Attend this session to take your first steps toward applying data science tools and techniques to solve your business problems. You will gain a fundamental understanding of time-based data and how to extract insights from it (e.g., what is a time series and how we can work with one). With some real-world examples we will demonstrate some simple analytics using time-based data in R. A focus will be on underlying assumptions behind time series, and how to sample and generate statistics and predictive models on such data. We will also mention some challenges and point to advanced topics for further study of time series analysis. This talk is for those getting started with analytics and PI. No prior R or PI experience is required.
Dr. Brian D. Davison is an associate professor of computer science and engineering and director of the undergraduate minor in data science. He teaches courses on data science, data mining, web search engines, networking, system administration, and C and UNIX programming. He heads Lehigh's Web Understanding, Modeling, and Evaluation (WUME) laboratory and serves as editor-in-chief of the ACM journal, Transactions on the Web. While on sabbatical during the 2013-2014 academic year, he worked in the Core Data Science group at Facebook. Dr. Davison earned his B.S. from Bucknell University and his M.S. and Ph.D. in Computer Science from Rutgers University. His research includes search, mining, recommendation and classification problems in text, on the Web and in social networks. He is an NSF Faculty Early Career award winner. Dr. Davison's research has been supported by the National Science Foundation, the Defense Advanced Research Projects Agency, Microsoft, and Sun Microsystems.