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#152

• Join this channel to get access to perks:   / learnbayesstats   • Proudly sponsored by PyMC Labs! Get in touch at alex.andorra@pymc-labs.com • Intro to Bayes Course (first 2 lessons free): https://topmate.io/alex_andorra/503302 • Advanced Regression Course (first 2 lessons free): https://topmate.io/alex_andorra/1011122 Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ ! Takeaways Decision theory workflows can complement traditional modeling workflows. Shifting focus from model accuracy to decision value is crucial. Quantifying the cost of model complexity can guide decision-making. Optimal decision-making frameworks have vast applications in industry. Eliciting utility functions can be easier than expected. Starting simple with decision-making models allows for iterative improvement. Relating decision-making to financial outcomes resonates with stakeholders. Uncertainty can significantly impact optimization outcomes. Risk aversion must be integrated into decision-making frameworks. Different utility functions can represent varying levels of risk aversion. Understanding the relationship between utility and belief is key. Chapters: 00:00 The Importance of Decision-Making in Data Science 06:41 From Philosophy to Bayesian Statistics 14:57 The Role of Soft Skills in Data Science 18:19 Understanding Decision Theory Workflows 22:43 Shifting Focus from Accuracy to Business Value 26:23 Leveraging PyTensor for Optimization 34:27 Applying Optimal Decision-Making in Industry 40:06 Understanding Utility Functions in Regulation 41:35 Introduction to Obeisance Decision Theory Workflow 42:33 Exploring Price Elasticity and Demand 45:54 Optimizing Profit through Bayesian Models 51:12 Risk Aversion and Utility Functions 57:18 Advanced Risk Management Techniques 01:01:08 Practical Applications of Bayesian Decision-Making 01:06:54 Future Directions in Bayesian Inference 01:10:16 The Quest for Better Inference Algorithms 01:15:01 Dinner with a Polymath: Herbert Simon Thank you to my Patrons (https://learnbayesstats.com/#patrons) for making this episode possible! Links from the show: Come meet Alex at the Field of Play Conference in Manchester, UK, March 27, 2026! https://www.fieldofplay.co.uk/ A Bayesian decision theory workflow: https://daniel-saunders-phil.github.i... Daniel's website: https://daniel-saunders-phil.github.i... Daniel on LinkedIn:   / dr-daniel-saunders-97239b174   Daniel on GitHub: https://github.com/daniel-saunders-phil PreliZ – Exploring and eliciting probability distributions: https://preliz.readthedocs.io/en/latest/ LBS #124 State Space Models & Structural Time Series, with Jesse Grabowski: https://learnbayesstats.com/episode/1... LBS #123 BART & The Future of Bayesian Tools, with Osvaldo Martin: https://learnbayesstats.com/episode/1... LBS #74 Optimizing NUTS and Developing the ZeroSumNormal Distribution, with Adrian Seyboldt: https://learnbayesstats.com/episode/7... LBS #76 The Past, Present & Future of Stan, with Bob Carpenter: https://learnbayesstats.com/episode/7...