Parametric Inference: The Power Function of the Test

May 1, 2015
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Parametric Inference: The Power Function of the Test

In Statistics, we model random phenomenon and make conclusions about its population. For example, in an experiment of determining the true heights of the students in the university. Suppose we take sample from the population of the students, and consid...

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96% Error in “Expert” Testimony Based on Probability of Hair Matches: It’s all Junk!

May 1, 2015
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96% Error in “Expert” Testimony Based on Probability of Hair Matches: It’s all Junk!

Imagine. The New York Times reported a few days ago that the FBI erroneously identified criminals 96% of the time based on probability assessments using forensic hair samples (up until 2000). Sometimes the hair wasn’t even human, it might have come from a dog, a cat or a fur coat!  I posted on  the unreliability of hair forensics a few […]

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Le Monde puzzle [#909]

April 30, 2015
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Le Monde puzzle [#909]

Another of those “drop-a-digit” Le Monde mathematical puzzle: Find all integers n with 3 or 4 digits, no exterior zero digit, and a single interior zero digit, such that removing that zero digit produces a divider of x. As in puzzle #904, I made use of the digin R function: and simply checked all integers […]

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Introduction to Applied Econometrics With R

April 30, 2015
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Introduction to Applied Econometrics With R

I came across a January post from David Smith at Revolution Analytics, in his Revolutions blog. It's titled, An Introduction to Applied Econometrics With R, and it refers to a very useful resource that's been put together by Bruno Rodrigues of the Univ...

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There are 6 ways to get rejected from PLOS: (1) theft, (2) sexual harassment, (3) running an experiment without a control group, (4) keeping a gambling addict away from the casino, (5) chapter 11 bankruptcy proceedings, and (6) having no male co-authors

April 30, 2015
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This story is pretty horrifying/funny. But the strangest thing was this part: [The author] and her colleague have appealed to the unnamed journal, which belongs to the PLoS family . . . I thought PLOS published just about everything! This is not a slam on PLOS. Arxiv publishes everything too, and Arxiv is great. The […] The post There are 6 ways to get rejected from PLOS: (1) theft, (2)…

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The hardest thing about teaching statistics

April 30, 2015
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The hardest thing about teaching statistics

(Note: this post should probably be titled "Quantitative Methods of Curricula Planning" but I thought the current title would draw more interest–though they would both lose out to "These Weird Approaches To Lesson Planning Will Leave You Speechless") Suppose you… Continue reading →

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Applied Econometrics – 4 Volume Set

April 30, 2015
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Applied Econometrics – 4 Volume Set

Back in 2012 I posted about a 4-volume set of readings, titled The Rise of Econometrics, edited by Duo Qin, and published by Taylor and Francis. That set appeared in January 2013.In response to a comment on that post, Bill Greene has recently...

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Figuring Out Learning Objectives the Hard Way

April 30, 2015
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When building the Genomic Data Science Specialization (which starts in June!) we had to figure out the learning objectives for each course. We initially set our ambitions high, but as you can see in this video below, Steven Salzberg brought us back to ...

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Good, mediocre, and bad p-values

April 30, 2015
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From my 2012 article in Epidemiology: In theory the p-value is a continuous measure of evidence, but in practice it is typically trichotomized approximately into strong evidence, weak evidence, and no evidence (these can also be labeled highly significant, marginally significant, and not statistically significant at conventional levels), with cutoffs roughly at p=0.01 and 0.10. […] The post Good, mediocre, and bad p-values appeared first on Statistical Modeling, Causal Inference,…

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Nice chart from the neck down

April 30, 2015
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Nice chart from the neck down

I was drawn to this Wall Street Journal chart because of the blue columns. The blue color solves a common problem in time-series plots when the time axis is incomplete. The first quarter of 2015 is dangling. The article is...

