Podcasts about bayesian analysis

Finding extraterrestrial life is a goal for a lot of space missions. Telescopes are analysing distant planets in search of biosignatures. We've spent a lot of time thinking about what it will be like to find life on other planets. But what if we don't? What happens then? Finding out in this interview.

Today, I have the pleasure of welcoming Nuno Reis to the show. I came across Nuno via his LinkedIn posts on uncertainty and in particularly around something called Bayesian Analysis or Bayesian Thinking. If you've never come across the term, Bayesian Analysis is the mathematical interpretation of probability. And it underpins so much of our world  - and increasingly so because many AI models are built on Bayesian Thinking. Nuno is quite critical of how Bayesian Thinking is applied – because we can never remove the human from the numbers and the models. He says that an embrace of Bayesian Thinking – useful as it is, has become an unhealthy dogma. And – that resonated with me particularly because as I looked at Nuno's background I saw someone saying this who is a trained mathematician with a PhD in Mathematics in String Theory and did a postdoc at Oxford. He worked in the financial sector during the Global Financial Crisis where he sees parallels now in the worlds of AI and related areas. So, I invited him to the show and we had a great conversation that covers not only the topics of Bayesian Thinking, the financial industry, but also the topic of uncertainty, lots of philosophy and running. I hope you enjoy it and find it insightful. Here is Nuno Reis. Show notes: Nuno on LinkedIn Nuno's free book, Beyond Luck Bayesian Thinking _ _ _ _ _ _ _ _ Like what you heard? Subscribe to All Things Risk wherever great podcasts are found: https://thedecisionmaking.studio/podcast Learn more about The Decision-Making Studio Join our “Decision Navigators” course (May 21, 2024 cohort now open)!  

FAST24 | June 10 - 12, 2024 | Wilmington, North CarolinaFAST24 is our annual conference for pre-hospital and critical care transport professionals, including nurses, paramedics, and other disciplines. It features engaging workshops, talks by industry leaders, and focused sessions on air and surface critical care transport medicine. The event also offers a unique vendor experience, special guest appearances from notable talent in the industry, catered lunches, as well as relaxing and entertaining networking and social opportunities. Tickets are limited so don't wait! Visit https://fastsymposium.com for more information.The debate about which drug to use for sedation prior to RSI will.. just.. not… die. Advocates for both ketamine and etomidate approach the argument with near-religious zeal. There have been studies. We've even covered some here. What we need is a systematic review and meta-analysis, preferably using a type of analysis that recognizes that this likely isn't a black and white question and can bring some.. .nuance to it. That's were our friend Bayes comes in. Dr. Jarvis is joined by Drs Remle Crowe and CJ Winkler to discuss this paper and what in the hell Bayesian analysis actually is. We get some nice book recommendations in the process. Plus, we check in with ChatGPT for answers.Oh, BTW... don't take zoological advice from Dr. Winkler. Contrary to his thoughts, Giraffe's do NOT, in fact, have larger hearts than elephants. Citations:1. Koroki T, Kotani Y, Yaguchi T, Shibata T, Fujii M, Fresilli S, Tonai M, Karumai T, Lee TC, Landoni G, Hayashi Y. Ketamine versus etomidate as an induction agent for tracheal intubation in critically ill adults: a Bayesian meta-analysis. Crit Care. 2024 Feb 17;28(1):48. doi: 10.1186/s13054-024-04831-4. PMID: 38368326; PMCID: PMC10874027.2. Russotto V, Myatra SN, Laffey JG, et al. Intubation Practices and Adverse Peri-intubation Events in Critically Ill Patients From 29 Countries. JAMA. 2021;325(12):1164-1172.Bonus book recommendations3. Heller J. Catch-22. New York, NY: Simon & Schuster; 1961.4. McGrayne SB. The Theory That Would Not Die. How Bayes' Rule Cracked The Enigma Code, Hunted Down Russian Submarines & Emerged Triumphant From Two Centuries of Controversy. Yale University Press; 2011.5. Salsburg D. The Lady Tasting Tea: How Statistics Revolutionized Science In The Twentieth Century. Henry Holt & Company; 2001.

In this episode Teun Teunis, MD, PhD discusses the concept of Bayesian statistical framework and the future of trial design as well as the implications for Hand Surgery. Teun Teunis currently works as an assistant professor of plastic surgery at the University of Pittsburgh Medical Center. He specialises in hand and upper extremity surgery, peripheral nerve surgery, including brachial plexus surgery and complex reconstructive and microsurgery. His research interests are related to his clinical practice, with an emphasis on mental and social health and their effects on patient reported outcomes. He received his medical degree with honours from Utrecht University in the Netherlands. He performed his PhD research at the Massachusetts General Hospital and the Harvard Medical School. He returned to the Netherlands to complete his plastic surgery residency at the University Medical Center Utrecht. After which he completed a Hand and Upper Extremity fellowship at the University of Pittsburgh Medical Center.

Host Dr. Paul Whiting interviews paper author Dr. William Obremskey as they discuss this 10 year study outcome relative to infection rates with Vancomycin and analyzing and interpreting the data using Bayesian analysis. This paper was presented at the 2022 OTA Annual Meeting. For additional educational resources visit https://ota.org/ To see the abstract while you listen, as well as explore OTA CME podcast episodes, download the ConveyMED App for free: Apple Store click here  Google Play click here

If you've never heard of Bayesian Analysis or don't know what it is, don't worry, Ethan didn't know what it was either. That's why we have this show! Bayesian Analysis is a tool used to help measure the probability of any given thing. It can be used for simple problem-solving like "Who ate my pizza?" as well as more complex issues like "Is there a God?" Today we learn from Exploring Reality what Bayesian Analysis is and how we can use it to make a case for belief in God, ie, Theism. Exploring Reality: Website: https://www.exploring-reality.com/ Youtube: https://www.youtube.com/@ExploringReality Tiktok: https://www.tiktok.com/@exploringreality Got any questions or topics you'd like to hear about? You can email us at thingsyoudonthearinchurchpod@gmail.com Like our content? Consider helping us grow through Patreon, a follow, or subscribe! Leave a rating on whatever platform you listen on and write some nice comments YOUTUBE here PATREON here INSTAGRAM: www.instagram.com/ thingsyoudonthearinchurchpod --- Support this podcast: https://anchor.fm/thingsyoudonthearinchurch/support

Brad Carlin is a statistical researcher, methodologist, consultant, and instructor.  He currently serves as Senior Advisor for Data Science and Statistics at PharmaLex, an international pharmaceutical consulting firm.  Prior to this, he spent 27 years on the faculty of the Division of Biostatistics at the University of Minnesota School of Public Health, serving as division head for 7 of those years.  He has also held visiting positions at Carnegie Mellon University, Medical Research Council Biostatistics Unit, Cambridge University (UK), Medtronic Corporation, HealthPartners Research Foundation, the M.D Anderson Cancer Center, and AbbVie Pharmaceuticals.   He has published more than 185 papers in refereed books and journals, and has co-authored three popular textbooks: “Bayesian Methods for Data Analysis” with Tom Louis, “Hierarchical Modeling and Analysis for Spatial Data” with Sudipto Banerjee and Alan Gelfand, and "Bayesian Adaptive Methods for Clinical Trials" with Scott Berry, J. Jack Lee, and Peter Muller.  From 2006-2009 he served as editor-in-chief of Bayesian Analysis, the official journal of the International Society for Bayesian Analysis (ISBA).  During his academic career, he served as primary dissertation adviser for 20 PhD students.  Dr. Carlin has extensive experience teaching short courses and tutorials, and won both teaching and mentoring awards from the University of Minnesota. During his spare time, Brad is a health musician and bandleader, providing keyboards, guitar, and vocals in a variety of venues.

