Schedule of Classes

Introduction to descriptive and inferential statistics with an emphasis on business applications. Topics covered include computation and application of descriptive measures, probability distributions, sampling, confidence intervals, hypothesis testing, correlation, and simple linear regression.

Linear and multiple regression, correlation, analysis of variance, contingency tables, time series, decision theory, and non-parametric methods. Data analysis using statistical computer packages.

Progressive topics relating to regression and correlation analysis with emphasis on computer-based learning. Time-series analysis. Application to business issues based on multiple analysis of variance (MANOVA), discriminant analysis, factor analysis and the use of latent variables. Cluster analysis and principal component analysis and Logit analysis included. Pattern recognition using Big Data.

Topics of special interest which may vary each time course is offered. Topic stated in current Schedule of Classes. May be repeated under different topics for a maximum of six hours.