Probability

Hat tip: Philip Cunningham April 7, 2017

From ScienceDaily: Could there be another planet out there with a society at the same stage of technological advancement as ours? To help find out, EPFL scientist Claudio Grimaldi, working in association with the University of California, Berkeley, has developed a statistical model that gives researchers a new tool in the search for the kind of signals that an extraterrestrial society might emit. His method — described in an article appearing today in Proceedings of the National Academy of Sciences — could also make the search cheaper and more efficient. … The advantage of Grimaldi’s statistical model is that it lets scientists interpret both the success and failure to detect signals at varying distances from Earth. His model employs Bayes’ Read More ›

Haebichan Jung tells us that he built an original pop music-making machine “that could rival deep learning but with simpler solutions.” Deep learning “is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks.” (Jason Brownlee, Machine Learning Mastery) Jung tells us that he went to considerable trouble to develop deep learning methods for generating machine pop music but in the end… I made a simple probabilistic model that generates pop music… Eric Holloway notes that this is an expected outcome based on the fact that computers cannot generate mutual information, where two variables are dependent on each other. Can simple probabilities outperform deep learning?” at Mind Matters Today Read More ›

Should science pursue truth regardless of consequences? Or must we succumb to political correctness? Must selectivity of females always equal males? Consider:
Academic Activists Send a Published Paper Down the Memory Hole – by Theodore P. Hill
“In the highly controversial area of human intelligence, the ‘Greater Male Variability Hypothesis’ (GMVH) asserts that there are more idiots and more geniuses among men than among women. Darwin’s research on evolution in the nineteenth century found that, although there are many exceptions for specific traits and species, there is generally more variability in males than in females of the same species throughout the animal kingdom.” . . . Read More ›

Contextual Bias David Nguyen is with Think Tank Learning. See also: Asking, what is more prone to error: Science or scientists?

From John D. Norton: (2018) Eternal Inflation: When Probabilities Fail. [Preprint] In eternally inflating cosmology, infinitely many pocket universes are seeded. Attempts to show that universes like our observable universe are probable amongst them have failed, since no unique probability measure is recoverable. This lack of definite probabilities is taken to reveal a complete predictive failure. Inductive inference over the pocket universes, it would seem, is impossible. I argue that this conclusion of impossibility mistakes the nature of the problem. It confuses the case in which no inductive inference is possible, with another in which a weaker inductive logic applies. The alternative, applicable inductive logic is determined by background conditions and is the same, non-probabilistic logic as applies to an Read More ›

For some time now, objector DiEb has been raising the question, what do we mean by speaking of “search” in the context of evolutionary search. At 311 in the parody thread, she [IIRC] remarks: >>Search is a central term in the work of Dr. Dr. William Dembski jr, Dr. Winston Ewert, and Dr. Robert Marks II (DEM): it appears in the title of a couple of papers written by at least two of the authors, and it is mentioned hundreds of times in their textbook “Introduction to Evolutionary Informatics“. Strangely – and in difference from the other central term information, it is not defined in this textbook, and neither is search problem or search algorithm. Luckily, dozens of examples of Read More ›

Note to Readers: The past few days on this thread there has been tremendous activity and much discussion about the concept of probability.  I had intended to post this OP months ago, but found it still in my drafts folder yesterday mostly, but not quite fully, complete.  In the interest of highlighting a couple of the issues hinted at in the recent thread, I decided to quickly dust off this post and publish it right away.  This is not intended to be a response to everything in the other thread.  In addition, I have dusted this off rather hastily (hopefully not too hastily), so please let me know if you find any errors in the math or otherwise, and I will be happy Read More ›