Posts Tagged ‘ statistics ’

splitting a field by annealing

October 17, 2017
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splitting a field by annealing

A recent riddle [from The Riddle] that I pondered about during a [long!] drive to Luxembourg last weekend was about splitting a square field into three lots of identical surface for a minimal length of separating wire… While this led me to conclude that the best solution was a T like separation, I ran a […]

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Lop-sided precincts, a visual exploration

October 17, 2017
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Lop-sided precincts, a visual exploration

Kaiser Fung, founder of Junk Charts, a leading data visualization blog, and Principal Analytics Prep, a premier data analytics bootcamp, discusses and remakes a Washington Post chart showing lop-sided precincts in the 2016 U.S. Presidential elections.

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Astrostatistics school

October 17, 2017
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Astrostatistics school

What a wonderful week at the Astrostat [Indian] summer school in Autrans! The setting was superb, on the high Vercors plateau overlooking both Grenoble [north] and Valence [west], with the colours of the Fall at their brightest on the foliage of the forests rising on both sides of the valley and a perfect green on […]

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Statistical skepticism: How to use significance tests effectively: 7 challenges & how to respond to them

October 13, 2017
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Statistical skepticism: How to use significance tests effectively: 7 challenges & how to respond to them

Here are my slides from the ASA Symposium on Statistical Inference : “A World Beyond p < .05”  in the session, “What are the best uses for P-values?”. (Aside from me,our session included Yoav Benjamini and David Robinson, with chair: Nalini Ravishanker.) 7 QUESTIONS Why use a tool that infers from a single (arbitrary) P-value […]

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[summer Astrostat school] room with a view [jatp]

October 9, 2017
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[summer Astrostat school] room with a view [jatp]

I just arrived in Autrans, on the Plateau du Vercors overlooking Grenoble and the view is fabulistic! Trees have started to turn red and yellow, the weather is very mild, and my duties are restricted to teaching ABC to a group of enthusiastic astronomers and cosmologists..! Second advanced course on ABC in the mountains this […]

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Rich maths with Dragons

October 9, 2017
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Rich maths with Dragons

Thanks to the Unlocking Curious Minds fund, StatsLC have been enabled to visit thirty rural schools in Canterbury and the West Coast and provide a two-hour maths event to help the children to see themselves as mathematicians. The groups include … Continue reading →

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mea culpa!

October 8, 2017
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mea culpa!

An entry about our Bayesian Essentials book on X validated alerted me to a typo in the derivation of the Gaussian posterior..! When deriving the posterior (which was left as an exercise in the Bayesian Core), I just forgot the term expressing the divergence between the prior mean and the sample mean. Mea culpa!!!Filed under: […]

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A la recherche des homonymes…

October 6, 2017
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A la recherche des homonymes…

Il y a quelques mois, Baptiste Coulmont m’avait contacté avec une question passionnante (comme chaque fois qu’il me contacte). Baptiste voulait travailler sur la proportion de personnes qui ont un homonymes dans une population de taille donnée, ou sur la probabilité de ne pas avoir d’homonymes dans un bureau de vote, par exemple. Or ce dernier problème n’est pas sans rappeler le “paradoxe des anniversaires“. Dans un groupe de 23 personnes,…

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Approximating the cut distribution

October 1, 2017
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Approximating the cut distribution

Hi, This post is about computational issues with the cut distribution for Bayesian inference in misspecified models. Some motivation was given in a previous post about a recent paper on modular Bayesian inference. The cut distribution, or variants of it, might play an important role in combining statistical models, especially in settings where one wants to propagate uncertainty […]

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Partial Pooling for Lower Variance Variable Encoding

September 28, 2017
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Partial Pooling for Lower Variance Variable Encoding

Banaue rice terraces. Photo: Jon Rawlinson In a previous article, we showed the use of partial pooling, or hierarchical/multilevel models, for level coding high-cardinality categorical variables in vtreat. In this article, we will discuss a little more about the how and why of partial pooling in R. We will use the lme4 package to fit … Continue reading Partial Pooling for Lower Variance Variable Encoding

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