We’ve all seen the images. And they are incredible. Like many natural disasters.
On 25 January, Niscemi, a small Sicilian town, split in two, after the torrential rains associated with Storm Harry, leaving a scar several kilometres long. We saw roads collapsing, cars vanishing, houses left hanging on the edge of a void. More than 1,600 people were evacuated. In the Guardian article, we are reminded that this was not the first time. We are told that the very same area had already slid in the 18th century, and again in 1997, and yet construction continued, especially from the 1950s and 1960s onwards.
Could we have known? Did we already know? And if we did, why does it still happen? Almost inevitably, after every natural disaster, I find that these questions come back too, again and again… I thought I could write a short post to recall that, on the one hand, there are striking regularities in the way some disasters unfold. But on the other hand, “predictable” does not mean “avoidable”, because disaster is also a social fact, a story of vulnerability, exposure, and public choices (at the risk of repeating myself, I know).
Continue reading Natural disasters, avoidable or unpredictable?

is the quantile of probability level
of the standard normal distribution
. But usually, standard deviation
(the something is was talking about earlier) is usually unknown. So we substitute an estimation of the standard deviation, e.g.


is the quantile of the Student distribution, of probability level
degrees of freedom.
i.i.d. with distribution
, a copula, but in practice, we start from a sample
with joint distribution
(assumed to have continuous margins, and – unique – copula 

are empirical cumulative distribution functions.
than on perfect sample
.

, but Christian and Johan obtained an analytical result. Hence, if we denote


,
