In the last post I outlined how statistics are utilised to explain patterns and trends in the study of history, whilst also providing an opportunity to engage in deeper critical thinking regarding the factors that underpin such trends. In this manner, such stats can be incredibly interesting. However, as the title of this post notes, they can also be incredibly dangerous. This second part outlines some ideas as to how statistics can be used to creatively consider new patterns, but also the way in which they can be abused and mistreated in order to establish a blurring of fact and fiction.

A way in which I introduced a creative and critical approach to use of statistics is by outlining the book Freakonomics,  written by Levitt and Dubner. Originally published in 2005, the book was intended to subvert the usual approach to this academic field, with the tagline noting: ‘A Rogue Economic Explores the Hidden Side of Everything.’ It became a best-seller and provoked heated debate, with chapter titles including the likes of: ‘What Do Schoolteachers and Sumo Wrestlers Have in Common?’, ‘How is the Ku Klux Klan Like a Group of Real-Estate Agents?’, and ‘Why Do Drug Dealers Still Live with Their Moms?’

The particular chapter/argument that I focus on has the title: ‘Where Have All the Criminals Gone?’ It outlines the trend of rising crime in the United States during the 1980s into the early 1990s; many during this period predicted that crime would continue to escalate and end up becoming more of a problem for politics and society. However, by the mid-1990s, crime started to fall and the apocalyptic predictions did not come to fruition. All of this led to much patting on the backs of various groups, with some trumpeting the role of the police and others believing that it was to do with additional funding in education. However, the authors of Freakonomics come up with a completely different theory: the origins of the 1990s falling crime rate can be traced back to the early 1970s.

The specific event is that of Roe v Wade from 1973. This famous/infamous case (depending on your political stance) legalised abortion in the United States. The argument followed by the Freakonomics authors contends that many of those who were aborted post 1973 would have grown up in poverty-stricken dis-advantaged homes, which would have increased the potential of committing crime in the future. The peak years of this crime activity would have been in their late-teens and early-twenties, which corresponds to the dip in crime in the mid-1990s (as shown in the graph below regarding homicides).


Such a theory is an incredibly contentious, especially for the way in which it lumps in abortions to the notion of a future criminal, and also for the manner in which it implies that those from poorer backgrounds go on to become criminals. For these reasons I find myself personally uneasy about the link between abortions and crime-rates. However, it uses statistical data to creatively conceive a different and innovative way of thinking and explaining a trend.

However, what about the more unscrupulous who mistreat statistics for their own partisan ends? History is littered with examples where political leaders have massaged the figures in order to create a more impressive notion of their rule. In Nazi Germany the unemployment figures were manipulated in order to highlight the great job of getting Germany out of the mess of the Great Depression; but behind the stats we can see that women and Jews were completely removed from the data, and many unemployed men were placed in gruelling work-based schemes for labour service. Governments in the Soviet Union regularly misreported information regarding the economic position of the country, stating that it had produced more much than in reality. And more recently we had the misleading claims utilised during campaigning for the Brexit referendum in 2016, such as the lie that the NHS would receive the £350 million a week that is sent to the European Union. The key problems with this claim:

  • £350 million is not provided to the EU every week
  • The NHS would not be receiving any sum


Statistics can be abused in a variety of ways, including:

  • Discarding of unfavourable data
  • Use of loaded questions
  • False causality
  • Data manipulation

One of my favourite type of manipulation is in the manner in which the data is presented. The image below provides one particular example from a supposed Starbucks presentation: the lack of an axis means that the data provided is unclear:


Furthermore, the image below provides another breakdown for the creative way in which the axis is twisted to suit a particular narrative:


Where does all of this lead us? Well, clearly we cannot simply mistrust all statistics and claim that they are all lies. As noted during these two posts, stats are incredibly useful in revealing patterns and for allowing us to ask critical questions about their causes. But when mistreated and used inappropriately they can be used to state false claims which can be, in the wrong situations, incredibly persuasive and dangerous. Hopefully in the next academic year the A-level students will utilise stats in an appropriate and objective manner, thereby enhancing their own arguments and conclusions.