Theoretical statistics is the theory of applied statistics: how to think about what we do (My talk at the University of Michigan this Friday 3pm)

February 7, 2017
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Theoretical statistics is the theory of applied statistics: how to think about what we do (My talk at the University of Michigan this Friday 3pm)

Theoretical statistics is the theory of applied statistics: how to think about what we do Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University Working scientists and engineers commonly feel that philosophy is a waste of time. But theoretical and philosophical principles can guide practice, so it makes sense for us to […] The post Theoretical statistics is the theory of applied statistics: how to think about…

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The Mannequin

February 7, 2017
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The Mannequin

Jonathan Falk points to this article, “Examining the impact of grape consumption on brain metabolism and cognitive function in patients with mild decline in cognition: A double-blinded placebo controlled pilot study,” and writes: Drink up! N=10, no effect on thing you’re aiming at, p value result on a few brain measurements (out of?), eminently pr-able […] The post The Mannequin appeared first on Statistical Modeling, Causal Inference, and Social Science.

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an accurate variance approximation

February 6, 2017
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an accurate variance approximation

In answering a simple question on X validated about producing Monte Carlo estimates of the variance of estimators of exp(-θ) in a Poisson model, I wanted to illustrate the accuracy of these estimates against the theoretical values. While one case was easy, since the estimator was a Binomial B(n,exp(-θ)) variate [in yellow on the graph], […]

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The “What does not kill my statistical significance makes it stronger” fallacy

February 6, 2017
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The “What does not kill my statistical significance makes it stronger” fallacy

As anyone who’s designed a study and gathered data can tell you, getting statistical significance is difficult. Lots of our best ideas don’t pan out, and even if a hypothesis seems to be supported by the data, the magic “p less than .05” can be elusive. And we also know that noisy data and small […] The post The “What does not kill my statistical significance makes it stronger” fallacy…

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What colors does PROC SGPLOT use for markers?

February 6, 2017
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What colors does PROC SGPLOT use for markers?

Suppose you create a scatter plot in SAS with PROC SGPLOT. What color does PROC SGPLOT use for the markers? If you specify the GROUP= option so that markers are colored by a grouping variable, what colors are used to represent the various groups? The following scatter plot shows the [...] The post What colors does PROC SGPLOT use for markers? appeared first on The DO Loop.

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Evolving R Tools and Practices

February 6, 2017
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Evolving R Tools and Practices

One of the distinctive features of the R platform is how explicit and user controllable everything is. This allows the style of use of R to evolve fairly rapidly. I will discuss this and end with some new notations, methods, and tools I am nominating for inclusion into your view of the evolving “current best … Continue reading Evolving R Tools and Practices

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Long Shot

February 5, 2017
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Frank Harrell doesn’t like p-values: In my [Frank’s] opinion, null hypothesis testing and p-values have done significant harm to science. The purpose of this note is to catalog the many problems caused by p-values. As readers post new problems in their comments, more will be incorporated into the list, so this is a work in […] The post Long Shot appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Data for the People

February 5, 2017
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Data for the People, by Andreas Weigend, is coming out this week, or maybe it came out last week. Andreas is a leading technologist (at least that's the most accurate one-word description I can think of), and I have valued his insights ever since we we...

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Prédire ou Prévoir, réflexions (probablement) personnelles

February 5, 2017
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Prédire ou Prévoir, réflexions (probablement) personnelles

Il y a quelques années, j’avais fait un billet où je m’énervais contre une phrase que j’avais entendu (“l’homme qui avait prédit la crise“). Le point de départ était surtout un énervement lié au fait que beaucoup de journalistes vivent avec des oeillères (par exemple en associant “économiste” à “type à la télé qui parle d’économie“), et ne connaissent pas la diversité de la communauté des économistes (surtout que la…

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Research connects overpublication during national sporting events to science-journalism problems

February 5, 2017
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Research connects overpublication during national sporting events to science-journalism problems

Ivan Oransky pointed me to a delightful science-based press release, “One’s ability to make money develops before birth”: Researchers from the Higher School of Economics have shown how the level of perinatal testosterone, the sex hormone, impacts a person’s earnings in life. Prior research confirms that many skills and successes are linked to the widely […] The post Research connects overpublication during national sporting events to science-journalism problems appeared first…

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Going to Strata / Hadoop World 2017 San Jose?

February 4, 2017
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Are you attending or considering attending Strata / Hadoop World 2017 San Jose? Are you interested in learning to use R to work with Spark and h2o? Then please consider signing up for my 3 1/2 hour workshop soon. We are about half full now, but I really want to fill the room, while making … Continue reading Going to Strata / Hadoop World 2017 San Jose?

