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LATEST NEWS UPDATES | Not in data's name: How not to be misled by biased statistics -Karthik Shashidhar

Not in data's name: How not to be misled by biased statistics -Karthik Shashidhar

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published Published on Jul 2, 2017   modified Modified on Jul 2, 2017
-Livemint.com

Going by official statistics, there was a marked increase in the number of crimes committed against women in India in 2013—compared to the previous year, the number of crimes against women increased by a whopping 27%. However, before we jump to the conclusion that the number of crimes against women saw a significant increase in 2013, we need to look at the context.

In December 2012, a woman in Delhi was assaulted and raped by five men in a moving bus, causing massive national outrage (the incident came to be known in popular imagination as the “Nirbhaya case”). The victim later succumbed to her injuries and died in a hospital. The widespread protests that followed attracted attention to crimes against women. Women were encouraged to speak up and report any cases of sexual assault or violence. At the same time, police came under greater pressure to register cases of crimes against women, including sexual crimes, rather than brushing them under the carpet.

The effect of the protests and their aftermath meant that, in 2013, women in India were much more likely to report cases of crimes and assault, and police more likely to register such cases. Hence, it is more than likely that the 27% rise in crimes against women that year was largely a consequence of increased reporting and data collection, rather than an increase in the incidence of such crimes.

This story is relevant in the context of some recent discussions on social media regarding the case of mob lynchings in India. On Wednesday, rallies were held in several cities under the #NotInMyName banner to protest against recent cases of mob violence and lynchings across the country, and the government’s indifferent response.

The protests were carried out on Twitter as well, and the hashtag “#NotInMyName” that the protesters used was soon trending in India. Not unexpectedly, left-right flame wars ensued, with one side coming out in support of the protests and the other decrying them as being without basis and “portraying India in bad light”.

While most such social media “discussions” are unworthy of comment, what made this particular set of discussions interesting was the introduction of data into the argument. Using data from media archives, one user reconstructed statistics of the number of possible lynchings in the last few years, especially when the previous government was in power, in order to argue that the number of lynching incidents this year is not out of the ordinary, and thus the protests are baseless.

The introduction of data into any argument is usually welcome, as it can provide a solid basis to what can otherwise degenerate into a charade of name-calling. What made the data problematic in this particular case, however, was the choice of data source—a survey of newspaper archives.

The problem with using newspaper archives to reconstruct historical data is twofold. Firstly, the news media suffers from what can be described as the spectacularness bias. To put it simply, “man bites dog” is far more newsworthy than “dog bites man”. In other words, a mundane occurrence is seldom newsworthy since the quantum of information it conveys is rather low. For this reason, a good reporter is always on the lookout for news that is either surprising, counterintuitive or rare.

At the same time, the media likes to ride on existing narratives. An event that supports a prevailing narrative is more likely to get media attention than one that either runs contrary to or is unrelated to the narrative.

These two together imply that media attention to a class of events (mob lynchings, for example) is at best volatile. Depending upon the prevailing narratives, the likelihood of an event being reported can vary significantly with time. Hence, using media archives to count how many events of a particular class happened in a particular period of time can lead to highly inconsistent data, from which little insight can be drawn (unless one is constructing an argument about the media’s inconsistencies, that is).

In this particular case (mob lynchings), making use of official statistics is unlikely to be of much help either. As we saw in the case with crimes against women, the number of cases filed and registered are also a function of the prevailing narrative and atmosphere. If there is a prevailing narrative that mob lynching is in some sense “acceptable”, at the margin the number of lynching cases filed will be lower. In an atmosphere where lynching cases are being widely reported, on the other hand, more cases are likely to get filed.

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Livemint.com, 1 July, 2017, http://www.livemint.com/Sundayapp/Ug4LRzh4vYnPVErEPe5BXJ/Not-in-datas-name-How-not-to-be-misled-by-biased-statistic.html


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