This course begins with a relatively advanced treatment of model building for decision makers (e.g., simulation models using Crystal Ball) and continues with a comprehensive presentation of the use of SPSS to analyze discrete multivariate models (i.e., models for purely categorical response variables). Whilst some attention is given to long-standing techniques for categorical data, like chisquare tests and contingency table analysis, the primary focus of the course will be “modeling techniques”, particularly logistic regression, discriminate analysis, and neural networks. Cases and practical illustrations used in the course derive from a variety of business disciplines. Prerequisite(s): Full-Time-DESC 593 Applied Data Analysis (2) or equivalent. Fully Employed-DESC 656 Quantitative Analysis for Business Operations (4).