The Largest Web Page on the Internet: 7 Billion People on One Page

April 22, 2013
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The Largest Web Page on the Internet: 7 Billion People on One Page

7 Billion World [7billionworld.com] displays 7 billion people together on a single webpage. Developed by Worldometers - which themselves were originally posted in the good year of 2005 -, the web page itself is generated through some small programmin...

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Prime Explorer: Exploring Patterns in Prime Number Spatial Layouts

April 22, 2013
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Prime Explorer: Exploring Patterns in Prime Number Spatial Layouts

Prime Explorer [bigblueboo.com], developed by a San Francisco-based software company called Mode of Expression, provides an interactive view of all the prime numbers ranging from 1 to 62,500. Each prime number is represented by a bright, white squar...

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The Price is Right Problem

April 22, 2013
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The Price is Right Problem

This article is an excerpt from Think Bayes, a book I am working on.  The entire current draft is available from http://thinkbayes.com.  I welcome comments and suggestions.The Price is Right ProblemOn November 1, 2007, contestants named Letia...

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Statistics Sweden’s statistics are available for new services

April 22, 2013
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Statistics Sweden’s statistics are available for new services

From: http://www.scb.se/Pages/List____354067.aspxNow companies and private individuals have access to Statistics Sweden’s statistics, which can be used for new products and services. This involves data from the Statistical Database that can be digita...

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Goal: Rules for Turing chess

April 22, 2013
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Goal:  Rules for Turing chess

Daniel Murell has more thoughts on Turing chess (last discussed here): When I played with my brother, we had it that if you managed to lap someone while running around the house, then you got an additional move. This means that if you had the option to take the king on your additional move, you [...]The post Goal: Rules for Turing chess appeared first on Statistical Modeling, Causal Inference, and…

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Statistics as inverse probability

April 22, 2013
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Statistics is sometimes described as inverse probability. In a typical probability problem, one starts by positing that a certain quantity has some given probability distribution, say the number of people entering a bank branch follows a Poisson distribution, and then goes on to compute probabilities such as the chance that more than 100 people (max capacity) require service at the same time. In a typical statistical problem, one observes the…

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Confusing Stats Terms Explained: Heteroscedasticity (Heteroskedasticity)

April 22, 2013
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Confusing Stats Terms Explained: Heteroscedasticity (Heteroskedasticity)

Heteroscedasticity is a hard word to pronounce, but it doesn't need to be a difficult concept to understand. Put simply, heteroscedasticity (also spelled heteroskedasticity) refers to the circumstance in which the variability of a variable is unequal across the range of values of a second variable that predicts it. A scatterplot of these variables will often create a cone-like shape, as the scatter (or variability) of the dependent variable (DV)…

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Confusing Stats Terms Explained: Heteroscedasticity (Heteroskedasticity)

April 22, 2013
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Confusing Stats Terms Explained: Heteroscedasticity (Heteroskedasticity)

Heteroscedasticity is a hard word to pronounce, but it doesn't need to be a difficult concept to understand. Put simply, heteroscedasticity (also spelled heteroskedasticity) refers to the circumstance in which the variability of a variable is unequal a...

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How to overlay custom curves with PROC SGPLOT

April 22, 2013
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How to overlay custom curves with PROC SGPLOT

I recently showed someone a trick to create a graph, and he was extremely pleased to learn it. The trick is well known to many SAS users, but I hope that this article will introduce it to even more SAS users. At issue is how to use the SGPLOT procedure [...]

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garch and the distribution of returns

April 22, 2013
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garch and the distribution of returns

Using garch to learn a little about the distribution of returns. Previously There are posts on garch — in particular: A practical introduction to garch modeling The components garch model in the rugarch package garch and long tails There has also been discussion of the distribution of returns, including a satire called “The distribution of … Continue reading →

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Meet @InfoVis_Ebooks, Your Source for Random InfoVis Paper Snippets

April 22, 2013
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Are you looking for inspiration while writing a paper or grant? Do you feel that there is a lack of information visualization content on Twitter? Is your timeline too empty and slow? Follow @InfoVis_Ebooks, a Twitter account that posts random pieces of text from infovis papers. Related Work Accounts that tweet more or less random snippets of text have become a genre in themselves. If you’ve spent any time on Twitter, you’ve…

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Nevins-Potti, Reinhart-Rogoff

April 22, 2013
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There's an interesting parallel between the Nevins-Potti debacle (a true debacle, in my mind) and the recent Reinhart-Rogoff kerfuffle. Both were exposed via some essentially small detail that had nothing to do with the real problem. In the case of … Continue reading →

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Is statistical enquiry a cycle?

