GPW·Oct 14A.I. for dummies (mannequins)Walking past the clothing section in the warehouse-sized grocery+department store, the football season October display of mannequins…
Chintala Saikiran·Oct 4📊 Inferential Statistics: A Practical Guide to Making Decisions from DataData is everywhere, but collecting information from an entire population is often difficult, expensive, or time-consuming.
Maria Oros·Jun 25When Physics Meets Statistics: Hamiltonian Monte Carlo from ScratchHow classical mechanics gives us one of the most powerful tools in modern Bayesian data science
Maria Oros·Jun 25The Distribution That Keeps Saving Actuaries at 2 AMHow a four-parameter family from 1984 quietly became the most powerful tool for heavy-tailed data — and why you’ve probably never heard of…
Soham Sarkar·Feb 8Understanding the p-value (without pretending it’s simple)Most people don’t misunderstand the p-value because it’s hard. They misunderstand it because it’s explained badly.
Dr Greeshma Sharma·Feb 5I’ve Reviewed 100+ Studies. 87% Make the Same Statistical Mistake.Most researchers treat 1–5 scales like measurements. But they’re actually ranks. Here’s why that matters—and what to do about it.
InOverviews, Reviews and Advances in StatisticalbyIbiloye Abiodun Christian·Jan 14Volumetric Approaches to Structural SufficiencyThe volumetric approach to assessing structural sufficiency treats the model's parameter space and the space of representable functions…
InEveryday AIbyMahmoud Abdelaziz, PhD·Jan 8Classical and Bayesian Inference as Probabilistic Frameworks
Mahmoud Abdelaziz, PhD·Dec 22, 2025Understanding Causal Inference in Student Outcomes Assessment: Why Timing Matters
