Porcine Joy

Spring showers bring pig flowers

Well, maybe not, but I haven’t featured any pigs recently. That could be in violation of the administrivial oink’s website charter.

The Ides of March are past, and we head into spring. We also approach the one-year anniversary of this blog on March 21 or thereabouts, right in time for the vernal equinox. I would like to take this opportunity to thank my loyal subscribers, all three of you, and my other readers, whether frequent or occasional. Never hesitate to leave comments, especially if it isn’t spam!

Statistics, probability and applied quantitative methods reading recommendations

Finally, I wish acknowledge subject matter experts with nice blogs in my fields of professional interest, including applied probability, (mostly) frequentist methods, and due diligence for purposes of financial and security-focused anomaly detection.

Stats with Cats I don’t like cats, but you can just ignore the photos. This is an accessible, frequently updated blog covering descriptive and inferential statistical methods, mostly explained through charming examples

Data Genetics This blog has excellent graphics (without gratuitous interactive data visualization!) accompanying posts demonstrating statistical, probability and mathematical methods for engineering as applied to a wide range of real world concerns e.g. using Benford’s Law to detect accounting fraud, Hamming Codes for error correction and solving combinatorics problems to demonstrate the poor odds for winning dice and card games.

Error Statistics Philosophy Error statistics quantifies how frequently and reliably different statistical models can be used to detect errors.Error probability statistics uses frequentist error probabilities, not frequentist probability. Frequentist error probability is the relative frequency of errors within a statistical model. Frequentist probability is merely the use of relative frequency of occurrence to infer probability of events. The introductory post, Frequentists in exile acknowledges the long-held perception that only Bayesian methods have respectable statistical foundations. Error Statistics Philosophy focuses on the defensible use of frequentist methods for probability and statistical models, especially in circumstances of limited information and high error avoidance requirements.

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