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 Newborns With Hypoxic-Ischemic Encephalopathy: A Randomized Clinical Trial Incorporating Adult Evidence Into Pediatric Research and Practice: Bayesian Designs to Expedite Obtaining Child-Specific Evidence

La créativité humaine est quelque chose d'incroyable. C'est grâce à elle que notre société évolue sans cesse. On développe, on améliore, on crée. C'est en même temps quelque chose de fondamental à notre espèce et d'unique, mais aussi quelque chose de très personnel pour chaque individu. D'où vient cette capacité humaine unique ? Quels processus neuronaux rendent possibles l'émergence de nouvelles idées ? Comment pouvons-nous tous développer cette capacité incroyable ? La créativité étant un vaste sujet, aujourd'hui je vais m'atteler à trois choses : 1/ Démanteler le mythe que la créativité vient du cerveau droit2/ Montrer comment naît une idée dans le cerveau 3/ Vous prouver que la créativité s'apprend et peut tout à fait se développer dans le cerveau.Si vous souhaitez avoir un éclairage neuro sur un sujet en particulier de la vie quotidienne, de notre fonctionnement, écrivez-moi à neurosapiens.podcast@gmail.com Production, animation, réalisation et illustration : Anaïs RouxLe site internet : www.neurosapiens.frSources : Bendetowicz D, Urbanski M, Garcin B, Foulon C, Levy R, Bréchemier ML, Rosso C, Thiebaut de Schotten M, Volle E. Brain. Two critical brain networks for generation and combination of remote associations. 2017 Nov 22.G. Gonen-Yaacovi et al., Rostral and caudal prefrontal contribution to creativity : a meta-analysis of functional imaging data, in Frontiers in Human Neuroscience, vol. 7, pp. 1-22, 2013.Rosen DS, Oh Y, Erickson B, Zhang FZ, Kim YE, Kounios J. Dual-process contributions to creativity in jazz improvisations: An SPM-EEG study. Neuroimage. 2020 Jun;213:116632. doi: 10.1016/j.neuroimage.2020.116632. Epub 2020 Feb 28. PMID: 32114150.Beaty, R. E., Kenett, Y. N., Christensen, A. P., Rosenberg, M. D., Benedek, M., Chen, Q., Fink, A., Qiu, J., Kwapil, T. R., Kane, M. J., & Silvia, P. J. (2018). Robust prediction of individual creative ability from brain functional connectivity. Proceedings of the National Academy of Sciences of the United States of America, 115(5), 1087–1092.Li, W., Yang, J., Zhang, Q., Li, G., & Qiu, J. (2016). The Association between Resting Functional Connectivity and Visual Creativity. Scientific reports, 6. Durante, D., & Dunson, D. B. (2018). Bayesian inference and testing of group differences in brain networks. Bayesian Analysis, 13(1), 29-58.Musique d'intro : KEEP ON GOINGMusique proposée par La Musique LibreJoakim Karud - Keep On Going : https://youtu.be/lOfg0jRqaA8Joakim Karud : https://soundcloud.com/joakimkarud Voir Acast.com/privacy pour les informations sur la vie privée et l'opt-out. Become a member at https://plus.acast.com/s/neurosapiens.

Alicia Carriquiry is a professor of statistics at Iowa State University. Between January of 2000 and July of 2004, she was Associate Provost at Iowa State. Her research interests are in Bayesian statistics and general methods. Her recent work focuses on nutrition and dietary assessment, as well as on problems in genomics, forensic sciences, and traffic safety. She currently teaches (and greatly enjoys!) a graduate-level course on Bayesian data analysis at Iowa State University and has four doctoral students working under her supervision at this time. Four of her Ph.D. students have already graduated work at Ohio State University, the National Cancer Institute, Carnegie Mellon University, and Iowa State University. Dr. Carriquiry is an elected Member of the International Statistical Institute and a Fellow of the American Statistical Association. She serves on the Executive Committee of the Institute of Mathematical Statistics and has been a member of the Board of Trustees of the National Institute of Statistical Sciences since 1997. She is also a past president of the International Society for Bayesian Analysis (ISBA) and a past member of the Board of the Plant Sciences Institute at Iowa State University. Dr. Carriquiry is Editor of Statistical Sciences and of Bayesian Analysis and serves on the editorial boards of several Latin American journals of statistics and mathematics. She has served on three National Academy of Sciences committees: the Subcommittee on Interpretation and Uses of Dietary Reference Intakes; the Committee on Evaluation of USDA's Methodology for Estimating Eligibility and Participation for the WIC Program and the Committee on Third Party Toxicity Research with Human Research Participants. Currently, she is a member of the Standing Committee on Applied and Theoretical Statistics of the National Research Council, the Committee on Assessing the Feasibility, Accuracy and Technical Capability of a Ballistics National Database of the National Research Council, and of the Committee on Gender Differences in the Careers in Science, Mathematics and Engineering Faculty of the National Academy of Sciences. She is a member of the Federal Steering Committee Future Directions for the CSFII/NHANES Diet/Nutrition Survey: What We Eat in America. Carriquiry received an MSc in animal science from the University of Illinois, and an MSc in statistics, and a Ph.D. in statistics and animal genetics from Iowa State University. --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app --- Send in a voice message: https://anchor.fm/changeyourpov/message Support this podcast: https://anchor.fm/changeyourpov/support

In this episode we're going to discuss a very special Bayesian Analysis conducted by some cool guys from Columbia University to tried to tackle the question, "What's the mathematical probability that intelligent alien life exists? We'll also set the stage for the next few episodes where we'll discuss 9/11, the Kennedy Assassination, and how they're related. --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app Support this podcast: https://anchor.fm/thedankgreene/support

