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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 me ...
 
The late invoice statistics from 2021 show that payments are still the norm these days and, as a business community, we need to ensure that businesses are preparing for this (and, hopefully, beginning to turn the tide).Brodmin.com has put in hundreds of hours to compile the latest invoice statistics from around the world.The focus of the research was to analyse and compare late invoice payments of different countries and make contextual points. Also, the highlighted statistical figures repre ...
 
The Department of Statistics at Oxford is a world leader in research including computational statistics and statistical methodology, applied probability, bioinformatics and mathematical genetics. In the 2014 Research Excellence Framework (REF), Oxford's Mathematical Sciences submission was ranked overall best in the UK. This is an exciting time for the Department. We have now moved into our new home on St Giles and we are currently settling in. The new building provides improved lecture and ...
 
The health podcast series brings you highlights and data snapshots from the wide range of health data collected by the Australian Bureau of Statistics (ABS). The Health podcast will showcase this data in a series of short conversations that discuss Australia's health status following release of data from the suite of health surveys conducted by the ABS. The episodes will discuss a variety of topics, including health risk factors such as smoking and obesity, rates of physical activity and die ...
 
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It’s been a while since I did an episode about sports analytics, right? And you know it’s a field I love, so… let’s do that! For this episode, I was happy to host Ehsan Bokhari, not only because he’s a first-hour listener of the podcast and spread the word about it whenever he can, but mainly because he knows baseball analytics very well! Currently…
 
Roger J. Lewis, MD, PhD, discusses Equipoise in Research—Integrating Ethics and Science in Human Research with Alex John London, PhD Related Content: Equipoise in Research—Integrating Ethics and Science in Human Research
 
In episode 40, we already got a glimpse of how useful Bayesian stats are in the speech and communication sciences. To talk about the frontiers of this field (and, as it happens, about best practices to make beautiful plots and pictures), I invited TJ Mahr on the show. A speech pathologist turned data scientist, TJ earned his PhD in communication sc…
 
The field of physics has brought tremendous advances to modern Bayesian statistics, especially inspiring the current algorithms enabling all of us to enjoy the Bayesian power on our own laptops. I did receive some physicians already on the show, like Michael Betancourt in episode 6, but in my legendary ungratefulness I hadn’t dedicated a whole epis…
 
The late invoice statistics from 2021 show that payments are still the norm these days and, as a business community, we need to ensure that businesses are preparing for this (and, hopefully, beginning to turn the tide). Brodmin.com has put in hundreds of hours to compile the latest invoice statistics from around the world. The focus of the research…
 
Roger J. Lewis, MD, PhD, discusses Bayesian Analysis: Using Prior Information to Interpret the Results of Clinical Trials with Melanie Quintana, PhD Related Content: Bayesian Analysis: Using Prior Information to Interpret the Results of Clinical Trials Effect of Therapeutic Hypothermia Initiated After 6 Hours of Age on Death or Disability Among New…
 
You wanna know something funny? A sentence from this episode became a meme. And people even made stickers out of it! Ok, that’s not true. But if someone could pull off something like that, it would surely be Chelsea Parlett-Pelleriti. Indeed, Chelsea’s research focuses on using statistics and machine learning on behavioral data, but her more genera…
 
As a podcaster, I discovered that there are guests for which the hardest is to know when to stop the conversation. They could talk for hours and that would make for at least 10 fantastic episodes. Frank Harrell is one of those guests. To me, our conversation was both fascinating — thanks to Frank’s expertise and the width and depth of topics we tou…
 
Cost-effectiveness analysis defines trade-offs between costs, harms, and benefits of alternative treatments and combines them into a single metric, the incremental cost-effectiveness ratio (ICER), that can inform decisions about which interventions to recommend when limited resources are available. Gillian Sanders-Schmidler, PhD, professor of popul…
 
Caroline Uhler (MIT), gives a OxCSML Seminar on Friday 2nd July 2021. Abstract: Massive data collection holds the promise of a better understanding of complex phenomena and ultimately, of better decisions. An exciting opportunity in this regard stems from the growing availability of perturbation / intervention data (genomics, advertisement, educati…
 
