Can you handle the truth?

“A study finds that”.“There is clear academic evidence that”. “Research shows that”. These are meaningless phrases today, when you can rustle up a report to support almost any claim you want, even if it’s deeply flawed or later debunked. May Contain Lies: How Stories, Statistics and Studies Exploit Our Biases – And What We Can Do About It by Alex Edmans, shows us how to be more discerning with evidence.Even sources that we consider reliable, like govt reports, are written by biased humans. Newspapers cite blockbuster findings that go nowhere. Some kinds of catchy misinformation stick around, like the idea that any skill can be mastered with 10,000 hours of practice.Checking facts only saves us from the first misstep, because we may interpret them erroneously. Someone can mislead us by hiding contradicting info, not gathering in the first place or drawing invalid conclusions from valid data. Left to ourselves, we succumb to motivated reasoning. So ask yourself: do I want this to be true? Then proceed mindfully. Another pitfall to avoid is black and white thinking: to think of stuff like carbs, or religion, or capitalism as good or bad, rather than with nuances. Nuance could mean marbling — seeing things as streaked with positive and negative elements.A popular claim that gender diversity in corporate boards improved financial performance did not hold up to scrutiny — but it spread because many people want it to be true. Likewise, a viral study on the ‘power pose’ helping you ace interviews and speeches has been debunked, but barely anybody has noticed the retraction.Take biographers’ explanations about why Steve Jobs was so successful — because he was adopted, or because of his company’s unique and inspirational values, and so on. These are examples of logic that are reverse-engineered from the fact of success. They’re simply a storyline imposed on different dots.Is a statement a fact, is a fact truly data, is that data genuinely evidence, and is that evidence proof? The book provides tips on sussing that out.The scientific way is to find a hypothesis, gather representative test and control samples, test for statistical significance, and only then reach a conclusion. But most of us go with compelling stories instead, we’re suckers for a good narrative. It’s hard for us to look at a bunch of facts without forcing an arrow of relationships among them. And even with all rigour, it’s important to remember that evidence is not always proof because it may not be universal, context and setting can change the picture.A lot of data doesn’t mean better data — it can be the result of data mining, there can be spurious correlations, the authors might have cherry-picked their sample. Data is not evidence either: for all the assertions and studies about breast-feeding being superior to bottle-feeding, causation remains elusive. Sometimes, data is merely describing things: countries that begin with the letter U (the US, the UK) are wealthier than average, but we know that changing the country’s name to a U name is not likely to boost its GDP.The book provides a checklist to evaluate facts and claims. Like be wary of superlatives, or universal implications in any statement. Such statistical literacy and critical thinking have never been more important, given the deluge of dodgy info around us.