I am happy to announce that I will be offering my tutorial, "Bayesian Statistics Made Simple" at PyCon 2014 in Montreal. The tutorial is based on material from Think Bayes. It includes some of the examples and exercises in the book. P...

Summer courses and workshop in doing Bayesian data analysis: Workshop, University of Oslo, Norway, June 4-6, 2014.Course offered through the University of St. Gallen Summer School in Empirical Research Methods (SSERM), St. Gallen, Switzerland, June 10-...

Chris Chambers and I had an enlightening discussion the other day at the blog of Rolf Zwaan, regarding the Garden of Forking Paths (go here and scroll down through the comments). Chris sent me the following note: I’m writing a book at the moment about reforming practices in psychological research (focusing on various bad practices […]The post Discussion on preregistration of research studies appeared first on Statistical Modeling, Causal Inference,…

Besides having coded a pretty cool MCMC app in Javascript, this guy Rasmus Bååth has started the Bayesian first aid project. The idea is that if there’s an R function called blabla.test performing test “blabla”, there should be a function bayes.blabla.test performing a similar test in a Bayesian framework, and showing the output in a […]

With each release of SAS/IML software, the language provides simple ways to carry out tasks that previously required more effort. In 2010 I blogged about a SAS/IML module that appeared in my book Statistical Programming with SAS/IML Software, which was written by using the SAS/IML 9.2. The blog post showed [...]

A friend of mine just alerted me to a story on NPR describing a prize on offer from Warren Buffett and Quicken Loans. The prize is a billion dollars (1B USD) for correctly predicting all 63 games in the men’s Division I college basketball tournament this March. The facebook page announcing the contest puts the odds at 1:9,223,372,036,854,775,808, […]

This week, in the MAT8595 course, we will start the section on inference for extreme values. To start with something simple, we will use maximum likelihood techniques on a Generalized Pareto Distribution (we’ve seen Monday Pickands-Balkema-de Hann theorem). Maximum Likelihood Estimation In the context of parametric models, the standard technique is to consider the maximum of the likelihood (or the log-likelihod).Let denote the parameter (with ). Given some – stnardard…

Together with many other packages written by Hadley Wickham, plyr is a package that I use a lot for data processing. The syntax is clean, and it works great for breaking down larger data.frame‘s into smaller summaries. The greatest disadvantage… See more ›

One of the new examples for the third edition of Bayesian Data Analysis is a spell-checking story. Here it is (just start at 2/3 down on the first page, with “Spelling correction”). I like this example—it demonstrates the Bayesian algebra, also gives a sense of the way that probability models (both “likelihood” and “prior”) are […]The post Spell-checking example demonstrates key aspects of Bayesian data analysis appeared first on Statistical…

MailChimp, a major vendor that companies use to send marketing emails to customers, published an analysis of the effect of Gmail marketing tabs (link). How should you read such a study? I'd begin by clarifying what problem the analyst is solving. In May, Google rolled out to all Gmail users a tabbed interface, in which the inbox is split into three parts: the regular inbox, a "promotional" email box, and…

FURTHER UPDATED: New course for Spring 2014: Thurs 3:30-6:15 (Randolph 209) first installment 6334 syllabus_SYLLABUS (first) Phil 6334: Philosophy of Statistical Inference and Modeling D. Mayo and A. Spanos Contact: error@vt.edu This new course, to be jointly taught by Professors D. Mayo (Philosophy) and A. Spanos (Economics) will provide an introductory, in-depth introduction to graduate […]

Dirk Kroese (from UQ, Brisbane) and Joshua Chen (from ANU, Canberra) just published a book entitled Statistical Modeling and Computation, distributed by Springer-Verlag (I cannot tell which series it is part of from the cover or frontpages…) The book is intended mostly for an undergrad audience (or for graduate students with no probability or statistics […]

This post is by Phil. I’m aware that there are some people who use a Bayesian approach largely because it allows them to provide a highly informative prior distribution based subjective judgment, but that is not the appeal of Bayesian methods for a lot of us practitioners. It’s disappointing and surprising, twenty years after my initial experiences, […]The post Everything I need to know about Bayesian statistics, I learned in eight schools.…

In the MAT8181 graduate course on Time Series, we will discuss (almost) only causal models. For instance, with , with some white noise , those models are obtained when . In that case, we’ve seen that was actually the innovation process, and we can write which is actually a mean-square convergent series (using simple Analysis arguments on series). From that expression, we can easily see that is stationary, since (which does…

In technical writing, three terms/phrases not to be used: Intuitively, ... It is clear that ... It is obvious that ... Just as well you could write Any idiot can plainly see ... These phrases may be true for you, the writer. However, the reader won't h...

We are very proud to announce the the Johns Hopkins Data Science Specialization on Coursera. You can see the official announcement from the Coursera folks here. This is the main reason Simply Statistics has been a little quiet lately. The … Continue reading →