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.10.01.322362v1?rss=1 Authors: Miller, B., Morse, A., Borgert, J. E., Liu, Z., Sinclair, K., Gamble, G., Zou, F., Newman, J., Leon-Novelo, L., Marroni, F., McIntyre, L. Abstract: Allelic imbalance (AI) occurs when alleles in a diploid individual are differentially expressed and indicates cis acting regulatory variation. What is the distribution of allelic effects in a natural population? Are all alleles the same? Are all alleles distinct? Tests of allelic effect are performed by crossing individuals and comparing expression between alleles directly in the F1. However, a crossing scheme that compares alleles pairwise is a prohibitive cost for more than a handful of alleles as the number of crosses is at least (n2-n)/2 where n is the number of alleles. We show here that a testcross design followed by a hypothesis test of AI between testcrosses can be used to infer differences between non-tester alleles, allowing n alleles to be compared with n crosses. Using a mouse dataset where both testcrosses and direct comparisons have been performed, we show that ~75% of the predicted differences between non-tester alleles are validated in a background of ~10% differences in AI. The testing for AI involves several complex bioinformatics steps. BASE is a complete bioinformatics pipeline that incorporates state-of-the-art error reduction techniques and a flexible Bayesian approach to estimating AI and formally comparing levels of AI between conditions. The modular structure of BASE has been packaged in Galaxy, made available in Nextflow and sbatch on github (https://github.com/McIntyre-Lab/BASE_2020). In the mouse data, the direct test identifies more cis effects than the testcross. Cis-by-trans interactions with trans-acting factors on the X contributing to observed cis effects in autosomal genes in the direct cross remains a possible explanation for the discrepancy. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.09.11.292706v1?rss=1 Authors: Kist, J. D., Bethlehem, R. A. I., Stonier, B., Sluijters, O. J. J., Crockford, S. K., de Jonge, E., Freyberg, J., Baron-Cohen, S., Parsons, O. E. Abstract: The ability to correctly identify emotions in social stimuli such as faces is proposed to affect ones level of cognitive empathy. The Fusiform Face Area shows a heightened neural response during the perception of faces relative to objects. We tested whether neural responses to social stimuli were associated with performance in a measure of cognitive empathy, the Reading the Mind in the Eyes Task. To quantify face perception, participants were presented with images during a fast serial presentation task which elicited a steady state visual evoked potential, measured using electroencephalography. A Sequential Bayesian Analysis was used to assess if face specific neural responses were associated with either cognitive empathy or age. Data were collected from a participant group of both neurotypical individuals and individuals on the autistic spectrum. We found no significant relationship between the face-specific neural signature, cognitive empathy or age. This study highlights the efficiency of the Sequential Bayesian Analysis as an effective method of participant recruitment. Copy rights belong to original authors. Visit the link for more info

Some of you may have heard of Bayesian analysis. You may think this is something fancy that only universities do. The post So what is up with this Bayesian analysis stuff appeared first on Accendo Reliability.

On this episode, we are going to weave a thread through three different areas of Python programming that at first seem unlikely to have much in common. Yet, the core will be the same throughout. I think this is a cool lesson to learn as you get deeper into programming and a great story to highlight it. We are going to meet Ravin Kumar who wrote Python code and data science tooling for oil rig tool manufacturer, a rocket company, and a hip multilocation restaurant chain. Links from the show Ravin on Twitter: @canyon289 PyMC3: pymc.io Arviz project: arviz-devs.github.io/arviz pystan project: pystan.readthedocs.io NumFocus: numfocus.org Bayesian Decision Making: canyon289.github.io open-aerospace project: open-aerospace.github.io SweetGreen: sweetgreen.com Get notified when Bayesian Computation In Python is out: docs.google.com/forms Bayesian Analysis with Python Book: packtpub.com Sponsors Sentry Error Monitoring, Code TALKPYTHON Linode Talk Python Training

Join the after party on Discord! Link: https://discord.gg/ZzJSrGP UFO sighting: 'Alien craft' over California sparks claim of secret army testing at Area 51 Link: https://www.express.co.uk/news/weird/1287102/UFO-sighting-alien-spacecraft-California-Area-51-UFO-army-testing-Scott-Waring A UFO photographed over Southern California may have come from the top-secret Area 51 airforce base, a prominent UFO hunter has claimed. The unidentified flying object (UFO) was photographed over Palm Springs, California, prompting claims of an alien craft in the skies. According to self-described UFO expert Scott C Waring, the UFO may have come from the highly classified US Air Force base known as Area 51. Area 51 has been at the heart of many UFO stories and alien conspiracy theories, including the 1947 Roswell incident. Mr Waring said on his blog ET Data Base: "This UFO was seen over Palm Springs, California this week. "The object was only seen for a few seconds. "It's located on far southern California so it's mostly rocky desert. "This is one of the prime areas that UFOs will be seen from Area S4, which is inside Area 51." The UFO photo was originally shared to MUFON or the Mutual UFO Network by an eyewitness on May 24. The photo appears to show a blurry, grey object flying far behind a power transformer seen in the foreground. According to the original eyewitness statement, the UFO appeared and disappeared "in a blink of the eye". The eyewitness said the object was tic tac-shaped with appendages. The UFO also disappeared as soon as its photo was taken. California is home to more military installations than any other state, with a total of 32. Army, Navy, Air Force, Marine Corps, Coast Guard, and National Guard/Reserve bases are located across California. The Army and the Air Force make up more than 75 percent of the manpower in Alaska at the Fort Wainwright, Fort Greely, and Joint Base Elmendorf-Richardson. Most of the training operations prepare service members for operating in inhospitable winter climates whether on the ground or in the air. Ohio's Wright Patterson Air Force Base is one of the Air Force's largest and most important installations. It is home to the world's first operational airfield. UFO sighting: Alien spaceship spotted in NASA Apollo 9 mission – claim Link: https://www.express.co.uk/news/weird/1286594/ufo-sighting-alien-spaceship-nasa-apollo-9-ufos-aliens-news ALIEN enthusiasts believe they have spotted a UFO in the clouds in images from NASA's historic Apollo 9 mission. Apollo 9 saw three NASA astronauts blasted into the Earth's orbit for 10 days as a test flight before the Apollo 11 mission, which saw the first people land on the Moon. Commander James McDivitt, Command Module Pilot David Scott, and Lunar Module Pilot Rusty Schweickart lifted off from Earth on March 3, 1969, before spending 10 days in orbit, completing 151 trips around Earth. The three men landed back on Earth on March 13, just four months before the Apollo 11 mission set off for the Moon. Prominent conspiracy theorist Scott C Waring has been analysing the images from the NASA astronauts and believes he has found a UFO which is "100 percent" proof of aliens. Mr Waring wrote on his blog ET Database: "I found a triangle UFO in an old Apollo 9 mission photo. The module was flying directly over Arizona at the time and this triangle UFO was seen in the clouds below. "The triangle looks dark brown. The object is blurry at an equal pace as that of the clouds and other objects [sic ]in the picture. "Had this been 100 percent focused and the clouds blurry, then we would know its not real, but thats not how it is here. "The UFO and the other things in the photo have the same focus which tells us its 100 percent real." This Math Formula Has Determined the Odds of Aliens Existing Link: https://www.popularmechanics.com/science/a32603529/math-formula-aliens-exist/ David Kipping leads, yes, the Cool Worlds Laboratory at Columbia University. In an explainer video (below), he describes some background for the question of intelligent life in the universe and concludes, “I've never been much for faith—I want an answer.” Kipping mentions the changing trends over centuries of human imagination: Basically, as soon as people realized what they saw in the sky included other planets, they began to wonder if other planets had intelligent life. An underdeveloped instrument caused astronomers to see “manmade” canals on the surface of Mars during the 1800s. Turn to Bayesian (bei·Zhn) analysis, a way of using what we do know to extrapolate what we don't. And to do that, Kipping put Earth's long history on a replay loop. The squeeze here is whether or not that life would eventually evolve intelligence. Instead of 3:1, the odds are just 3:2, meaning three of every five reruns with life would become intelligent life. So overall, that means a 75 percent probability of life and 60 percent likelihood of intelligence, for an overall probability of 45 percent. If the Bayesian analysis is right, that means even for Earth to be itself was the probabilistic minority. But it's still a more concrete argument for the existence of life on Earthlike planets around the universe. “Overall, our work supports an optimistic outlook for future searches for biosignatures,” the paper explains. Show Stuff Join the fan chat on Discord! Link: https://discord.gg/ZzJSrGP The Dark Horde Podcast: https://www.spreaker.com/show/the-dark-horde The Dark Horde, LLC – http://www.thedarkhorde.com Twitter @DarkHorde or https://twitter.com/HordeDark Support the podcast and shop @ http://shopthedarkhorde.com UBR Truth Seekers Facebook Group: https://www.facebook.com/groups/216706068856746 UFO Buster Radio: https://www.facebook.com/UFOBusterRadio YouTube Channel: https://www.youtube.com/channel/UCggl8-aPBDo7wXJQ43TiluA To contact Manny: manny@ufobusterradio.com, or on Twitter @ufobusterradio Call the show anytime at (972) 290-1329 and leave us a message with your point of view, UFO sighting, and ghostly experiences or join the discussion on www.ufobusterradio.com For Skype Users: bosscrawler

