Phil/Stat/Law: What Bayesian prior should a jury have? (Schachtman)

July 18, 2013
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Phil/Stat/Law: What Bayesian prior should a jury have? (Schachtman)

Nathan Schachtman, Esq., PC* emailed me the following interesting query a while ago: When I was working through some of the Bayesian in the law issues with my class, I raised the problem of priors of 0 and 1 being off “out of bounds” for a Bayesian analyst.  I didn’t realize then that the problem […]

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9th IMACS seminar on Monte Carlo Methods, Annecy

July 17, 2013
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9th IMACS seminar on Monte Carlo Methods, Annecy

As astute ‘Og’s readers may have gathered (!), I am now in Annecy, Savoie, for the 9th IMACS seminar on Monte Carlo Methods. Where I was kindly invited to give a talk on ABC. IMACS stands for “International Association for Mathematics and Computers in Simulation” and the conference gathers themes and sensibilities I am not […]

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Interview

July 17, 2013
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Apparently, while at the next JSM in Montreal (in which I'll present some work on the RDD project $-$ of course, the talk is still far from being written, but scheduled for next week), I'll give a video interview to promote the book. The brilliant...

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Figuring out which Simpsons character is speaking

July 17, 2013
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Figuring out which Simpsons character is speaking

Update: you can find the next post in this series here. You probably have a favorite Simpsons character. Maybe you hope to someday block out the sun, Mr. Burns style, maybe you enjoy Homer’s skill in averting meltdowns, or maybe you identify wi...

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Name 5 statisticians, now name 5 young statisticians

July 17, 2013
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I have been thinking for a while how hard it is to find statisticians to interview for the blog. When I started the interview series, it was targeted at interviewing statisticians at the early stages of their careers. It is … Continue reading →

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“Stop and frisk” statistics

July 17, 2013
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“Stop and frisk” statistics

Washington Post columnist Richard Cohen brings up one of my research topics: In New York City, blacks make up a quarter of the population, yet they represent 78 percent of all shooting suspects — almost all of them young men. We know them from the nightly news. Those statistics represent the justification for New York […]The post “Stop and frisk” statistics appeared first on Statistical Modeling, Causal Inference, and Social…

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Causal thinking

July 17, 2013
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Andrew Gelman, Columbia professor, wrote an important post about causal thinking (link) that I highly recommend reading. While he approaches the topic from a researcher's perspective, his framing of the issue is very practical, as I will demonstrate in this post. Gelman's main point is the two modes of causal thinking: Forward causality is asking the question, if we change X, how does that change Y? This is typically answered…

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Figuring out which Simpsons character is speaking

July 17, 2013
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Figuring out which Simpsons character is speaking

Update: you can find the next post in this series here. You probably have a favorite Simpsons character. Maybe you hope to someday block out the sun, Mr. Burns style, maybe you enjoy Homer's skill in averting meltdowns, or maybe you identify with Lisa's struggles for acceptance. Through its characters, the Simpsons made a huge impact on a generation, and although the show is still running, my best memories will…

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A simple implementation of two-dimensional binning

July 17, 2013
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A simple implementation of two-dimensional binning

In a previous article I discussed how to bin univariate observations by using the BIN function, which was added to the SAS/IML language in SAS/IML 9.3. You can generalize that example and bin bivariate or multivariate data. Over two years ago I wrote a blog post on 2D binning in [...]

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A poll that throws away data???

July 17, 2013
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Mark Blumenthal writes: What do you think about the “random rejection” method used by PPP that was attacked at some length today by a Republican pollster. Our just published post on the debate includes all the details as I know them. The Storify of Martino’s tweets has some additional data tables linked to toward the […]The post A poll that throws away data??? appeared first on Statistical Modeling, Causal Inference,…

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The ANOVA madness has to stop (rant)

July 16, 2013
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The ANOVA madness has to stop (rant)

Imagine a world in which people are taught that there’s two kinds of counting: there’s potato-counting, and there’s counting other stuff (beans, points, cards, etc.) Potatoes are special, so that potato-counting gets its own courses, under the name “Kartoffelanalysis”. When you take a Kartoffelanalysis 101 course, nobody mentions that you could use the same techniques […]

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Priors

July 16, 2013
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Nick Firoozye writes: While I am absolutely sympathetic to the Bayesian agenda I am often troubled by the requirement of having priors. We must have priors on the parameter of an infinite number of model we have never seen before and I find this troubling. There is a similarly troubling problem in economics of utility […]The post Priors appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Light entertainment: a ribbon chart

July 16, 2013
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Light entertainment: a ribbon chart

A reader sent in this amusement. See if you can figure out the chart: The article is here. It then goes into a lot of numbers about 200 accidents. I didn't pay much attention after that first paragraph, where it...

