Title: The social construction of data
Course: UGQuants (SSPS) > Section: Beyond data collection and analysis

The Social Construction of Data

Statistics are part of everyday life. They cannot be avoided. When we turn on the TV or open a newspaper, we are confronted with statistics spanning a variety of issues from sports, business and politics to advertising. Whilst the use of statistics is undoubtedly widespread, the quality and accuracy of their use varies dramatically. As such, society has a somewhat uneasy relationship with statistics. On the one hand, there are those who are readily swayed and convinced by the power of numbers. Such people view statistical data as cold hard fact very often without questioning issues of reliability and accuracy. On the other hand, there are the sceptics and cynics who are inherently suspicious and mistrusting of statistical data. Such people view statistical data as the results of number crunching and the massaging of figures to make them ‘fit’ a particular viewpoint or stance. Both stances can arise from a lack of understanding and knowledge as to the interpretation and creation of statistical data.

The Social Construction of Statistics

Many of us will have heard the phrase, ‘there are three kinds of lie: lies, damned lies and statistics’. A well-known and memorable phrase, it is also somewhat misleading in suggesting that statistics are inherently deceptive. In reality, statistics are not necessarily truth or lie; rather it is their use that makes them so. Unfortunately, statistics can be and often are misused, sometimes unintentionally, other times purposefully. The media, advertisers and politicians can all be guilty of misusing statistics to their own ends, whether that is to achieve attention grabbing headlines, to promote a product or to bolster electoral support.

An example of the misuse of statistics

The world of academia is also not immune to the misuse of statistics. Joel Best, in his book entitled ‘Damned Lies and Statistics’ (2001), considers what is arguably one of the best examples of the misuse of statistics. He tells us of a graduate student whose doctoral research proposal’s opening line contained a quote: ‘Every year since 1950, the number of American children gunned down has doubled’.  Best talks us through the quite ridiculous nature of such a claim explaining that if in 1950 the number of American children gunned down was one, by 1995, the publication year of the article from which the quote was cited, that number would have stood at over 35 trillion. After checking the original source and confirming that the graduate student had not simply misquoted the original article, Best contacted the article’s author to question the basis for the statistic. The author duly provided the origin of this statistic which in its original form read: ‘The number of American children killed each year by guns has doubled since 1950’ (Children’s Defense Fund, 1994). The meaning and significance of this statistic is obviously quite different to that created by its inaccurate rewording and is clearly a blatant case of the misuse and misinterpretation of statistical data.