Archive for statistical modelling

Statistical rethinking [book review]

Posted in Books, Kids, R, Statistics, University life with tags , , , , , , , , , , , , , , , , , , , , , on April 6, 2016 by xi'an

Statistical Rethinking: A Bayesian Course with Examples in R and Stan is a new book by Richard McElreath that CRC Press sent me for review in CHANCE. While the book was already discussed on Andrew’s blog three months ago, and [rightly so!] enthusiastically recommended by Rasmus Bååth on Amazon, here are the reasons why I am quite impressed by Statistical Rethinking!

“Make no mistake: you will wreck Prague eventually.” (p.10)

While the book has a lot in common with Bayesian Data Analysis, from being in the same CRC series to adopting a pragmatic and weakly informative approach to Bayesian analysis, to supporting the use of STAN, it also nicely develops its own ecosystem and idiosyncrasies, with a noticeable Jaynesian bent. To start with, I like the highly personal style with clear attempts to make the concepts memorable for students by resorting to external concepts. The best example is the call to the myth of the golem in the first chapter, which McElreath uses as an warning for the use of statistical models (which almost are anagrams to golems!). Golems and models [and robots, another concept invented in Prague!] are man-made devices that strive to accomplish the goal set to them without heeding the consequences of their actions. This first chapter of Statistical Rethinking is setting the ground for the rest of the book and gets quite philosophical (albeit in a readable way!) as a result. In particular, there is a most coherent call against hypothesis testing, which by itself justifies the title of the book. Continue reading

interesting mis-quote

Posted in Books, pictures, Statistics, Travel, University life with tags , , , , , , , , on September 25, 2014 by xi'an

At a recent conference on Big Data, one speaker mentioned this quote from Peter Norvig, the director of research at Google:

“All models are wrong, and increasingly you can succeed without them.”

quote that I found rather shocking, esp. when considering the amount of modelling behind Google tools. And coming from someone citing Kernel Methods for Pattern Analysis by Shawe-Taylor and Christianini as one of his favourite books and Bayesian Data Analysis as another one… Or displaying Bayes [or his alleged portrait] and Turing in his book cover. So I went searching on the Web for more information about this surprising quote. And found the explanation, as given by Peter Norvig himself:

“To set the record straight: That’s a silly statement, I didn’t say it, and I disagree with it.”

Which means that weird quotes have a high probability of being misquotes. And used by others to (obviously) support their own agenda. In the current case, Chris Anderson and his End of Theory paradigm. Briefly and mildly discussed by Andrew a few years ago.

Statistics second slides

Posted in Books, Kids, Statistics, University life with tags , , , , , on September 24, 2014 by xi'an

La Défense from Paris-Dauphine, Nov. 15, 2012This is the next chapter of my Statistics course, definitely more standard, with some notions on statistical models, limit theorems, and exponential families. In the first class, I recalled the convergence notions with no proof but counterexamples and spend some time on a slide not included here, borrowed from Chris Holmes’ talk last Friday on the linear relation between blood pressure and the log odds ratio of an heart condition. This was a great example, both to illustrate the power of increasing the number of observations and of using a logistic regression model. Students kept asking questions about it.

10w2170, Banff

Posted in Books, Mountains, R, Statistics with tags , , , , , , , , on September 11, 2010 by xi'an

Yesterday night, we started the  Hierarchical Bayesian Methods in Ecology workshop by trading stories. Everyone involved in the programme discussed his/her favourite dataset and corresponding expectations from the course. I found the exchange most interesting, like the one we had two years ago in Gran Paradiso, because of the diversity of approaches to Statistics reflected by the exposition. However, a constant theme is the desire to compare and rank models (this term having different meanings for different students) and the understanding that hierarchical models are a superior way to handle heterogeneity and to gather strength from the whole dataset. A two-day workshop is certainly too short to meet students’ expectations and I hope I will manage to focus on the concepts rather than on the maths and computations…

As each time I come here, the efficiency of BIRS in handling the workshop and making everything smooth and running amazes me. Except for the library, I think it really compares with Oberwolfach in terms of environment and working facilities. (Oberwolfach offers the appeal of seclusion and the Black Forest, while BIRS is providing summits all around plus the range of facility of the Banff Centre and the occasional excitement of a bear crossing the campus or a cougar killing a deer on its outskirt…)