Description
 This is a graduate lecture course that covers multivariate data analysis and advanced regression applications for students. The goal of the course is to ensure that graduate students in engineering and management fields are able to interpret, implement, and employ basic regression analysis of several different types of data. The course is primarily devoted to advanced regression analysis. The emphasis is on developing a rigorous calculus and matrix algebrabased understanding of ordinary least squares (OLS), violations of regression assumptions, hypothesis testing, and the general linear model. Also, the emphasis of this course is on the acquisition and understanding of analytical techniques such as basic concepts of statistics (descriptive and inferential statistics, probability distributions), simple linear regression, multiple linear regression, logistic regression, loglinear model.

