Sir David Spiegelhalter, former President of the Royal Statistical Society, blogs on the anniversary of the refreshed Code of Practice for Statistics.
I must be honest: a Code of Practice for Statistics is not something I would usually get very excited about. So why do I trumpet the virtues of the new Code in the talks I give?
There are two main reasons. First, the rumours of a ‘post-truth’ society mean that it is timely to talk about trust in numbers, science and experts, and whenever I hear the word ‘trust’ I turn to Baroness Onora O’Neill, author of the 2002 Reith Lectures (a brilliant listen or read) and presenter of one of the best TedX talks I have seen – summarising everything that’s about important about trust, quoting Kant, telling jokes, all in nine minutes.
O’Neill makes the fundamental point that when organisations say they want to be trusted, they are missing the whole point. Trust is something that is offered to us, we have to earn it, and we earn it by demonstrating trustworthiness. It is such a simple idea, and yet when I introduce it in talks, people pull out their phones and start photographing the slide. And so of course I think it is completely appropriate that trustworthiness forms the first pillar in the Code.
My second reason for cheerleading the Code is its emphasis on communication and transparency. And again I return to Onora O’Neill, who has closely examined the idea of transparency within the context of open data. Under the term ‘intelligent transparency’, she identifies four important features – information should be
- accessible – people should be able to get at it
- comprehensible – people should be able to understand it
- useable – it should suit their needs, and
- assessable – interested parties should, if necessary, be able to examine the workings and assess its quality.
When I put this list up, audiences reach for their phones again (nobody seems to take pictures when I put my own words of wisdom up, but then again I have not spent a lifetime as a philosopher). I use this list repeatedly when considering our own advice for communicating statistics, and so I advertise the importance the Code places on showing the pedigree of statistical claims.
I believe a vital aspect of transparency about statistics is the open acknowledgement of uncertainty, and anyone seeing me recently will have heard my harangue about the importance of clear communication of margins of error around unemployment or migration figures, as well as acknowledging deeper, unquantified uncertainties due to, say, lack of reliability of data sources. So I am delighted the Code emphasises the importance of communicating uncertainty, supported by the excellent, and recently updated, GSS document on Communicating Quality, Uncertainty and Change.
You may possibly have noticed that statisticians can have bit of an image problem, although I find their tendency toward pedantry rather endearing. I therefore think it is a fine achievement to produce a Code of Practice that is not only full of good sense, but that someone might actually want to read.