Forecasting and "As-If" Discounting

March 21, 2017
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Check out the fascinating and creative new paper, "Myopia and Discounting", by Xavier Gabaix and David Laibson. From their abstract (slightly edited):We assume that perfectly patient agents estimate the value of future events by generating noisy, unbia...

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Some natural solutions to the p-value communication problem—and why they won’t work

March 21, 2017
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Blake McShane and David Gal recently wrote two articles (“Blinding us to the obvious? The effect of statistical training on the evaluation of evidence” and “Statistical significance and the dichotomization of evidence”) on the misunderstandings of p-values that are common even among supposed experts in statistics and applied social research. The key misconception has nothing […] The post Some natural solutions to the p-value communication problem—and why they won’t work…

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Your charts need the gift of purpose

March 21, 2017
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Your charts need the gift of purpose

Via Twitter, I received this chart: My readers are nailing it when it comes to finding charts that deserve close study. On Twitter, the conversation revolved around the inversion of the horizontal axis. Favorability is associated with positive numbers, and...

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Data validation with the assertr package

March 20, 2017
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Data validation with the assertr package

Version 2.0 of my data set validation package assertr hit CRAN just this weekend. It has some pretty great improvements over version 1. For those new to the package, what follows is a short and new introduction. For those who… Continue reading →

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Clarke’s Law: Any sufficiently crappy research is indistinguishable from fraud (Pizzagate edition)

March 20, 2017
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Clarke’s Law: Any sufficiently crappy research is indistinguishable from fraud (Pizzagate edition)

This recent Pizzagate post by Nick Brown reminds me of our discussion of Clarke’s Law last year. P.S. I watched a couple more episodes of Game of Thrones on the plane the other day. It was pretty good! And so I continue to think this watching GoT is more valuable than writing error-ridden papers such […] The post Clarke’s Law: Any sufficiently crappy research is indistinguishable from fraud (Pizzagate edition)…

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Discover information about SAS formats… programmatically

March 20, 2017
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Discover information about SAS formats… programmatically

SAS formats are very useful and can be used in a myriad of creative ways. For example, you can use formats to display decimal values as a fraction. However, SAS supports so many formats that it is difficult to remember details about the format syntax, such as the default field [...] The post Discover information about SAS formats... programmatically appeared first on The DO Loop.

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ML and Metrics VIII: The New Predictive Econometric Modeling

March 19, 2017
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[Click on "Machine Learning" at right for earlier "Machine Learning and Econometrics" posts.] We econometricians need -- and have always had -- cross section and time series ("micro econometrics" and "macro/financial econometrics"), causal estimation a...

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Practical Data Science with R: ACM SIGACT News Book Review and Discount!

March 19, 2017
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Practical Data Science with R: ACM SIGACT News Book Review and Discount!

Our book Practical Data Science with R has just been reviewed in Association for Computing Machinery Special Interest Group on Algorithms and Computation Theory (ACM SIGACT) News by Dr. Allan M. Miller (U.C. Berkeley)! The book is half off at Manning March 21st 2017 using the following code (please share/Tweet): Deal of the Day March … Continue reading Practical Data Science with R: ACM SIGACT News Book Review and Discount!

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Practical Data Science with R: ACM SIGACT News Book Review and Discount!

March 19, 2017
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Practical Data Science with R: ACM SIGACT News Book Review and Discount!

Our book Practical Data Science with R has just been reviewed in Association for Computing Machinery Special Interest Group on Algorithms and Computation Theory (ACM SIGACT) News by Dr. Allan M. Miller (U.C. Berkeley)! The book is half off at Manning form March 21st 2017 using the following code (please share/Tweet): Deal of the Day … Continue reading Practical Data Science with R: ACM SIGACT News Book Review and Discount!

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The Econometric Game, 2017

March 19, 2017
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The Econometric Game, 2017

This year's edition of The Econometric Game is scheduled to take place next month in Amsterdam.Specifically, between 5 and 7 April the University of Amsterdam will once again host visiting teams of econometrics students from around the world to compete...

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The U.S. Has Been At War 222 Out of 239 Years

March 19, 2017
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The U.S. Has Been At War 222 Out of 239 Years

This morning, I discovered an interesting statistic, America Has Been At War 93% of the Time – 222 Out of 239 Years – Since 1776,  i.e. the U.S. has only been at peace for less than 20 years total since its birth. I wanted to check, get a better understanding and look at other countries in the world. As always, we can try to extract information from wikipedia, since there are…

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Whassup, Pace investigators? You’re still hiding your data. C’mon dudes, loosen up. We’re getting chronic fatigue waiting for you already!

March 19, 2017
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Whassup, Pace investigators?  You’re still hiding your data.  C’mon dudes, loosen up.  We’re getting chronic fatigue waiting for you already!

