decisions under certainty and uncertainty; performance evaluation. Prerequisites: Permission of instructor, basic understanding of probability and economics recommended.
IEMS 340 Field Project Methods (1): Use of field research methods to solve management problems. Assignments focus on individual student projects.Students define projects, design field studies and pilot tests of data collection instruments, and present results. Prerequisites: Prerequisite for nonmajors: permission of instructor.
IEMS 342 Organizational Behavior (1): A general manager's view of tools available to recruit, develop, appraise, compensate, organize and lead a team going through change. Application of psychological principles relating to human dynamics, motivation, teams, power, and organizational culture. Prerequisites: Work experience recommended.
IEMS 373 Financial Engineering (1): Theory and practice of financial engineering. Financial markets, derivative securities, risk management, mathematical models in finance. Foreign exchange, debt, equity, commodity markets. Investing, trading, hedging, arbitrage. Forwards, futures, options, swaps, exotic derivatives. Models of price dynamics, binomial models, introduction to Black-Scholes, Monte Carlo simulation. Prerequisites: IEMS 315, IEMS 326, or equivalent.
IEMS 381 Supply Chain Modeling and Analysis (1): Application and development of mathematical modeling tools for the analysis of strategic, tactical and operational supply chain problems, including facility location, customer assignment, vehicle routing, and inventory management. Related topics, including the role of information and decision support systems in supply chains. Prerequisites: IEMS 313 or IEMS 310.
IEMS 382 Production Planning and Scheduling (1): Applications of operations research methods to practical problems of production and inventory control. Forecasting; aggregate planning; deterministic and stochastic inventory models; MRP; JIT; variability; scheduling in production and service systems. Prerequisites: IEMS 313 or IEMS 310; background in probability.
IEMS 395 Special Topics in Industrial Engineering (1): Topics suggested by students or faculty, with approval of the department.
IEMS 401 Intermediate Statistics (1): Linear model theory with application to multiple regression and analysis of variance. Statistical inference methods including likelihood estimation and testing, resampling and the Bayesian approach.
IEMS 402 Engineering Management (1): Introduces students to business functions through the creation and simulation of a comprehensive business plan. Provides background for advanced engineering management courses.
IEMS 404 Financial Issues for Engineers (1): Basic engineering economy along with capital asset pricing, debt versus equity decisions, cost of capital, financial leverage, and the management of working capital. Other topics include financial justification of operational "intangibles" such as shorter lead times, better quality, and improved customer responsiveness.
IEMS 405 Marketing Issues for Engineers (1): Modern methods of procurement, marketing, and strategic planning are applied to the acquisition and sales of industrial and government products. Market structure and segmentation, sales, buying, and proposals and their evaluation are taught. Organization and development of procurement and purchasing offices.
IEMS 407 Decision Tools for Managers (1): Mathematical modeling techniques useful in managerial decision making. Deterministic models: linear programming and its extensions. Stochastic models: decision trees, queuing theory, simulation, and regression analysis. Case studies. Prerequisites: IEMS 301 or equivalent, a course in Linear Algebra.
IEMS 410 Introduction to Technology Management (1): N/A
IEMS 411 Field Research in Organizations (1): Methods for testing and evaluating proposed improvements or changes in the management of technical projects or organizations. Topics include problem identification and design and pilot test of data-gathering protocols (interviews, questionnaires, observation and records) for a real-world problem chosen by the student.
IEMS 413 Information Systems and Telecommunications Management (1): Conceptual and practical approaches to problems in telecommunications management. Understanding of strategic applications of technology in communications-based information system environments. Implementation process in complex networks.
IEMS 414 Information Systems Design and Installation (1): The objective of the course is to provide tools and to build the intuition necessary for the successful planning, deployment and use of information systems.
IEMS 415 Computer Simulation for Risk and Operations Analysis (1): Computer simulation of business and manufacturing systems that are subject to uncertainty or risk. Spreadsheet simulation and systems simulation will be covered.
