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#50 Ta(l)king Risks & Embracing Uncertainty, with David Spiegelhalter

#50 Ta(l)king Risks & Embracing Uncertainty, with David Spiegelhalter

Released Saturday, 6th November 2021
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#50 Ta(l)king Risks & Embracing Uncertainty, with David Spiegelhalter

#50 Ta(l)king Risks & Embracing Uncertainty, with David Spiegelhalter

#50 Ta(l)king Risks & Embracing Uncertainty, with David Spiegelhalter

#50 Ta(l)king Risks & Embracing Uncertainty, with David Spiegelhalter

Saturday, 6th November 2021
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Folks, this is the 50th episode of LBS — 50th! I never would have thought that there were so many Bayesian nerds in the world when I first interviewed Osvaldo Martin more than 2 years ago. 

To celebrate that random, crazy adventure, I wanted to do a special episode at any random point, and so it looks like it’s gonna be #50! This episode is special by its guest, not its number — although my guest knows a thing or two about numbers. Most recently, he wrote the book Covid by Numbers.

A mathematical statistician dedicated to helping the general public understand risk, uncertainty and decision-making, he’s the author of several books on the topic actually, including The Art of Statistics. You may also know him from his podcast, Risky Talk, or his numerous appearances in newspapers, radio and TV shows.

Did you guess who it is?

Maybe you just know him as the reigning World Champion in Loop – a version of pool played on an elliptical table – and are just discovering now that he is a fantastic science communicator – something that turns out to be especially important for stats education in times of, let’s say, global pandemic for instance.

He holds a PhD in Mathematical Statistics from the University of London and has been the Chair of the Winton Centre for Risk and Evidence Communication at Cambridge University since 2016. He was also the President of the famous Royal Statistical Society in 2017-2018.

Most importantly, he was featured in BBC1’s Winter Wipeout in 2011 – seriously, go check it out on his website; it’s hilarious.

So did you guess it yet? Yep, my guest for this episode is no other than Sir David Spiegelhalter — yes, there are Bayesian knights!

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, Brian Huey, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, Demetri Pananos, James Ahloy, Jon Berezowski, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Tim Radtke, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Alejandro Morales and Tomáš Frýda.

Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)

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From The Podcast

Learning Bayesian Statistics

Are you a researcher or data scientist / analyst / ninja? Do you want to learn Bayesian inference, stay up to date or simply want to understand what Bayesian inference is? Then this podcast is for you! You'll hear from researchers and practitioners of all fields about how they use Bayesian statistics, and how in turn YOU can apply these methods in your modeling workflow. When I started learning Bayesian methods, I really wished there were a podcast out there that could introduce me to the methods, the projects and the people who make all that possible. So I created "Learning Bayesian Statistics", where you'll get to hear how Bayesian statistics are used to detect black matter in outer space, forecast elections or understand how diseases spread and can ultimately be stopped. But this show is not only about successes -- it's also about failures, because that's how we learn best. So you'll often hear the guests talking about what *didn't* work in their projects, why, and how they overcame these challenges. Because, in the end, we're all lifelong learners! My name is Alex Andorra by the way. By day, I'm a Senior data scientist. By night, I don't (yet) fight crime, but I'm an open-source enthusiast and core contributor to the python packages PyMC and ArviZ. I also love Nutella, but I don't like talking about it – I prefer eating it. So, whether you want to learn Bayesian statistics or hear about the latest libraries, books and applications, this podcast is for you -- just subscribe! You can also support the show and unlock exclusive Bayesian swag on Patreon!

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