Bayesian Thinking
Case Studies and AI Tools to Support Data-Driven Decisions in Engineering, Science, and Business
$211.61
- Hardcover
288 pages
- Release Date
9 December 2026
Summary
Apply Bayesian analysis to real engineering, science, and business problems
Professionals facing uncertain data need a complete workflow from problem framing to defensible decisions. Bayesian Thinking: Case Studies and AI Tools to Support Data-Driven Decisions in Engineering, Science, and Business delivers that workflow through case studies in reliability engineering, medical diagnostics, economics, and product quality. Readers master every stage: framing real-…
Book Details
| ISBN-13: | 9781394450138 |
|---|---|
| ISBN-10: | 1394450133 |
| Author: | David A. Hoeflin, Michael Tortorella |
| Publisher: | John Wiley & Sons Inc |
| Imprint: | John Wiley & Sons Inc |
| Format: | Hardcover |
| Number of Pages: | 288 |
| Release Date: | 9 December 2026 |
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David A. Hoeflin
David A. Hoeflin, PhD
David A. Hoeflin holds a PhD in Mathematics from Iowa State University. Over his nearly thirty-year career, first at AT&T Bell Labs and then at AT&T Labs, he rose to become a Director in the Optimization, Reliability and Customer Analytics department. He led the development of advanced statistical methods for network performance analysis, reliability engineering, and cybersecurity applications. He is a named inventor on multiple patents and has authored numerous peer-reviewed papers.
Michael Tortorella, PhD
Michael Tortorella retired as a Distinguished Member of Technical Staff at Bell Laboratories, where he worked for 26 years. He subsequently worked as a Research Professor in the Rutgers Center for Operations Research (RUTCOR) at Rutgers University and as an Adjunct Professor at Stevens Institute of Technology. He holds a PhD in Mathematics from Purdue University and is a recognized expert in reliability engineering and probabilistic methods for complex systems.
He is the author of the Wiley textbook Reliability, Maintainability, and Supportability: Best Practices for Systems Engineers and has published extensively in reliability theory, engineering, and management, numerical analysis, and operations research.
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