## quick(er) calculations [book review]

Posted in Statistics with tags , , , , , , , , , , , , on July 5, 2021 by xi'an

Upon my request, Oxford University Press sent me this book for review in CHANCE. With the extended title How to add, subtract, multiply, divide, square, and square root more swiftly. This short (173 pages) book is written by Trevor Davis Lipscombe, currently Director of the Catholic University of America Press (which are apparently not suited for his books, since his former Physics of Rugby got published by Nottingham University Press). The concept of the book is to list tricks and shortcuts to handle seemingly tough operations on a list of numbers. Illustrated by short anecdotes mostly related to religion, sports (including the Vatican cricket team!), and history, albeit not necessarily related with the computation at hand and not providing an in-depth coverage of calculation across the ages and the cultures. While the topic is rather dry, as illustrated by the section titles, e.g., “Multiply two numbers that differ by 2, 4, 6, or 20” or “Multiply or divide by 66 or 67, 666 or 667” (!), the exposition is somewhat facilitated by the (classics) culture of the author. (I have to confess I got lost by the date chapter, i.e., finding which day of the week was December 18, 1981, for instance. Especially by the concept of Doomsday which I thought was a special day of the year in the UK. Or in the USA.) Still, while recognising some simple decompositions I also used for additions and subtractions, and acknowledging the validity of the many tricks I had never though of, I wonder at the relevance of learning those dozens of approaches beyond maintaining a particular type of mental agility… Or preparing for party show-time. Especially for the operations that do not enjoy exact solutions, like dividing by √3 or multiplying by π… The book reminded me of a physics professor in Caen, Henri Eyraud, who used to approximate powers and roots faster than it took us to get a slide rule out of our bags! But Guesstimation, which I reviewed several years ago, seemed more far-reaching that Quick(er) calculations, in that I had tried to teach my kids (with limited success) how to reach the right order of magnitude of a quantity, but never insisted [beyond primary school] on quick mental calculations. (The Interlude V chapter connects with this idea.)

[Disclaimer about potential self-plagiarism: this post or an edited version should eventually appear in my Books Review section in CHANCE.]

## poems that solve puzzles [book review]

Posted in Books, Kids, University life with tags , , , , , , , , , , , , , , , , , , on January 7, 2021 by xi'an

Upon request, I received this book from Oxford University Press for review. Poems that Solve Puzzles is a nice title and its cover is quite to my linking (for once!). The author is Chris Bleakley, Head of the School of Computer Science at UCD.

“This book is for people that know algorithms are important, but have no idea what they are.”

These is the first sentence of the book and hence I am clearly falling outside the intended audience. When I asked OUP for a review copy, I was more thinking in terms of Robert Sedgewick’s Algorithms, whose first edition still sits on my shelves and which I read from first to last page when it appeared [and was part of my wife’s booklist]. This was (and is) indeed a fantastic book to learn how to build and optimise algorithms and I gain a lot from it (despite remaining a poor programmer!).

Back to poems, this one reads much more like an history of computer science for newbies than a deep entry into the “science of algorithms”, with imho too little on the algorithms themselves and their connections with computer languages and too much emphasis on the pomp and circumstances of computer science (like so-and-so got the ACM A.M. Turing Award in 19… and  retired in 19…). Beside the antique algorithms for finding primes, approximating π, and computing the (fast) Fourier transform (incl. John Tukey), the story moves quickly to the difference engine of Charles Babbage and Ada Lovelace, then to Turing’s machine, and artificial intelligence with the first checkers codes, which already included some learning aspects. Some sections on the ENIAC, John von Neumann and Stan Ulam, with the invention of Monte Carlo methods (but no word on MCMC). A bit of complexity theory (P versus NP) and then Internet, Amazon, Google, Facebook, Netflix… Finishing with neural networks (then and now), the unavoidable AlphaGo, and the incoming cryptocurrencies and quantum computers. All this makes for pleasant (if unsurprising) reading and could possibly captivate a young reader for whom computers are more than a gaming console or a more senior reader who so far stayed wary and away of computers. But I would have enjoyed much more a low-tech discussion on the construction, validation and optimisation of algorithms, namely a much soft(ware) version, as it would have made it much more distinct from the existing offer on the history of computer science.