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Econometrics – Young Researcher Award

February 4, 2017
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Econometrics – Young Researcher Award

The journal, Econometrics, hasn't been around all that long, but it has published some great articles by some very prominent econometricians. And it's "open access" to readers, which is always good news.Today, I received an email with the fol...

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Death of the Party

February 4, 2017
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Death of the Party

Under the subject line, “Example of a classy response to someone pointing out an error,” Charles Jack​son writes: In their recent book, Mazur and Stein describe the discovery of an error that one of them had made in a recent paper writing: “Happily, Bartosz Naskreki spotted this error . . .” See below for full […] The post Death of the Party appeared first on Statistical Modeling, Causal Inference, and…

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February Reading

February 4, 2017
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February Reading

Here are some suggestions for your reading list this month:Aastveit, A., C. Foroni, and F. Ravazzolo, 2016. Density forecasts with midas models. Journal of Applied Econometrics, online.Chang, C-L. and M. McAleer, 2016.  The fiction of full BEKK. T...

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Pizzagate, or the curious incident of the researcher in response to to people pointing out 150 errors in four of his papers

February 3, 2017
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Pizzagate, or the curious incident of the researcher in response to to people pointing out 150 errors in four of his papers

There are a bunch of things about this story that just don’t make a lot of sense to me. For those who haven’t been following the blog recently, here’s the quick backstory: Brian Wansink is a Cornell University business school professor and self-described “world-renowned eating behavior expert for over 25 years.” It’s come out that […] The post Pizzagate, or the curious incident of the researcher in response to to…

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Pizzagate, or the curious incident of the researcher in response to people pointing out 150 errors in four of his papers

February 3, 2017
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Pizzagate, or the curious incident of the researcher in response to people pointing out 150 errors in four of his papers

There are a bunch of things about this story that just don’t make a lot of sense to me. For those who haven’t been following the blog recently, here’s the quick backstory: Brian Wansink is a Cornell University business school professor and self-described “world-renowned eating behavior expert for over 25 years.” It’s come out that […] The post Pizzagate, or the curious incident of the researcher in response to people…

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Deep thinking about your data

February 3, 2017
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Deep thinking about your data

In the on-going series of posts about the IMDB dataset, from Kaggle, I have so far looked at several of the scraped variables, including the number of faces on movie posters (1, 2), plot keywords (3), and movie rating by title year (4). In this post, I tackle the variables resulting from a data merge between IMDB and Facebook. These columns have names like "Director Facebook Likes", "Actor 1 Facebook…

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Forecasting practitioner talks at ISF 2017

February 2, 2017
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Forecasting practitioner talks at ISF 2017

The International Symposium on Forecasting is a little unusual for an academic conference in that it has always had a strong presence of forecasters working in business and industry as well as academic forecasters, mostly at universities. We value the ...

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Forecasting practitioner talks at ISF 2017

February 2, 2017
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Forecasting practitioner talks at ISF 2017

The International Symposium on Forecasting is a little unusual for an academic conference in that it has always had a strong presence of forecasters working in business and industry as well as academic forecasters, mostly at universities. We value the ...

Read more »

Forecasting practitioner talks at ISF 2017

February 2, 2017
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Forecasting practitioner talks at ISF 2017

The International Symposium on Forecasting is a little unusual for an academic conference in that it has always had a strong presence of forecasters working in business and industry as well as academic forecasters, mostly at universities. We value the combination and interaction as it helps the academics understand the sorts of problems facing forecasters […]

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a well-hidden E step

February 2, 2017
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a well-hidden E step

A recent question on X validated ended up being quite interesting! The model under consideration is made of parallel Markov chains on a finite state space, all with the same Markov transition matrix, M, which turns into a hidden Markov model when the only summary available is the number of chains in a given state […]

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a well-hidden E step

February 2, 2017
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a well-hidden E step

A recent question on X validated ended up being quite interesting! The model under consideration is made of parallel Markov chains on a finite state space, all with the same Markov transition matrix, M, which turns into a hidden Markov model when the only summary available is the number of chains in a given state […]

Read more »

Big data and the law

February 2, 2017
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Big data and the law

Excerpt from the new book Big Data of Complex Networks: Big Data and data protection law provide for a number of mutual conflicts: from the perspective of Big Data analytics, a strict application of data protection law as we know it today would set an immediate end to most Big Data applications. From the perspective of […]

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