All models are wrong…

… but some are more wrong than others. It’s emerged that a risk calculator for cholesterol-related heart disease risk is giving some highly dubious results. So completely healthy people could start taking unnecessary drugs. It’s not clear if the problem is in the specification or the implementation: but either way, the results seem rather dubious. […]

Unlikely but just about plausible

I’ve been recently been working with the Centre for Risk Studies in Cambridge on some extreme scenarios: one-in-200, or even less likely events. It’s been an interesting challenge, not least because it’s very difficult to make things extreme enough. We find ourselves saying that the step in the scenario that we’re working would never actually […]

Swiss cheese

Why do things go wrong? Sometimes, it’s a whole combination of factors. Felix Salmon has some good examples, and reminded me of one of my favourite metaphors: the Swiss cheese model of accident causation. In the Swiss Cheese model, an organization’s defenses against failure are modeled as a series of barriers, represented as slices of […]

Reinhart and Rogoff: was Excel the problem?

There’s a bit of a furore going on at the moment: it turns out that a controversial paper in the debate about the after-effects of the financial crisis had some peculiarities in its data analysis. Rortybomb has a great description, and the FT’s Alphaville and Tyler Cowen have interesting comments. In summary, back in 2010 […]

Software risks: testing might help (or not)

It’s good to test your software. That’s pretty much a given, as far as I’m concerned. If you don’t test it, you can’t tell whether it will work. It seems pretty obvious. It also seems pretty obvious that a) you shouldn’t use test data in a live system, b) in order to test whether it’s […]