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General Bulletin 2008-2010

Courses of Instruction

DECISION SCIENCES (DSC-Business; Department of Decision Sciences and Management Information Systems)

203 Supplementary Business Statistics (1)

Review of elementary statistics. Regression analysis and statistical process control. For students needing additional coursework to complete the topics in DSC 205. Prerequisite: MTH 151, STA 261 or equivalents.

MPT 205 Business Statistics (4)

Basic probability. Discrete and continuous distributions. Sampling theory, confidence intervals, and hypothesis testing. Analysis of process data. Simple and multiple regression analysis. Emphasis on computer implementation. Prerequisite: MTH 151 and a high school course in computers or equivalent. Credit not given for both DSC 205 and any other introductory statistics course (for example, STA 261, STA 368).

MPT 291 Applied Regression Analysis in Business (3)

Multiple regression as related to analysis of business problems. Includes useful regression models, statistical inference (intervals and hypothesis tests) in regression, model building, regression assumptions, remedies for violations of assumptions, applications in experimental design, and time series analysis. Prerequisite: DSC 205 or equivalent.

MPT 321 Quantitative Analysis of Business Problems (3)

Examination of business problems from a quantitative model building point of view. Selected models from management science, including linear and nonlinear programming and simulation. Methodologies combined with those from prerequisite courses. Prerequisite: DSC 205.

330 Professional Practice (0)

Students participating in an internship program register for this course during the semester they are on work assignment. Prerequisite: permission of departmental internship coordinator.

331 Quantitative Methods of Decision Making (3)

Models for managerial decision making under conditions of risk or uncertainty with single or multiple goals. Prerequisite: ACC 222, DSC 205, ECO 201 or 202. Offered infrequently.

MPT 333 Nonparametric Statistics (3)

Applied statistical techniques useful in estimating parameters of a business population whose underlying distribution is unknown. Chi-square, sign, rank, and runs tests included. Prerequisite: DSC 205 or equivalent. Cross-listed with STA 333.

MPT 365 Statistical Quality Control (3)

Statistical procedures used in quality control. Control charts for measurement and attribute data. Process capability studies. Acceptance sampling and other industrial applications. Prerequisite: DSC 205 or STA 363 or STA 368 or equivalent. Cross-listed with STA 365.

421/521 Computer Modeling in Business (3)

A course in computer modeling of business and economic processes. Deterministic and stochastic models of the firm and its components, statistical aspects of business models, Monte Carlo studies, computer languages. Prerequisite: (421) DSC 321; (521) DSC 616 or 618 or permission of instructor.

MPT 432/532 Survey Sampling in Business (3)

Survey sampling with application to problems of business research. Simple random sampling, systematic sampling, stratified random sampling, ratio estimation, and cluster sampling. Prerequisite(s): DSC 305 or STA 363 or STA 401 or permission of instructor. Cross-listed with STA 432.

442/542 Design of Experiments in Business (3)

Completely randomized design, randomized block design, factorial arrangement of treatments, analysis of covariance. Regression approach included. Prerequisite: DSC 305 or equivalent. Offered infrequently.

MPT 444/544 Business Forecasting (3)

Applied techniques useful in analyzing and forecasting business time series. Emphasis on Box/Jenkins methodology. Time series regression with autocorrelated errors, exponential smoothing, and classical decomposition are also discussed. Prerequisite: DSC 305 or equivalent.

447/547 Analysis of Multivariate Business Data (3)

Introduction to multivariate data analysis as applied to business problems in which many variables play an important role. Exploratory data, discriminant, classification, factor, and cluster analysis; multidimensional scaling, and other related techniques. Offered infrequently.

480/580 Topics in Decision Sciences (1-3; maximum 3)

Issues oriented seminar focused upon significant emerging topics in the decision sciences field. Prerequisite: determined by professor.

601 Quantitative Business Analysis (1)

Introduces the MBA students to the use of spreadsheets for constructing and using mathematical models of business problems as an aid to the decision making process.

602 Graduate Survey in Statistics (2)

A survey of basic statistics for analysis of business problems; designed for students in the fulltime MBA program.

615 Statistical Methods for Managerial Decision Making (3)

Discussion of statistical reasoning for managers and statistical methodology most useful for solving business problems. Process control and capability. Simple and multiple regression analysis. Residual analysis and model building. Time series forecasting. Experimental design. For full-time M.B.A. students only.

616 Quantitative Models for Business Decision Making (3)

Presents process of modeling and using quantitative models as an aid for solving business problems. Provides the foundation for employment of modeling and models in all functional areas of business. The pedagogy encourages integration of quantitative methods with content of functional areas of business. For full-time M.B.A. students only.

618 Business Operations Research (3)

Study and critical evaluation of operations research techniques from a business administrative viewpoint. Prerequisite: DSC 601, 602, or equivalent.

619 Statistical Modeling for Business Decision Making (3)

Applied presentation of statistical techniques employed in business decision making. Analysis and problem solving using computer based statistical programs. Prerequisite: DSC 601, 602, or equivalent.

671 Statistical Process Analysis and Improvement for Managers (3)

Statistical methods for analyzing and improving business processes. Advanced control chart methods for eliminating assignable cause variation. Cusum and EWMA charts. Control procedures for autocorrelated process data. Experimental design methods for reducing common cause variation. One-way and two-way ANOVA. Fractional factorial designs. Prerequisite: DSC 615.

681 Special Studies in Decision Sciences (1-3)

Intensive reading or research in a selected field of advanced decision sciences. Prerequisite: graduate standing and permission of instructor.

700 Thesis (3-6; minimum 3, maximum 6)

 


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