StatisTRICKS: when data deceives

There comes a point in reading the news when one takes numbers for granted, so to speak, and skips over the calculations required to fully comprehend the scale of a number. Take the famous ‘we send the EU £350 million a week’ on the side of a bus during the Brexit campaign. Initially, this number seems seems to indicate a huge chunk of our country’s budget going to the EU (to the average person, being in possession of £350 million would be life-changing). But let’s break it down: the UK Government, pre-pandemic in the years 2018-2019, spent a total of £851.3 BILLION, on everything from defence to health and education. In the same year, this statistic on the bus claims we would have sent £18.2 billion. Putting the number from the bus alongside this figure, we can see that £350 million a week ends up as only 2.14% of the government’s total annual budget. So, while the initial figure was utilised to make it look like the EU was siphoning off a significant part of taxpayers’ money, in reality this was only a tiny part of the annual budget, and this kind of Brexit ‘marketing’ was utilising people’s ignorance of the government’s annual budget to make them feel like we were crippled by EU contributions. Whether this was reprehensible remains a question of ethics and politics, but the point remains that clever presentation of statistics can manipulate our understanding of them.


Take data surrounding the pandemic. Statistics have driven our comprehension of what’s happening and the severity of the situation around us, but some have been misleading. For example, in August last year, the USA was reported to hit a ‘grim milestone’ of 6 million confirmed Covid cases. Reading about this in the news at the time may have been enough to scare and upset the reader, but the reality was actually much worse; despite the fact being true, it was misleading as it pushed the assumption that ‘confirmed Covid cases’ is the most comprehensive measure of how the pandemic is affecting the country. ‘Confirmed cases’ can easily be confused with the actual number of Covid infections (given how it’s hard for the average reader to assume what percentage of cases go unreported, so they rely on the former to feel more sure they comprehend the situation), but this latter figure was estimate to be 12 times higher than reported cases. Thus, we were somewhat sheltered from a much grimmer reality, but at what cost? The manipulation of numbers on the basis of public ignorance or misinterpretation in this way could achieve a number of objectives, for example preventing a dip in public approval of politicians at critical times in elections, or undermining efforts aimed at persuading people to take action against the spread of the virus because it doesn’t seem to be such a large-scale problem.


These are just two relevant examples of the manipulation of statistics to spin a situation to look a certain way, but the truth is that such tricks of rhetoric have been used by people since ancient times (see Aristotle’s Art of Rhetoric). The key to not being roped in to believing a biased message that seems credible because it is based on data is to engage critically and learn how to interpret data in context.This prevents going with one’s first instincts about what a statistic implies, and helps get a view of the number in a more realistic – rather than distorted – sense.


Featured Image: Dimitris Kalogeropoylos on Flickr with license 

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