IEMS 419 Technical Entrepreneurship Inside and Outside the Company (1): Research and development projects and ventures. Circumstances requiring special treatment, alternative organizational forms for venture/entrepreneurial projects, kinds of people required, financial considerations, impact on career paths, and organizational relations.
IEMS 423 Accounting Issues for Engineers (1): Basic accounting concepts such as "T" accounts, assets, liabilities, owner's equity, along with traditional cost accounting concepts such as product costing, cost terminology, job order and process costing, budgeting, cost- volume profit analysis, and standard costs as well as nontraditional cost accounting topics.
IEMS 424 Leadership and Organizational Behavior (1): Techniques for enhancing leadership, influence, and collaborative styles within a variety of organizations.
IEMS 426-1 Project Management I (1): Basic engineering economy along with capital asset pricing, debt versus equity decisions, cost of capital, financial leverage, and the management of working capital. Other topics include financial justification of operational "intangibles" such as shorter lead times, better quality, and improved customer responsiveness.
IEMS 426-2 Project Management II (1): Provides hands-on opportunity to manage project team of undergraduate students through their senior design project, usually conducted with local companies and involving real engineering projects taken from the field.
IEMS 427 Factory Operations Analysis (1): Basic principles for analyzing factory operations. Topics include analysis of inventory control policies; the differences between MRP and JIT; production planning and scheduling; fundamental relationships between cycle time, work-in-process, throughput, and variability; and the differences between Push and Pull manufacturing environments.
IEMS 428 Quality Engineering Tools (1): Overview of project management applied to technology-intensive product development projects. Emphasizes basic tools of project management success, basic process model, and key techniques and factors for project success in high-risk technology environment.
IEMS 430 Systems Analysis (1): Complex system design using contemporary examples and field exercises drawn from government and industry. Preliminary design and planning techniques for major projects, development of requirements, transition to conceptual design, writing proposals, system management, and system testing. System tools such as PPBS, PERT, PERT-COST, and CPM.
IEMS 432 Systems Engineering (1): Design and development of complex, multidisciplinary systems. Establishing systems requirements, detail design process, problems and methods, generating alternative designs, testing and evaluation, and operational use.
IEMS 433 Theory and Practice of Evaluation (1): A general theory of evaluation using objective and subjective measurement. A taxonomy of evaluation allowing choice of appropriate methods at all system levels. Design and critique evaluations. Education, health care, criminal justice, churches, closed-circuit TV, and computer systems.
IEMS 434 Systems Methodology (1): Introduction to the concept of a system and unstructured, multidisciplinary problems. Fundamental systems models and concepts, modeling, and selected decision-making approaches.
IEMS 435 Introduction to Stochastic Simulation (1): Discrete event simulation modeling. Design and analysis of simulation experiments. Simulation programming in standard languages. Applications to manufacturing and services. Prerequisites: IEMS 302 and IEMS 303, or equivalent.
IEMS 436 Engineering Project Management (1): Methods for planning, evaluating, and controlling engineering project performance, schedule, and cost; methods for project team management; special problems.
IEMS 437 Strategic Management for Engineers (1): Draws from all functional areas of an enterprise to provide strategic direction to an organization. Teaches strategies for effective management. A framework is developed to understand the interrelation of accounting, finance, operations, engineering, human resources, and marketing.
IEMS 439 Business Laboratory (1): This course provides students with an opportunity to integrate their understanding of the various business disciplines in the creation of a comprehensive business plan. Prerequisites: IEMS 423, IEMS 425, and IEMS 431.
IEMS 445 Decision and Risk Analysis (1): Theory and practice of decision making under uncertainty. Decision trees, influence diagrams, the value of information; Bayesian approaches, including conjugate and predictive distributions; utility theory foundations, risk preference, multi-attribute utility; applications such as earthquake risk analysis, pumped storage sitting, setting pollution standards, and medical decision making. Prerequisites: IEMS 302 or equivalent.
