Partial least squares regression, which has been around for about four decades, is
a dimension-reduction algorithm for fitting linear regression models without
requiring that the sample size be larger than the number of predictors. It was
developed primarily by the Chemometrics community where it is now ingrained
as a core method, and it is apparently used throughout the applied sciences.
Statisticians, the original data scientists, stand ready to interpret the information of the digital age. In less than three years we will be producing over 1.7 megabytes of new information every single second for every human being on the planet. This new information, along with the vast amount of information that has already been collected, ranges from the mundane to the extraordinary.
Assistant Professor Lan Liu’s interest in statistics happened by chance, but she hasn’t looked back since. Involved in infectious disease research, statistical consulting, and causality research with the FDA, Liu has seen firsthand the real-world challenges statistics can overcome.
Seniors Sabrina Li and Ryan Lerch participated on an analytics team for the College of Liberal Arts’ First-Year Experience, looking at how a first-year student’s demographic background affects their sense of belonging.
As director of the Institute for Research on Statistics and its Applications, Associate Professor Singdhansu Chatterjee discusses its goals, future plans, and recent events—including a visit from LinkedIn’s vice president of artificial intelligence, Dr. Deepak Agarwal.