Pooling is relative to the model

February 13, 2016
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Ryan Raaum writes: I’m hoping you’ll be willing to shed some light on a question I have regarding “pooling” in modeling. In your book with Jennifer Hill, you lay out two ends of a spectrum for dealing with structured data: (1) “Complete pooling” – ignoring the groups and pooling everything together for an overall average […] The post Pooling is relative to the model appeared first on Statistical Modeling, Causal…

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The Simple Reason Sanders Is Winning

February 13, 2016
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The Simple Reason Sanders Is Winning

Sanders has way more backers across the United States (with the possible exception of the South). Hillary Clinton might be doing well at the polls. However, the shocking fact of polling is that only 8-9% of those asked to participate in polls combined ...

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Rubbing off, uncertainty, confidence, and Nate Silver

February 13, 2016
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Rubbing off, uncertainty, confidence, and Nate Silver

Nate Silver describes “How we’re forecasting the primaries” using confidence intervals. Never mind that the estimates are a few weeks old, and put entirely to one side any predictions he makes or will make. I’m only interested in this one interpretive portion of the method, as Silver describes it: In our interactive, you’ll see a bunch of funky-looking curves […]

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Voting and vaccinating

February 13, 2016
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Some people think it isn’t rational to vote. Usually the argument is as follows: the probability of being pivotal, that is: the probability that your vote will ‘decide’...

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Not So Standard Deviations Episode 9 – Spreadsheet Drama

February 12, 2016
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For this episode, special guest Jenny Bryan (@jennybryan) joins us from the University of British Columbia! Jenny, Hilary, and I talk about spreadsheets and why some people love them and some people despise them. We also discuss blogging as part of scientific discourse. Subscribe to the podcast on iTunes. Show notes: Jenny's Stat 545 Coding

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“Priming Effects Replicate Just Fine, Thanks”

February 12, 2016
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“Priming Effects Replicate Just Fine, Thanks”

I came across this 2012 post by John Bargh who does not seem to be happy about the failures of direct replications of his much-cited elderly-words-and-slow-walking study. What strikes me about Bargh’s comments is how they illustrate the moving-target approach to much of science. Here’s the quick story. In 1996, Bargh, Chen, and Burrows published […] The post “Priming Effects Replicate Just Fine, Thanks” appeared first on Statistical Modeling, Causal…

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new version of abcrf

February 12, 2016
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new version of abcrf

Version 1.1 of our R library abcrf version 1.1  is now available on CRAN.  Improvements against the earlier version are numerous and substantial. In particular,  calculations of the random forests have been parallelised and, for machines with multiple cores, the computing gain can be enormous. (The package does along with the random forest model choice […]

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Improving on Chebyshev’s inequality

February 12, 2016
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Improving on Chebyshev’s inequality

Chebyshev’s inequality says that the probability of a random variable being more than k standard deviations away from its mean is less than 1/k2. In symbols, This inequality is very general, but also very weak. It assumes very little about the random variable X but it also gives a loose bound. If we assume slightly more, […]

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Not So Standard Deviations Episode 9 – Spreadsheet Drama

February 12, 2016
By

For this episode, special guest Jenny Bryan (@jennybryan) joins us from the University of British Columbia! Jenny, Hilary, and I talk about spreadsheets and why some people love them and some people despise them. We also discuss blogging as part of sci...

Read more »

Not So Standard Deviations Episode 9 – Spreadsheet Drama

February 12, 2016
By

For this episode, special guest Jenny Bryan (@jennybryan) joins us from the University of British Columbia! Jenny, Hilary, and I talk about spreadsheets and why some people love them and some people despise them. We also discuss blogging as part of sci...

Read more »

Arrow’s Theorem in the news: Sleazy-ass political scientists cut-and-paste their way to 3 publications from the same material

February 12, 2016
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Arrow’s Theorem in the news:  Sleazy-ass political scientists cut-and-paste their way to 3 publications from the same material

I’m posting this one in the evening because I know some people just hate when I write about plagiarism. But this one is so ridiculous I had to share it with you. John Smith (or maybe I should say “John Smith”?) writes: Today on a political science forum I saw this information about plagiarism by […] The post Arrow’s Theorem in the news: Sleazy-ass political scientists cut-and-paste their way to…

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Everything Ends on Wednesday

February 12, 2016
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Everything Ends on Wednesday

The Brazilian Carnival just ended this week, but for some people it is time to starting worry about crazy things that may have happened over the days of the flesh festival. Watching the news, the spokesperson of the Test and Prevention Center (CTA) in Brasilia estimated that the number of people seeking counseling and test kits increases on average 40% the day after the carnival (Wednesday). He also disclosed that…

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The answer is e, what was the question?!