Join the after party on Discord! Link: https://discord.gg/ZzJSrGP UFO sighting: 'Alien craft' over California sparks claim of secret army testing at Area 51 Link: https://www.express.co.uk/news/weird/1287102/UFO-sighting-alien-spacecraft-California-Area-51-UFO-army-testing-Scott-Waring A UFO photographed over Southern California may have come from the top-secret Area 51 airforce base, a prominent UFO hunter has claimed. The unidentified flying object (UFO) was photographed over Palm Springs, California, prompting claims of an alien craft in the skies. According to self-described UFO expert Scott C Waring, the UFO may have come from the highly classified US Air Force base known as Area 51. Area 51 has been at the heart of many UFO stories and alien conspiracy theories, including the 1947 Roswell incident. Mr Waring said on his blog ET Data Base: "This UFO was seen over Palm Springs, California this week. "The object was only seen for a few seconds. "It's located on far southern California so it's mostly rocky desert. "This is one of the prime areas that UFOs will be seen from Area S4, which is inside Area 51." The UFO photo was originally shared to MUFON or the Mutual UFO Network by an eyewitness on May 24. The photo appears to show a blurry, grey object flying far behind a power transformer seen in the foreground. According to the original eyewitness statement, the UFO appeared and disappeared "in a blink of the eye". The eyewitness said the object was tic tac-shaped with appendages. The UFO also disappeared as soon as its photo was taken. California is home to more military installations than any other state, with a total of 32. Army, Navy, Air Force, Marine Corps, Coast Guard, and National Guard/Reserve bases are located across California. The Army and the Air Force make up more than 75 percent of the manpower in Alaska at the Fort Wainwright, Fort Greely, and Joint Base Elmendorf-Richardson. Most of the training operations prepare service members for operating in inhospitable winter climates whether on the ground or in the air. Ohio's Wright Patterson Air Force Base is one of the Air Force's largest and most important installations. It is home to the world's first operational airfield. UFO sighting: Alien spaceship spotted in NASA Apollo 9 mission – claim Link: https://www.express.co.uk/news/weird/1286594/ufo-sighting-alien-spaceship-nasa-apollo-9-ufos-aliens-news ALIEN enthusiasts believe they have spotted a UFO in the clouds in images from NASA's historic Apollo 9 mission. Apollo 9 saw three NASA astronauts blasted into the Earth's orbit for 10 days as a test flight before the Apollo 11 mission, which saw the first people land on the Moon. Commander James McDivitt, Command Module Pilot David Scott, and Lunar Module Pilot Rusty Schweickart lifted off from Earth on March 3, 1969, before spending 10 days in orbit, completing 151 trips around Earth. The three men landed back on Earth on March 13, just four months before the Apollo 11 mission set off for the Moon. Prominent conspiracy theorist Scott C Waring has been analysing the images from the NASA astronauts and believes he has found a UFO which is "100 percent" proof of aliens. Mr Waring wrote on his blog ET Database: "I found a triangle UFO in an old Apollo 9 mission photo. The module was flying directly over Arizona at the time and this triangle UFO was seen in the clouds below. "The triangle looks dark brown. The object is blurry at an equal pace as that of the clouds and other objects [sic ]in the picture. "Had this been 100 percent focused and the clouds blurry, then we would know its not real, but thats not how it is here. "The UFO and the other things in the photo have the same focus which tells us its 100 percent real." This Math Formula Has Determined the Odds of Aliens Existing Link: https://www.popularmechanics.com/science/a32603529/math-formula-aliens-exist/ David Kipping leads, yes, the Cool Worlds Laboratory at Columbia University. In an explainer video (below), he describes some background for the question of intelligent life in the universe and concludes, “I've never been much for faith—I want an answer.” Kipping mentions the changing trends over centuries of human imagination: Basically, as soon as people realized what they saw in the sky included other planets, they began to wonder if other planets had intelligent life. An underdeveloped instrument caused astronomers to see “manmade” canals on the surface of Mars during the 1800s. Turn to Bayesian (bei·Zhn) analysis, a way of using what we do know to extrapolate what we don't. And to do that, Kipping put Earth's long history on a replay loop. The squeeze here is whether or not that life would eventually evolve intelligence. Instead of 3:1, the odds are just 3:2, meaning three of every five reruns with life would become intelligent life. So overall, that means a 75 percent probability of life and 60 percent likelihood of intelligence, for an overall probability of 45 percent. If the Bayesian analysis is right, that means even for Earth to be itself was the probabilistic minority. But it's still a more concrete argument for the existence of life on Earthlike planets around the universe. “Overall, our work supports an optimistic outlook for future searches for biosignatures,” the paper explains. Show Stuff Join the fan chat on Discord! Link: https://discord.gg/ZzJSrGP The Dark Horde Podcast: https://www.spreaker.com/show/the-dark-horde The Dark Horde, LLC – http://www.thedarkhorde.com Twitter @DarkHorde or https://twitter.com/HordeDark Support the podcast and shop @ http://shopthedarkhorde.com UBR Truth Seekers Facebook Group: https://www.facebook.com/groups/216706068856746 UFO Buster Radio: https://www.facebook.com/UFOBusterRadio YouTube Channel: https://www.youtube.com/channel/UCggl8-aPBDo7wXJQ43TiluA To contact Manny: manny@ufobusterradio.com, or on Twitter @ufobusterradio Call the show anytime at (972) 290-1329 and leave us a message with your point of view, UFO sighting, and ghostly experiences or join the discussion on www.ufobusterradio.com For Skype Users: bosscrawler

