Calorie labeling reduces obesity Obesity increased more slowly in California, Seattle, Portland (Oregon), and NYC, compared to some other places in the west coast and northeast that didn’t have calorie labeling

August 16, 2016
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Calorie labeling reduces obesity Obesity increased more slowly in California, Seattle, Portland (Oregon), and NYC, compared to some other places in the west coast and northeast that didn’t have calorie labeling

Ted Kyle writes: I wonder if you might have some perspective to offer on this analysis by Partha Deb and Carmen Vargas regarding restaurant calorie counts. [Thin columnist] Cass Sunstein says it proves “that calorie labels have had a large and beneficial effect on those who most need them.” I wonder about the impact of […] The post Calorie labeling reduces obesity Obesity increased more slowly in California, Seattle, Portland…

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Probably the most useful R function I’ve ever written

August 15, 2016
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The function in question is scriptSearch. I’m not much for superlatives — “most” and “best” imply one dimension, but we live in a multi-dimensional world. I’m making an exception. The statistic I have in mind for this use of “useful” is the waiting time between calls to the function divided by the human time saved […] The post Probably the most useful R function I’ve ever written appeared first on…

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The history of characterizing groups of people by their averages

August 15, 2016
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Andrea Panizza writes: I stumbled across this article on the End of Average. I didn’t know about Todd Rose, thus I had a look at his Wikipedia entry: Rose is a leading figure in the science of individual, an interdisciplinary field that draws upon new scientific and mathematical findings that demonstrate that it is not […] The post The history of characterizing groups of people by their averages appeared first…

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Tax Day: The Birthday Dog That Didn’t Bark

August 15, 2016
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Tax Day:  The Birthday Dog That Didn’t Bark

Following up on Valentine’s Day and April Fools, a journalist was asking about April 15: Are there fewer babies born on Tax Day than on neighboring days? Let’s go to the data: These are data from 1968-1988 so it would certainly be interesting to see new data, but here’s what we got: – April 1st […] The post Tax Day: The Birthday Dog That Didn’t Bark appeared first on Statistical…

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On deck this week

August 15, 2016
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Mon: The history of characterizing groups of people by their averages Tues: Calorie labeling reduces obesity Obesity increased more slowly in California, Seattle, Portland (Oregon), and NYC, compared to some other places in the west coast and northeast that didn’t have calorie labeling Wed: What’s gonna happen in November? Thurs: An ethnographic study of the […] The post On deck this week appeared first on Statistical Modeling, Causal Inference, and…

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Counting the Olympic medals

August 15, 2016
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Counting the Olympic medals

Reader Conor H. sent in this daily medals table at the NBC website: He commented that the bars are not quite the right lengths. So even though China and Russia both won five total medals that day, the bar for...

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More on Nonlinear Forecasting Over the Cycle

August 15, 2016
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Related to my last post, here's a new paper that just arrived from Rachidi Kotchoni and Dalibor Stevanovic, "Forecasting U.S. Recessions and Economic Activity". It's not non-parametric, but it is non-linear. As Dalibor put it, "The method is very simpl...

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Formats for p-values and odds ratios in SAS

August 15, 2016
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Formats for p-values and odds ratios in SAS

Last week I showed some features of SAS formats, including the fact that you can use formats to bin a continuous variable without creating a new variable in the DATA step. During the discussion I mentioned that it can be confusing to look at the output of a formatted variable […] The post Formats for p-values and odds ratios in SAS appeared first on The DO Loop.

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The Repetitive and Boring History of Visualization

August 15, 2016
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The Repetitive and Boring History of Visualization

When people talk about the history of data visualization, the same set of names always comes up: Playfair, Nightingale, Snow, Minard. They are historically important, alright, but why do they overshadow all the other work that was done? And what do we know about how important they actually were? The Usual Suspects They’re like old … Continue reading The Repetitive and Boring History of Visualization

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Nearest-Neighbor Forecasting in Times of Crisis

August 14, 2016
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Nonparametric K-nearest-neighbor forecasting remains natural and obvious and potentially very useful, as it has been since its inception long ago. [Most crudely: Find the K-history closest to the present K-history, see what followed it, and use that a...

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Modeling correlation of issue attitudes and partisanship within states

August 14, 2016
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John Kuk writes: I have taught myself multilevel modeling using your book and read your work with Delia Baldassarri about partisanship and issue alignment. I have a question about related to these two works. I want to find the level of correlation between partisanship and issues at the state level. Your work with Professor Baldassarri […] The post Modeling correlation of issue attitudes and partisanship within states appeared first on…

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Deep Learning in R

August 14, 2016
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Deep Learning in R

Deep learning has a wide range of applications, from speech recognition, computer vision, to self-driving cars and mastering the game of Go. While the concept is intuitive, the implementation is often tedious and heuristic. We will take a stab at sim...

