The New York Times has published some letters to the Editor in response to the piece by Clifton Leaf on clinical trials. You can also see our response here.

The New York Times has published some letters to the Editor in response to the piece by Clifton Leaf on clinical trials. You can also see our response here.

You still have until midnight Pacific Standard Time to enter the book quiz (link). The prize is a signed copy of Numbersense: How to use Big Data to Your Advantage. The sample pages (from Chapter 1) have been placed on Slideshare in case you don't like or can't read PDFs. *** Steroids are in the news again, with Tyson Gay, Asafa Powell, etc. testing positive recently. These are top names…

Update: you can find the next post in this series here. In a previous post, I looked at transcripts of Simpsons episodes and tried to figure out which character was speaking which line. This worked decently, but it wasn’t great. It gave us memorable scenes like this one: 1 2 3 4 5 6 Homer : D'oh! A deer! A female deer. Marge : Son, you're okay! Bart : Dad,…

I came across the link to the John Ehlers paper: Predictive Indicators for Effective Trading Strategies, while reading the Dekalog Blog. John Ehlers offers a different way to smooth prices and incorporate the new filter into the oscillator construction. Fortunately, the EasyLanguage code was also provided and i was able to translate it into R. […]

Update: you can find the next post in this series here. In a previous post, I looked at transcripts of Simpsons episodes and tried to figure out which character was speaking which line. This worked decently, but it wasn't great. It gave us memorable scenes like this one: Homer : D'oh! A deer! A female deer. Marge : Son, you're okay! Bart : Dad, I can't let you sell him.…

At first glance, that’s what I thought Tyler Cowen was asking. I assumed he was asking about the characters, not the audience, as watching a play seems like a pretty safe activity (A. Lincoln excepted). Characters in plays die all the time. I wonder what the chance is? Something between 5% and 10%, I’d guess. […]The post “How big is your chance of dying in an ordinary play?” appeared first…

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…

Mark Street writes: I teach a high school (grade 11) statistics class outside the USA and I am always looking for hands-on demonstrations. In fact, last week (the start of our school year here), I did the in-class exercise about “guessing ages of ten pictures” (p. 11-13) from your book “Teaching Statistics – A Bag […]The post Data to use for in-class sampling exercises? appeared first on Statistical Modeling, Causal…

Once you’ve seen one visualization book, you’ve seen them all. They tend to all look similar, use the same examples, and don’t provide much depth. Is it too easy to write a book when you can use such compelling images? I’m reading a visualization book right now, and I’m disappointed. I don’t even blame this particular book, they all kind of look the same: lots of images, many of them…

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 […]

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 […]

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...

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 →

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…

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…

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…

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,…

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 […]