IEMS 448 Probabilistic Reasoning in Expert Systems (1): Bayesian inference: review and introduction; an overview of rule-based systems, methods of uncertainty propagation in rule-based systems; causal networks; structure and properties; probability propagation in singly and multiply connected causal networks; adductive inference; generating explanations; applications. Prerequisites: IEMS 302 or equivalent probability background.
IEMS 450-1,2 Mathematical Programming I, II (1)(1): First Quarter: Linear programming formulation, simplex algorithm, optimality conditions, duality, practical computation, extensions, applications, and case studies. Second Quarter: Constrained and unconstrained nonlinear optimization, networks, discrete optimization, applications, and case studies. Prerequisites: Linear algebra and calculus.
IEMS 452 Combinatorial Optimization (1): Efficient methods and min-max results for combinatorial optimization problems including minimum spanning trees, shortest paths, maximum flows, minimum cost flows, matching; polyhedral combinatorics; complexity theory. Prerequisites: IEMS 450-1 or equivalent.
IEMS 454 Large-Scale Optimization (1): Practical methods for solving large optimization problems on a computer, principally the simplex method of linear programming. Organization of storage, sparse elimination, LU updating, choice of simplex pivots, partial and steepest-edge pricing, and numerical stability. Nonlinear, combinatorial, or special-structured optimization as appropriate. Prerequisites: IEMS 450-1 or equivalent.
IEMS 457 Integer Programming (1): Methods for NP-hard discrete optimization problems including general methods like branch and bound and cutting planes, as well as special purpose branch-and-cut methods and heuristics. Prerequisites: IEMS 450-1 or equivalent.
IEMS 458 Advanced Mathematical Programming (1): Polyhedral theory, decomposition, projection, modified simplex algorithm, primal and primal-dual interior-point methods, semi-definite and convex programming.
IEMS 459 Design and Analysis of Heuristics (1): Design and analysis of heuristic algorithms. Construction and improvement heuristics; genetic algorithms, simulated annealing and tabu search. Applications including logistics and production planning.
IEMS 460-1,2 Stochastic Models (1)(1): Bernoulli processes, Poisson processes, Markov chains, Markov processes, renewal theory, regenerative process, and queuing models. Theory and applications. Prerequisites: Permission of instructor.
IEMS 461 Advanced Stochastic Models (1): Martingales, Brownian motion, branching processes, and stationary processes. Prerequisites: IEMS 460-1 or equivalent.
IEMS 464 Advanced Queuing Theory (1): Queuing theory and the stochastic processes arising from the study of queuing and storage systems. Overview of classical results and recent topics (bounds and approximations, queuing networks). Applications in manufacturing systems. Advanced level. Prerequisites: IEMS 435 and IEMS 460-1 or equivalent.
IEMS 465 Simulation Experiment Design and Analysis (1): Point of error estimation, experiment design, run-length control, variance reduction, optimization via simulation, and input modeling for discrete-event stochastic simulation. Prerequisites: IEMS 435 and IEMS 560-1, or equivalent.
IEMS 466 Computational Methods in Applied Probability (1): Algorithms for computing the stationary distribution of Markov chains; transient results for Markov chains; algorithms for queuing networks; transform methods. Prerequisites: IEMS 460-1 or equivalent.
IEMS 468 Stochastic Control (1): Optimal control of Markov chains, dynamic programming, finite horizon and discounted models, and applications in operations research. Prerequisites: IEMS 460-1 or equivalent.
IEMS 473 Financial Engineering II (1): Advanced derivative securities. Fixed income markets and derivatives. Risk management. Mathematical models and computational tools of financial engineering. Prerequisites: IEMS 373 Financial Engineering I.
IEMS 480-1,2 Production and Logistics I, II (1)(1): First Quarter: Introduction to production/logistics including: multi-objective, stochastic and dynamic facility location problems, multi-echelon and multi-item inventory models and heuristic, approximate and exact vehicle routing algorithms. Second Quarter: Introduction to production/distribution facility design and control, capacity management, push and pull production systems: MRP, JIT, ConWIP; introduction to deterministic and stochastic production scheduling: job shop, flow shop. Prerequisites: IEMS 450-1 and at least concurrent enrollment in IEMS 460-1.
