## Picking a (bio)statistics thesis topic for real world impact and transferable skills

April 22, 2014
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One of the things that was hardest for me in graduate school was starting to think about my own research projects and not just the ideas my advisor fed me. I remember that it was stressful because I didn't quite … Continue reading →

## Russ Altman’s Translational Bioinformatics Year in Review

April 22, 2014
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A few weeks ago the 2014 AMIA Translational Bioinformatics Meeting (TBI) was held in beautiful San Francisco.  This meeting is full of great science that spans the divide between molecular and clinical research, but a true highlight of this meetin...

## Examen, Séries Chronologiques

April 22, 2014
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Après les exposés des dernières séances, l’examen du cours MAT8181, Séries Chronologiques avait lieu ce matin (et devrait finir dans quelques minutes, avec un peu de temps supplémentaire pour certain, compte tenu de la panne de métro qu&#...

## Ticket to Baaaaarf

April 22, 2014
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A link from the comments here took me to the wonderfully named Barfblog and a report by Don Schaffner on some reporting. First, the background: A university in England issued a press release saying that “Food picked up just a few seconds after being dropped is less likely to contain bacteria than if it is […] The post Ticket to Baaaaarf appeared first on Statistical Modeling, Causal Inference, and Social…

## Stata-Bloggers revamped

April 22, 2014
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STATA-Bloggers has been out for a year and has gotten a bit of a facelift.  Still far fewer bloggers (9) than would be ideal to maintain an aggregator, but probably the best source for an aggregate feed on Stata news.  Please contact me if yo...

## Notes from the Tokyo R User Group meeting, 17 April 2014

April 22, 2014
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Last Thursday I had the pleasure to attend the Tokyo R user group meeting. And what a fun meeting it was! Over 40 R users had come together in central Tokyo. Yohei Sato, who organises the meetings, allowed me to talk a little about the recent developme...

## Seven forecasting blogs

April 22, 2014
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There are several other blogs on forecasting that readers might be interested in. Here are seven worth following: No Hesitations by Francis Diebold (Professor of Economics, University of Pennsylvania). Diebold needs no introduction to forecasters. He primarily covers forecasting in economics and finance, but also xkcd cartoons, graphics, research issues, etc. Econometrics Beat by Dave Giles. Dave is a professor of economics at the University of Victoria (Canada), formerly from my own…

## More On the Limitations of the Jarque-Bera Test

April 21, 2014
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Testing the validity of the assumption, that the errors in a regression model are normally distributed, is a standard pastime in econometrics. We use this assumption when we construct standard confidence intervals  for, or test hypotheses about, t...

## Ray Fair’s Model(s) in EViews

April 21, 2014
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Here's a follow-up to my recent post about the Federal Reserve U.S. macroeconometric model being freely available in EViews formatRay Fair's well-known model for the U.S. economy is also now available in a form that's ready to play with in EViews....

## Stan Model of the Week: Hierarchical Modeling of Supernovas

April 21, 2014
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$Stan Model of the Week: Hierarchical Modeling of Supernovas$

The Stan Model of the Week showcases research using Stan to push the limits of applied statistics.  If you have a model that you would like to submit for a future post then send us an email. Our inaugural post comes from Nathan Sanders, a graduate student finishing up his thesis on astrophysics at Harvard. […] The post Stan Model of the Week: Hierarchical Modeling of Supernovas appeared first on…

## RStata: Funny or just annoying?

April 21, 2014
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Okay okay.  The joke is up.  Besides likely necessitating an emergency call to from the Stata Management Team to the Stata Legal Team, my post on April 1st of 2014 entitled "RStata: Stata Fully Mapped into R", was intended as a practical joke...

