Archive for tribune

Monsieur le Président [reposted]

Posted in Books, Statistics, University life with tags , , , , , , , , , , , on April 11, 2020 by xi'an

Let us carry out screening campaigns on representative samples of population!

Mr President of the Republic, as you rightly indicated, we are at war and everything must be done to combat the spread of CODIV-19. You had the wisdom to surround yourself with a Scientific Council and an Analysis, Research and Expertise Committee, both competent, and, as you know, applied mathematicians, statisticians have a role to play in this battle. Yes, to predict the evolution of the epidemic, mathematical models are used at different scales. This allows us estimate the number of people infected in the coming weeks and months. We are at war and these predictions are essential to the development of the best control strategy. They inform political decisions. This is especially with the help of these items of information that the confinement of the French population has been decided and renewed.

Mr President we are at war and these predictions must be the most robust possible. The more precise they are, the better the decisions they will guide. Mathematical models include a number of unknown parameters whose values ​​should be set based on expert advice or data. These include the transmission rate, incubation time, contagion time, and, of course, to initialize dynamic mathematical models, the number of covered individuals. To enjoy more reliable predictions, it is necessary to better estimate such crucial quantities. The proportion of healthy carriers appears to be a particularly critical parameter.

Mr President, we are at war and we must assess the proportions of healthy carriers by geographic areas. We do not currently have the means to implement massive screenings, but we can carry out surveys. This means, for a well-defined geographic area, to run biological tests on samples of individuals that are drawn at random and are representative of the total population of the area. Such data would come to supplement those already available and would considerably reduce the uncertainty in model predictions.

Mr. President, we are at war, let us give ourselves the means to fight effectively against this scourge. Thanks to a significant effort, the number of individuals that can be tested daily increases significantly, let’s devote some of these available tests to samples representative. For each individual drawn at random, we will perform a nasal swab, a blood test, let us collect clinical data and other items of information on its follow-up barriers. This would provide important information on the percentage of immunized French people. This data would open the possibility to feed mathematical models wisely, and hence to make informed decisions about the different strategies of deconfinement.

Mr. President, we are at war. This strategy, which could at first be deployed only in the most affected sectors, is, we believe, essential. It is doable: designing the survey and determining a representative sample is not an issue, going to the homes of the people in the sample, towards taking samples and having them fill out a questionnaire is also perfectly achievable if we give ourselves the means to do so. You only have to decide that a few of the available PCR tests and serological tests will be devoted to these statistical studies. In Paris and in the Grand Est, for instance, a mere few thousand tests on a representative population of individuals properly selected could better assess the situation and help in taking informed decisions.

Mr. President, a proposal to this effect has been presented to the Scientific Council and to the Analysis, Research and Expertise Committee that you have set up by a group of mathematicians at École Polytechnique with Professor Josselin Garnier at their head. You will realise by reading this tribune that the statistician that I am does support very strongly. I am in no way disputing the competence of the councils which support you but you have to act quickly and, I repeat, only dedicate a few thousand tests to statistics studies. Emergency is everywhere, assistance to the patients, to people in intensive care, must of course be the priority, but let us attempt to anticipate as well . We do not have the means to massively test the entire population, let us run polls.

Jean-Michel Marin
Professeur à l’Université de Montpellier
Président de la Société Française de Statistique
Directeur de l’Institut Montpelliérain Alexander Grothendieck
Vice-Doyen de la Faculté des Sciences de Montpellier

where K. works

Posted in Books, Mountains, pictures, Statistics, Travel, University life with tags , , , , , , , , on December 2, 2019 by xi'an

Nature snippets

Posted in Statistics with tags , , , , , , , , , , , , , on October 1, 2019 by xi'an

In the August 1 issue of Nature I took with me to Japan, there were many entries of interest. The first pages included a tribune (“personal take on events”) by a professor of oceanography calling for a stop to the construction of the TMT telescope on the Mauna Kea mountain. While I am totally ignorant of the conditions of this construction and in particular of the possible ecological effects on a fragile altitude environment, the tribune is fairly confusing invoking mostly communitarian and religious, rather than scientific ones. And referring to Western science and Protestant missionaries as misrepresenting a principle of caution. While not seeing the contradiction in suggesting the move of the observatory to the Canary Islands, which were (also) invaded by Spanish settlers in the 13th century.

