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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 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 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 ...
 
This course provides an introduction to the quantitative methods social scientists use to collect and evaluate empirical data about society. Through this course you will learn to gather, describe, and analyze data with an emphasis on the application and interpretation of these methods. This course will also help you to be a more informed and critical reader of academic research, public opinion polling, and advertisement claims that present statistical evidence. Lecture slides and additional ...
 
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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show series
 
The big problems with classic hypothesis testing are well-known. And yet, a huge majority of statistical analyses are still conducted this way. Why is it? Why are things so hard to change? Can you even do (and should you do) hypothesis testing in the Bayesian framework? I guess if you wanted to name this episode in a very Marvelian way, it would be…
 
JAMA Statistical Editor Roger Lewis, MD, PhD, discusses Use of Run-in Periods in Randomized Trials with Jane M. Armitage, MBBS. Related Content: Use of Run-in Periods in Randomized Trials With Dr Armitage Short- and Long-term Effects of a Mobile Phone App in Conjunction With Brief In-Person Counseling on Physical Activity Among Physically Inactive …
 
Why do we, humans, communicate? And how? And isn’t that a problem that to study communication we have to… communicate? Did you ever ask yourself that? Because J.P. de Ruiter did — and does everyday. But he’s got good reasons: JP is a cognitive scientist whose primary research focus is on the cognitive foundations of human communication. He aims to …
 
In large-scale one-off civil infrastructure, decision-making under uncertainty is part of the job, that’s just how it is. But, civil engineers don't get the luxury of building 10^6 versions of the bridge, offshore wind turbine or aeronautical structure to consider a relative frequency interpretation! And as you’ll hear, challenges don’t stop there:…
 
JAMA Statistical Editor Roger Lewis, MD, discusses Regression Discontinuity Design with Matthew L. Maciejewski, PhD. Related Content: Regression Discontinuity Design Using Instrumental Variables to Address Bias From Unobserved Confounders
 
A high-level overview of key areas of AI ethics and not-ethics, exploring the challenges of algorithmic decision-making, kinds of bias, and interpretability, linking these issues to problems of human-system interaction. Much attention is now being focused on AI Ethics and Safety, with the EU AI Act and other emerging legislation being proposed to i…
 
A brief introduction to various legal and procedural ethical concepts and their applications within and beyond academia. It's all very well to talk about truth, beauty and justice for academic research ethics. But how do you do these things at a practical level? If you have a big idea, or stumble across something with important implications, what d…
 
This seminar explains and illustrates the approach of Markov melding for joint analysis. Integrating multiple sources of data into a joint analysis provides more precise estimates and reduces the risk of biases introduced by using only partial data. However, it can be difficult to conduct a joint analysis in practice. Instead each data source is ty…
 
Rapid training of deep neural networks without skip connections or normalization layers using Deep Kernel Shaping. Using an extended and formalized version of the Q/C map analysis of Pool et al. (2016), along with Neural Tangent Kernel theory, we identify the main pathologies present in deep networks that prevent them from training fast and general…
 
Professor Denise Lievesley discusses ethical issues and codes of conduct relevant to applied statisticians. Statisticians work in a wide variety of different political and cultural environments which influence their autonomy and their status, which in turn impact on the ethical frameworks they employ. The need for a UN-led fundamental set of princi…
 
Lionel Riou-Durand gives a talk on sampling methods. Sampling approximations for high dimensional statistical models often rely on so-called gradient-based MCMC algorithms. It is now well established that these samplers scale better with the dimension than other state of the art MCMC samplers, but are also more sensitive to tuning. Among these, Ham…
 
Professor Samir Bhatt gives a talk on the mathematics underpinning infectious disease models. Mathematical descriptions of infectious disease outbreaks are fundamental to understanding how transmission occurs. Reductively, two approaches are used: individual based simulators and governing equation models, and both approaches have a multitude of pro…
 
You know when you have friends who wrote a book and pressure you to come on your podcast? That’s super annoying, right? Well that’s not what happened with Ravin Kumar, Osvaldo Martin and Junpeng Lao — I was the one who suggested doing a special episode about their new book, Bayesian Modeling and Computation in Python. And since they cannot say no t…
 
No, no, don't leave! You did not click on the wrong button. You are indeed on Alex Andorra’s podcast. The podcast that took the Bayesian world by a storm: “Learning Bayesian Statistics”, and that Barack Obama deemed “the best podcast in the whole galaxy” – or maybe Alex said that, I don’t remember. Alex made us discover new methods, new ideas, and …
 
Did you know there is a relationship between the size of firetrucks and the amount of damage down to a flat during a fire? The bigger the truck sent to put out the fire, the bigger the damages tend to be. The solution is simple: just send smaller firetrucks! Wait, that doesn’t sound right, does it? Our brain is a huge causal machine, so it can inst…
 
What’s the common point between fiction, fake news, illusions and meditation? They can all be studied with Bayesian statistics, of course! In this mind-bending episode, Dominique Makowski will for sure expand your horizon. Trained as a clinical neuropsychologist, he is currently working as a postdoc at the Clinical Brain Lab in Singapore, in which …
 
Let’s be honest: evolution is awesome! I started reading Improbable Destinies: Fate, Chance, and the Future of Evolution, by Jonathan Losos, and I’m utterly fascinated. So I’m thrilled to welcome Florian Hartig on the show. Florian is a professor of Theoretical Ecology at the University of Regensburg, Germany. His research concentrates on theory, c…
 
Get a 30% discount on Todd's book by entering the code BDABNS22 at checkout! The behavioral and neural sciences are a nerdy interest of mine, but I didn’t dedicate any episode to that topic yet. But life brings you gifts sometimes (especially around Christmas…), and here that gift is a book, Bayesian Data Analysis for the Behavioral and Neural Scie…
 
Did I mention I like survey data, especially in the context of electoral forecasting? Probably not, as I’m a pretty shy and reserved man. Why are you laughing?? Yeah, that’s true, I’m not that shy… but I did mention my interest for electoral forecasting already! And before doing a full episode where I’ll talk about French elections (yes, that’ll co…
 
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