Archive for Science

how many T-Rex can you fit in your backyard?

Posted in Statistics with tags , , , , , on April 30, 2021 by xi'an

A fascinating question examined in this issue of Science [as pointed out by Nature!] in a paper by Marshall et al. on how many T. Rex(es) roamed the Earth at a given time (in the Cretaceous).  The figure is evaluated from Damuth’s Law and relying on estimates of their body mass (8 tons?), the range of its habitat, the longevity of the species (1.2 million years?), its generation time (18 years?), somewhat surprisingly taking the maximum age (28 years) as the age of the oldest observed fossil.

“We assessed the impact of uncertainties in the data used with Monte Carlo simulations, but these simulations do not accommodate uncertainties that might stem from the choices made in the design of our approach.”

The resulting global evaluation is of an abundance of about 20,000 individuals at a given time, albeit with a 95% confidence interval between 1300 and 328,000 animals, with around 127,000 generations, and a total number of T. rex that ever lived amounting to 2.5 billion animals. Fun exercise, but I am rather reserved at the validity of the evaluation, given the uncertainty and poor data about most terms in the equation.

laser sharp random number generator

Posted in Books, pictures, Statistics, University life with tags , , , , , , , , on April 1, 2021 by xi'an

Caught the headline of Science News on a super-fast random number generator based on a dysfunctional laser! Producing “254 trillion random digits per second”.

“…when the laser is shined on a surface, its light contains a constantly changing pattern of tiny pinpricks that brighten and dim randomly. The brightness at each spot in the pattern over time can be translated by a computer into a random series of ones and zeros.”

I presume this is covered in the original Science paper [which I cannot access] but the parallel series of 0’s and 1’s should be checked to produce independent Bernoulli B(½) variates before being turned into a genuine random number generator.

Olympus at work [Nature snapshot]

Posted in Books, pictures, Travel, University life with tags , , , , , , , on June 28, 2020 by xi'an

ABC on COVID-19

Posted in Books, pictures, Statistics, Travel with tags , , , , , , , , on March 20, 2020 by xi'an

The paper “The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak”, published in Science on 06 March by Matteo Chinazzi and co-authors, considers the impact of travel restriction in Wuhan on the propagation of the virus. (Terrible graph by the way since the overall volume of traffic dropped considerably after the ban.)

“The travel quarantine of Wuhan delayed the overall epidemic progression by only 3 to 5 days in Mainland China, but has a more marked effect at the international scale, where case importations were reduced by nearly 80% until mid February.”

They use a SLIR (susceptible-latent-infectious-removed) pattern of transmission, along with a travel flow network based on 2019 air and ground travel statistics, resorting to ABC for approximating the posterior distribution of the basic reproductive number. It is however unclear to me that the model is particularly accurate at the levels of the transmission pattern (which now seems to occur much earlier than when the symptoms appear) and of the detection rates (which vary greatly from one place to another).

Yikes! “AI can predict which criminals may break laws again better than humans”

Posted in Books, pictures, Statistics with tags , , , , , , , on February 28, 2020 by xi'an

Science (the journal!) has this heading on its RSS feed page, which makes me wonder if they have been paying any attention to the well-documented issues with AI driven “justice”.

“…some research has given reason to doubt that algorithms are any better at predicting arrests than humans are.”

Among other issues, the study compared volunteers with COMPAS‘ or LSI-R predictive abilities for predicting violent crime behaviour, based on the same covariates. Volunteers, not experts! And the algorithms are only correct 80% of the time which is a terrible perfomance when someone’s time in jail depends on it!

“Since neither humans nor algorithms show amazing accuracy at predicting whether someone will commit a crime two years down the line, “should we be using [those forecasts] as a metric to determine whether somebody goes free?” Farid says. “My argument is no.””

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