Tails you win - the science (and joys) of chance

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Remember BBC Four’s amazing The Joy of Stats...? Well, for those of you who have seen it and for those of you who have not (where have you been!?), the producers –  Wingspan  – have created something wonderful again. This time for everyone interested (or not yet interested, but soon will be) in numbers, chance, risk and probability.
 
The new production entitled “Tails you win – the science of chance” is presented by David Spiegelhalter, Winton Professor of Public Understanding of Risk.
 
Travelling between the UK and the USA, the story of chance is told: our discovery of how it works, how to calculate the odds for the future, how we usually fail to conquer chance but are learning to celebrate it and turn it to our advantage in cracking scientific problems.  Other contributors include:  former England cricketer Ed Smith; Las Vegas gambling legend Mike Shackleford;  the self-styled ‘Wizard of Odds’;  Chief Economist at the Bank of England Spencer Dale.
 
“Tails you win – the science of chance” is expected to air on 18 October 2012.
 

A small but appetising taste of risky TV

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Just to whet our appetite, Wingspan Productions have alerted us to the new ‘Tails you win” clip on the BBC’s YouTube channel. The 4.5 mins snippet shares David’s positive outlook on life and why he thinks that knowing more about chance and risk may actually increase our enjoyment of life (and perhaps boost our life expectancy too).
 
For those of us keen to know more about the numbers and research underlying the clip, see David Spiegelhalter’s  Blog at Understanding Uncertainty.
 
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Tails you win: the science of chance, will first air on BBC Four at 2100 hrs on 18 October 2012. It will be repeated at 0210 hrs on 19 October 2012.
 

Let's get noisy about data in electioneering

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In an  interview with the BBC on his new book ‘The Signal and the Noise: why so many predictions fail, but some don’t”  - Nate Silver suggests that there is a big gap between what we think we know in politics and what we actually do know.
 
It is easier, he says, to predict the outcome of baseball than a presidential election as there is a lot more data available on baseball (162 games are played every year) than there is for an event which only happens every 4 years. In elections, we are trying to make inferences about what will happen in the future based on a small amount of historical data.  Outcomes are inferred from various sources of data including factors such as the state of the economy and levels of unemployment at the time of the election (the assumption is usually that there is a direct relationship between these and election results – invariably, not the case in US elections).
 
Today, there is more data than ever to draw on to predict election outcomes but  “in some ways having more data can get you into more trouble if you don’t know what to do with it”.
 
There’s a wider point about our knowledge gap when it comes to politics. Baseball apart, there are few occasions when data is quite so abundant and the public’s interest in the information in data stronger than during an election. But how well do we grasp the information in data ? How well-equipped are we as voters to handle the ‘noise’ …the cacophony of data we experience ? Do we scrutinise the statistics in manifestos and in the content of pre-election ‘fact-flinging’ debates?.  How good are the media at reporting that data?
 
And politicians’ ‘knowledge gap?. how often are candidates really comparing like with like? how often do they exaggerate numbers, how much real data underpins the big promises they make? and then how evidence-informed is the subsequent media coverage?
 
Perhaps, we should then ask ourselves how much impact the ability of candidates to use statistics accurately and appropriately in the run-up to an election has on the final election results?. Few would disagree that evidence-informed debate and policy-making should be the norm in parliaments everywhere, let’s not overlook the need for evidence-informed electioneering too.
 

Stats skills for social scientists - A major initiative

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Within a few years, all students on social science courses at British universities will possess basic statistical capacity, if the hopes of the promoters of a new initiative are borne out.
 
With financial support from the Nuffield Foundation – its director, Sharon Witherspoon, is pictured left – the Economic and Social Research Council and the Higher Education Funding Council for England, new centres of excellence in teaching social science undergraduates quantitative methods are to be established. The plan is that they will boost capacity, first among those undertaking postgraduate work then later among academic staff, ensuring future supplies of sociologists, social policy specialists, political scientists who can pass on their quantitative skills.
 
The British Academy issued a position paper welcoming the £15.5m endowment. It has recently established a high-level strategy group to promote stats and quantitative capacity outside the so-called STEM (science and technology) subjects. Writing in THE, the group’s chair Professor Ian Diamond the vice chancellor of the University of Aberdeen and a distinguished social statistician deploreda gap in national capacity, that could reduce the overall quality of research and teaching in such subjects as sociology.
 
Writing in the Guardian Sharon Witherspoon said that UK social science had many strengths, ‘not least in our impressive data infrastructure (with birth cohort studies, longitudinal studies and others), and in imaginative qualitative research. But over the years it has become increasingly clear that it is weaker than it should be in quantitative research skills.’
 
