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in our research, which involves talking to statisticians, public servants and journalists who produce and communicate the statistics that govern our lives, people say overwhelmingly that faith and trust are essential parts of what makes statistics useful. Despite the objective and impartial appearance of statistics, it is a web of people and human processes that makes them trustworthy.

Where else have you seen risk claims like "x causes 50% increase in health-problem y"? Do you tend to trust these claims? Do you understand what they mean? Would they change your behaviour? "Interpreting health (or any other) risk estimates reported in the media is not straightforward. Even health professionals can get tripped up trying to make sense of these statistics, so it is no wonder the public can easily be confused or misled. Often there is tendency to overreact to risk estimates, so it's worth unpacking what these really mean."

Dismissing people's worries as baseless, whether that's about the safety of mobile phones or fluoridated drinking water, is one of the least effective ways of communicating public health risks. Yet it is common for people to "reassure" like this, both at home and in professional roles as experts, officials or corporate managers. 1. Hose down your own outrage first 2. Respect people's fears 3. Build trust 4. Don't panic about panic 5. Your actions communicate more than your words 6. Play the long game

Why do arguments change people's minds in some cases and backfire in others? Hugo Mercier explains how arguments are more convincing when they rest on a good knowledge of the audience, taking into account what the audience believes, who they trust, and what they value.

It's not just disadvantaged and vulnerable groups that struggle with financial decision-making. People who are highly educated in finance also make poor decisions - for instance, by focusing too much on growing their assets and ignoring risks. But studies show that when regulation is effective and the financial system can be trusted, even consumers with limited financial knowledge and information-processing capabilities have the potential to deal with complex financial decisions. For example, when considering mortgage protection insurance, applicants stand to benefit from knowing the actual risk of events like serious illness or injury that can affect their ability to meet monthly loan repayments.

Not so much about data, but about how we use evidence when we don't know the original source, and how e e.g. a politician failing to deny something might be good confirmation that it's actually true. 5 tips for reading stories with unnamed sources

A piece I wrote on how psychology helps us understand fake news and information seeking. Every day we face complex situations in which the information we need, and who we trust to provide that information, has a very real impact on our lives. How do we evaluate the competing claims of politicians on climate change policy, or Brexit; navigate medical information regarding vaccinating our children; or assess the relative merits of diet versus regular foods in adopting a healthy lifestyle?

Sometimes it's hard to know what statistics are worthy of trust. But we shouldn't count out stats altogether ... instead, we should learn to look behind them. In this delightful, hilarious talk, data journalist Mona Chalabi shares handy tips to help question, interpret and truly understand what the numbers are saying.

What happens once misinformation is corrected? Is it effective at all? A major problem for social media platforms resides in the difficulty to reduce the spread of misinformation. In response, measures such as the labeling of false content and related articles have been created to correct users' perceptions and accuracy assessment. Although this may seem a clever initiative coming from social media platforms, helping users to understand which information can be trusted, restrictive measures also raise pivotal questions. What happens to those posts which are false, but do not display any tag flagging their untruthfulness? Will we be able to discern them?