Nick Woolsey

Dr. Woolsey provides statistical consulting services related to data analysis, statistical modelling, and data visualization. He has experience with regression, measurement error, Bayesian statistics, survival analysis, neural networks, and machine learning. He leverages these skills to solve problems in biopharmaceuticals, public health, warranty analysis, and environmental data.

Dr. Woolsey's consulting approach integrates a mixture of novel and classical statistical methods, such as likelihood inference, time series analysis, classification methods, kernel-based nonparametric methods, bootstrapping, Bayesian methods, and general robust statistics. These methods allow for a wide array of solutions that are not only effective but also interpretable, and lead to an understanding of underlying causes. Further, he utilizes statistical software such as R, SAS, Python, MATLAB, and Weibull++ to enact these methods and create illustrative data visualization.

Before joining Exponent, Dr. Woolsey attended the University of South Carolina, where he served as a graduate assistant in the department of Statistics. His thesis centered on modelling atypical data, specifically data which could be periodic, noisy, or heavily skewed, and applying those models foot traffic data.