[Disclaimer about potential self-plagiarism: this post or an edited version of it will eventually appear in my Books Review section in CHANCE.]

## on-line parameter estimation with Wasserstein

Posted in Books, Statistics, University life with tags , , , , , , , , on November 27, 2019 by xi'an

Just found out that our paper On parameter estimation with the Wasserstein distance with Espen Bernton, Pierre Jacob, and Mathieu Gerber, has now appeared on-line on Information and Inference: A Journal of the IMA,

## 9 pitfalls of data science [book review]

Posted in Books, Kids, Statistics, Travel, University life with tags , , , , , , , , , , , , , on September 11, 2019 by xi'an

I received The 9 pitfalls of data science by Gary Smith [who has written a significant number of general public books on personal investment, statistics and AIs] and Jay Cordes from OUP for review a few weeks ago and read it on my trip to Salzburg. This short book contains a lot of anecdotes and what I would qualify of small talk on job experiences and colleagues’ idiosyncrasies…. More fundamentally, it reads as a sequence of examples of bad or misused statistics, as many general public books on statistics do, but with little to say on how to spot such misuses of statistics. Its title (It seems like the 9 pitfalls of… is a rather common début for a book title!) however started a (short) conversation with my neighbour on the train to Salzburg as she wanted to know if the job opportunities in data sciences were better in Germany than in Austria. A practically important question for which I had no clue. And I do not think the book would have helped either! (My neighbour in the earlier plane to München had a book on growing lotus, which was not particularly enticing for launching a conversation either.)

## Is that a big number? [book review]

Posted in Books, Kids, pictures, Statistics with tags , , , , , , , , , on July 31, 2018 by xi'an

A book I received prior to its publication a few days ago from OXford University Press (OUP), as a book editor for CHANCE (usual provisions apply: the contents of this post will be more or less reproduced in my column in CHANCE when it appears). Copy that I found in my mailbox in Warwick last week and read over the (very hot) weekend.

The overall aim of this book by Andrew Elliott is to encourage numeracy (or fight innumeracy) by making sense of absolute quantities by putting them in perspective, teaching about log scales, visualisation, and divide-and-conquer techniques. And providing a massive list of examples and comparisons, sometimes for page after page… The book is associated with a fairly rich website, itself linked with the many blogs of the author and a myriad of other links and items of information (among which I learned of the recent and absurd launch of Elon Musk’s Tesla car in space! A première in garbage dumping…). From what I can gather from these sites, some (most?) of the material in the book seems to have emerged from the various blog entries.

“Length of River Thames (386 km) is 2 x length of the Suez Canal (193.3 km)”

Maybe I was too exhausted by heat and a very busy week in Warwick for our computational statistics week, the football  2018 World Cup having nothing to do with this, but I could not keep reading the chapters of the book in a continuous manner, suffering from massive information overdump! Being given thousands of entries kills [for me] the appeal of outing weight or sense to large and very large and humongous quantities. And the final vignette in each chapter of pairing of numbers like the one above or the one below

“Time since earliest writing (5200 y) is 25 x time since birth of Darwin (208 y)”

only evokes the remote memory of some kid journal I read from time to time as a kid with this type of entries (I cannot remember the name of the journal!). Or maybe it was a journal I would browse while waiting at the hairdresser’s (which brings back memories of endless waits, maybe because I did not like going to the hairdresser…) Some of the background about measurement and other curios carry a sense of Wikipediesque absolute in their minute details.

A last point of disappointment about the book is the poor graphical design or support. While the author insists on the importance of visualisation on grasping the scales of large quantities, and the webpage is full of such entries, there is very little backup with great graphs to be found in “Is that a big number?” Some of the pictures seem taken from an anonymous databank (where are the towers of San Geminiano?!) and there are not enough graphics. For instance, the fantastic graphics of xkcd conveying the xkcd money chart poster. Or about future. Or many many others

While the style is sometimes light and funny, an overall impression of dryness remains and in comparison I much more preferred Kaiser Fung’s Numbers rule your world and even more both Guesstimation books!