February 11, 2016
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The answer is e, what was the question?!

A rather exotic question on X validated: since π can be approximated by random sampling over a unit square, is there an equivalent for approximating e? This is an interesting question, as, indeed, why not focus on e rather than π after all?! But very quickly the very artificiality of the problem comes back to […]

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The aviator

February 11, 2016
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The aviator

To continue with the weirdest week in terms of emails, I have received one today that says: Dear Dr. Baio,I represent XXX (an imprint of YYY).  We are looking to publish books in aviation that are scientific, academic or professional in natur...

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New R Code for High-Frequency Financial Data Analysis

February 11, 2016
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I looked through the manual (below). Looks well done.From the email:Package features estimators for working with high frequency market data.Microstructure Noise:- Autocovariance Noise Variance- Realized Noise Variance- Unbiased Realized Noise Variance...

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Trends and Opportunities in Data Analysis

February 11, 2016
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Trends and Opportunities in Data Analysis

Andy Warhol said “In the future, everyone will be world-famous for 15 minutes.” Here’s my 15 seconds of fame, a soundbite from the IBM Insight conference last year. My comments start at 1:30. In a nutshell, I predict that data analyt...

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In general, hypothesis testing is overrated and hypothesis generation is underrated, so it’s fine for these data to be collected with exploration in mind.

February 11, 2016
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In preparation for writing this news article, Kelly Servick asked me what I thought about the Kavli HUMAN Project (see here and here). Here’s what I wrote: The general idea of gathering comprehensive data seems reasonable to me. I’ve often made the point that careful data collection and measurement are important. Data analysis is the […] The post In general, hypothesis testing is overrated and hypothesis generation is underrated, so…

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A follow-up to Crowdsourcing Research

February 11, 2016
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A follow-up to Crowdsourcing Research

Last month I published some thoughts on crowdsourcing research, inspired by Anthony Goldbloom’s talk at Statistical Programming DC on the Kaggle experience. Today, I found a rather similar discussion  on crowdsourcing research (on the online version of the magazine Good) as a potential way to increase the accuracy of scientific research and reducing bias. I think more consideration needs to […]

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Data handcuffs

February 10, 2016
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A few years ago, if you asked me what the top skills I got asked about for students going into industry, I'd definitely have said things like data cleaning, data transformation, database pulls, and other non-traditional statistical tasks. But as companies have progressed from the point of storing data to actually wanting to do something with

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La guerre des étoiles : distinguer le signal du bruit

February 10, 2016
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La guerre des étoiles : distinguer le signal du bruit

La grande difficulté dans la modélisation et la construction de modèles prédictifs est de réussir à distinguer le signal et le bruit (pour reprendre le titre du classique de Nate Silver). La réponse statistique est la notion de significativité, et la recherche des ‘étoiles’ dans les sorties de régression. Avec l’explosion du nombre de données, il est devenu crucial de faire cette distinction, de savoir quelles sont les interactions qui…

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Scientific explanation of Panther defeat!

February 10, 2016
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Scientific explanation of Panther defeat!

Roy’s comment on our recent post inspires me to reveal the true explanation underlying the Carolina team’s shocking Super Bowl loss. The Panthers were primed during the previous week with elderly-themed words such as “bingo” and “Manning.” As well-established research has demonstrated, this caused Cam and the gang to move more slowly, hence all the […] The post Scientific explanation of Panther defeat! appeared first on Statistical Modeling, Causal Inference,…

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More on Policy Uncertainty

February 10, 2016
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Speaking of policy uncertainty (earlier blog post here), read here about the exciting ongoing project at the Becker-Friedman Institute of the University of Chicago.

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Who do you think I am?

February 10, 2016
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Who do you think I am?

Today I've received an email inviting me to submit a paper to a scientific journal (it doesn't really matter what journal it is, or whether or not my own work is actually relevant for them). I looove the way they've addressed to me, though. I think tha...

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