Detailed course offerings (Time Schedule) are available for
QMETH 201 Introduction to Statistical Methods (4) NW, QSR
Survey of principles of data analysis and their applications for management problems. Elementary techniques of classification, summarization, and visual display of data. Applications of probability models for inference and decision making are illustrated through examples. Prerequisite: either MATH 112, MATH 124, MATH 125, MATH 134, or MATH 145.
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QMETH 450 Spreadsheet Models for Managerial Decision Making (4)
Formulation and solution of business problems using operations research techniques in a spreadsheet environment. Techniques of linear and integer programming, decision analysis, network optimization, queuing, and simulation. Applications from marketing, finance, and operations. Prerequisite: I S 300.
View course details in MyPlan: QMETH 450
QMETH 490 Special Problems in Quantitative Analysis (1-6, max. 12)
Specialized quantitative techniques useful for solving business problems. Topics from operation research, statistics, computer methods. Emphasis on application. Prerequisite: either ECON 311, QMETH 201, PSYCH 213, PSYCH 218, STAT 220, STAT 301, STAT 311, or STAT 390.
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QMETH 499 Undergraduate Research (1-6, max. 9)
Research in selected problems in business statistics, operations research, decision theory, and computer applications.
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QMETH 500 Statistical Data Analysis for Management (4)
Statistical models, techniques, and tools for aiding management decisions. Use of spreadsheets in basic business problems. Probability distributions, random sampling and standard errors, hypothesis testing, multiple regression, ANOVA, chi-square tests. Prerequisite: preparation in elementary calculus and successful completion of University-administered proficiency exam.
View course details in MyPlan: QMETH 500
QMETH 501 Decision Support Models (2)
Introduction to computer-based modeling techniques for management decision making. Linear programming, decision analysis, and simulation. Formulation and interpretation. Prerequisite: QMETH 500, B A 500, or equivalent.
View course details in MyPlan: QMETH 501
QMETH 503 Practical Methods for Data Analysis (4)
Basic exploratory data analysis with business examples. Data summaries, multivariate data, time series, multiway tables. Techniques include graphical display, transformation, outlier identification, cluster analysis, smoothing, regression, robustness. Departmental credit allowed for only one of 403 and 503. Prerequisite: B A 500 or QMETH 500 or equivalent or permission of instructor. Offered: jointly with STAT 503.
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QMETH 510 Data Analysis (2)
Covers statistics and probability relevant to the collection, analysis, and interpretation of data, and deals with uncertainty in the decision-making process. Offered: A.
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QMETH 520 Managerial Applications of Regression Models (4)
Data exploration and inference using regression models for business forecasting and management. Models include simple, multiple, logistic, and nonlinear regression, use of dummy variables, transformations, variable selection, and diagnostics. Prerequisite: QMETH 500 or B A 500.
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QMETH 528 Survey Sampling Applications (4)
Introduction to design and implementation of sample surveys with emphasis on business applications. Simple random, stratified, cluster, multistage sample methods. Probability sampling, optimal allocation of sampling units. Mail, telephone, interview methods. Estimation methods, Questionnaire design. Non-response. Prerequisite: QMETH 500 or B A 500 or equivalent or permission of instructor.
View course details in MyPlan: QMETH 528
QMETH 530 Forecasting Models in Business (4)
Introduction to time series analysis and forecasting. Topics include seasonal adjustment, decomposition, exponential smoothing, moving average, and autoregression as well as model identification, estimation, diagnostics, and adaptive forecasting illustrations using real data. Prerequisite: QMETH 500 or B A 500.
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QMETH 551 Modeling with Spreadsheets (4)
Advanced formulation and modeling of business problems in a spreadsheet environment. Techniques of linear, integer, and nonlinear programming, multi-objective goal programming, and simulation. Applications from finance, marketing, and operations. Prerequisite: B A 502 or QMETH 501 or equivalent.
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QMETH 579 Special Topics in Quantitative Methods (2-4, max. 12)
Presentation of topics of current concern to students and faculty in operations research and applied business statistics. Potential topics include applications and extensions of mathematical programming, stochastic processes, discrete programming, networks models, and the application of statistical techniques.
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QMETH 580 Mathematical Programming (4)
Advanced survey of mathematical programming with applications to business problems. Includes linear, integer, stochastic, nonlinear, and dynamic programming and network optimization. Treatment includes formulation, optimality conditions, duality theory, solution algorithms. Applications to production, scheduling, marketing, finance, and equipment replacement. Prerequisite: B A 501 or equivalent and doctoral student or permission of instructor.
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QMETH 592 Stochastic Models: Queuing and Simulation (4)
Application of stochastic processes to business problems. Focuses on development and application of queuing theory and discrete event simulation. Prerequisite: stochastic processes, knowledge of high level programming language, and doctoral student or permission of instructor.
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QMETH 599 Doctoral Seminar in Operations Research (1, max. 12)
Study and research in advanced topics of operations research. Concerned with unpublished areas of research and conducted by visiting professors and departmental faculty. Prerequisite: doctoral student status. Credit/no-credit only.
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QMETH 600 Independent Study or Research (*-)
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