James Coyne writes: For those of you who have not heard of the struggle for release of the data from the publicly funded PACE trial of adaptive pacing therapy, cognitive behaviour therapy, graded exercise therapy, and specialist medical care for chronic fatigue syndrome, you can access my [Coyne’s] initial call for release of the portion […] The post Whassup, Pace investigators? You’re still hiding your data. C’mon dudes, loosen up.…

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“Bias” and “variance” are two ways of looking at the same thing. (“Bias” is conditional, “variance” is unconditional.)

March 18, 2017
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Someone asked me about the distinction between bias and noise and I sent him some links. Then I thought this might interest some of you too, so here it is: Here’s a recent paper on election polling where we try to be explicit about what is bias and what is variance: And here are some […] The post “Bias” and “variance” are two ways of looking at the same thing.…

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“A blog post that can help an industry”

March 18, 2017
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Tim Bock writes: I understood how to address weights in statistical tests by reading Lu and Gelman (2003). Thanks. You may be disappointed to know that this knowledge allowed me to write software, which has been used to compute many billions of p-values. When I read your posts and papers on forking paths, I always […] The post “A blog post that can help an industry” appeared first on Statistical…

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Academic phishing

March 18, 2017
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Academic phishing

Invitations to write for bogus journals and speak at bogus conferences keep rolling in. Here is one I received today. Dear Dr. Rob J. Hyndman, It is our great pleasure to welcome you to join in Part 2: Knowledge Economy Symposium of GCKE-2017, which will be held in Qingdao, China during September 19-21, 2017. And […]

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Fatal Lady

March 17, 2017
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Eric Loken writes: I guess they needed to add some drama to Hermine’s progress. [background here] P.S. The above post was pretty short. I guess I should give you some more material. So here’s this, that someone sent me: You’ve written written about problems with regression discontinuity a number of times. This paper that just […] The post Fatal Lady appeared first on Statistical Modeling, Causal Inference, and Social Science.

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what does more efficient Monte Carlo mean?

March 16, 2017
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what does more efficient Monte Carlo mean?

“I was just thinking that there might be a magic trick to simulate directly from this distribution without having to go for less efficient methods.” In a simple question on X validated a few days ago [about simulating from x²φ(x)] popped up the remark that the person asking the question wanted a direct simulation method […]

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Dark Angel

March 16, 2017
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Dark Angel

Chris Kavanagh writes: I know you are all too frequently coming across defensive, special pleading-laced responses to failed replications so I thought I would just point out a recent a very admirable response from Will Gervais posted on his blog. He not only commends the replicators but acknowledges that the original finding was likely a […] The post Dark Angel appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Forrester’s 2017 Take on Tools for Data Science

March 16, 2017
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Forrester’s 2017 Take on Tools for Data Science

In my ongoing quest to track The Popularity of Data Science Software, I’ve updated the discussion of the annual report from Forrester, which I repeat here to save you from having to read through the entire document. If your organization … Continue reading →

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Ensemble Methods are Doomed to Fail in High Dimensions

March 15, 2017
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Ensemble Methods are Doomed to Fail in High Dimensions

Ensemble methods By ensemble methods, I (Bob, not Andrew) mean approaches that scatter points in parameter space and then make moves by inteprolating or extrapolating among subsets of them. Two prominent examples are: Ter Braak’s differential evolution   Goodman and Weare’s walkers There are extensions and computer implementations of these algorithms. For example, the Python […] The post Ensemble Methods are Doomed to Fail in High Dimensions appeared first on…

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There is no New Thing under the Sun – Yes and No

March 15, 2017
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There is no New Thing under the Sun – Yes and No

Twitter reminded me that there’s #NTTS2017 going on, Eurostat’s biennial scientific conference on New Techniques and Technologies for Statistics (NTTS). The opening session also focused on official statistics and its actual and future role in a world of data deluge and alt-facts. What will be Official Statistics in 30 years? In Diego Kuonen’s presentation and discussion on ‘Big … Continue reading There is no New Thing under the Sun – Yes and No

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New screencast: using R and RStudio to install and experiment with Apache Spark

March 15, 2017
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I have new short screencast up: using R and RStudio to install and experiment with Apache Spark. More material from my recent Strata workshop Modeling big data with R, sparklyr, and Apache Spark can be found here.

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Cage match: Null-hypothesis-significance-testing meets incrementalism. Nobody comes out alive.

March 15, 2017
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Cage match:  Null-hypothesis-significance-testing meets incrementalism.  Nobody comes out alive.

It goes like this. Null-hypothesis-significance-testing (NHST) only works when you have enough accuracy that you can confidently reject the null hypothesis. You get this accuracy from a large sample of measurements with low bias and low variance. But you also need a large effect size. Or, at least, a large effect size, compared to the […] The post Cage match: Null-hypothesis-significance-testing meets incrementalism. Nobody comes out alive. appeared first on…

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