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Wakefield: Random Data Set (Part II)

April 30, 2015
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Wakefield: Random Data Set (Part II)

This post is part II of a series detailing the GitHub package, wakefield, for generating random data sets. The First Post (part I) was a test run to gauge user interest. I received positive feedback and some ideas for improvements, … Continue reading →

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Wakefield: Random Data Set (Part II)

April 30, 2015
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Wakefield: Random Data Set (Part II)

This post is part II of a series detailing the GitHub package, wakefield, for generating random data sets. The First Post (part I) was a test run to gauge user interest. I received positive feedback and some ideas for improvements, … Continue reading →

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Modeling the Latent Structure That Shapes Brand Learning

April 30, 2015
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Modeling the Latent Structure That Shapes Brand Learning

What is a brand? Metaphorically, the brand is the white sphere in the middle of this figure, that is, the ball surrounded by the radiating black cones. Of course, no ball has been drawn, just the conic thorns positioned so that we construct the sphere ...

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Volatility Institute 2015

April 30, 2015
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I'm baaaaaack...Speaking of being back, I'm just back from the Rob Engle / NYU Volatility Institute Annual Conference.  (Well, more or less just back.) Great people, great science, tightly-focused on a fascinating and timely area, the bond market ...

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the most patronizing start to an answer I have ever received

April 29, 2015
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the most patronizing start to an answer I have ever received

Another occurrence [out of many!] of a question on X validated where the originator (primitivus petitor) was trying to get an explanation without the proper background. On either Bayesian statistics or simulation. The introductory sentence to the question was about “trying to understand how the choice of priors affects a Bayesian model estimated using MCMC” […]

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Data analysis subcultures

April 29, 2015
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Roger and I responded to the controversy around the journal that banned p-values today in Nature. A piece like this requires a lot of information packed into very little space but I thought one idea that deserved to be talked about more was the idea of data analysis subcultures. From the paper: Data analysis is taught

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Video: The Danger of Glitziness

April 29, 2015
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Wayne Lytle created this video about the Viz-O-Matic that provides lots of tools to make visualization glitzier. It’s a nice little spoof, and a throwback to the computer graphics of the early 1990s (it was made for SIGGRAPH 1993). This video was brought up in a discussion about storytelling at CHI last week, though I … Continue reading Video: The Danger of Glitziness

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Carl Morris: Man Out of Time [reflections on empirical Bayes]

April 29, 2015
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I wrote the following for the occasion of his recent retirement party but I thought these thoughts might of general interest: When Carl Morris came to our department in 1989, I and my fellow students were so excited. We all took his class. The funny thing is, though, the late 1980s might well have been […] The post Carl Morris: Man Out of Time [reflections on empirical Bayes] appeared first…

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Create and use a permutation matrix in SAS

April 29, 2015
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Create and use a permutation matrix in SAS

Suppose that you compute the correlation matrix (call it R1) for a set of variables x1, x2, ..., x8. For some reason, you later want to compute the correlation matrix for the variables in a different order, maybe x2, x1, x7,..., x6. Do you need to go back to the […] The post Create and use a permutation matrix in SAS appeared first on The DO Loop.

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Informed priors for Bayesian comparison of two groups

April 29, 2015
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The BEST programs, for Bayesian estimation of two groups, were written with generic vague priors only minimally informed by the scale of the data. Here are new versions of the programs that are better suited for specifying informed priors.A little back...

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Videos for EViews 9

April 28, 2015
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Videos for EViews 9

The team at EViews has put together a great set of videos that highlight some of the new features in EViews 9.You can find them here, and I strongly recommend them.© 2015, David E. Giles

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What’s the most important thing in statistics that’s not in the textbooks?

April 28, 2015
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What’s the most important thing in statistics that’s not in the textbooks?

As I wrote a couple years ago: Statistics does not require randomness. The three essential elements of statistics are measurement, comparison, and variation. Randomness is one way to supply variation, and it’s one way to model variation, but it’s not necessary. Nor is it necessary to have “true” randomness (of the dice-throwing or urn-sampling variety) […] The post What’s the most important thing in statistics that’s not in the textbooks?…

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Reading between the gridlines

April 28, 2015
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Reading between the gridlines

Reader Jamie H. pointed me to the following chart in the Guardian (link), which originated from Spotify. This chart is likely inspired by the Arctic ice cover chart discussed here last year (link): Spotify calls its chart "the Coolness Spiral...

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