Decision Science (DS)
DS 2310 Business Statistics I
An introductory study of statistical methods as applied to business and economic problems. Topical coverage includes descriptive statistics, set theory, probability theory, random variables, probability distributions, the normal distribution, sampling methods, sampling distributions, statistical estimation, hypothesis testing, and simple linear regression and correlation analysis.
Prerequisites: MATH 1325 with a grade of "C" or better.
DS 6320 Multivariate Statistics
Business data frequently measure more than one aspect; that is, it is multivariate. The objective of this course is to introduce powerful methods for understanding and obtaining managerial insight from multivariate data. Multivariate methods studied in the course include a selection of principle component analysis, factor analysis, canonical correlation, discriminate analysis, multidimensional scaling, cluster analysis, and neural nets. Readings, cases, examples and exercises are drawn from diverse areas of business.
Prerequisites: Consent of the instructor and the Graduate Advisor.