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Interesting perspective on communicating evidence. With controversy about science communication, facts and alternative facts hitting the headlines recently, I've been having a number of conversations with colleagues from all over the world about why science seems to be losing in the current war on reason. This isn't in the usual fringe battle fronts like creationism or flat-Earthers. It's on topics deep behind our lines, in areas like whether climate change exists or not, how many people were present at a given time at a given place and whether one man with a questionable grasp on reality should be the only source people get their news from.

just knowing facts doesn't necessarily guarantee that one's opinions and behaviors will be consistent with them. For example, many people "know" that recycling is beneficial but still throw plastic bottles in the trash. Or they read an online article by a scientist about the necessity of vaccines, but leave comments expressing outrage that doctors are trying to further a pro-vaccine agenda. Convincing people that scientific evidence has merit and should guide behavior may be the greatest science communication challenge, particularly in our "post-truth" era. Luckily, we know a lot about human psychology - how people perceive, reason and learn about the world - and many lessons from psychology can be applied to science communication endeavors.

This week, Hannah Devlin speaks with some of the statistical vigilantes who are scouring datasets to identify cases of fraud and poor scientific practice. These include the consultant anaesthetist John Carlisle, from Torbay Hospital in Devon, who details his role in the Fujii scandal. Hannah also speaks to a PhD student from Tilburg University in the Netherlands, Michèle Nuijten, about software she has helped develop to "spell-check" statistics found in psychology papers. And finally, we hear from the University of Cambridge's Winton professor for the public understanding of risk, David Spiegelhalter, who is also president of the Royal Statistical Society, about the dangers of statistical malpractice.

The argument is simple, and goes a bit like this. Science does not work by appeal to authority, but rather by the acquisition of experimentally verifiable evidence. Appeals to scientific bodies are appeals to authority, so should be rejected. ...If legitimate authorities are not to be consulted, presumably there is no point in having scientists around at all, as each person would need to verify any claim on their own terms and with their own resources. That would mean a speedy decline into very dark times indeed.

Aleks Krotoski explores why science is being drowned out by Snake Oil online, and how the balance can be shifted to keep desperate people from being exploited. But despite there being more scientific information online than ever, in the modern day the power of the internet has completely flipped. Verified science and medicine are crowded out by a plethora of misinformation and snake oil salesmen. From the relatively harmless quackery such as infrared light treatments or 'wellness' focused diets, to conspiracy theories around vaccinations that are influencing political policy, and have resulted in outbreaks of dangerous, preventable diseases across the world - what is happening online is having a tangible impact across the globe. Aleks Krotoski explores how the infrastructure of the internet allows medical misinformation to thrive, finds out how people can be drawn into communities centred around medical misinformation and conspiracy theory, and how both scientists and every day internet users can redress the balance online.

"I am quite sure now that often, very often, in matters of religion and politics a man's reasoning powers are not above the monkey's," wrote Mark Twain. Having written a book about our most common reasoning errors, I would argue that Twain was being rather uncharitable - to monkeys. Whether we are discussing Trump, Brexit, or the Tory leadership, we have all come across people who appear to have next to no understanding of world events - but who talk with the utmost confidence and conviction. And the latest psychological research can now help us to understand why.

There's a huge debate going on in social science right now. The question is simple, and strikes near the heart of all research: What counts as solid evidence? The answer matters because many disciplines are currently in the midst of a "replication crisis" where even textbook studies aren't holding up against rigorous retesting. ...

To communicate uncertainty in climate change models and predictions, the IPCC uses a range of expressions to describe the probability that a particular event will occur. For example, in the phrase: "It is very likely that heat extremes will become more frequent in the future," the phrase 'very likely' is used to describe a likelihood of more than 90 per cent, says Smithson.