IEMS 482 Routing and Scheduling (1): Efficient allocation of resources to tasks over time. Topics include machine scheduling in production processes and vehicle routing in distribution systems. Prerequisites: IEMS 450-1 or equivalent.
IEMS 483 Reliability and Maintenance in Production Systems (1): Topics in reliability, engineering, optimal maintenance and replacement policies; repair and maintenance of automated production systems; control of manufacturing systems with limited repair capacity. Prerequisites: IEMS 460-1 and IEMS 480-2.
IEMS 484 Inventory and Distribution Systems (1): Multistage inventory and production models, multiproduct systems, distribution systems, and random yield models. Prerequisites: IEMS 480-1,2.
IEMS 485 Stochastic Models of Manufacturing Systems (1): Modeling and analysis of manufacturing and service systems, using stochastic and simulation techniques. Topics varying with research trends but generally addressing questions of system design, performanceevaluation, and managment insight. Prerequisites: IEMS 460 and IEMS 480-1,2.
IEMS 486 Supply Chain Management (1): Planning models and practical tools for inventory control, distribution management and multi-plant coordination. Exploring robust tools and off the shelf software packages useful in dealing with strategic decisions, tactical decisions, and operational decisions in logistics management.
IEMS 487 Investment Decisions and Engineering Analysis (1): Economic and operations research analysis of project evaluation, equipment investment and replacement, and facility location and investment. Project evaluation in the public sector, including cost-benefit analysis and environmental and energy conservation. Prerequisites: IEMS 488 or permission of instructor.
IEMS 488 Economics and Decision Analysis (1): Investment project evaluation: time value of money, treatment of risk, asset evaluation; decision trees, utility theory and risk attitude, multiobjectives. Public sector decision analysis, including cost/benefit analysis, and cost/effectiveness analysis. Prerequisites: Calculus.
IEMS 489 Transportation Network Design and Operation (1): Interrelationship between transportation, inventory, and production costs; design and operation of physical distribution and collection systems; role of terminals and transshipments; relevant analysis and methodologies. Prerequisites: IEMS 480-1.
IEMS 497 Special Topics in Industrial Engineering (0.5) : Topics selected from work of current interest in industrial engineering and management sciences.
IEMS 499 Projects (1-3) : Special projects under faculty direction. Permission of instructor and department required. May be repeated for credit.
IEMS 590 Research (1-3) : Independent investigation of selected problems pertaining to thesis or dissertation. May be repeated for credit.
Related Courses
CHEM_ENG 459 Selected Topics in Design or Simulation and Monitoring (1): Topics on the construction and analysis of process models; classification of process behavior from measurements; development of black-box models; and statistical analysis of models and measurements.
CIV_ENG 471-1,2 Transportation Systems Analysis I, II (1)(1): Applications of optimization methods to analysis, design, and operation of transportation and logistics networks. Network equilibrium; flow prediction in congested multicommodity networks; vehicle routing and fleet management; dynamic and stochastic transportation network modeling. Prerequisites: IEMS 310 or equivalent background.
CIV_ENG 479 Transportation Systems Planning and Management (1): Functional and structural description of transportation systems; characteristics of major US transportation modes; transportation analysis, planning, problem-solving, and decision-making methods illustrated through urban, freight, and intercity case studies.
CIV_ENG 480-1,2 Travel Demand Analysis and Forecasting I, II (1)(1): Introduction and application of statistical, econometric, and marketing research techniques to study and forecast travel behavior. First Quarter: Introduction to theory, analysis, and model development. Second Quarter: Advanced theory, disaggregate choice models, and prediction methods.
CIV_ENG 482 Evaluation and Decision Making for Infrastructure Systems (1): Theories and methods of evaluation and choice from alternatives for transportation and other infrastructure projects and systems. Economic, quantitative, and judgmental methods for both a priori and before-and-after evaluation. Measurement, modeling, analysis, and presentation problems. Prerequisites: CIV_ENG 306.
