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Last week, the American Cancer Society published new guidelines that call for colorectal cancer screening to begin at age 45 - five years earlier than the group had previously recommended. But some experts are saying not so fast. The new recommendation was made in reaction to increasing rates of colorectal cancer among people younger than 50. But while the rise in cancers among this younger age group is troubling, this new recommendation was made before we know what's behind the new trend. And it's not clear that screening can help.It makes intuitive sense to respond to increasing rates of colon cancer among young people by lowering the screening age, said Michael Hochman, director of the the Gehr Family Center for Health Systems Science at the Keck School of Medicine in Los Angeles. "But if I had a quarter for every time in medicine that we were tricked by an idea with intuitive appeal, I'd be a rich man," Hochman said.

Here's a discussion of how data science techniques that look at the kinds of things you watch, and try and make recommendations or customise based on that can work, and what might be problematic about that. "Some are noticing Netflix's tendency to entice black users with movie posters featuring black actors, no matter how minor their role in the film."

In this case, because pancreatic cancer is relatively rare, the impressive-sounding 50% reduction doesn't amount to very much. According to the American Cancer Society, a 60-year-old man has a 0.41% (1 in 241) chance of developing pancreatic cancer during the next ten years. (Risk varies greatly with age and is much lower at younger ages.) So cutting that risk in half might bring it down to about 0.2% (1 in 480). It's a 50% drop, sure, but the risk was already very small to begin with. In this case, it's more helpful to news and health care consumers to describe it as a 0.2 percentage point reduction. And then there are the harms of regular aspirin use; the Yale news release that the tweet links to doesn't mention any. But taking aspirin regularly isn't a harmless intervention - far from it. It's well known that taking aspirin every day can cause serious bleeding in the gastrointestinal system and, less frequently, in the brain. That's why guidelines for aspirin use in cardiovascular disease prevention don't recommend it for people at low risk of a heart attack. The potential benefits may be outweighed by the risks of a serious bleed.

Read the comments alongside the article here - interesting speculation and use of evidence. initiatives will not turn the affordability problem around while tax settings continue to support existing homeowners and investors at the expense of first time buyers and renters. Moreover, apart from a brief interruption 2008-2012, the Commonwealth has been steadily winding back its explicit housing role for more than 20 years. The post of housing minister was deleted in 2013, and just last month Government senators dismissed calls for renewed Commonwealth housing policy leadership recommended by the Senate's extensive (2013-2015) Affordable Housing Inquiry. This complacency cannot go unchallenged.

Excellent discussion of absolute and relative risk in the context of alcohol safety. "But claiming there is no 'safe' level does not seem an argument for abstention. There is no safe level of driving, but government do not recommend that people avoid driving."

Medicine's decades-long march toward patient autonomy means patients are often now asked to make the hard decisions - to weigh trade-offs, to grapple with how their values suggest one path over another. This is particularly true when medical science doesn't offer a clear answer: Doctors encourage patients to decide where evidence is weak, while making strong recommendations when evidence is robust. But should we be doing the opposite?People in general are not great at evaluating risk. They worry more about shark attacks than car crashes.

"Anonymised" data lies at the core of everything from modern medical research to personalised recommendations and modern AI techniques. Unfortunately, according to a paper, successfully anonymising data is practically impossible for any complex dataset.

BBC guidelines on reporting statistics - excellent resource for AEI! http://downloads.bbc.co.uk/rmhttp/guidelines/editorialguidelines/pdfs/ReportingStatistics.pdf The BBC "accepts recommendations [...] to improve statistical training for BBC journalists and to ensure that journalists are better placed to challenge statistical claims made by people in public office...." It also has "plans to create a 'hub' for data journalism, recruit a new head of statistics and develop guidance based on 'guidelines from, for example, the Royal Statistical Society and others'."

Have you ever you looked for a product online and then been recommended the exact thing you need to complement it? Or have you been thinking about a particular purchase, only to receive an email with that product on sale? All of this may give you a slightly spooky feeling, but what you're really experiencing is the result of complex algorithms used to predict, and in some cases, even influence your behaviour.

Statistics have played an important role both in our understanding of the coronavirus pandemic, and our attempts to fight it. The RSS sets out ten lessons the government can learn, and a series of recommendations for what they should do now, to ensure that the country's data infrastructure is prepared for the next crisis - whatever form it takes.

Numbers are often used to persuade rather than inform, statistical literacy needs to be improved, and so surely we need more statistics courses in schools and universities? Well, yes, but this should not mean more of the same. After years of researching and teaching statistical methods, I am not alone in concluding that the way in which we teach statistics can be counterproductive, with an overemphasis on mathematical foundations through probability theory, long lists of tests and formulae to apply, and toy problems involving, say, calculating the standard deviation of the weights of cod. The American Statistical Association's Guidelines for Assessment and Instruction in Statistics Education (2016) strongly recommended changing the pedagogy of statistics into one based on problemsolving, real-world examples, and with an emphasis on communication.

Blame the algorithm. That's become the go-to refrain for why your Instagram feed keeps surfacing the same five people or why YouTube is feeding you questionable "up next" video recommendations. But you should blame the algorithm - those ubiquitous instructions that tell computer programs what to do - for more than messing with your social media feed. Algorithms are behind many mundane, but still consequential, decisions in your life. The code often replaces humans, but that doesn't mean the results are foolproof. An algorithm can be just as flawed as their human creators. These are just some of the ways hidden calculations determine what you do and experience.

Adrienne is a Marvel movie fanatic: Her favorite films all involve the Hulk, Thor or Black Panther. Brandon prefers animated features like Inside Out, The Incredibles and anything with Buzz Lightyear. I like both kinds, although I'm probably closer to Adrienne than Brandon. And I might skew a little toward Cora, who loves thrillers like Get Out and The Shining. Whose movie preferences are closest to yours: Adrienne's, Brandon's or Cora's? And how far are your cinematic tastes from those of the other two? It might seem strange to ask "how far" here. That's a question about distance, after all. What does distance mean when it comes to which movies you like? How would we measure it?