Alex Andorra, host of the new podcast Learning Bayesian Statistics joins The Local Maximum today to talk about these fascinating issues: - The growing role of Bayesian Analysis in Science and Technology - How the pollsters and journalists cover election data, and how it can be improved - Ways to look at election polls from a Bayesian standpoint - Strategic voting, comparative political systems, and social choice theory - Approaches to explaining these topics in audio (podcast) form! localmaxradio.com/98

What do neurodegenerative diseases, gerrymandering and ecological inference all have in common? Well, they can all be studied with Bayesian methods — and that’s exactly what Karin Knudson is doing. In this episode, Karin will share with us the vital and essential work she does to understand aspects of neurodegenerative diseases. She’ll also tell us more about computational neuroscience and Dirichlet processes — what they are, what they do, and when you should use them. Karin did her doctorate in mathematics, with a focus on compressive sensing and computational neuroscience at the University of Texas at Austin. Her doctoral work included applying hierarchical Dirichlet processes in the setting of neural data and focused on one-bit compressive sensing and spike-sorting. Formerly the chair of the math and computer science department of Phillips Academy Andover, she started a postdoc at Mass General Hospital and Harvard Medical in Fall 2019. Most importantly, rock climbing and hiking have no secrets for her! Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ ! Links from the show, personally curated by Karin Knudson: Karin on Twitter: https://twitter.com/karinknudson Spike train entropy-rate estimation using hierarchical Dirichlet process priors (Knudson and Pillow): https://pillowlab.princeton.edu/pubs/abs_Knudson_HDPentropy_NIPS13.html Fighting Gerrymandering with PyMC3, PyCon 2018, Colin Carroll and Karin Knudson: https://www.youtube.com/watch?v=G9I5ZnkWR0A Expository resources on Dirichlet Processes: Chapter 23 of Bayesian Data Analysis (Gelman et al.) and http://www.gatsby.ucl.ac.uk/~ywteh/research/npbayes/dp.pdf Hierarchical Dirichlet Processes (introduced the HDP and included applications in topic modeling and for working with time-series data and Hidden Markov Models): https://www.stat.berkeley.edu/~aldous/206-Exch/Papers/hierarchical_dirichlet.pdf A Sticky HDP-HMM with applications to speaker diarization (a nice example of how the HDP can be used with HMM, in this case cleverly adapted so that states have more persistence): https://arxiv.org/abs/0905.2592 If you want to get deeper into the weeds and also get a sense of the history: Dirichlet Processes with Applications to Bayesian Nonparametric Problems (https://projecteuclid.org/euclid.aos/1176342871) and A Bayesian Analysis of Some Nonparametric Problems (https://projecteuclid.org/euclid.aos/1176342360) --- Send in a voice message: https://anchor.fm/learn-bayes-stats/message

Mags Wiley speaks to Colin Gillespie from Newcastle University about his modelling of sheep flocking.

What do you get when you put a physicist, a biologist and a data scientist in the same body? Well, you’re about to find out… In this episode you’ll meet Osvaldo Martin. Osvaldo is a researcher at the National Scientific and Technical Research Council in Argentina and is notably the author of the book Bayesian Analysis with Python, whose second edition was published in December 2018. He also teaches bioinformatics, data science and Bayesian data analysis, and is a core developer of PyMC3 and ArviZ, and recently started contributing to Bambi. Originally a biologist and physicist, Osvaldo trained himself to python and Bayesian methods – and what he’s doing with it is pretty amazing! We also touch on how accepted are Bayesian methods in his field, which models he’s currently working on, and what it’s like to be an open-source developer. Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com! Links from the show: Bayesian Analysis with Python, 2nd edition: https://www.amazon.com/dp/B07HHBCR9G Bayesian Analysis with Python, code repository; https://github.com/aloctavodia/BAP Osvaldo on Twitter: https://twitter.com/aloctavodia PyMC3, Probabilistic Programming in Python: https://docs.pymc.io/ ArviZ, Exploratory analysis of Bayesian models: https://arviz-devs.github.io/arviz/ BAyesian Model-Building Interface (BAMBI) in Python: https://bambinos.github.io/bambi/ --- Send in a voice message: https://anchor.fm/learn-bayes-stats/message

Dr Paul Wu is a Research Fellow, Associate Investigator for the Australian Research Council centre of excellence of mathematical and statistical frontiers. He is also a member of the Bayesian Research and Applications Group at QUT. Paul has been involved in some interesting research at sports, including predictive modelling of fatigue (with the AIS) and Bayesian analysis in sports.Read more about Paul here.Podcasts cost money to make, equipment, software and the like. Thankfully Betfair has sponsored this podcast which means I can just concentrate on getting fantastic guests!

In this episode physics professor Brian Blais joins Andrew and Matthew to discuss The Fine Tuning Argument, The Second Law of Thermodynamics, contingency, evidence for the Christian claim of a historical resurrection of Jesus of Nazareth, and other topics found in Justin Brierley's book Unbelievable?: Why After Ten Years of Talking With Atheists, I'm Still a Christian. As you listen, you can decide for yourself whether Christian Apologetics draws appropriate conclusions from the best science of today. And, you will also have a meaningful guide if you read Justin's book. Dr. Blais has a Ph. D. In physics that emphasized computational neuroscience and was the recipient of a three year NSF research grant to study computational neuroscience and the recipient of the Biomedical Research Infrastructure Network (BRIN) grant. He is an active member of many professional organizations including The Geochemical Society and The American Statistical Association. He teaches undergraduate physics at Bryant University and is a research professor at The Institute for Brain and Neural Systems at Brown University. Brian has written extensively on Bayesian Probability and is currently writing a book about Bayesian Analysis that is geared toward readers with a less mathematical background but nevertheless have interest in understanding probability. He also listens to and regularly blogs concerning topics covered on Unbelievable?. To read more from Professor Blais, including the topics discussed in this episode, visit his blog: https://bblais.github.io For Justin Brierley's book visit: https://www.amazon.com/Unbelievable-After-Talking-Atheists-Christian/dp/0281077983/ref=sr_1_5?keywords=unbelievable&qid=1558145223&s=gateway&sr=8-5 At the end of the show, we promised a link to The Shawn Carroll William Lane Craig debate. Visit this YouTube page to watch their debate: https://www.youtube.com/watch?v=X0qKZqPy9T8 --- Send in a voice message: https://anchor.fm/still-unbelievable/message

