Archive for no starch press

The CS detective

Posted in Books, Kids, Travel, University life with tags , , , , , , , on October 29, 2016 by xi'an

A few weeks ago, I received a generic email from No Starch Press promoting The CS Detective, and as I had liked their earlier Statistics Done Wrong, I requested a review copy of the book. Which I received in Warwick while I was there, last week. And read over my trip back to Paris. As it is a very quick read.

“The trouble with having an open mind, of course, is that people will insist on coming along and trying to put things in it.” T. Pratchett

The idea of the book is to introduce some concepts of tree searching algorithms through a detective-cum-magic story, a very shallow story if somewhat à la Terry Pratchett. (While this reference does not appear in the book, there are enough mentions made of turtles to suspect the filiation. Even though it is turtles all the way down. Hence I could not swear Frank Runtime was 100% inspired from Sam Vimes. But it rhymes.) I cannot say I am a bit fan of this approach as the story is an hindrance rather than an help, I do not find it particularly funny or enticing, and I keep wishing for the next concept to appear to end the current chapter and its inane plot. Of course, once the story is set aside, the book contains not that much in terms of search algorithms, because they all are limited to discrete tree structures. Namely, exhaustive, binary, breadth- and depth-first, iterative deepening, best-first, search algorithms, along with the notions of arrays, queues, stacks, and heaps. This fills about 50 pages of technical vignettes found at the end of each chapter…

So I end up wondering at what age this book would appeal to a young reader. Trying to remember from my own experience with summer vacation riddle and puzzle books, I would think the range 10-12 could be most appropriate although mileage will vary. Since the author, Jeremy Kubica, animates the Computational Fairy Tales blog with stories of the same flavour, you may start by tasting and testing this approach to popular science before getting the entire book

Statistics done wrong [book review]

Posted in Books, Kids, pictures, Statistics, University life with tags , , , , , , , , , on March 16, 2015 by xi'an

no starch press (!) sent me the pdf version of this incoming book, Statistics done wrong, by Alex Reinhart, towards writing a book review for CHANCE, and I read it over two flights, one from Montpellier to Paris last week, and from Paris to B’ham this morning. The book is due to appear on March 16. It expands on a still existing website developed by Reinhart. (Discussed a year or so away on Andrew’s blog, most in comments, witness Andrew’s comment below.) Reinhart who is, incidentally or not, is a PhD candidate in statistics at Carnegie Mellon University. After apparently a rather consequent undergraduate foray into physics. Quite an unusual level of maturity and perspective for a PhD student..!

“It’s hard for me to evaluate because I am so close to the material. But on first glance it looks pretty reasonable to me.” A. Gelman

Overall, I found myself enjoying reading the book, even though I found the overall picture of the infinitely many mis-uses of statistics rather grim and a recipe for despairing of ever setting things straight..! Somehow, this is an anti-textbook, in that it warns about many ways of applying the right statistical technique in the wrong setting, without ever describing those statistical techniques. Actually without using a single maths equation. Which should be a reason good enough for me to let all hell break loose on that book! But, no, not really, I felt no compunction about agreeing with Reinhart’s warning and if you have reading Andrew’s blog for a while you should feel the same…

“Then again for a symptom like spontaneous human combustion you might get excited about any improvement.” A. Reinhart (p.13)

Maybe the limitation in the exercise is that statistics appears so much fraught with dangers of over-interpretation and false positive and that everyone (except physicists!) is bound to make such invalidated leaps in conclusion, willingly or not, that it sounds like the statistical side of Gödel’s impossibility theorem! Further, the book moves from recommendation at the individual level, i.e., on how one should conduct an experiment and separate data for hypothesis building from data for hypothesis testing, to a universal criticism of the poor standards of scientific publishing and the unavailability of most datasets and codes. Hence calling for universal reproducibility protocols that reminded of the directions explored in this recent book I reviewed on that topic. (The one the rogue bird did not like.) It may be missing on the bright side of things, for instance the wonderful possibility to use statistical models to produce simulated datasets that allow for an evaluation of the performances of a given procedure in the ideal setting. Which would have helped the increasingly depressed reader in finding ways of checking how wrongs things could get..! But also on the dark side, as it does not say much about the fact that a statistical model is most presumably wrong. (Maybe a physicist’s idiosyncrasy!) There is a chapter entitled Model Abuse, but all it does is criticise stepwise regression and somehow botches the description of Simpson’s paradox.

“You can likely get good advice in exchange for some chocolates or a beer or perhaps coauthorship on your next paper.” A. Reinhart (p.127)

The final pages are however quite redeeming in that they acknowledge that scientists from other fields cannot afford a solid enough training in statistics and hence should hire statisticians as consultants for the data collection, analysis and interpretation of their experiments. A most reasonable recommendation!