Rate My Professor Frank Tuyl

Dr. Frank Tuyl is an Honorary Lecturer in the School of Computer and Information Sciences (Data Science and Statistics) within the College of Engineering, Science and Environment at the University of Newcastle, Australia. He holds a PhD in Statistics from the University of Newcastle. Dr. Tuyl's research focuses on Applied Statistics, Biostatistics, and Statistical Theory, particularly Bayesian methods and their applications. He has published and presented at conferences in this field. His publications appear in leading journals including Statistical Science, The American Statistician, The Lancet, Bayesian Analysis, and the International Statistical Review. Notable works include 'On the Certainty of an Inductive Inference: The Binomial Case' (Statistical Science, 2024, with Gerlach and Mengersen); 'Bayesian Benefits for Binomial Applications in Practice' (Journal of Education, Society and Behavioural Science, 2019, with Howley); 'A Method to Handle Zero Counts in the Multinomial Model' (The American Statistician, 2019); 'A note on priors for the multinomial model' (The American Statistician, 2017); 'Consensus priors for multinomial and binomial ratios' (Journal of Statistical Theory and Practice, 2016, with Gerlach and Mengersen); 'Simplifying Life Through Bayes: Hints for Practitioners New to Bayesian Inference' (Quality Management Journal, 2016, with Howley); 'Global trends and projections for tobacco use, 1990-2025: an analysis of smoking indicators from the WHO Comprehensive Information Systems for Tobacco Control' (The Lancet, 2015, with Bilano et al.); 'The rule of three, its variants and extensions' (International Statistical Review, 2009, with Gerlach and Mengersen); 'Posterior predictive arguments in favor of the Bayes-Laplace prior as the consensus prior for binomial and multinomial parameters' (Bayesian Analysis, 2009, with Gerlach and Mengersen); and 'A comparison of Bayes-Laplace, Jeffreys, and other priors: the case of zero events' (The American Statistician, 2008, with Gerlach and Mengersen).

Dr. Tuyl possesses more than 20 years of statistical and operations research consulting experience in manufacturing, information technology, academia, and health sectors, with skills in a large variety of statistical and operations research techniques. Previously, he served as a lecturer in the School of Mathematical and Physical Sciences at the University of Newcastle.