This course covers the basic principles and implementation techniques of analysis of variance, simple and multiple regression analysis. It also covers techniques used in simple and multiple regression analysis, including residual analysis, assumption violations, variable selection techniques, correlated independent variables, qualitative independent and dependent variables, polynomial and non-linear regression, regression with time-series data and forecasting. Applications related to business decision-making will be emphasized. Makes use of statistical software packages. Prerequisties: Undergraduate statistics course.