Julien Cornebise is a Director of Research, AI for Good at Element AI and head of the London Office. He is also an honorary researcher at University College London. Prior to Element AI, Julien was at DeepMind (later acquired by Google) as an early employee, where he led several fundamental research projects used in early demos and fundraising. After leaving DeepMind in 2016, he worked with Amnesty International. Julien holds an MSc in Computer Engineering, an MSc in Mathematical Statistics, and a PhD in Mathematics, specialized in Computational Statistics, from University Paris VI Pierre and Marie Curie and Telecom ParisTech. He received the 2010 Savage Award in Theory and Methods from the International Society for Bayesian Analysis for his PhD work. In today's episode Julien shares some considerations on what makes AI good or bad; reflections on the ethics and drive for purpose of the humans that build technology; his experience working alongside anthropologists and sociologists as part of Element AI's team of AI for Good; the value of diversity in teams and how to prevent replicating bias with AI; advice to anthropologists considering to transition to industry ; some key points of the keynote he will give at the Anthropology + Technology Conference 2019 happening on Oct 3rd in Bristol, UK under the theme of Championing socially responsible AI. Mentioned in Podcast: DeepMind Technologies ElementAI AI for Good Kentaro Toyama Geek Heresy: Rescuing Social Change from the Cult of Technology, Kentaro Toyama UN Sustainable Development Goals 2019 AI Talent report - issued by element AI Tech Workers Now Want to Know: What Are We Building This For?, Kate Conger, Cade Metz, NY Times, Oct 7 2018 Thomas Piketty Capital in the Twenty-First Century, Thomas Piketty Davos 2019: Historian Rutger Bregman berates billionaires at World Economic Forum over tax avoidance Utopia for Realists: How We Can Build the Ideal World, Rutger Bregman Anthropology + Technology Conference 2019 Julien's work: Google Scholar profile: https://scholar.google.co.uk/citations?user=6fkVVz4AAAAJ&hl=en&oi=ao Social media and other links: Email: julien AT elementai.com LinkedIn profile: https://www.linkedin.com/in/juliencornebise Twitter profile: https://twitter.com/JCornebise

Our guest this episode is data scientist Peadar Coyle. Topics include Brexit whether Europe is a Python continent or an R continent GDPR how data science is different in Europe than it is in the USA Joel's stock rant against "domain expertise" PyMC3 and Bayesian Analysis teaching online courses whether "primer" is pronounced "primer" or "primer" what Joel and Andrew are most excited about in data science Please listen to it.

Show Notes: (2:07) Chintan talked about his undergraduate education in India at the Dharmsinh Desai University, studying Electronics & Communication. (2:53) Chintan recalled the most useful knowledge from his undergraduate experience. (3:42) Chintan explained his decision to pursue a Master degree in Communication and Signal Processing at Newcastle University in the UK. (5:09) Chintan discussed advanced communication systems knowledge he learned during his Master. (6:25) Chintan talked about his decision to continue his academic journey with a Ph.D. in Underwater Acoustic Communication at Newcastle University. (8:15) Chintan went in depth to explain the study of Underwater Acoustic Communication and how it is different from normal communication systems. (11:45) Chintan discussed his Ph.D. thesis on applying Bayesian theorem for Turbo coding to solve signal processing problems under the water. (15:00) Chintan elaborated on the benefits of doing a Ph.D. degree. (19:01) Chintan mentioned the importance of collaboration in the academic community. (20:18) Chintan talked about his Post-Doc experience at University of Illinois Urbana Champaign. (22:00) Chintan discussed his next career step moving back to the UK working as a digital communication engineer at Schlumberger, a big company in the oil and gas industry. (27:30) Chintan characterize datasets that are particular to oil and gas. (28:58) Chintan examined the technique of vibration analysis in his work. (31:23) Chintan next landed a role as a Software Engineer at a company called SmartFocus in London. (34:52) Chintan mentioned the best resources he used to learn machine learning and data science. (36:51) Chintan recalled his experience searching for a data science job. (38:02) Chintan briefly went over the interesting projects that he has involved with at Avanade, his current employer. (40:34) Chintan talked about his recent transition from a Senior Data Scientist role to a Manager in Advanced Analytics role. (43:35) Chintan shared his view about the data science community in London. (44:44) Closing segments. His Contact Info: Twitter GitHub LinkedIn His Recommended Resources: Andrew Ng’s Machine Learning Coursera Course MIT’s The Analytics Edge edX Course London’s Data Science Festival Nate Silver’s “The Signal and The Noise” Charles Wheelan’s “Naked Statistics” Philip Tetlock’s “Superforecasting”

Show Notes: (2:07) Chintan talked about his undergraduate education in India at the Dharmsinh Desai University, studying Electronics & Communication. (2:53) Chintan recalled the most useful knowledge from his undergraduate experience. (3:42) Chintan explained his decision to pursue a Master degree in Communication and Signal Processing at Newcastle University in the UK. (5:09) Chintan discussed advanced communication systems knowledge he learned during his Master. (6:25) Chintan talked about his decision to continue his academic journey with a Ph.D. in Underwater Acoustic Communication at Newcastle University. (8:15) Chintan went in depth to explain the study of Underwater Acoustic Communication and how it is different from normal communication systems. (11:45) Chintan discussed his Ph.D. thesis on applying Bayesian theorem for Turbo coding to solve signal processing problems under the water. (15:00) Chintan elaborated on the benefits of doing a Ph.D. degree. (19:01) Chintan mentioned the importance of collaboration in the academic community. (20:18) Chintan talked about his Post-Doc experience at University of Illinois Urbana Champaign. (22:00) Chintan discussed his next career step moving back to the UK working as a digital communication engineer at Schlumberger, a big company in the oil and gas industry. (27:30) Chintan characterize datasets that are particular to oil and gas. (28:58) Chintan examined the technique of vibration analysis in his work. (31:23) Chintan next landed a role as a Software Engineer at a company called SmartFocus in London. (34:52) Chintan mentioned the best resources he used to learn machine learning and data science. (36:51) Chintan recalled his experience searching for a data science job. (38:02) Chintan briefly went over the interesting projects that he has involved with at Avanade, his current employer. (40:34) Chintan talked about his recent transition from a Senior Data Scientist role to a Manager in Advanced Analytics role. (43:35) Chintan shared his view about the data science community in London. (44:44) Closing segments. His Contact Info: Twitter GitHub LinkedIn His Recommended Resources: Andrew Ng’s Machine Learning Coursera Course MIT’s The Analytics Edge edX Course London’s Data Science Festival Nate Silver’s “The Signal and The Noise” Charles Wheelan’s “Naked Statistics” Philip Tetlock’s “Superforecasting”

