From: http://www.statslife.org.uk/news/1299-report-of-mps-inquiry-into-uk-statistics-and-open-data-published?utm_source=feedburner&utm_medium=email&utm_campaign=Feed%3A+rss-enews+%28StatsLife+-+all+the+latest+statistics+news%29Written by W...

With Matt Moores and Kerrie Mengersen, from QUT, we wrote this short paper just in time for the MCMSki IV Special Issue of Statistics & Computing. And arXived it, as well. The global idea is to cut down on the cost of running an ABC experiment by removing the simulation of a humongous state-space vector, […]

One of the most satisfying experiences for an academic is when someone asks a question that you’ve already answered. This happened in the comments today. Daniel Gotthardt wrote: So for applied stat courses like for sociologists, political scientists, psychologists and maybe also for economics, what do we actually want to accomplish with our intro courses? […]The post Teaching Bayesian applied statistics to graduate students in political science, sociology, public health,…

I happen to think that SQL is a very viable option for analyzing big data. I was thinking about this when I a book review recently:For instance, Siegel reports, people who buy small felt pads that adhere to the bottom of chair legs (to protect th...

Monday, in our MAT8181 class, we’ve discussed seasonal unit roots from a practical perspective (the theory will be briefly mentioned in a few weeks, once we’ve seen multivariate models). Consider some time series , for instance traffic on ...

From 2008: The candy weighing demonstration, or, the unwisdom of crowds My favorite statistics demonstration is the one with the bag of candies. I’ve elaborated upon it since including it in the Teaching Statistics book and I thought these tips might be useful to some of you. Preparation Buy 100 candies of different sizes and […]The post The candy weighing demonstration, or, the unwisdom of crowds appeared first on Statistical…

Overfitting occurs when a statistical model or machine learning algorithm captures the noise of the data. Intuitively, overfitting occurs when the model or the algorithm fits the data too well. Specifically, overfitting occurs if the model or algorithm shows low bias but high variance. Overfitting is often a result of an excessively complicated model, and […]

Having taught and tutored introductory statistics numerous times, I often hear students misinterpret the Central Limit Theorem by saying that, as the sample size gets bigger, the distribution of the data approaches a normal distribution. This is not true. If your data come from a non-normal distribution, their distribution stays the same regardless of the […]

Editor's note: This has nothing to do with statistics. I do a lot of statistics for a living and would claim to know a relatively large amount about it. I also know a little bit about a bunch of other scientific … Continue reading →

An interview with me from 2012: You’re a statistician and wrote a book, Red State, Blue State, Rich State, Poor State, looking at why Americans vote the way they do. In an election year I think it would be a good time to revisit that question, not just for people in the US, but anyone around […]The post How Americans vote appeared first on Statistical Modeling, Causal Inference, and Social Science.

It's Spring Break at NYU, which for professors, is not a break. I have been marking midterms for my business analytics class. Since I like to set open-ended questions (are there anything else in statistics?), I get a variety of answers. One of the questions helps clarify what I mean by numbersense. The question asks students to comment on the distribution of a variable (median income) in a dataset of…

Last month I blogged about defining SAS/IML functions that have default parameter values. This language feature, which was introduced in SAS/IML 12.1, enables you to skip arguments when you call a user-defined function. The same technique enables you to define optional parameters. Inside the function, you can determine whether the […]