MA485 Applied Regression and Time Series Analysis

Regression - in its various guises from Kalman filtering to backpropogation neural networks to predictive analytics - is concerned with building mathematical models from empirical data. Regression models are widely used in engineering, science, technology and business. Regression models also impact your lives in ways ranging from online used car pricing to credit scores. For example, your FICO credit score is generated by a regression model; see the predictive analytics link below. In this course we will start with standard multiple regression models then move on to more advanced procedures including time series analysis and sparse regression procedures. We will use Minitab and the open-source software package R. For more information about regression and analytics please see the two Wikipedia links below. And, of course, if you have any questions please e-mail me at inlow@rose-hulman.edu.