Issue 112 of Radical Statistics includes the winner and runner-up in the 2014 Radical Statistics essay competition (open entry) and features a host of articles on topics as diverse as a 19th century radical German demographer, deprivation in a former mining area in Yorkshire and official statistics in Norway. As such it nicely highlights the range of topics that can be subjected to a radical statistics perspective!

The essay by the first prize winner, Elisabeth Garratt, provides an excellent overview of the rise in foodbanks in the UK. This is an area that has received growing policy and media attention. This essay highlights that increased use of food aid is cannot be explained by its growing acceptability or people taking advantage of charity, but rather is associated with growing food insecurity. The essay also usefully outlines what different types of data can, and cannot, tell us about food insecurity. The second placed essay, by Dr Pauline McGovern, provides a highly engaging take on the use of path analysis. In her essay she makes use of creative and engaging metaphors and research on the effect of former occupation on the health of retired people. The essay is an excellent example of how we can present statistics in an immediate and creative way. Look out for the two student competition winning essays, which will be featured in the next issue of Radical Statistics.

The issue continues with two articles that, in different ways, examine area-level statistics. The first, by Sinead D’Silva and Paul Norman, explores the utility of administrative data in producing a simple scale of ‘social stress’ at the area level. Focusing on areas in Doncaster that have suffered coal mine closure, and consequent job loss and deprivation, they show that a relatively simple scale, constructed from publically available area-level data, provides a surprisingly good proxy for more complex Indices of Multiple Deprivation. The second article, by Mark A Green and Mark Strong, focuses on health-related quality of life (HRQoL). They note that it can be difficult to illustrate the impact of neighbourhood deprivation on HRQoL. As such they propose a novel solution: using BMI (a summary of weight that is socially meaningful) when explaining epidemiological effects to lay audiences. For instance, enabling us to see the approximate equivalence, in terms of HRQoL, of individual morbid obesity and living in a deprived neighbourhood.

The article by Asle Rolland engages with an important debate regarding the independence of official statistics. The article highlights crucial dimensions related to independence, and the desirability and potential limitations of independence, drawing on empirical examples and references to common practice, regulations as well as underlying philosophical principles. Continuing the focus on official statistics, albeit in this instance, their unavailability, Frank and Sarah Houghton, explore the health situation in Ireland, arguing that it is highly correlated with poverty, but that it is difficult to show this with any precision due to insufficient information, the tendency of the Irish government to restrict access to what information exists and diminishing regulation and data oversight. They suggest that there is no clear and transparent health funding model and the Irish health care delivery system is in a dire state, especially for the impoverished.

The final article is a biography of radical statistician Robert René Kuczynski (1876-1947). Kuczynski was a German economist, demographer and one of the founders of modern German vital statistics. As an urban statistician he investigated the housing conditions of the working population. He also was a proponent of democracy in Weimar Germany, but in 1933 he had to leave Germany and settled in England where he lectured in demography at the LSE, and later became a demographic adviser to the Colonial Office.

Issue 112 returns to contemporary issues to conclude with two brief comments by Christina Beatty and Alison Macfarlane. These highlight the British government’s increasing insistence that academic partners destroy data within an (overly) restrictive timescale.

Finally, a reminder that Radical Statistics welcomes your contributions. If you have either a full-length article or a brief comment that you would like to contribute, or if you are interested in reviewing a book that you believe is of potential interest to Radical Statistics’ readers, please get in touch with us at editors@radstats.org.uk.
Further information about how to submit is also available at: www.radstats.org.uk/journal

Rachel Lara Cohen, Trude Sundberg, Eileen Magnello, Larry Brownstein

On 19 January 2015, I attended the meeting on Big Data at the RSS. The speakers included: Kenneth Cukier (Data Editor at The Economist); Haishan Fu (Director of Development Data Group at the World Bank); Alex ‘Sandy’ Pentland (Professor at MIT and Academic Director of Data-Pop Alliance); Nuria Oliver (Scientific Director at Telefonica); John Pullinger (UK National Statistician), with Denise Lievesley (Dean of Faculty, King’s College) as Chair.

It is impossible to summarise the contributions or the excellent discussion, but here are some comments (recorded approximately) that give a flavour of the discussion.

Kenneth Cukier: “Big Data allows data to be produced as frequently as is needed, not at the convenience of the producers.”

Haishan Fu: “The WB’s aim is to support national data producers and to incentivise the private sector … with a particular aim to help poorer countries ‘leap-frog’ to catch up”.

Nuria Oliver: “Access to data from phone systems allows inferences, at macro levels about responses to large-scale flooding, and at individual levels about the socio-economic status of the user or their likely responses on a range of social issues.”

Sandy Pentland: “Having access to more data will allow us to solve more problems … data [ownership? / access?] should be decentralised to the citizen.”

John Pullinger: “Big Data provides a wake-up call, and an opportunity, for our statistical institutions.”

At the end of the session, the Chair, Denise Lievesley, asked for reactions from the audience, in terms of what we would take away from the meeting. My reaction was that the discussion had made me realise, even more strongly, that statisticians (along with others) over the years have refined a number of crucial ideas, based on a sense of methodological quality (or validity). These relate to several issues.

First, causality is to be distinguished from correlation. This can of course be accomplished by RCT designs, as well as by carefully-controlled and replicated non-experimental studies.

Second, it is important to appreciate how the available indicators have been constructed and understood by the human beings (or processes) producing them. Hence John Pullinger’s timely offer of a course in questionnaire design to one of the “Big Data-enthusiasts” on the panel.

Third, the data analyst also needs knowledge of how the sample before us has been selected, and attenuated by various forms of non-response.

These three methodological concerns are not always fully acknowledged by enthusiasts for big data. An era when “Big Data” is being extensively hyped will produce additional challenges for statisticians re. data management and data analysis. These are already being addressed by inter-disciplinary teams many in universities and organisations. But there is no reason for statisticians to be reticent about the contributions they can make to these clearly important debates.

Jeff Evans