Professor Risk

As of the 23rd May 2022 this website is archived and will receive no further updates.

was produced by the Winton programme for the public understanding of risk based in the Statistical Laboratory in the University of Cambridge. The aim was to help improve the way that uncertainty and risk are discussed in society, and show how probability and statistics can be both useful and entertaining.

Many of the animations were produced using Flash and will no longer work.

Sluice Gates BeckonDavid Spiegelhalter's proper title is Professor of the Public Understanding of Risk. He is in two minds (literally) about playing it safe or chucking caution to the wind. Decisions, decisions!? Are bacon sandwiches really that dangerous and is it wise to drive when you love cycling? David shows us how to use statistics to face up to life's major risks.


Some risks are very straightforward, e.g. the risk of losing when buying a lottery ticket. Others are not so simple, and if you know more, the headline figure can be considerably modified. For example, the low risk of having an accident in a car depends on the low accident rate and high mileage on motorways, so off the motorway, the risk will be higher than the figure shows. And every activity doesn't just have one risk, often it will have several risks - and sometimes benefits that can offset the risks. For example, driving a car carries a risk of killing or seriously injuring another person, which is almost absent from walking or cycling. Doing this might not shorten your life directly, but would, for most people, result in considerable emotional distress, even if the other party seems to be mainly to blame. And if cycling is your only exercise, not doing it would increase risks of ill health unless you compensate with other activity. The risks of cycling also depend very heavily on location (to take an extreme example, they are very much lower in Holland than in the UK) and age - the older, the safer. Apart from this, surely the numerical risks associated with driving, cycling, and motorcycling must depend heavily on careless and reckless drivers, cyclists and motorcyclists, who will presumably have the greatest risk of accidents. I wonder if the relative risks of the different activities are the same for those who are careful?

There's always a danger in applying averages universally. The mean figure can lie because it doesn't tell you the spread of the data and can't be applied to everyone or every situation. To say that the risk of motorcycling (something I did safely for 21 years) is x micromorts is only an average. Motorcyclists could be segmented into different statistical groups, each with a different average and therefore micromort. Buying a lottery ticket levels the field because everyone has an equal chance of winning. A careless motorcyclist has a greater chance of being killed than a careful one. There are many more variables (how the motorcyclists rides, where s/he's riding, the weather, levels of traffic etc). You can apply the average to every motorcyclist on the road but individuals are more or less likely to conform to the mean.