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, and I live in Paris. By day, I'm a data scientist and modeler at the PyMC Labs consultancy. 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 election forecasting and, most importantly, 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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Bayes in Theoretical Ecology, with Florian Hartig
A discussion about theoretical ecology, computer simulations and machine learning in ecology & evolution
Bayesian Stats for the Behavioral & Neural Sciences, with Todd Hudson
Why is Bayes useful in the behavioral and neural sciences? How to model behavioral and neural data with Bayesian statistics? How to estimate measurement error and compare models?
Election forecasting models in Germany, with Marcus Gross
How do you design a forecasting model that's tailored to Germany's electoral system? And then how do you communicate about what it can tell you... and cannot tell you?
Bernoulli's Fallacy & the Crisis of Modern Science, with Aubrey Clayton
About statistical illogic and the crisis of modern science. We talked about a catastrophic error in the logic of the standard statistical methods in almost all the sciences and why this error manifests even outside of science, like in medicine, law, public policy...
Ta(l)king Risks & Embracing Uncertainty, with David Spiegelhalter
Using statistics to help the general public understand risk, uncertainty and decision-making
The Present & Future of Baseball Analytics, with Ehsan Bokhari
What working in the stats department of a baseball team looks like, how Bayesian are baseball analytics, which pushbacks does Ehsan get, and what the future of baseball analytics look like to him
Great guests & topics