Quantitative Business Analysis (QBA)

QBA 221 Statistical Analysis. (3) F, S
Methods of statistical description. Application of probability theory and statistical inference in business. Prerequisites: MAT 119, 210. General Studies: N2.

QBA 321 Applied Quality Analysis I. (3) A
Applications of statistical tools employed in empirical studies related to quality analysis. Applications focus on service processes. Prerequisite: QBA 221.

QBA 391 Management Science. (3) N
Study of mathematical models and solution techniques which can be used to aid decision makers. Prerequisites: MAT 119, 210, 242; QBA 221; professional program business student. General Studies: N2.

QBA 410 Applied Business Forecasting. (3) N
Application of forecasting techniques in business and institutional environments. Prerequisite: QBA 321.

QBA 421 Applied Quality Analysis II. (3) A
Applications of statistical tools employed in manufacturing and experimental research. Applications focus on design and improvement of processes. Prerequisite: QBA 321.

QBA 450 Operations and Process Analysis. (3) A
Implementation of quantitative techniques for the analysis of quality problems related to operations and process analysis. Prerequisites: OPM 301; QBA 221.

QBA 502 Managerial Decision Analysis. (3) F, S
Fundamentals of quantitative analysis to aid management decision making under uncertainty. Prerequisites: MAT 210; computer literacy; graduate degree program student.

QBA 505 Management Science. (3) N
Quantitative approaches to decision making, including linear programming and simulation, with an emphasis on business applications. Prerequisites: MAT 210; QBA 502.

QBA 510 Managerial Statistics. (3) A
Statistical methods used in decision making, including analysis of variance and simple and multiple linear regression. Prerequisites: MAT 210; QBA 502 or an introductory statistics course.

QBA 511 Sampling Techniques in Business. (3) N
Planning, execution and analysis of surveys in business research. Prerequisite: QBA 502.

QBA 525 Applied Regression Models. (3) A
Simple linear regression, multiple regression, indicator variables, and logistic regression. Emphasis on business and economic applications. Prerequisites: MAT 210; QBA 510.

QBA 527 Categorical Data Analysis. (3) N
Discrete data analysis in business research. Multidimensional contingency tables and other discrete models. Prerequisite: QBA 525.

QBA 528 Exploratory Data Analysis. (3) N
Introduces student to principles and methods of exploratory data analysis. Prerequisite: QBA 502.

QBA 530 Experimental Design. (3) A
Experimental designs used in business research. Balanced and unbalanced factorial designs, repeated measures designs, and multivariate analysis of variance. Prerequisite: QBA 525 or equivalent.

QBA 535 Multivariate Methods. (3) A
Advanced statistical methods used in business research. Multivariate analysis of association and interdependence. Prerequisite: QBA 525.

QBA 540 Forecasting. (3) N
Foundation of statistical forecasts and forecast intervals; application of classical and computer-assisted forecasting methods to business forecasting problems. Prerequisites: MAT 210; QBA 502.

QBA 550 Intermediate Decision Analysis. (3) N
Quantitative decision analysis methods for business decision making under uncertainty, including decision diagrams, subjective probabilities, and preference assessment. Prerequisites: MAT 210; QBA 502.

QBA 552 Statistical Decision Theory. (3) N
Statistical decision methods for business decision making under uncertainty, including Bayesian inference, optimal statistical decisions, and value of information assessment. Prerequisites: MAT 210; QBA 510 or 550.

QBA 560 Probabilistic Models. (3) N
Development and application of probabilistic models for quantitative business analysis. Prerequisites: MAT 210; QBA 502.

QBA 561 Mathematical Programming. (3) N
Techniques for solving mathematical programming models of business problems. Prerequisites: MAT 210, 242.

QBA 562 Network Flow Models. (3) N
Introduction to network structure, applications, and algorithms; development of data structures for network algorithms applied to business problems. Prerequisites: QBA 561 or MAT 242 and QBA 505.

QBA 564 Nonlinear Optimization. (3) N
Basic properties of solutions and algorithms for constrained and unconstrained minimization, basic descent methods, and barrier methods. Prerequisites: QBA 561 or MAT 242 and QBA 505.

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