Danny Modlin

Danny Modlin is a Senior Analytical Training Consultant at SAS world headquarters in Cary, North Carolina. Since starting at SAS in 2011, Danny has taught and developed courses that span across many areas of statistics and SAS platforms, with a specialization in the application of Bayesian analyses. Danny received his Bachelor of Science in Mathematics from Elon College (now Elon University), a Masters of Mathematics from the University of North Carolina at Wilmington, and a Masters of Statistics from North Carolina State University.

Prior to his time at SAS, Danny was a mathematics, statistics, and computer science teacher at the middle school, high school, and collegiate levels. Outside of SAS, Danny’s interests include local sports and meteorology.

Bayesian Methods with SAS®: Special Collection

Foreword by Danny Modlin

The heart of Bayesian analysis is the ability to incorporate outside information (also called prior information) into the analysis. Thanks to advances in technology, applying Bayesian techniques is easier than ever. SAS offers many different solutions to estimate probability using Bayesian methods, and this book presents several groundbreaking papers that have been written to demonstrate these techniques.