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"Someone points me to this report from Tilburg University on disgraced psychology researcher Diederik Stapel. The reports includes bits like this: When the fraud was first discovered, limiting the harm it caused for the victims was a matter of urgency. This was particularly the case for Mr Stapel's former PhD students and postdoctoral researchers . . . However, the Committees were of the opinion that the main bulk of the work had not yet even started. . . . Journal publications can often leave traces that reach far into and even beyond scientific disciplines. The self-cleansing character of science calls for fraudulent publications to be withdrawn and no longer to proliferate within the literature. In addition, based on their initial impressions, the Committees believed that there were other serious issues within Mr Stapel's publications . . . This brought into the spotlight a research culture in which this sloppy science, alongside out-and-out fraud, was able to remain undetected for so long. . . . The scientific literature must be cleansed of everything that is fraudulent, especially if it involves the work of a leading academic. Sounds familiar? I think it also applies to recipients of the Founders Award from the American Statistical Association. There's more: The most important reason for seeking completeness in cleansing the scientific record is that science itself has a particular claim to the finding of truth. This is a cumulative process, characterized in empirical science, and especially in psychology, as an empirical cycle, a continuous process of alternating between the development of theories and empirical testing. . . . My first reaction was that all seems like overkill given how obvious the fraud is, but given what happened with comparable cases in the U.S., I suppose this "Powell doctrine" approach (overwhelming force) is probably the best way to go."

"As we get more data, we can fit more model. But at some point we become so overwhelmed by data that, for computational reasons, we can barely do anything at all. Thus, the curve above could be thought of as the product of two curves: a steadily increasing curve showing the statistical ability to fit more complex models with more data, and a steadily decreasing curve showing the computational feasibility of doing so."

"It is a wonder that we have yet to officially write about probability theory on this blog. Probability theory underlies a huge portion of artificial intelligence, machine learning, and statistics, and a number of our future posts will rely on the ideas and terminology we lay out in this post. Our first formal theory of machine learning will be deeply ingrained in probability theory, we will derive and analyze probabilistic learning algorithms, and our entire treatment of mathematical finance will be framed in terms of random variables."

Android applications downloaded by as many as 185 million users can expose end users' online banking and social networking credentials, e-mail and instant-messaging contents because the programs use inadequate encryption protections, computer scientists have found. The researchers identified 41 applications in Google's Play Market that leaked sensitive data as it traveled between handsets running the Ice Cream Sandwich version of Android and webservers for banks and other online services. By connecting the devices to a local area network that used a variety of well-known exploits, some of them available online, the scientists were able to defeat the secure sockets layer and transport layer security protocols implemented by the apps. Their research paper didn't identify the programs, except to say they have been downloaded from 39.5 million and 185 million times, based on Google statistics.

Eureqa (pronounced "eureka") is a software tool for detecting equations and hidden mathematical relationships in your data. Its goal is to identify the simplest mathematical formulas which could describe the underlying mechanisms that produced the data. Eureqa is free to download and use. Below you will find the program download, video tutorial, user forum, and other and reference materials.

After reading your recent post, I thought you might find this interesting - especially the scanned interview that is included at the bottom of the posting. It's an old OMNI interview with Walter Stewart that was the first thing I read (at a young and impressionable age ;) about the prevalence of errors, fraud and cheating in science, the institutional barriers to tackling it, the often high personal costs to whistleblowers, the difficulty of accessing scientific data to repeat published analyses, and the surprisingly negative attitude towards criticism within scientific communities. Highly recommended entertaining reading - with some good examples of scientific investigations into implausible effects. The post itself contains the info I once dug up about what happened to him later - he seems like an interesting and very determined guy: when the NIH tried to stop him from investigating scientific errors and fraud he went on a hunger strike.