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Science reporters are getting the picture

August 13, 2016
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Enrico Schaar points me to two news articles: What psychology’s crisis means for the future of science by Brian Resnick and These doctors want to fix a huge problem with drug trials. Why isn’t anyone listening? by Julia Belluz. I don’t really have anything to add here beyond what I’ve blogged on these topics before. […] The post Science reporters are getting the picture appeared first on Statistical Modeling, Causal…

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Will youths who swill Red Bull become adult cocaine addicts?

August 12, 2016
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Will youths who swill Red Bull become adult cocaine addicts?

The above is the question asked to me by Michael Stutzer, who writes: I have attached an increasingly influential paper [“Effects of Adolescent Caffeine Consumption on Cocaine Sensitivity,” by Casey O’Neill, Sophia Levis, Drew Schreiner, Jose Amat, Steven Maier, and Ryan Bachtell] purporting to show the effects of caffeine use in adolescents (well, lab rats […] The post Will youths who swill Red Bull become adult cocaine addicts? appeared first…

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A little story of the Folk Theorem of Statistical Computing

August 12, 2016
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I know I promised I wouldn’t blog, but this one is so clean and simple. And I already wrote it for the stan-users list anyway so it’s almost no effort to post it here too: A colleague and I were working on a data analysis problem, had a very simple overdispersed Poisson regression with a […] The post A little story of the Folk Theorem of Statistical Computing appeared first…

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NBA in NYC

August 11, 2016
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NBA in NYC

Jason Rosenfeld writes: We’re holding the first ever NBA Basketball Analytics Hackathon on Saturday, September 24 at Terminal 23 in midtown Manhattan. I can’t guarantee that Bugs will be there, but ya never know! The post NBA in NYC appear...

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Install Theano under Anaconda3 Python 3.5

August 11, 2016
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Install Theano under Anaconda3 Python 3.5

As of writing, Deep Learning package Theano can't be installed under Python 3.5, which causes some problems with my project. ruslanagit provided a viable solution that works for me under Windows 10.For convenience, I copied his solution below:Well, the...

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Various ways of showing distributions 2

August 11, 2016
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Various ways of showing distributions 2

In a comment to the previous post, Evan pointed to this Washington Post graphic: (link to article) This chart doesn't render properly in Firefox, nor in Safari. But we can see the designer's intention. It has an added dimension of...

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Are stereotypes statistically accurate?

August 11, 2016
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Apparently there’s a debate in psychology about the accuracy of stereotypes. Lin Bian and Andrei Cimpian write: In his book Social Perception and Social Reality, Lee Jussim suggests that people’s beliefs about various groups (i.e., their stereotypes) are largely accurate. We unpack this claim using the distinction between generic and statistical beliefs—a distinction supported by […] The post Are stereotypes statistically accurate? appeared first on Statistical Modeling, Causal Inference, and…

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Know your data 19: don’t tell me you are 2 blocks away when you are 20 blocks away

August 11, 2016
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Well, it didn't take long but private investigators have found the next big thing: Big Data. Bloomberg reported on a company called IDI, who sells our data to private investigators. (link) Unfortunately, this article is short on details and long on sensationalized catchphrases ("Every move you make. Every click you take...") The CEO of IDI boasted that "We have data on that 21-year-old who’s living at home with mom and…

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George Orwell on the Olympics

August 11, 2016
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George Orwell on the Olympics

From 1945: If you wanted to add to the vast fund of ill-will existing in the world at this moment, you could hardly do it better than by a series of football matches between Jews and Arabs, Germans and Czechs, Indians and British, Russians and Poles, and Italians and Jugoslavs, each match to be watched […] The post George Orwell on the Olympics appeared first on Statistical Modeling, Causal Inference,…

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Add Table of Contents to your Jupyter Notebook

August 10, 2016
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Add Table of Contents to your Jupyter Notebook

Jupyter notebook does not support Table Of Contents (ToC) out of box, unlike R Markdown. There are nbextensions that ppl made to support this. It is easy to add this capability, following these steps to add Table of Contents to your notebook: 1. F...

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Link: Our World in Data

August 10, 2016
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Link: Our World in Data

Our World in Data looks at a wide variety of data about the world: health, population, energy, growth, inequality, etc. Max Roser and his colleagues dig through the vast amounts of open data to find many interesting connections and insights. As an example, this recent posting on healthcare spending vs. life expectancy uses a connected scatterplot to show … Continue reading Link: Our World in Data

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