Posts Tagged ‘ Miscellaneous Statistics ’

The birthday problem

August 10, 2013
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The birthday problem

A friend with a baby who was born a couple weeks late commented that he would’ve liked a website that gave an estimated due date that was something more accurate than the usual “last menstrual period + 40 weeks.” I did a quick google and found this and this. Based on their descriptions of what […]The post The birthday problem appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Statistical significance and the dangerous lure of certainty

August 8, 2013
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In a discussion of some of the recent controversy over promiscuously statistically-significant science, Jeff Leek Rafael Irizarry points out there is a tradeoff between stringency and discovery and suggests that raising the bar of statistical significance (for example, to the .01 or .001 level instead of the conventional .05) will reduce the noise level but […]The post Statistical significance and the dangerous lure of certainty appeared first on Statistical Modeling,…

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Evidence on the impact of sustained use of polynomial regression on causal inference (a claim that coal heating is reducing lifespan by 5 years for half a billion people)

August 5, 2013
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Evidence on the impact of sustained use of polynomial regression on causal inference (a claim that coal heating is reducing lifespan by 5 years for half a billion people)

Yu Xie thought I’d have something to say about this recent paper, “Evidence on the impact of sustained exposure to air pollution on life expectancy from China’s Huai River policy,” by Yuyu Chen, Avraham Ebenstein, Michael Greenstone, and Hongbin Li, which begins: This paper’s findings suggest that an arbitrary Chinese policy that greatly increases total […]The post Evidence on the impact of sustained use of polynomial regression on causal inference…

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What are the key assumptions of linear regression?

August 4, 2013
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Andy Cooper writes: A link to an article, “Four Assumptions Of Multiple Regression That Researchers Should Always Test”, has been making the rounds on Twitter. Their first rule is “Variables are Normally distributed.” And they seem to be talking about the independent variables – but then later bring in tests on the residuals (while admitting […]The post What are the key assumptions of linear regression? appeared first on Statistical Modeling,…

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Response by Jessica Tracy and Alec Beall to my critique of the methods in their paper, “Women Are More Likely to Wear Red or Pink at Peak Fertility”

July 31, 2013
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Last week I published in Slate a critique of a paper that appeared in the journal Psychological Science. That paper, by Alec Beall and Jessica Tracy, found that women who were at peak fertility were three times more likely to wear red or pink shirts, compared to women at other points in their menstrual cycles. […]The post Response by Jessica Tracy and Alec Beall to my critique of the methods…

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Top 5 stat papers since 2000?

July 22, 2013
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Jeff Leek writes: I just wrote this post about what the 5 most influential papers in statistics from 2000-2010. I would be really curious to know your list too? Scarily enough I can’t think of any truly influential papers from that decade. I suppose this means I’m getting old! P.S. I did once make a […]The post Top 5 stat papers since 2000? appeared first on Statistical Modeling, Causal Inference,…

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My talks that were scheduled for Tues at the Data Skeptics meetup and Wed at the Open Statistical Programming meetup

July 22, 2013
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Statistical Methods and Data Skepticism Data analysis today is dominated by three paradigms: null hypothesis significance testing, Bayesian inference, and exploratory data analysis. There is concern that all these methods lead to overconfidence on the part of researchers and the general public, and this concern has led to the new “data skepticism” movement. But the […]The post My talks that were scheduled for Tues at the Data Skeptics meetup and…

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You’ll get a high Type S error rate if you use classical statistical methods to analyze data from underpowered studies

July 18, 2013
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Brendan Nyhan sends me this article from the research-methods all-star team of Katherine Button, John Ioannidis, Claire Mokrysz, Brian Nosek, Jonathan Flint, Emma Robinson, and Marcus Munafo: A study with low statistical power has a reduced chance of detecting a true effect, but it is less well appreciated that low power also reduces the likelihood […]The post You’ll get a high Type S error rate if you use classical statistical…

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“Frontiers in Massive Data Analysis”

July 10, 2013
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Mike Jordan sends along this National Academies report on “big data.” This is not a research report but it could be interesting in that it conveys what are believed to be important technical challenges. The post “Frontiers in Massive...

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How to think about a Psychological Science paper that seems iffy but is not obviously flawed?

July 8, 2013
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How to think about a Psychological Science paper that seems iffy but is not obviously flawed?

So I open the email one day and see this: hi, Andrew – FYI, here’s another paper from the Annals of Small-N Correlational Studies, also known as Psychological Science: http://www.futurity.org/society-culture/can-bigger-desks-make-us-dishonest/ and http://www.huffingtonpost.com/2013/06/26/physical-environment-dishonesty-space-corrupt-behavior-study_n_3497126.html hope all is well! The research paper he was referring to is called “The Ergonomics of Dishonesty: The Effect of Incidental Posture on [...]The post How to think about a Psychological Science paper that seems iffy but is…

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