## Ticket to Baaaath

April 21, 2014
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Ooooooh, I never ever thought I’d have a legitimate excuse to tell this story, and now I do! The story took place many years ago, but first I have to tell you what made me think of it: Rasmus Bååth posted the following comment last month: On airplane tickets a Swedish “å” is written as […] The post Ticket to Baaaath appeared first on Statistical Modeling, Causal Inference, and Social…

## On deck this week

April 21, 2014
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Mon: Ticket to Baaaath Tues: Ticket to Baaaaarf Wed: Thinking of doing a list experiment? Here’s a list of reasons why you should think again Thurs: An open site for researchers to post and share papers Fri: Questions about “Too Good to Be True” Sat: Sleazy sock puppet can’t stop spamming our discussion of compressed […] The post On deck this week appeared first on Statistical Modeling, Causal Inference, and…

## Inferring participation rates in service projects

April 21, 2014
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About a week ago I taught my tutorial, Bayesian Statistics Made Simple, at PyCon 2014 in Montreal.  My slides, the video, and all the code, are on this site.  The turnout was great.  We had a room full of enthusiastic Pythonistas who are...

## Habits are hard to shake off

April 21, 2014
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For those who don't use an iPhone, what you are staring at is the new keyboard. Is the SHIFT key on or off? For most of us who use the iPhone, we can't tell you either. It's been confusing and...

## On Kaggle Forecasting Competitions, Part 1: The Hold-Out Sample(s)

April 21, 2014
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Kaggle competitions are potentially pretty cool. Kaggle supplies in-sample data ("training data"), and you build a model and forecast out-of-sample data that they withhold ("test data"). The winner gets a significant prize, often \$100,000.00 or mo...

## Local functions (not!) in the SAS/IML language

April 21, 2014
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I have previously written about the scope of local and global variables in the SAS/IML language. You might wonder whether SAS/IML modules can also have local scope. The answer is no. All SAS/IML modules are known globally and can be called by any other modules. Some object-oriented programming languages support […]

## High incidence in Measles Data in Project Tycho

April 21, 2014
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In this third post on Measles data I want to have a look at some high incidence occasions. As described before, the data is from Project Tycho, which contains data from all weekly notifiable disease reports for the United States dating back to 18...

## Notes on evaluating predictions, or Background to my airfare predictor article

April 20, 2014
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My article on whether we can trust airfare prediction models is published today at FiveThirtyEight, the new data journalism venture launched by Nate Silver after he moved to ESPN. This topic was originally conceived as a chapter of Numbersense (link) but I dropped it. As I have noted in my review of Nate Silver's book, he has a keen interest in evaluating predictions, and not surprisingly, he encouraged me to…

## Fooled by randomness

April 20, 2014
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From 2006: Naseem Taleb‘s publisher sent me a copy of “Fooled by randomness: the hidden role of chance in life and the markets” to review. It’s an important topic, and the book is written in a charming style—I’ll try to respond in kind, with some miscellaneous comments. On the cover of the book is a […] The post Fooled by randomness appeared first on Statistical Modeling, Causal Inference, and Social…

## Getting Credit (or blame) for Something You Didn’t Do (BP oil spill)

April 20, 2014
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Four years ago, many of us were glued to the “spill cam” showing, in real time, the gushing oil from the April 20, 2010 explosion sinking the Deepwater Horizon oil rig in the Gulf of Mexico, killing 11, and spewing oil until July 15 (see video clip that was added below).Remember junk shots, top kill, blowout preventers? [1] The EPA has […]

## Monotonicity of EM Algorithm Proof

April 19, 2014
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Here the monotonicity of the EM algorithm is established. $$f_{o}(Y_{o}|\theta)=f_{o,m}(Y_{o},Y_{m}|\theta)/f_{m|o}(Y_{m}|Y_{o},\theta)$$ $$\log L_{o}(\theta)=\log L_{o,m}(\theta)-\log f_{m|o}(Y_{m}|Y_{o},\theta) \label{eq:loglikelihood}$$ where $$L_{o}(\theta)$$ is the likelihood under the observed data and $$L_{o,m}(\theta)$$ is the likelihood under the complete data. Taking the expectation of the second line with respect to the conditional distribution of $$Y_{m}$$ given $$Y_{o}$$ and […] The post Monotonicity of EM Algorithm Proof appeared first on Lindons Log.

## Why the “sample from infinite population” metaphor has been such a disaster for reproducible science.

April 19, 2014
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The “sampling from an infinite population” metaphor beloved by statisticians of all types is a disaster for reproducible science. To explain why I’ll show what sampling from a finite population has going for it that’s not there ...