Philip Gigliotti | Guest Author on Statistics Globe

Phil Gigliotti is a data scientist working in the healthcare data analytics space. He is also a PhD candidate in public administration and policy, with a portfolio of academic research that applies econometric causal inference methods to large observational data sets, with applications to healthcare and education policy.

His professional mission is focused on using data analytics to create positive social impact, broadly conceived. While his quantitative training is in frequentist mathematical statistics, he is also excited about the incorporation of statistical learning, Bayesian methods, and structural modeling to maximize the impact and utility of future data analytic applications.

He is an enthusiastic R programmer, working mostly with Tidyverse approaches.

Find him online at his LinkedIn profile.