Learning Bayesian Statistics

#112 Advanced Bayesian Regression, with Tomi Capretto


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Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!

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Takeaways:

  • Teaching Bayesian Concepts Using M&Ms: Tomi Capretto uses an engaging classroom exercise involving M&Ms to teach Bayesian statistics, making abstract concepts tangible and intuitive for students.
  • Practical Applications of Bayesian Methods: Discussion on the real-world application of Bayesian methods in projects at PyMC Labs and in university settings, emphasizing the practical impact and accessibility of Bayesian statistics.
  • Contributions to Open-Source Software: Tomi’s involvement in developing Bambi and other open-source tools demonstrates the importance of community contributions to advancing statistical software.
  • Challenges in Statistical Education: Tomi talks about the challenges and rewards of teaching complex statistical concepts to students who are accustomed to frequentist approaches, highlighting the shift to thinking probabilistically in Bayesian frameworks.
  • Future of Bayesian Tools: The discussion also touches on the future enhancements for Bambi and PyMC, aiming to make these tools more robust and user-friendly for a wider audience, including those who are not professional statisticians. 

Chapters:

05:36 Tomi's Work and Teaching

10:28 Teaching Complex Statistical Concepts with Practical Exercises

23:17 Making Bayesian Modeling Accessible in Python

38:46 Advanced Regression with Bambi

41:14 The Power of Linear Regression

42:45 Exploring Advanced Regression Techniques

44:11 Regression Models and Dot Products

45:37 Advanced Concepts in Regression

46:36 Diagnosing and Handling Overdispersion

47:35 Parameter Identifiability and Overparameterization

50:29 Visualizations and Course Highlights

51:30 Exploring Niche and Advanced Concepts

56:56 The Power of Zero-Sum Normal

59:59 The Value of Exercises and Community

01:01:56 Optimizing Computation with Sparse Matrices

01:13:37 Avoiding MCMC and Exploring Alternatives

01:18:27 Making Connections Between Different Models

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Learning Bayesian StatisticsBy Alexandre Andorra

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