https://www.edx.org/learn/architecture/harvard-university-the-architectural-imagination
HarvardX: The Architectural Imagination | edX
August 12, 2025Roman Architecture | Coursera
August 12, 2025https://www.coursera.org/learn/roman-architecture
Roman Architecture | Coursera
Random number generator seed mistakes & how to seed an RNG
August 10, 2025Scientists Found a Ghost Code Hidden in the Human Genome
August 10, 2025r414-reprint.pdf – Simpson’s paradox
August 9, 2025American Statistician, 68(1):8-13, February 2014. TECHNICAL REPORT R-414 Comment: Understanding Simpson’s Paradox Judea PEARL
Causal Analysis in Theory and Practice » Lord’s Paradox: The Power of Causal Thinking
August 9, 2025Goodreads & Amazon reviews
August 6, 2025Goodreads & Amazon reviews
https://www.goodreads.com/review/show/3990715575
https://www.amazon.com/review/R23LOUDQ5JELVC/ref=pe_123899240_1043597390_SRTC0204BT_cm_rv_eml_rv0_rv
Some “strong quotes” from the Book of Why
August 3, 2025QT:{{‘
Even two decades ago, asking a statistician a question like “Was it the aspirin that stopped my headache?” would have been like asking if he believed in voodoo. To quote an esteemed colleague of mine, it would be “more of a cocktail conversation topic than a scientific inquiry.” But today, epidemiologists, social scientists, computer scientists, and at least some enlightened economists and statisticians pose such questions routinely and answer them with mathematical precision.
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QT:{{”
Ironically, the need for a theory of causation began to surface at the same time that statistics came into being. In fact, modern statistics hatched from the causal questions that Galton and Pearson asked about heredity and their ingenious attempts to answer them using
cross-generational data. Unfortunately, they failed in this endeavor, and rather than pause to ask why, they declared those questions off …
This was a critical moment in the history of science. The opportunity to equip causal questions with a language of their own came very close to being realized but was squandered. In the following years, these questions were declared unscientific and went underground. Despite heroic efforts by the geneticist Sewall Wright (1889–1988), causal vocabulary was virtually prohibited for more than half a century. And when you prohibit speech, you prohibit thought and stifle principles, methods, and tools. Readers do not have to be scientists to witness this prohibition. In Statistics 101, every student learns to chant, “Correlation is not causation.” With good reason! The rooster’s crow is highly correlated with the sunrise; yet it does not cause the sunrise. Unfortunately, statistics has fetishized this commonsense observation.
…
The rest of statistics, including the many disciplines that looked to it for guidance, remained in the Prohibition era, falsely believing that the answers to all scientific questions reside in the data, “}}
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