DECS 444 Stochastic Models for Management and Economics (1): Stochastic methods and their applications, emphasizing statement, heuristic derivation, and interpretation of main results. Topics include Markov processes, martingales, Poisson processes, Brownian motion, stochastic calculus, and stochastic control. Prerequisites: Knowledge of probability theory.
ECON 410-1,2,3 Microeconomics (1)(1)(1): Modern theory of consumer behavior and of the firm; competitive equilibrium; game theory; informational asymmetries in markets. (Required sequence.)
ECON 412-1,2 Economic Theory and Methods (1)(1): Methodological aspects of modern economic theory. Problems in economic decision making, strategic interaction, and welfare economics.
ECON 414-1,2,3 Economics of Information (1)(1)(1): Asymmetric information in markets and organizations. Topics include search, signaling, bidding, rational expectations, moral hazard, principal-agent problems, and contract-mechanism design.
EECS 333 Introduction to Communication Networks (1): Data communication basics. Telephone, cellular, cable and computer networks. Layered network architectures, models and protocols. Switching, routing, flow control, and congestion control. Medium access control, ARQ, and local area networks. Queuing models and network performance analysis. Prerequisites: MATH 330 or equivalent.
EECS 336 Design and Analysis of Algorithms (1): Analysis techniques: solving recurrence equations. Algorithm design techniques: divide and conquer, the greedy method, backtracking, branch-and-bound, and dynamic programming. Sorting and selection algorithms, order statistics, heaps, and priority queues. Prerequisites: EECS 310, EECS 311, or permission of instructor.
EECS 479 Nonlinear Optimization (1): Numerical solution of unconstrained optimization problems, nonlinear least squares and nonlinear systems of algebraic equations, large-scale nonlinear optimization, quadratic programming, and constrained optimization. Prerequisites: EECS 328.
EECS 486 Queuing Models for Computer Communication (1): Queuing models for design and analysis of computer communication networks. Elementary queuing analysis. Networks of queues: open, closed, and Jackson. Routing and flow controls. Applications to packet radio, satellite, and local networks. Prerequisites: EECS 422.
EECS 490 Advanced Robotic Systems (1): Dynamic calculation and robot simulation, design of robot control systems, force sensors and compliance, robot programming language, different planning of trajectory, and task planning. Prerequisites: EECS 390.
ES_APPM 442-1,2,3 Stochastic Differential Equations (1)(1)(1): Brownian motion and Langevin's equation. Ito and Stratonovich stochastic integrals. Stochastic calculus and Ito's formula. SDEs and PDEs of Kolmogorov, Fokker-Planck, and Dynkin. Boundary conditions, exit times, exit distributions, stability. Asymptotic analysis of SDE, the Smoluchowski-Kramers approximation, and diffusion approximation to Markov chains. Applications.
MATH 310-1,2,3 Probability and Statistics (1)(1)(1): First Quarter: Discrete probability spaces, random variables, expected value, combinational problems, special distributions, independence, and conditional probability. Second Quarter: Integrating density functions, convolutions, law of large numbers, central limit theorem, random walk, and stochastic processes. Third Quarter: Elementary decision theory, estimation, testing hypotheses, Bayes procedures, linear models, and nonparametric procedures.
MATH 450-1,2 Probability (1)(1): Probability spaces, random variables, distribution functions, conditional probability, laws of large numbers, and central limit theorem. Random walk, Markov chains, martingales, and stochastic processes.
MECH_ENG 442 Metal Forming (1): Metal forming processes: drawing, extrusion, rolling, forging, and sheet metal forming. Process analysis and design: force estimation, friction and redundant work effects, temperatures generated, defects, and process and equipment limitations.
MECS 462 Decision Theory (1): Foundations of the theory of decision under uncertainty. Special focus on axiomatic derivatives of numerical representations of preferences, and on behavioral versus cognitive data as observational definitions of theoretical terms. Covers axiomatic derivations of utility in general, and the classical works of von Neumann and Morgenstern, Savage, Anscombe, and Aumann on expected utility. Additional topics may include applications and attitudes toward risk; paradoxesand violations of expected utility; generalizations and variations of expected utility-as well as alternative theories, with applications to economics.
