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.
Featured Authors
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Todd Case has been working in the pharmaceutical industry as a statistical programmer for over 20 years. He completed his MS in Epidemiology from Columbia University and has worked at Forest Laboratories (now Allergan), Genentech, Bristol-Myers Squibb, and Biogen. He currently works at Vertex Pharmaceuticals.
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Terisa Roberts is a director and Global Solution lead for Risk Modeling and Decisioning at SAS. She has extensive experience in quantitative risk management, regulatory compliance, and model governance and validation. She has worked in financial services, telecommunications, government, energy, and retail sectors.
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Ron Klimberg, PhD, is a professor at the Haub School of Business at Saint Joseph's University in Philadelphia, PA.
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Robert N. Rodriguez retired from SAS in 2018 after serving as a senior director in research and development. Bob received a PhD in statistics from the University of North Carolina at Chapel Hill and was a research statistician at General Motors Research Laboratories before joining SAS.