Show Notes: (2:05) Chris recalled his Econometrics and Quantitative Economics study during his undergraduate days. (4:14) Chris talked about his research work focus on oil and gas at the Center for Energy Studies at Louisiana State University. (5:53) Chris gave some insights on how data science and econometrics can solve problems in the energy industry. (7:51) Chris talked about his decision to pursue a Masters in Applied Statistics. (9:02) Chris emphasized the importance of learning statistical theory. In particular, survival analysis is very similar to conversion rate analysis. (10:28) Chris discussed his Master’s thesis work in analyzing the churn rate for Treehouse. (12:05) Chris maintained his own website called Statwonk. (13:18) Chris mentioned the popularity of count data on consumer products. (14:40) Chris gave some recommendations for those who want to learn fundamental statistics: Think Stats, Think Bayes, Statistical Inference, and Statistical Intervals. (16:20) Chris recalled how he got a job as the first data scientist at Treehouse. (16:52) Chris described Treehouse CEO Ryan Carson as a “marketing genius.” (18:34) Chris spotted the number one most challenging aspect for a data scientist within a business - translating technical jargon to comprehensible concepts. (20:11) Chris recalled building a company dashboard from scratch for Treehouse. (22:46) Chris shared the background overview of his next employer, Zapier. (24:25) Chris shared his favorite things working as a data scientist as Zapier. (32:07) Chris recalled building an AnamolyBot to keep track of Slack communication between Zapier team members. (36:33) Chris talked about the open-source project he has been working on during his spare time. (39:10) Chris gave advice for people who want to seek remote positions. (42:20) Closing segments. His Contact Info: Website Twitter LinkedIn GitHub His recommended resources: Shopify’s Cameron-Davidson Pilon Stitch Fix’s Kim Larsen R for Data Science Hadley Wickham John Tukey’s “Exploratory Data Analysis” William Cleveland’s “The Elements of Graphing Data” #rstats #PyData

Show Notes: (2:05) Chris recalled his Econometrics and Quantitative Economics study during his undergraduate days. (4:14) Chris talked about his research work focus on oil and gas at the Center for Energy Studies at Louisiana State University. (5:53) Chris gave some insights on how data science and econometrics can solve problems in the energy industry. (7:51) Chris talked about his decision to pursue a Masters in Applied Statistics. (9:02) Chris emphasized the importance of learning statistical theory. In particular, survival analysis is very similar to conversion rate analysis. (10:28) Chris discussed his Master’s thesis work in analyzing the churn rate for Treehouse. (12:05) Chris maintained his own website called Statwonk. (13:18) Chris mentioned the popularity of count data on consumer products. (14:40) Chris gave some recommendations for those who want to learn fundamental statistics: Think Stats, Think Bayes, Statistical Inference, and Statistical Intervals. (16:20) Chris recalled how he got a job as the first data scientist at Treehouse. (16:52) Chris described Treehouse CEO Ryan Carson as a “marketing genius.” (18:34) Chris spotted the number one most challenging aspect for a data scientist within a business - translating technical jargon to comprehensible concepts. (20:11) Chris recalled building a company dashboard from scratch for Treehouse. (22:46) Chris shared the background overview of his next employer, Zapier. (24:25) Chris shared his favorite things working as a data scientist as Zapier. (32:07) Chris recalled building an AnamolyBot to keep track of Slack communication between Zapier team members. (36:33) Chris talked about the open-source project he has been working on during his spare time. (39:10) Chris gave advice for people who want to seek remote positions. (42:20) Closing segments. His Contact Info: Website Twitter LinkedIn GitHub His recommended resources: Shopify’s Cameron-Davidson Pilon Stitch Fix’s Kim Larsen R for Data Science Hadley Wickham John Tukey’s “Exploratory Data Analysis” William Cleveland’s “The Elements of Graphing Data” #rstats #PyData

Summary: Alicia Carriquiry is professor of statistics at Iowa State University.  Between January of 2000 and July of 2004 she was Associate Provost at Iowa State. Her research interests are in Bayesian statistics and general methods.  Her recent work focuses on nutrition and dietary assessment, as well as on problems in genomics, forensic sciences and traffic safety. She currently teaches (and greatly enjoys!) a graduate-level course on Bayesian data analysis at Iowa State University and has four doctoral students working under her supervision at this time. Four of her PhD students have already graduated work at The Ohio State University, the National Cancer Institute, Carnegie Mellon University and Iowa State University. Dr. Carriquiry is an elected Member of the International Statistical Institute and a Fellow of the American Statistical Association.  She serves on the Executive Committee of the Institute of Mathematical Statistics and has been a member of the Board of Trustees of the National Institute of Statistical Sciences since 1997. She is also a past president of the International Society for Bayesian Analysis (ISBA) and a past member of the Board of the Plant Sciences Institute at Iowa State University. Dr. Carriquiry is Editor of Statistical Sciences and of Bayesian Analysis, and serves on the editorial boards of several Latin American journals of statistics and mathematics.   She has served on three National Academy of Sciences committees: the Subcommittee on Interpretation and Uses of Dietary Reference Intakes;  the Committee on Evaluation of USDA's Methodology for Estimating Eligibility and Participation for the WIC Program and the Committee on Third Party Toxicity Research with Human Research Participants.  Currently, she is a member of the standing Committee on Applied and Theoretical Statistics of the National Research Council, the Committee on Assessing the Feasibility, Accuracy and Technical Capability of a Ballistics National Database of the National Research Council  and of the Committee on Gender Differences in the Careers in Science, Mathematics and Engineering Faculty of the National Academy of Sciences. She is a member of the Federal Steering Committee Future Directions for the CSFII/NHANES Diet/Nutrition Survey: What we Eat in America.  Carriquiry received a MSc in animal science from the University of Illinois, and an MSc  in statistics and a PhD in statistics and animal genetics from Iowa State University. In This Particular Episode You Will Learn: Dr. Carriquiry's background and experience The research project and stated goals One of the main problems regarding veteran mental health: veterans do not perceive a need for mental health services, and if they do, they don't access them Family support as a facilitating factor in accessing mental health services Culturally competent care in the VA as compared to community mental health providers The VA as a whole provides beneficial mental health services, but this isn't the case across the entire VA The need for community providers to collaborate with VA providers to provide the best care possible The benefits of telehealth in providing mental health care to those areas and populations that have limited access Links and Resources Mentioned in This Episode: Dr. Carriquirry's biography and website, including her email contact Synopsis of the Report from the National Academies  Key findings and recommendations of the report You can be sure to find future episodes of Head Space and Timing, and all of the CYPOV Podcast Network Shows, by subscribing through your Podcast player of choice, like iTunes. Using an app makes subscribing and listening to podcasts (both ours and others) so much simpler. Just subscribe to Change Your POV Podcast within your app and it will automatically update every time a new episode is released. Please Leave a Review on iTunes – Learn How Here. Would you like to be a guest on Head Space and Timing? Follow This Link.