This is a great list of evidence based stories by FiveThirtyEight (FiveThirtyEight uses statistical analysis - hard numbers - to tell compelling stories about elections, politics, sports, science, economics) They also produced a list of some great stories from other venues: http://fivethirtyeight.com/features/damn-we-wish-wed-written-these-11-stories/

Over recent years, data has become an indispensable source for journalists and news organisations, providing excellent material for investigative work as well as storytelling. This has led to the emergence of data journalism, which, broadly speaking, uses information science and analytical techniques in conjunction with journalistic workflows to produce compelling stories rooted in data. Despite the relative maturity of data journalism and the growing application of data in editorial workflows, there is still a lot to learn about the systematic, seamless and effective integration of data and computational tools in newsrooms. It is time time for a holistic assessment of this emerging field by looking deeply into the ways newsrooms across the world have adopted data in their day-to-day workflows, the formation of their data teams, their best practices for producing high quality data driven investigative work, their success and failure stories, and emerging training requirements.

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 1967, following riots in Detroit, Philip Meyer used survey research methods, powered by a computer, to show that college-educated people were just as likely to have rioted as high school drop outs. His story was one of the first examples of computer assisted reporting and precision journalism, in which journalists use social science methodologies to extract and tell stories. In recognition of his contribution to the area, each year's best computer-driven and precision stories are celebrated through the Philip Meyer Journalism Award. The Award's 2016 winners have just been announced, with the successful entries showcasing techniques derived from quantitative and qualitative methods, such as surveys using randomly-selected respondents, descriptive and inferential statistical analysis, social network analysis, content analysis, field experiments, and more.

Social media algorithms, artificial intelligence, and our own genetics are among the factors influencing us beyond our awareness. This raises an ancient question: do we have control over our own lives? This article is part of The Conversation's series on the science of free will.

The importance of understanding #fallacies for helping to understand why people deny scientific explanations.

Last Week Tonight clip: John Oliver hosts a mathematically representative climate change debate, with the help of special guest Bill Nye the Science Guy, of course. Using performence & comedy to communicate a scientific point

'Significance' is a magazine published by the UK Royal Statistical Society and American Statistical Association. E.g. this article discusses the data we might use to analyse food security, thinking about what sources of data are available and the questions they might help us answer. "data on food insecurity is biased towards the environment in which it was created and the priorities of those who collect or commission it. Data from schools is concerned with reimbursement; government data might be focused on budgetary constraints or accountability; grocery stores could (if willing) tell us what food is bought, but not how it is used; meanwhile, non-profits are most interested in demonstrating impact to funders. There is a wide variety of data sets available, but very few are created with the intent to understand the real drivers of hunger and poverty. The data may be repurposed, but modellers must be especially careful to moderate the assumptions of each data set. ...... It is also especially important that those experiencing hunger and poverty are consulted when designing any data analysis project. The input of domain experts is crucial to the success of data science endeavours, and those experiencing poverty know the right questions to ask."

How statistics, and research-design have changed the face of medicine. We tend to think of medicine as a science, but for most of human history it has been scientific-ish at best. In the first episode of a three-part series, we look at the grotesque mistakes produced by centuries of trial-and-error, and ask whether the new era of evidence-based medicine is the solution.

How are your intuitions shaped by the immediate world around you? The importance of evidence over anecdote and considering the bigger picture! If it's hot outside, you're more likely to believe in climate change. The public perception of climate change is shaped by the weather that people experience, according to a study published yesterday in the Proceedings of the National Academy of Sciences journal.

Many public conversations we have about science-related issues involve communicating risks: describing them, comparing them and trying to inspire action to avoid or mitigate them. Just think about the ongoing stream of news and commentary on health, alternative energy, food security and climate change. Good risk communication points out where we are doing hazardous things. It helps us better navigate crises. It also allows us to pre-empt and avoid danger and destruction. But poor risk communication does the opposite. It creates confusion, helplessness and, worst of all, pushes us to actively work against each other even when it's against our best interests to do so. So what's happening when risk communications go wrong?

The Sun is crossing the line that divides the reporting of conspiracy theories and the promotion of them. As the piece in question shows, it's certainly not in the business of debunking them. As a news article, it represents the sloppiest of standards. In its willingness to degrade the credibility of science in an attempt to induce profitable hysteria, it is lamentable.