The other day I received an email from the British Academy (for Humanities and Social Sciences) announcing a new position statement on what they call Quantitative Skills. The complete text of this statement, which is entitled Society Counts and which is well worth reading, is now available on the British Academy website.
Here’s an excerpt from the letter accompanying the document:
The UK has a serious deficit in quantitative skills in the social sciences and humanities, according to a statement issued today (18 October 2012) by the British Academy. This deficit threatens the overall competitiveness of the UK’s economy, the effectiveness of public policy-making, and the UK’s status as a world leader in research and higher education.
The statement, Society Counts, raises particular concerns about the impact of this skills deficit on the employability of young people. It also points to serious consequences for society generally. Quantitative skills enable people to understand what is happening to poverty, crime, the global recession, or simply when making decisions about personal investment or pensions.
Citing a recent survey of MPs by the Royal Statistical Society’s getstats campaign – in which only 17% of Conservative and 30% of Labour MPs thought politicians use official statistics and figures accurately when talking about their policies – Professor Sir Adam Roberts, President of the British Academy, said: “Complex statistical and analytical work on large and complex data now underpins much of the UK’s research, political and business worlds. Without the right skills to analyse this data properly, government professionals, politicians, businesses and most of all the public are vulnerable to misinterpretation and wrong decision-making.”
The statement clearly identifies a major problem, not just in the Humanities and Social Sciences but throughout academia and wider society. I even think the British Academy might be a little harsh on its own constituency because, with a few notable exceptions, statistics and other quantitative data analysis methods are taught very poorly to science students too. Just the other day I was talking to an undergraduate student who is thinking about doing a PhD in physics about what that’s likely to entail. I told him that the one thing he could be pretty sure he’d have to cope with is analysing data statistically. Like most physics departments, however, we don’t run any modules on statistical techniques and only the bare minimum is involved in the laboratory session. Why? I think it’s because there are too few staff who would be able to teach such material competently (because they don’t really understand it themselves).
Here’s a paragraph from the British Association statement:
There is also a dearth of academic staff able to teach quantitative methods in ways that are relevant and exciting to students in the social sciences and humanities. As few as one in ten university social science lecturers have the skills necessary to teach a basic quantitative methods course, according to the report. Insufficient curriculum time is devoted to methodology in many degree programmes.
Change “social sciences and humanities” to “physics” and I think that statement would still be correct. In fact I think “one in ten” would be an overestimate.
The point is that although physics is an example of a quantitative discipline, that doesn’t mean that the training in undergraduate programmes is adequate for the task. The upshot is that there is actually a great deal of dodgy statistical analysis going on across a huge number of disciplines.
So what is to be done? I think the British Academy identifies only part of the required solution. Of course better training in basic numeracy at school level is needed, but it shouldn’t stop there. I think there also needs to a wider exchange of knowledge and ideas across disciplines and a greater involvement of expert consultants. I think this is more likely to succeed than getting more social scientists to run standard statistical analysis packages. In my experience, most bogus statistical analyses do not result from using the method wrong, but from using the wrong method…
A great deal of astronomical research is based on inferences drawn from large and often complex data sets, so astronomy is a discipline with a fairly enlightened attitude to statistical data analysis. Indeed, many important contributions to the development of statistics were made by astronomers. In the future I think we’ll see many more of the astronomers working on big data engage with the wider academic community by developing collaborations or acting as consultants in various ways.
We astronomers are always being challenged to find applications of their work outside the purely academic sphere, and this is one that could be developed much further than it has so far. It disappoints me that we always seem to think of this exclusively in terms of technological spin-offs, while the importance of transferable expertise is often neglected. Whether you’re a social scientist or a physicist, if you’ve got problems analysing your data, why not ask an astronomer?
In the Dark 