Among other news, Indonesia following regional tendencies to nationalise research by forcing foreign researchers to have their data vetted by the national research agency and to include Indonesian nationals in their projects. And, although this now sounds stale news, the worry about the buffoonesque Prime Minister of the UK. And of the eugenic tendencies of his cunning advisor… A longer article by Patrick Riley from Google on three problems with machine learning, from splitting the data inappropriately (biases in the data collection) to hidden variables (unsuspected confounders) to mistaking the objective (impact of the loss function used to learn the predictive function). (Were these warnings heeded in the following paper claiming that deep learning was better at predicting kidney failures?)  Another paper of personal interest was reporting a successful experiment in Guangzhou, China, infecting tiger mosquitoes with a bacteria to make the wild population sterile. While tiger mosquitoes have reached the Greater Paris area,  and are thus becoming a nuisance, releasing 5 million more mosquitoes per week in the wild may not sound like the desired solution but since the additional mosquitoes are overwhelmingly male, we would not feel the sting of this measure! The issue also contained a review paper on memory editing for clinical treatment of psychopathology, which is part of the 150 years of Nature anniversary collection, but that I did not read (or else I forgot!)

y a plus de mouchoirs au bureau des pleurs

Posted in pictures, University life with tags , , , , , , , , , on January 10, 2019 by xi'an

Once the French government started giving up to some requests of the unstructured “gilets jaunes” protesters, it was like a flood or flush gate had opened and every category was soon asking for a rise (in benefits) and a decrease (in taxes) or the abolition of a recent measure (like the new procedure for entering university after high school). As an illustration, I read a rather bemusing tribune in Le Monde from a collective of PhD students against asking non-EU students (including PhD students) to pay fees to study in French universities. This may sound a bit of a surrealistic debate from abroad, but the most curious point in the tribune [besides the seemingly paradoxical title of students against Bienvenue En France!] is to argue that asking these students to pay the intended amount would bring their net stipends below the legal minimum wage, considering that they are regular workers… (Which is not completely untrue when remembering that in France the stipends are taxed for income tax and retirement benefits and unemployment benefits, meaning that a new PhD graduate with no position can apply for these benefits.) It seems to me that the solution adopted in most countries, namely that the registration fees are incorporated within the PhD grants, could apply here as well… The other argument that raising these fees from essentially zero to 3000 euros is going to stop bright foreign students to do their PhD in France is not particularly strong when considering that the proportion of foreign students among PhD students here is slightly inferior to the proportion in the UK and the US, where the fees are anything but negligible, especially for foreign students.

gender gaps

Posted in Statistics, University life with tags , , , , , , , , , , on March 31, 2018 by xi'an

Two of my colleagues [and co-authors] at Dauphine, Elyès Jouini and Clotilde Napp, published a paper in Science last week (and an associated tribune in Le Monde which I spotted first) about explaining differences in national gender inequalities in maths (as measured by PISA) in terms of the degree of overall inequality in the respective countries. Gaps in the highest maths performer sex ratio. While I have no qualm about the dependency or the overall statistical cum machine learning analysis (supported by our common co-author Jean-Michel Marin), and while I obviously know nothing about the topic!, I leisurely wonder at the cultural factor (which may also partly explain for the degree of inequality) when considering that the countries at the bottom of the above graphs are rather religious (and mostly catholic). I also find it most intriguing that the gender gap is consistently reversed when considering higher performer sex ratio for reading, because mastering the language should be a strong factor in power structures and hence differences therein should also lead to inequalities…

truth or truthiness [book review]

Posted in Books, Kids, pictures, Statistics, University life with tags , , , , , , , , , , , , on March 21, 2017 by xi'an

This 2016 book by Howard Wainer has been sitting (!) on my desk for quite a while and it took a long visit to Warwick to find a free spot to quickly read it and write my impressions. The subtitle is, as shown on the picture, “Distinguishing fact from fiction by learning to think like a data scientist”. With all due respect to the book, which illustrates quite pleasantly the dangers of (pseudo-)data mis- or over- (or eve under-)interpretation, and to the author, who has repeatedly emphasised those points in his books and tribunes opinion columns, including those in CHANCE, I do not think the book teaches how to think like a data scientist. In that an arbitrary neophyte reader would not manage to handle a realistic data centric situation without deeper training. But this collection of essays, some of which were tribunes, makes for a nice reading  nonetheless.