Qiang Liu (University of Texas at Austin) gives the OxCSML Seminar on Friday 4th June 2021. Abstract: Stein's method is a powerful technique for deriving fundamental theoretical results on approximating and bounding distances between probability measures, such as central limit theorem. Recently, it was found that the key ideas in Stein's method, de…
 
Cynthia Rudin (Duke University) gives a OxCSML Seminar on Friday 14th May 2021. Abstract: While the trend in machine learning has tended towards more complex hypothesis spaces, it is not clear that this extra complexity is always necessary or helpful for many domains. In particular, models and their predictions are often made easier to understand b…
 
Aki Vehtari (Aalto University) gives the OxCSML Seminar on Friday 7th May 2021 Abstract: I discuss the use of the Pareto-k diagnostic as a simple and practical approach for estimating both the required minimum sample size and empirical pre-asymptotic convergence rate for Monte Carlo estimates. Even when by construction a Monte Carlo estimate has fi…
 
Episode sponsored by Paperpile: paperpile.com Get 20% off until December 31st with promo code GOODBAYESIAN21 Bonjour my dear Bayesians! Yes, it was bound to happen one day — and this day has finally come. Here is the first ever 100% French speaking ‘Learn Bayes Stats’ episode! Who is to blame, you ask? Well, who better than Rémi Louf? Rémi currentl…
 
Episode sponsored by Paperpile: paperpile.com Get 20% off until December 31st with promo code GOODBAYESIAN21 I don’t know if you’ve heard, but there is a virus that took over most of the world in the past year? I haven’t dedicated any episode to Covid yet. First because research was moving a lot — and fast. And second because modeling Covid is very…
 
Quan Zhou, Texas A and M University, gives an OxCSML Seminar on Friday 25th June 2021. Abstract:In a model selection problem, the size of the state space typically grows exponentially (or even faster) with p (the number of variables). But MCMC methods for model selection usually rely on local moves which only look at a neighborhood of size polynomi…
 
Episode sponsored by Paperpile: paperpile.com Get 20% off until December 31st with promo code GOODBAYESIAN21 We often talk about applying Bayesian statistics on this podcast. But how do we teach them? What’s the best way to introduce them from a young age and make sure the skills students learn in the stats class are transferable? Well, lucky us, M…
 
Distinguished Speaker Seminar - Friday 18th June 2021, with Susan Murphy, Professor of Statistics and Computer Science, Harvard John A. Paulson School of Engineering and Applied Sciences. Reinforcement Learning provides an attractive suite of online learning methods for personalizing interventions in a Digital Health. However after a reinforcement …
 
Graduate Lecture - Thursday 3rd June 2021, with Dr Fergus Boyles. Department of Statistics, University of Oxford. Drug discovery is a long and laborious process, with ever growing costs and dwindling productivity making it ever more difficult to bring new medicines to the market in an affordable and timely fashion. There is a long history of applyi…
 
OxCSML Seminar - Friday 28th May 2021, presented by Alexandra Carpentier (University of Magdeburg). In this talk we will discuss the thresholding bandit problem, i.e. a sequential learning setting where the learner samples sequentially K unknown distributions for T times, and aims at outputting at the end the set of distributions whose means \mu_k …
 
Let’s think Bayes, shall we? And who better to do that than the author of the well known book, Think Bayes — Allen Downey himself! Since the second edition was just released, the timing couldn’t be better! Allen is a professor at Olin College and the author of books related to software and data science, including Think Python, Think Bayes, and Thin…
 
Benjamin Guedj, University College London, gives a OxCSML Seminar on 26th March 2021. Abstract: PAC-Bayes is a generic and flexible framework to address generalisation abilities of machine learning algorithms. It leverages the power of Bayesian inference and allows to derive new learning strategies. I will briefly present the key concepts of PAC-Ba…
 
We all know about these accidental discoveries — penicillin, the heating power of microwaves, or the famous (and delicious) tarte tatin. I don’t know why, but I just love serendipity. And, as you’ll hear, this episode is deliciously full of it… Thanks to Allison Hilger and Timo Roettger, we’ll discover the world of linguistics, how Bayesian stats a…
 
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