politics coming [too close to] statistics [or the reverse]

On 30 April, David Spiegelhalter wrote an opinion column in The Guardian, Coronavirus deaths: how does Britain compare with other countries?, where he pointed out the difficulty, even “for a bean-counting statistician to count deaths”, as the reported figures are undercounts, and stated that “many feel that excess deaths give a truer picture of the impact of an epidemic“. Which, on the side, I indeed believe is a more objective material, as also reported by INSEE and INED in France.

“…my cold, statistical approach is to wait until the end of the year, and the years after that, when we can count the excess deaths. Until then, this grim contest won’t produce any league tables we can rely on.” D. Spiegelhalter

My understanding of the tribune is that the quick accumulation of raw numbers, even for deaths, and their use in the comparison of procedures and countries is not helping in understanding the impacts of policies and actions-reactions from a week ago. Starting with the delays in reporting death certificates, as again illustrated by the ten day lag in the INSEE reports. And accounting for covariates such as population density, economic and health indicators. (The graph below for instance relies on deaths so far attributed to COVID-19 rather than on excess deaths, while these attributions depend on the country policy and its official statistics capacities.)

“Polite request to PM and others: please stop using my Guardian article to claim we cannot make any international comparisons yet. I refer only to detailed league tables—of course we should now use other countries to try and learn why our numbers are high.” D. Spiegelhalter

However, when on 6 May Boris Johnson used this Guardian article during prime minister’s questions in the UK Parliement, to defuse a question from the Labour leader, Keir Starmer, David Spiegelhalter reacted with the above tweet, which is indeed that even with poor and undercounted data the total number of cases is much worse than predicted by the earlier models and deadlier than in neighbouring countries. Anyway, three other fellow statisticians, Phil Brown, Jim Smith (Warwick), and Henry Wynn, also reacted to David’s tribune by complaining at the lack of statistical modelling behind it and the fatalistic message it carries, advocating for model based decision-making, which would be fine if the data was not so unreliable… or if the proposed models were equipped with uncertainty bumpers accounting for misspecification and erroneous data.

more games of life

Another puzzle in memoriam of John Conway in The Guardian:

Find the ten digit number, abcdefghij. Each of the digits is different, and

• a is divisible by 1
• ab is divisible by 2
• abc is divisible by 3
• abcd is divisible by 4
• abcde is divisible by 5
• abcdef is divisible by 6
• abcdefg is divisible by 7
• abcdefgh is divisible by 8
• abcdefghi is divisible by 9
• abcdefghij is divisible by 10

Which brute force R coding by checking over random permutations of (1,2,…,9) [since j=0] solves within seconds:

while(0<1)
  if (prod(!(x<-sum(10^{0:8}*sample(1:9)))%/%10^{7:0}%%2:9))break()

into x=3816547290. And slightly less brute force R coding even faster:

while(0<1){
e=sample(c(2,6,8))#even
o=sample(c(1,3,7,9))#odd
if((!(o[1]+e[1]+o[2])%%3)&
(!(10*o[2]+e[2])%%4)&
(!(o[1]+e[1]+o[2]+e[2]+5+4)%%3)&
(!sum(10^{6:0}*c(o[1],e[1],o[2],e[2],5,4,o[3]))%%7)&
(!(10*o[3]+e[3])%%8)&
(!(sum(o)+sum(e))%%9)){
print(sum(10^{9:0}*c(o[1],e[1],o[2],e[2],4,5,o[3],e[3],o[4],0)));break()}}

Thin Air [book review]

When visiting Vancouver last December [at a time when traveling was still possible], I had the opportunity to revisit White Dwarf Books [thirty years after my first visit] and among other books bought a Richard Morgan‘s novel, Thin Air, that I did not know existed and which was recommended by the [friendly] book seller. As superior to Morgan’s foray into dark fantasy (that I did not dislike so much). As I had really enjoyed the Altered Carbon series, I jumped on this new novel, which is a form of sequel to Th1rt3en, and very very similar in its futuristic pastiche of tough detectives à la Marlowe, dry humour included. A form of space noir, as The Guardian puts it. I sort of got quickly lost in the plot and (unusually) could not keep track of some characters, which made reading the book a chore towards the end. Thanks to the COVID-19 quarantine, I still managed to finish it, while home cycling!, the very end being more exciting than the beginning drudgery and the predictable sex scenes bound to occur in every of his novels. The Martian world in the novel is only alluded to, which makes it more appealing, despite the invasive jargon, however it sounds too much like a copy of our 20th century with car chase and gun/knife fights. Enhanced by an embedded AI when one can afford it. Certainly not the best read in the series but enough to tempt me into looking at the first episodes of Altered Carbon on Netflix. [Note: the book is not to be confused with the bestselling Krakauer’s Into Thin Air, which relates the 1996 Everest disaster, soon turned into a rather poor movie. I had not realised till today that the same Krakauer wrote Into the Wild…!]

Art Ensemble of Chicago

psycho-history [Hari Seldon to the rescue!]

A “long read” article in the Guardian a few weeks ago sounds like Isaac Asimov’s Foundation‘s core concept, namely psychohistory, turning into a real academic discipline! In the books of this fantastic series, the father of this new science of predictive mathematical (or statistical) sociology, Hari Seldon, makes predictions that extend so far in the future that, at every major crisis of Asimov’s galactic empire, he delivers a per-registered message that indicates how to cope with the crisis to save the empire. Or so it seems! (As a teenager, I enjoyed the Foundation books very much, reading the three first volumes several times, to the point I wonder now if they were influential to my choice of a statistics major…! Presumably not, but it makes a nice story!!! Actually, Paul Krugman blames Asimov for his choice of economics as being the closest to psychohistory.)

“I assumed that the time would come when there would be a science in which things could be predicted on a probabilistic or statistical basis (…) can’t help but think it would be good, except that in my stories, I always have opposing views. In other words, people argue all possible… all possible… ways of looking at psychohistory and deciding whether it is good or bad. So you can’t really tell. I happen to feel sort of on the optimistic side. I think if we can somehow get across some of the problems that face us now, humanity has a glorious future, and that if we could use the tenets of psychohistory to guide ourselves we might avoid a great many troubles. But on the other hand, it might create troubles. It’s impossible to tell in advance.” I. Asimov

The Guardian entry is about Peter Turchin, a biologist who had “by the late 1990s answered all the ecological questions that interested him” and then turned his attention to history, creating a new field called cliodynamics. Which bears eerie similarities with Seldon’s psychohistory! Using massive databases of historical events (what is a non-historical event, by the way?!) to predict the future. And relying on a premise of quasi-periodic cycles to fit such predictions with a whiff of Soviet-era theories… I did not read in depth the entire paper (it’s a “long read”, remember?!) and even less the background theory, but I did not spot there a massive support from a large academic community for Turchin’s approach (mentioned in the psychohistory entry in Wikipedia). And, while this is not a major argument from Feyerabend’s perspective (of fundamental scientific advances resulting from breaks from consensus), it seems hard to think of a predictive approach that is not negatively impacted by singularity events, from the emergence of The Mule in Foundation, to the new scale of challenges posed by the acceleration of the climate collapse or the societal globalisation cum communitarian fragmentation caused by social media. And as a last warning, a previous entry in the same column wanted to warn readers “how statistics lost their power and big data controlled by private companies is taking over”, hence going the opposite direction.