The  BA Position Statement – Society Counts concluded the deficit in quantitative skills ‘has serious implications for the future of the UK’s status as a world leader in research and higher education, for the employability of our graduates, and for the competitiveness of the UK’s economy’.
 
Professor Diamond’s group includes representatives from the Department of Business, Innovation and Skills, the learned societies and exam boards and RSS getstats.
 

Killer statistics

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Jack Warner, National Security Minister for Trinidad and Tobago, has hit the international headlines with an intriguingly positive view of statistics. They make you do bad things.
 
Warner,  already controversial because of his role in FIFA (he was forced to stand down as vice president amid allegations of cronyism), said when figures show a drop in crime, or even identify areas with no crime, criminals are encouraged to perpetrate crime in response. ’They want to make news, they want to make headlines that spoil the record, and they get an incentive to do this’
 
The remedy, he says, to is to suppress crime data.  ’No figures of any kind will be given  anywhere … I’ve also instructed the police not to reveal any figures on  murders anywhere, anytime,’ he said.
 
Kevin Baldeosingh, a columnist on the Trinidad Express, had some fun with the proposed ban – which police chiefs have so far resisted. He noted that the minister had been said by the Court of Arbitration for Sport in July to be ’prone to an economy with the truth’. To measure how prone, he went, on you need a statistical theorem.
 
‘This theorem, which describes the effect of experience on opinion, says that P (A\B) = P (B\A) x P (A)/ {P (B\A) x P (A)} + {P (B|~A) x P (~A)} where P is the probability that Jack lies (B) when he talks (A). If we assign a probability of 50 per cent to A and 66 per cent to B, that gives us a 67 per cent probability that, when Jack speaks, he lies. Which would explain why he doesn’t like statistics.’
 

Mums know best but stats can help debate

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To breastfeed or not to breastfeed?  With last week’s Unicef UK report ‘Preventing Disease and Saving Resources’, the case in favour of mothers breast feeding babies until they are at least 6 months old seems to be stacking up and there’s a lot of international, national and local data on the subject.
 
International data? UNICEF data shows that UK breastfeeding rates are increasing but remain among the lowest in Europe. 81% of British babies are breastfed when they are first born, but the figure for 1-week old babies drops considerably and by 6-8 weeks, just under 50% of babies are still breastfed and by 6 months the figure is less than 2 %  (although more are still receiving breast milk).
 
National data? the Department of Health (DoH)s’ Infant Feeding survey is run every 5 years.
 
Local data? There is a local case study in the UNICEF report. The DoH analyses local data too.  Since 2008/09, each primary care trust has been required to submit quarterly data on the prevalence of breastfeeding at 6-8 weeks.
 
And now, there are cited data projecting health benefits (for example that 10,000 fewer young children a year would require hospital treatment), and data projecting at least £ 31 m savings for the NHS (due to lower incidences of some cancers in women who have breastfed and in illness in babies breastfed for longer).
 
The rate of breastfeeding is a sensitive issue with complex societal, family, health (and now economic) aspects. But whilst statistical findings may build a body of evidence,  how to feed their children remains a mother’s choice.  The statistical findings of this report and other sources of data should not be viewed as advocacy or weapons with which to target mothers who do not breast feed but as knowledge to support well-informed debate.
 
An Independent article,  ’How women feed babies isn’t just about statistics’ puts this case clearly. However,  references in the same article, to “mind-boggling statistics” and to those statistics leaving mothers “feeling they have put their child’s health at risk” are less helpful. So, let’s not make statistics the bogey man in this debate.  Statistics are the information in numbers. More enlightening than ‘boggling’ and they serve an important purpose in public discourse and the development of policy.
 

Datakindness helps not-for-profits see a little data go a long way

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We hear a lot about the data revolution and the benefits that large organisations are reaping from big data but it is not always apparent how useful data analysis can be to smaller outfits in the not-for-profit sector too. This is a sector where it is often the case that data are collected  but then…because of limited capacity including know-now and resources, next steps  - analysing, interpreting and using the data to good effect - can be a struggle.
 
It is great to hear that a New York-based charity – DataKind  - with a mission to use data to serve humanity – is sharing the benefits of the data revolution and data’s worth to charities.  It’s doing this in an immediate and practical way, helping them to work more productively and efficiently and achieve fresh and quantifiable insight into their organisations’ achievements and impact.
 
In this week’s Economist, ‘Data Huggers‘ reports on a recent 2-day DataKind ”hackathon” in London when data scientists did just this. One of their teams helped a charity which offers counselling to troubled schoolchildren. By working through their data they enabled the charity to evaluate its work and, in particular, to see which of their audiences responded most to which services and where they were having most impact. During an earlier hackathon in the US, DataKind analysed months of a the text message data of a not-for-profit group which enables rural patients in India to use their mobile phones to secure the advice of doctors based in cities hours away.
 

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