Summary: Alicia Carriquiry is professor of statistics at Iowa State University.  Between January of 2000 and July of 2004 she was Associate Provost at Iowa State. Her research interests are in Bayesian statistics and general methods.  Her recent work focuses on nutrition and dietary assessment, as well as on problems in genomics, forensic sciences and traffic safety. She currently teaches (and greatly enjoys!) a graduate-level course on Bayesian data analysis at Iowa State University and has four doctoral students working under her supervision at this time. Four of her PhD students have already graduated work at The Ohio State University, the National Cancer Institute, Carnegie Mellon University and Iowa State University. Dr. Carriquiry is an elected Member of the International Statistical Institute and a Fellow of the American Statistical Association.  She serves on the Executive Committee of the Institute of Mathematical Statistics and has been a member of the Board of Trustees of the National Institute of Statistical Sciences since 1997. She is also a past president of the International Society for Bayesian Analysis (ISBA) and a past member of the Board of the Plant Sciences Institute at Iowa State University. Dr. Carriquiry is Editor of Statistical Sciences and of Bayesian Analysis, and serves on the editorial boards of several Latin American journals of statistics and mathematics.   She has served on three National Academy of Sciences committees: the Subcommittee on Interpretation and Uses of Dietary Reference Intakes;  the Committee on Evaluation of USDA's Methodology for Estimating Eligibility and Participation for the WIC Program and the Committee on Third Party Toxicity Research with Human Research Participants.  Currently, she is a member of the standing Committee on Applied and Theoretical Statistics of the National Research Council, the Committee on Assessing the Feasibility, Accuracy and Technical Capability of a Ballistics National Database of the National Research Council  and of the Committee on Gender Differences in the Careers in Science, Mathematics and Engineering Faculty of the National Academy of Sciences. She is a member of the Federal Steering Committee Future Directions for the CSFII/NHANES Diet/Nutrition Survey: What we Eat in America.  Carriquiry received a MSc in animal science from the University of Illinois, and an MSc  in statistics and a PhD in statistics and animal genetics from Iowa State University. In This Particular Episode You Will Learn: Dr. Carriquiry's background and experience The research project and stated goals One of the main problems regarding veteran mental health: veterans do not perceive a need for mental health services, and if they do, they don't access them Family support as a facilitating factor in accessing mental health services Culturally competent care in the VA as compared to community mental health providers The VA as a whole provides beneficial mental health services, but this isn't the case across the entire VA The need for community providers to collaborate with VA providers to provide the best care possible The benefits of telehealth in providing mental health care to those areas and populations that have limited access Links and Resources Mentioned in This Episode: Dr. Carriquirry's biography and website, including her email contact Synopsis of the Report from the National Academies  Key findings and recommendations of the report You can be sure to find future episodes of Head Space and Timing, and all of the CYPOV Podcast Network Shows, by subscribing through your Podcast player of choice, like iTunes. Using an app makes subscribing and listening to podcasts (both ours and others) so much simpler. Just subscribe to Change Your POV Podcast within your app and it will automatically update every time a new episode is released. Please Leave a Review on iTunes – Learn How Here. Would you like to be a guest on Head Space and Timing? Follow This Link.

Wed, 1 Jan 2014 12:00:00 +0100 https://epub.ub.uni-muenchen.de/24216/1/oa_24216.pdf Dyk, Danny van; Bobeth, Christoph; Beaujean, Frederik

The available data on | Delta B| = | Delta S| = 1 decays are in good agreement with the Standard Model when permitting subleading power corrections of about 15 at large hadronic recoil. Constraining new- physics effects in C7, C9, C10, the data still demand the same size of power corrections as in the StandardModel. In the presence of chirality- flipped operators, all but one of the power corrections reduce substantially. The Bayes factors are in favor of the Standard Model. Using new lattice inputs for B. K* form factors and under our minimal prior assumption for the power corrections, the favor shifts towardmodelswith chirality- flipped operators. We use the data to further constrain the hadronic form factors in B. K and B. K* transitions.

Matthew Johnson gives a talk at the Bubbles in the Sky workshop.

This paper develops a Bayesian method for estimating and testing the parameters of the endogenous switching regression model and sample selection models. Random coefficients are incorporated in both the decision and regime regression models to reflect heterogeneity across individual units or clusters and correlation of observations within clusters. The case of tobit type regime regression equations are also considered. A combination of Markov chain Monte Carlo methods, data augmentation and Gibbs sampling is used to facilitate computation of Bayes posterior statistics. A simulation study is conducted to compare estimates from full and reduced blocking schemes and to investigate sensitivity to prior information. The Bayesian methodology is applied to data sets on currency hedging and goods trade, cross-country privatisation, and adoption of soil conservation technology. Estimation and inference results on marginal effects, average decision or selection effect as well as model comparison are presented. The expected decision effect is broken down into average effect of individual's decision on the response variable, decision effect due to random components, and differential effect due to latent correlated random components. Application of the proposed Bayesian MCMC algorithm to real data sets reveal that the normality assumption still holds for most commonly encountered economic data.

We discuss Bayesian estimation of a logistic regression model with an unknown threshold limiting value (TLV). In these models it is assumed that there is no effect of a covariate on the response under a certain unknown TLV. The estimation of these models with a focus on the TLV in a Bayesian context by Markov chain Monte Carlo (MCMC) methods is considered. We extend the model by accounting for measurement error in the covariate. The Bayesian solution is compared with the likelihood solution proposed by Kuechenhoff and Carroll (1997) using a data set concerning the relationship between dust concentration in the working place and the occurrence of chronic bronchitis.

This paper deals with a dynamic version of the cumulative probit model. A general multivariate autoregressive structure is proposed for modeling the temporal dynamic of both regression and threshold parameters. Conjugate and diffuse prior distributions are used for the variances of the (normally distributed) transition error terms. Introducing latent variables for each ordered categorical observation, statistical inference is done by means of the Gibbs sampler. The applicability is illustrated with two examples. The first analyzes monthly business panel data focusing on the effect of several covariates on a specific ordered response variable. In the second example results of the German soccer league 1993/94 are viewed as response from a dynamic ordered paired comparison system. Here unknown regression parameters corresponding to the underlying time-dependent abilities of the different teams are estimated based on the scores of each game (win-draw-loss).