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No data on the need to bring data

July 16, 2013
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The preface to Elements of Statistical Learning opens with the popular quote In God we trust, all others bring data. — William Edwards Deming The footnote to the quote is better than the quote: On the Web, this quote has been widely attributed to both Deming and Robert W. Hayden; however Professor Hayden told us […]

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Quick review: R in Insurance Conference

July 16, 2013
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Quick review: R in Insurance Conference

Yesterday the first R in Insurance conference took place at Cass Business School in London. I think the event went really well, but as a member of the organising committee my view is probably skewed. Still, we had a variety of talks, a full house, a gr...

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Getting Started with Reproducible Research: A chapter from my new book

July 15, 2013
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Getting Started with Reproducible Research: A chapter from my new book

This is an abridged excerpt from Chapter 2 of my new book Reproducible Research with R and RStudio. It's published by Chapman & Hall/CRC Press. You can purchase it on Amazon. "Search inside this book" includes a complete table of contents. Researc...

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How to Consume Big Data

July 15, 2013
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How to Consume Big Data

Over at the McGraw-Hill blog, I wrote about how to consume Big Data (link), which is the core theme of my new book. In that piece, I highlight two recent instances in which bloggers demonstrated numbersense in vetting other people's data analyses. (Since the McGraw-Hill link is not working as I'm writing this, I placed a copy of the post here in case you need it.) Below is a detailed…

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How to Consume Big Data (from McGraw-Hill blog)

July 15, 2013
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When you hear about Big Data, you almost always hear about the supply side: Behold the data in un-pronounceable units of bytes! Admire the new science inspired by all the data! Missing from this narrative is the consumption side. A direct consequence of Big Data will be the explosion of data analyses—there will be more people producing more data analyses more quickly. This will be a world of confusing and…

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Find the determinant of a matrix

July 15, 2013
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Find the determinant of a matrix

The determinant of a matrix is a number associated with a square (nxn) matrix. The determinant can tell us if columns are linearly correlated, if a system has any nonzero solutions, and if a matrix is invertible. See the wikipedia entry for more details on this. Computing a determinant is key to a lot of linear algebra, and by extension, to a lot of machine learning. It is easy to…

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Find the determinant of a matrix

July 15, 2013
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Find the determinant of a matrix

The determinant of a matrix is a number associated with a square (nxn) matrix. The determinant can tell us if columns are linearly correlated, if a system has any nonzero solutions, and if a matrix is invertible. See the wikipedia entry for more details on this. Computing a determinant is key to a lot of linear algebra, and by extension, to a lot of machine learning. It is easy to…

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Yes, Clinical Trials Work

July 15, 2013
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This saturday the New York Times published an opinion pieces wondering "do clinical trials work?". The answer, of course, is: absolutely. For those that don't know the history, randomized control trials (RCTs) are one of the reasons why life spans skyrocketed … Continue reading →

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Forward causal reasoning statements are about estimation; reverse causal questions are about model checking and hypothesis generation

July 15, 2013
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Forward causal reasoning statements are about estimation; reverse causal questions are about model checking and hypothesis generation

Consider two broad classes of inferential questions: 1. Forward causal inference. What might happen if we do X? What are the effects of smoking on health, the effects of schooling on knowledge, the effect of campaigns on election outcomes, and so forth? 2. Reverse causal inference. What causes Y? Why do more attractive people earn […]The post Forward causal reasoning statements are about estimation; reverse causal questions are about model…

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Wasserman on noninformative priors

July 15, 2013
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Wasserman on noninformative priors

Larry Wasserman calls the use of noninformative priors a “lost cause.” I agree for the reasons he stated, and the fact that there are always better alternatives anyway. At the very least, there are the heavy-tailed “weakly informative priors” t...

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