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

Note: Course numbers at two levels (such as 421/521) may be taken for either undergraduate or graduate credit. Graduate students must complete additional work to receive graduate credit.

421/521 Computer Modeling in Business (3)

A course in computer modeling of business and economic processes. Deterministic and stochastic mod- els 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.

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: 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.

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)

Intro 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)

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 (2-3)

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

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)