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.

Develops basic principles and techniques of forecasting through integration of scientific and judgmental forecasting in financial applications. Objective analysis of historical data is combined with subjective insight to demonstrate how data for budgets can be developed, profits maximized, and risks reduced. Emphasis on use of forecasting by individual firms.