April 21, 2013
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Is statistical enquiry a cycle?

What is the statistical enquiry cycle and why is it a cycle? Is it really a cycle? The New Zealand curriculum for Mathematics and statistics was recently held up as an example of good practice with regard to statistics. Yay … Continue reading →

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Neuroscience, statistical power and how to increase it

April 21, 2013
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Neuroscience, statistical power and how to increase it

There has been quite a bit of buzz recently about the Button et al. Nature Reviews Neuroscience paper on statistical power. Several similar reviews have been published in psychology and other disciplines and come to broadly the same conclusion - that m...

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More on Bayesian model selection in high-dimensional settings

April 21, 2013
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David Rossell writes: A friend pointed out that you were having an interesting philosophical discussion on my paper with Val Johnson [on Bayesian model selection in high-dimensional settings]. I agree with the view that in almost all practical situations the true model is not in the set under consideration. Still, asking a model choice procedure [...]The post More on Bayesian model selection in high-dimensional settings appeared first on Statistical Modeling,…

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Big Data, Open Data and Official Statistics

April 21, 2013
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Big Data, Open Data and Official Statistics

There are (at least) two big challenges official statistics will be faced with in the  next few years and which will possibly …Continue reading »

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Exponential increase in the number of stat majors

April 21, 2013
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Exponential increase in the number of stat majors

Joe Blitztein sent around the following graph: (The x-axis goes from 2000 to 2012 and the y=axis goes from 0 to 120.) 100 statistics majors (this combines sophomores, juniors, and seniors, but still, that’s a lot more than the 1 or 2 or 3 a year we’re used to seeing). At first I was like, [...]The post Exponential increase in the number of stat majors appeared first on Statistical Modeling,…

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Ordinal data, models with observers

April 21, 2013
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I recently made three posts regarding analysis of ordinal data. A post looking at all methods I could find in R, a post with an additional method and a post using JAGS. Common in all three was using the cheese data, a data set where...

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In three months, I’ll be in Vegas (trying to win against the house)

April 21, 2013
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In three months, I’ll be in Vegas (trying to win against the house)

In fact, I’m going there with my family and some friends, including two probabilists (I mean professionals, I am merely an amateur), with this incredible challenge: will I be able to convince  probabilists to go to play at the Casino? Actually, I also want to study them carefully, to understand how we should play optimally. For example, I hope I can make them play the roulette. Roulette is simple. With…

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My new forecasting book is finally finished

April 21, 2013
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My new forecasting book is finally finished

My new online forecasting book (written with George Athanasopoulos) is now completed. I previously described it on this blog nearly a year ago. In reality, an online book is never complete, and we plan to continually update it. But it is now at the poi...

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Metric driven Agile for Big Data

April 20, 2013
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Metric driven Agile for Big Data

Working in Bing Local Search brings together a number of interesting challenges. Firstly, we are in a moderately sized organization, which means that our org chart has some rough similarities to our high level system architecture. This means that we...

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A mess with which I am comfortable

April 20, 2013
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Having established that survey weighting is a mess, I should also acknowledge that, by this standard, regression modeling is also a mess, involving many arbitrary choices of variable selection, transformations and modeling of interaction. Nonetheless, regression modeling is a mess with which I am comfortable and, perhaps more relevant to the discussion, can be extended [...]The post A mess with which I am comfortable appeared first on Statistical Modeling, Causal…

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Displaying inferences from complex models

April 20, 2013
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David Williams writes: I am completing my doctoral dissertation dealing with modeling adverse birth outcomes. The models are complex with 9 risk factors, 5 area level variables and 4 individual level variables. I used hierarchical logistic regression (SAS glimmix) to analyze the data. I am now faced with reporting the results. Can you please recommend [...]The post Displaying inferences from complex models appeared first on Statistical Modeling, Causal Inference, and…

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