https://statmodeling.stat.columbia.edu/2024/03/14/abraham-lincoln-and-confidence-intervals/ Abraham Lincoln and confidence intervalsAndrew GelmanPosted on March 14, 2024 9:04 AM “In a problem where the confidence interval is [0.1, 0.4], “the lower and upper endpoints of the
What I Read: High-Dimensional Variance
https://gregorygundersen.com/blog/2023/12/09/covariance-matrices/ High-Dimensional VarianceGregory Gundersen09 December 2023 “A useful view of a covariance matrix is that it is a natural generalization of variance to higher dimensions.”
What I Read: reliance on AI-assisted decisions
https://statmodeling.stat.columbia.edu/2024/03/06/defining-optimal-reliance-on-model-predictions-in-ai-assisted-decisions/Defining optimal reliance on model predictions in AI-assisted decisionsJessica Hullman3/6/24 12:31 PM “…AI-assisted decision task is of interest as organizations deploy predictive models to assist human decision-making in domains like
What I Read: Confidence intervals, balanced accuracy
https://code.groundlight.ai/python-sdk/blog/confidence-intervals-for-balanced-accuracy Tales from the Binomial Tail: Confidence intervals for balanced accuracyTed SandlerSenior Applied Scientist at GroundlightLeo DiracCTO and Co-founder at GroundlightJanuary 16, 2024 “…we put careful thought into measuring the
What I Read: Smooth Noisy Data
https://towardsdatascience.com/the-perfect-way-to-smooth-your-noisy-data-4f3fe6b44440?gi=a6f62aaf2818 The Perfect Way to Smooth Your Noisy DataAndrew BowellOct 25, 2023 “Insanely fast and reliable smoothing and interpolation with the Whittaker-Eilers method.”