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Engaging with Bayesian Statistics: Balancing Theory and Accessibility
This chapter explores the difficulties of understanding technical academic papers in Bayesian statistics and the speakers' preference for contextual storytelling in writing. They also discuss efforts to make academic work more accessible and share a promotional offer for listeners to win a book from Cambridge University Press.
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!
If there is one guest I don’t need to introduce, it’s mister Andrew Gelman. So… I won’t! I will refer you back to his two previous appearances on the show though, because learning from Andrew is always a pleasure. So go ahead and listen to episodes 20 and 27.
In this episode, Andrew and I discuss his new book, Active Statistics, which focuses on teaching and learning statistics through active student participation. Like this episode, the book is divided into three parts: 1) The ideas of statistics, regression, and causal inference; 2) The value of storytelling to make statistical concepts more relatable and interesting; 3) The importance of teaching statistics in an active learning environment, where students are engaged in problem-solving and discussion.
And Andrew is so active and knowledgeable that we of course touched on a variety of other topics — but for that, you’ll have to listen ;)
Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !
Thank you to my Patrons for making this episode possible!
Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau, Luis Fonseca, Dante Gates, Matt Niccolls, Maksim Kuznecov, Michael Thomas, Luke Gorrie, Cory Kiser, Julio, Edvin Saveljev, Frederick Ayala, Jeffrey Powell, Gal Kampel, Adan Romero, Will Geary and Blake Walters.
Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)
Takeaways:
- Active learning is essential for teaching and learning statistics.
- Storytelling can make statistical concepts more relatable and interesting.
- Teaching statistics in an active learning environment engages students in problem-solving and discussion.
- The book Active Statistics includes 52 stories, class participation activities, computer demonstrations, and homework assignments to facilitate active learning.
- Active learning, where students actively engage with the material through activities and discussions, is an effective approach to teaching statistics.
- The flipped classroom model, where students read and prepare before class and engage in problem-solving activities during class, can enhance learning and understanding.
- Clear organization and fluency in teaching statistics are important for student comprehension and engagement.
- Visualization plays a crucial role in understanding statistical concepts and aids in comprehension.
- The future of statistical education may involve new approaches and technologies, but the challenge lies in finding effective ways to teach basic concepts and make them relevant to real-world problems.
Chapters:
00:00 Introduction and Background
08:09 The Importance of Stories in Statistics Education
30:28 Using 'Two Truths and a Lie' to Teach Logistic Regression
38:08 The Power of Storytelling in Teaching Statistics
57:26 The Importance of Visualization in Understanding Statistics
01:07:03 The Future of Statistical Education
Links from the show:
Transcript
This is an automatic transcript and may therefore contain errors. Please get in touch if you're willing to correct them.
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Listen to all your favourite podcasts with AI-powered features
Listen to the best highlights from the podcasts you love and dive into the full episode