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Mathematical and statistical concepts employed in the solution of managerial problems. Applications of functions, elements of calculus, and linear algebra. Introduction to probability, frequency distributions, statistical inference, and regression and correlation. For non-M.B.A. students only. (Fall, spring, and summer)
Survey of analytical models for decision making and their applications. Topics include probabilistic, deterministic, and sequential models, single- and multiattribute utility theory, graphical models, Bayesian inference, forecasting, and concepts from game theory. Prerequisite: MBAd 220 and 231. (Fall and spring)
Industrial purchasing and materials management principles and practices. Organization and functions in materials management. Determination of requirements, supplier qualifications, source selection, buying practices, policies, and ethics. International purchasing. (Fall and spring)
Supply chain management in production, service, and public organizations. Analytical tools for planning and establishing operating systems and for their operation, control, and modification. Examination of processes, products, services, equipment, and facilities. Relationships of human systems and operating systems. (Fall)
Inventory and production control concepts, techniques, and strategies for effective integration with basic finance, marketing, and manufacturing objectives. Forecasting methods, material requirements planning systems, distribution requirements planning techniques, process control, and classical reorder-point inventory models. (Fall)
Concepts and methods for making complex decisions in both business and government; identifying criteria and alternatives, setting priorities, allocating resources, strategic planning, resolving conflict, and making group decisions. (Fall and spring)
Framework, processes, and technical components for building decision support systems dealing with unstructured and underspecified problems from managerial and organizational perspectives. Construction and exploration of decision support system models. Prerequisite: Mgt 220 or permission of instructor.(Fall and spring)
Modeling approaches in supply chain management; optimization of cost and service. Alternatives available to the manager, given the economic situation, competitive conditions, and regulatory environment of the several transportation modes. Model location theory and logistics network planning and design. Prerequisite: Mgt 222. (Spring)
Basic procurement and logistics methods and techniques that influence formulation of a firm’s strategic policy. Traditional and updated and improved systems for controlling capacity and output. Examination of productivity analysis, cost control, materials planning, and other topics to ensure that the strategy formulation/operations function contributes to overall profit. (Spring)
Advanced topics in management decision making. Topics vary but usually include Bayesian statistics and decision analysis, graphical models, strategic decision making, and business applications of game theory. Prerequisite: Mgt 220, 224, or permission of instructor. (Spring)
Principles and concepts essential to effecting large procurement programs. Planning, sourcing, and contractual design for diverse acquisitions. Emphasis on federal government policy with comparison of buying at other governmental levels and the private sector. (Spring)
Practical examination of how projects can be managed from start to finish, including specific emphasis on planning and controlling to avoid common pitfalls. Identifying needs, defining requirements, project costing, scheduling, resource allocation, and project politics. (Fall, spring, and summer)
Practical examination of project management concepts by quantitative application using various software tools. Research in real cost data to support project calculations. Prerequisite: Mgt 231, 267.
Fundamentals of contract management from a project manager’s perspective. The outsourcing process, associated project strategies, and legal elements. Acquisition planning, vendor selection, contract formulation, and performance control.
Foundations and methodologies for problem solving in multicultural project environments. Prerequisite: Mgt 202. (Fall, spring, and summer)
Basic principles of risk management practices. Developing a risk management plan, including identifying, analyzing, mitigating, and monitoring projects risks. Prerequisite: Mgt 201, 202, 224.
Integrated schedule development and control. Schedule analysis, concepts and techniques, including resource allocation, earned value, and reporting process. Prerequisite: Accy 201, Mgt 202. (Fall, spring, and summer)
Formalized procedures, tools, and techniques used in developing the project estimate during the planning stages and updating the estimate throughout the project life-cycle; tools and techniques used in monitoring, managing, and controlling the cost of the project. Prerequisite: M.S.P.M. candidacy and Mgt 270. (Fall and spring)
Students will be expected to demonstrate integration of the knowledge accumulated in their study plan and apply integrated knowledge and experience to best practices, a project case history, and a handbook. Prerequisite: M.S.P.M. candidacy or permission of instructor. (Fall and spring)
The process of specifying, analyzing, and testing models of human and systemic behavior. Formalization of models; statistical test comparison and selection; computer implementation of univariate, bivariate, and multivariate tests. General linear model: linear regression, analysis of variance, and analysis of covariance. Prerequisite: MBAd 220 or equivalent. (Fall and spring)
Advanced topics associated with the general linear model. Testing for and remediation of assumption violations. Detection of outliers, influential observations, and multicollinearity. Alternative design strategies in the analysis of variance; latent growth analysis; hierarchical linear modeling; testing for interactions and parallelism. Prerequisite: DNSC 274 or permission of instructor.
Methods for exploratory and multivariate data analysis. Application and comparison of advanced multivariate analytical procedures. Multivariate and discriminant analysis, LISREL analysis, and canonical correlation. Prerequisite: DNSC 274 or permission of instructor. (Fall)
Introduction to various forecasting techniques, including time-series regression models, cyclical trends, exponential smoothing methods, seasonal and nonseasonal ARIMA processes, and the Box-Jenkins approach. Application of forecasting methods in economics, finance, and marketing. Prerequisite: MBAd 220 or permission of instructor. (Spring)
Techniques that can be used to discover relationships in large data sets, including regression models, decision trees, neural networks, clustering, and association analysis.
Experimental offering; new course topics and teaching methods. May be repeated once for credit.
Special topics and advanced applications, such as catastrophe theory, Markovian decision processes, and Bayesian statistics. May be repeated once for credit.
Recent developments in production and logistics management; impact of technological economic and social change; significant related trends. Private- and public-sector policy implications. New and emerging analysis techniques. Open only to doctoral students.
Research problems and issues related to student dissertations form topics for readings, group discussions, and assigned papers. (Fall and spring)
Philosophy of science as applied to research in administration. Topics include the nature and current problems of epistemology, the development and role of theories, and the relationship between theory, methodology, and empirical data. (Fall and spring)
Use of models and theoretical frameworks in research; formulation of research questions, hypotheses, operational definitions, research designs, sampling and data analysis approaches. For doctoral candidates who have completed the general examination and all courses and are preparing for their dissertation. (Fall and spring)
Current research and scholarly issues in management science.
Limited to doctoral candidates preparing for the general examination. May be repeated for credit.
Limited to doctoral candidates. May be repeated for credit.
Statistical concepts employed in the solution of managerial problems. Descriptive statistics, frequency distributions, probability, sampling distributions, statistical inference and testing, correlation analysis, regression modeling, analysis of variance. Introduction to forecasting and statistical process control. Statistical software is used for applications.
Fundamentals of operations management and strategic and tactical decision making. Inventory management, resource allocation, production planning, project management, location and transportation analysis, investment planning, queuing systems, equipment selection and maintenance. Technologies for decision modeling. Prerequisite: MBAd 220.