. . . We really do have the best comment section on the internet. The post They say it because it’s true . . . appeared first on Statistical Modeling, Causal Inference, and Social Science.

. . . We really do have the best comment section on the internet. The post They say it because it’s true . . . appeared first on Statistical Modeling, Causal Inference, and Social Science.

We have another position available, this time for a lecturer (equivalent to an assistant professor tenure track in the US). The department covers a wide range of areas in statistics and econometrics, but for this position we are looking for someone with expertise in at least one of business analytics, data science, actuarial science, computational […]

Yeah, I know, I need to work some on the clickbait titles . . . Anyway, people keep asking me why different election forecasts are so different. At the time of this writing, Nate Silver gives Clinton a 66.2% [ugh! See Pedants Corner below] chance of winning the election while Drew Linzer, for example, gives […] The post Different election forecasts not so different appeared first on Statistical Modeling, Causal…

I prefer 50% to 95% intervals for 3 reasons: 1. Computational stability, 2. More intuitive evaluation (half the 50% intervals should contain the true value), 3. A sense that in aplications it’s best to get a sense of where the parameters and predicted values will be, not to attempt an unrealistic near-certainty. This came up […] The post Why I prefer 50% rather than 95% intervals appeared first on Statistical…

David Leonhardt of the NYT asked a bunch of different people, including me, which of various Romney-won states in 2012 would be likely to be won by a Democrat in 2020, 2024, or 2028, and which of various Obama-won states would go for a Republican in any of those future years. If I’m going to […] The post Modeling statewide presidential election votes through 2028 appeared first on Statistical Modeling,…

Dan Kahan points me to this paper: It is impossible to make sense of persistent controversy over certain forms of decision-relevant science without understanding what happens in the vastly greater number of cases in which members of the public converge on the best available evidence without misadventure. In order to live well—or just to live, […] The post Kahan: “On the Sources of Ordinary Science Knowledge and Ignorance” appeared first…

Being still puzzled (!) by the ratio-of-uniform approach, mostly failing to catch its relevance for either standard distributions in a era when computing a cosine or an exponential is negligible, or non-standard distributions for which computing bounds and boundaries is out-of-reach, I kept searching for solutions that would include unbounded densities and still produce compact […]

Check out this new prize, http://statprize.org/ (Thanks, Dave Giles, for informing me via your tweet.) It should be USD 1 Million, ahead of the Nobel, as statistics is a key part (arguably the key part) of the foundation on which every science builds....

In an beautiful new paper, Betancourt writes: The geometric foundations of Hamiltonian Monte Carlo implicitly identify the optimal choice of [tuning] parameters, especially the integration time. I then consider the practical consequences of these principles in both existing algorithms and a new implementation called Exhaustive Hamiltonian Monte Carlo [XMC] before demonstrating the utility of these […] The post Michael Betancourt has made NUTS even more awesome and efficient! appeared first…

I happened to be looking up some things on cat-owner Dan Kahan’s blog and I came across this interesting comment from 2013 that I’d not noticed before. The comment came from science journalist Dan Vergano, and it was in response to a post of Kahan that discussed an article of mine that had given advice […] The post How to improve science reporting? Dan Vergano sez: It’s not about reality,…

Next summer of 2017, the biennial International Conference on Monte Carlo Methods and Applications (MCM) will take place in Montréal, Québec, Canada, on July 3-7. This is a mathematically-oriented meeting that works in alternance with MCqMC and that is “devoted to the study of stochastic simulation and Monte Carlo methods in general, from the theoretical […]