MORS 459 Managing Technology: Development and Deployment (1): Importance of technology as a determinant of global competitiveness. Examines the quality of techno-business intelligence; external tech-sourcing and alliance development; valuation and control of intellectual property; speed and finesse in adapting technology, standards, specifications, and designs to meet worldwide market needs; and properly structuring and organizing firms to be first-class global technology players. Prerequisites: MORS 430.
OPNS 452 Operations Scheduling (1): Decision models for sequencing customized operations, assigning standardized processes, and scheduling nonrepetitive activities.
OPNS 453 Inventory Management (1): Planning and control of procurement and production quantities and processing capacities. Forecasting; inventory systems; just-in-time production; material requirements planning; capacity management. Prerequisites: OPNS 430 or permission of instructor.
OPNS 455 Logistics and Supply Chain Management (1): What are the key capabilities a supply chain must develop to support the business strategy of a firm? What is the relationship between the desired capabilities and the structure of a supply chain? This course provides a framework to answer these questions. We define supply chain structure in terms of the following drivers of performance: facilities, information, inventory and transportation. The relationship between structure and performance is analyzed using various case studies that require students to develop analytical spreadsheet models to support their decision making. Prerequisites: OPNS 430 or OPNS 438 or IEMS 471 or MECN 430.
SOCIOL 403 Field Methods (1): Application of the methods of case study, interviewing, and participant observation.
STAT 325 Survey Sampling (1): Probability sampling, simple random sampling, error estimation, determination of sample size, stratification, systematic sampling, replication and pseudoreplication methods, ratio and regression estimation, cluster sampling, multiphase sampling, and nonsampling errors.
STAT 350 Regression Analysis (1): Simple linear regression and correlation, multiple regression, residual analysis, stepwise regression and other methods of selecting subsets of variables, multicollinearity and shrinkage estimation, and nonlinear regression.
STAT 351 Design and Analysis of Experiments (1): Methods of designing experiments and analyzing data obtained from them: one-way and two-way layouts, incomplete block designs, Latin squares, Youden squares, factorial and fractional factorial designs, random-effects and mixed-effects models, and split-plot and nested designs.
STAT 352 Nonparametric Statistical Methods (1): Survey of nonparametric methods with emphasis on understanding their application. Topics include sign test, Wilcoxon signed-rank test, Mann-Whitney test, Kolmogorov-Smirnov test, Friedman test, Kruskal-Wallis test, nonparametric confidence intervals, nonparametric regression, and rank correlation.
STAT 355 Analysis of Qualitative Data (1): An introduction to the analysis of qualitative data. Measures of association, long-linear models, and logits and probits.
STAT 420-1,2,3 Advanced Statistics: Introduction to Statistical Theory and Methodology (1)(1)(1): First Quarter: Distribution theory, characteristic functions, moments and cumulants, random variables, sampling theory, and common statistical distributions. Second Quarter: Methods of estimation, hypothesis tests, confidence intervals, least squares, likelihood methods, and large-sample methods. Third Quarter: Theories of inference, multivariate methods, and contingency tables.
STAT 448 Multivariate Statistical Methods (1): Multivariate normal distribution, Hotelling's T2-test, multivariate analysis of variance, discriminant analysis, canonical correlation, principal components, and factor analysis. Use of computer packages.
STAT 453 Survival Analysis (1): Life-table construction, Kaplan-Meier estimation, exponential survival distributions, Weibull distributions, and Cox regression models.
STAT 454 Time-Series Analysis (1): Harmonic analysis, power spectra, filtering, cross-spectra, linear processes, and forecasting.
STAT 455 Advanced Analysis of Qualitative Data (1): Probit, logit, log-linear, and latent-class models. Multi-dimensional contingency tables; polytomous responses with continuous independent variables.
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