The running shoe company Hoka (One One) is known *among runners at least) for its oversized soles that allow more cushion than competitors. (It was created in Annecy, French Alps, for local trailers, before being bought by an American group. The name of the brand means flying on Earth in Maori.) I had never tried any of their shoes, primarily due to the cost of the fastest ones, but in the days after Marseille-Cassis, I saw an add mentioning a free return after a 30 day trial and thus decided on testing a (pricey) competition model, the Cielo X1. Advertised as the fastest in their collection (with no mention made of any car brand!)I received the package a few days prior to my Boulogne half-marathon.
The shoe is highly unusual (for me), in that its soles are far from flat and make walking with then unpleasant. (When I travelled to Boulogne, I had to jog to keep my [detailed] balance!) The design is intended for (aggressive) forefoot attack, followed by a bounce from the talon created by a massive carbon plate. The upper part is also original, with a light but tight slipper that stabilises the foot inside the shoe. When I first tried them (the day they arrived), I was most puzzled and did a first short 8km run to check I could at all run with them. And realised that even without trying, I was running at a higher pace, especially downhill. The next day, I pushed a bit harder on my 10km route and noticed the same improvement, hence got confident that I should use them for the Boulogne half-marathon. Post-race, I remain convinced them helped in keeping a below 4mn pace, if not enormously (with a 90 second gain compared with 2023), as my muscles started protesting about half-way. But the end of the race was not as dreadful as usual, possibly thanks to the shoes, possibly thanks to a higher training volume. Will I keep the shoes? At that price, I am afraid not! But this was a great experience (and I will keep looking for sales in the coming months).
Archive for design
trialing a Porsch[o]e
Posted in Mountains, pictures, Running, Travel with tags Annecy, Boulogne-Billancourt, carbon plate, competition, design, detailed balance, foam protection, France, French Alps, Hoka One One, Maori language, running shoes, semi-marathon, trail running, ultramarathon on December 5, 2024 by xi'anThe Effect [book review]
Posted in Books, R, Running, Statistics, University life with tags book review, bootstrap, causality, CHANCE, cholera, computer simulation, confinement, COVID-19, CRC Press, design, econometrics, instrumental variables, John Snow, Lasso, lockdown, ordinary least squares, P.C. Mahalanobis, Python, R, random forests, six minute mile, Stata on March 10, 2023 by xi'an
While it sounds like the title of a science-fiction catastrophe novel or of a (of course) convoluted nouveau roman, this book by Nick Huntington-Klein is a massive initiation to econometrics and causality. As explained by the subtitle, An Introduction to Research Design and Causality.
This is a hüûüge book, actually made of two parts that could have been books (volumes?). And covering three langages, R, Stata, and Python, which should have led to three independent books. (Seriously, why print three versions when you need at best one?!) I carried it with me during my vacations in Central Québec, but managed to loose my notes on the first part, which means missing the opportunity for biased quotes! It was mostly written during the COVID lockdown(s), which may explain for a certain amount of verbosity and rambling around.
“My mom loved the first part of the book and she is allergic to statistics.”
The first half (which is in fact a third!) is conceptual (and chatty) and almost formula free, based on the postulate that “it’s a pretty slim portion of students who understand a method because of an equation” (p.xxii). For this reader (or rather reviewer) and on explanations through example, it makes the reading much harder as spotting the main point gets harder (and requires reading most sentences!). And a very slow start since notations and mathematical notions have to be introduced with an excess of caution (as in the distinction between Latin and Greek symbols, p.36). Moving through single variable models, conditional distributions, with a lengthy explanation of how OLS are derived, data generating process and identification (of causes), causal diagrams, back and front doors (a recurrent notion within the book), treatment effects and a conclusion chapter.
“Unlike statistical research, which is completely made of things that are at least slightly false, statistics itself is almost entirely true.” (p.327)
The second part, called the Toolbox, is closer to a classical introduction to econometrics, albeit with a shortage of mathematics (and no proof whatsoever), although [warning!] logarithms, polynomials, partial derivatives and matrices are used. Along with a consequent (3x) chunk allocated to printed codes, the density of the footnotes significantly increases in this section. It covers an extensive chapter on regression (including testing practice, non-linear and generalised linear models, as well as basic bootstrap without much warning about its use in… regression settings, and LASSO), one on matching (with propensity scores, kernel weighting, Mahalanobis weighting, one on simulation, yes simulation! in the sense of producing pseudo-data from known generating processes to check methods, as well as bootstrap (with resampling residuals making at last an appearance!), fixed and random effects (where the author “feels the presence of Andrew Gelman reaching through time and space to disagree”, p.405). The chapter on event studies is about time dependent data with a bit of ARIMA prediction (but nothing on non-stationary series and unit root issues). The more exotic chapters cover (18) difference-in-differences models (control vs treated groups, with John Snow pumping his way in), (19) instrumental variables (aka the minor bane of my 1980’s econometrics courses), with double least squares and generalised methods of moments (if not the simulated version), (20) discontinuity (i.e., changepoints), with the limitation of having a single variate explaining the change, rather than an unknown combination of them, and a rather pedestrian approach to the issue, (iv) other methods (including the first mention of machine learning regression/prediction and some causal forests), concluding with an “Under the rug” portmanteau.
Nothing (afaict) on multivariate regressed variates and simultaneous equations. Hardly an occurrence of Bayesian modelling (p.581), vague enough to remind me of my first course of statistics and the one-line annihilation of the notion.
Duh cover, but nice edition, except for the huge margins that could have been cut to reduce the 622 pages by a third (and harnessed the tendency of the author towards excessive footnotes!). And an unintentional white line on p.238! Cute and vaguely connected little drawings at the head of every chapter (like the head above). A rather terse matter index (except for the entry “The first reader to spot this wins ten bucks“!), which should have been completed with an acronym index.
“Calculus-heads will recognize all of this as taking integrals of the density curve. Did you know there’s calculus hidden inside statistics? The things your professor won’t tell you until it’s too late to drop the class.
Obviously I am biased in that I cannot negatively comment on an author running 5:37 a mile as, by now, I could just compete far from the 5:15 of yester decades! I am just a wee bit suspicious at the reported time, however, given that it happens exactly on page 537… (And I could have clearly taken issue with his 2014 paper, Is Robert anti-teacher? Or with the populist catering to anti-math attitudes as the above found in a footnote!) But I enjoyed reading the conceptual chapter on causality as well as the (more) technical chapter on instrumental variables (a notion I have consistently found confusing all the [long] way from graduate school). And while repeated references are made to Scott Cunningham’s Causal Inference: The Mixtape I think I will stop there with 500⁺ page introductory econometrics books!
[Disclaimer about potential self-plagiarism: this post or an edited version will potentially appear in my Books Review section in CHANCE.]
Þe Norse farce [design #2]
Posted in Kids, Mountains, pictures with tags Þe Norse face, þ, design, helmet, parody, Scandinavia, thor, Viking helmet, ye Norse farce on November 19, 2018 by xi'an
JASP, a really really fresh way to do stats
Posted in Statistics with tags Bayes factors, Bayesian inference, design, Harold Jeffreys, JASP, tee-shirt, University of Amsterdam on February 1, 2018 by xi'an
The Norse Farce [design #2]
Posted in Statistics with tags competition, design, mug, The Norse Farce on December 7, 2017 by xi'anIn reply to my call for designs along the Norse farce pun, here is a nice proposal from Thomas, which stands so far as a strong competitor for the best design! I welcome more submissions: remember, a free mug to the winner!!!