I presume that in this post-truth and alternative facts [dark] era, the notion of truthiness is familiar to most readers! It is often based on a misunderstanding or a misappropriation of data leading to dubious and unfounded conclusions. The book runs through dozens of examples (some of them quite short and mostly appealing to common sense) to show how this happens and to some extent how this can be countered. If not avoided as people will always try to bend, willingly or not, the data to their conclusion.

There are several parts and several themes in Truth or Truthiness, with different degrees of depth and novelty. The more involved part is in my opinion the one about causality, with illustrations in educational testing, psychology, and medical trials. (The illustration about fracking and the resulting impact on Oklahoma earthquakes should not be in the book, except that there exist officials publicly denying the facts. The same remark applies to the testing cheat controversy, which would be laughable had not someone ended up the victim!) The section on graphical representation and data communication is less exciting, presumably because it comes after Tufte’s books and message. I also feel the 1854 cholera map of John Snow is somewhat over-exploited, since he only drew the map after the epidemic declined.  The final chapter Don’t Try this at Home is quite anecdotal and at the same time this may the whole point, namely that in mundane questions thinking like a data scientist is feasible and leads to sometimes surprising conclusions!

“In the past a theory could get by on its beauty; in the modern world, a successful theory has to work for a living.” (p.40)

The book reads quite nicely, as a whole and a collection of pieces, from which class and talk illustrations can be borrowed. I like the “learned” tone of it, with plenty of citations and witticisms, some in Latin, Yiddish and even French. (Even though the later is somewhat inaccurate! Si ça avait pu se produire, ça avait dû se produire [p.152] would have sounded more vernacular in my Gallic opinion!) I thus enjoyed unreservedly Truth or Truthiness, for its rich style and critical message, all the more needed in the current times, and far from comparing it with a bag of potato chips as Andrew Gelman did, I would like to stress its classical tone, in the sense of being immersed in a broad and deep culture that seems to be receding fast.

the end of statistics [not!]

Posted in Statistics with tags , , , , , , , , , , on January 31, 2017 by xi'an

endofstatsLast week I spotted this tribune in The Guardian, with the witty title of statistics loosing its power, and sort of over-reacted by trying to gather enough momentum from colleagues towards writing a counter-column. After a few days of decantation and a few more readings (reads?) of the tribune, I cooled down towards a more lenient perspective, even though I still dislike the [catastrophic and journalistic] title. The paper is actually mostly right (!), from its historical recap of the evolution of (official) statistics across centuries, to the different nature of the “big data” statistics. (The author is “William Davies, a sociologist and political economist. His books include The Limits of Neoliberalism and The Happiness Industry.”)

“Despite these criticisms, the aspiration to depict a society in its entirety, and to do so in an objective fashion, has meant that various progressive ideals have been attached to statistics.”

A central point is that public opinion has less confidence in (official) statistics than it used to be. (warning: Major understatement, here!) For many reasons, from numbers used to support any argument and its opposite, to statistics (-ians) being associated with experts, found at every corner of news and medias, hence with the “elite” arch-enemy, to a growing innumeracy of both the general public and of the said “elites”—like this “expert” in a debate about the 15th anniversary of the Euro currency on the French NPR last week equating a raise from 2.4 Francs to 6.5 Francs to 700%…—favouring rhetoric over facts, to a disintegration of the social structure that elevates one’s community over others and dismisses arguments from those others, especially those addressed at the entire society. The current debate—and the very fact there can even be a debate about it!—about post-truths and alternative facts is a sad illustration of this regression in the public discourse. The overall perspective in the tribune is one of a sociologist on statistics, but nothing to strongly object to.

“These data analysts are often physicists or mathematicians, whose skills are not developed for the study of society at all.”

The second part of the paper is about the perceived shift from (official) statistics to another and much more dangerous type of data analysis. Which is not a new view on the field, as shown by Weapons of Math Destruction. I tend to disagree with this perception that data handled by private companies for private purposes is inherently evil. The reticence in trusting the conclusions drawn from such datasets also extends to publicly available datasets and is not primarily linked to the lack of reproducibility of such analyses (which would be a perfectly rational argument!). It is neither due to physicists or mathematicians running those, instead of quantitative sociologists! The roots of the mistrust are rather to be found in an anti-scientism that has been growing in the past decades, in a paradox of an equally growing technological society fuelled by scientific advances. Hence, calling for a governmental office of big data or some similar institution is very much unlikely to solve the issue. I do not know what could, actually, but continuing to develop better statistical methodology cannot hurt!