I’ve been looking for something like this for a while. It is a repository for data sets associated with peer-reveiwed publicattions. I have only glanced at it briefly, but it looks fairly easy to use with a fair number of interesting data sets/publications. Continue reading
I heard about a new series of conferences for learning about R. I have not attended any of them, but they look interesting. Continue reading
I got a question from one of the students in my “Introduction to R” class asking what are the important packages for R. That’s a hard question to answer, but if I got only easy questions, they wouldn’t be paying me the big bucks. Here’s what I think. Continue reading
This is a nice summary about the prosecution of a statistician, Andreas Georgiu, who was only doing his job. Continue reading
I’ve not had a chance to test this code, but it looks pretty good for anyone who might want to analyze one of the dozens of large databases produced by the U.S. Government. Continue reading
I attended a talk about a decade ago on the problems with for-profit publishing of scientific research and the need to aggressively adopt the open source publication model. It was a message I was ready for, because I had benefited greatly from citing open source resources on my website. I knew that if I cited an open source resource, anyone anywhere could look up that resource. They didn’t need access to a University Library.
This article explains how the for-profit research journals (perhaps better described as a reader-pays model, in contrast to an author-pays model) developed a system that locked in research libraries to their product and then hiked the price. Then they developed journal bundles that further squeezed libraries by forcing them into a take-it-all-or-leave-it-all system that devastated their budgets.
There is still a struggle between the reader-pays model of for-profit publishing and the author-pays model of open source publishing, and I believe there is room for both approaches, though I would argue that we need to promote open source publishing more aggressively than we currently are doing.
This article provides a very nice historical context to the development of for-profit publishing in scientific research. It oversimplifies things, perhaps, and may be a bit too harsh, but it is definitely worth reading.
As an ironic footnote, newspapers have been devastated by the Internet because of the expectations of readers that all of their content should be available for free. There is a note at the bottom of the Guardian article that reads: “Since you’re here we have a small favour to ask. More people are reading the Guardian than ever but advertising revenues across the media are falling fast. And unlike many news organisations, we haven’t put up a paywall – we want to keep our journalism as open as we can. So you can see why we need to ask for your help. The Guardian’s independent, investigative journalism takes a lot of time, money and hard work to produce. But we do it because we believe our perspective matters – because it might well be your perspective, too.”
Take some time to read this and think about it. I normally ignore pitches like this on Wikipedia and elsewhere, but the irony of citing a newspaper article available for free to criticize for-profit research publishing got to me, so I became a supporter of the Guardian at $6.99 per month.
This is yet another interesting source of data. This site specializes in databases prepared by the United States government. Continue reading
In contrast to the five thirty eight databases which are mostly smallish, the Kaggle data sets are, as a rule, very large. They also include a lot of text data, for natural language processing, sentiment analysis, etc. Continue reading
This is a github repository of a lot of interesting data sets created by the Five Thirty Eight website. I presume there is a story associated with most of these data sets. The data sets look to be moderate in size for the most part and would make interesting teaching examples. Continue reading
If you work with probability distributions a lot, you find there are mutliple parameterizations (e.g., the two different forms of the exponential distribution), as well as interesting relationships (the geometric distribution is a discrete version of the exponential distribution). I have found Wikipedia to be a nice guide for some of this, but the coverage is uneven in quality. One of the Wikipedia links mentioned a new website, ProbOnto, that offers a systematic and standardized attempt to catalog every important probability distribution and the relationships among these distributions. Continue reading