Statistics & Probability

Inference, estimators, Bayesian methods, and uncertainty quantification.

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everydaysociologyblog.com > 11/08/2010 > crossword-puzzles-and-the-null-hypothesis

Crossword Puzzles and the Null Hypothesis

1+ week, 1+ day ago   (764+ words) Most Sundays I enjoy working on the crossword puzzle in my local newspaper. I typically fill it in with a pen since pencil can be hard to read on newspaper. Of course it can get messy as I make mistakes…...


quantumzeitgeist.com > tensor-networks-causal-dag-moral-graph-recovery

Researchers Map Causal Links from Probability Data

6+ hour, 34+ min ago   (959+ words) Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to…...


eurekalert.org > news-releases > 1146723

Mapping causal biology: Mendelian randomization in the era of big data

18+ hour, 43+ min ago   (306+ words) Mendelian randomization leverages genetic variants to mitigate confounding bias in causal inference. This paper systematically reviews the methodological evolution of Mendelian randomization, elaborates on its expanding applications in epidemiology and drug target validation, and identifies future research directions to address…...


medium.com > @rahulkmch22 > five-probability-distributions-every-ml-beginner-meets-bernoulli-binomial-poisson-uniform-and-70b7f887b3df

Five Probability Distributions Every ML Beginner Meets: Bernoulli, Binomial, Poisson, Uniform and Normal

22+ hour, 17+ min ago   (1848+ words) What each one actually describes, the one question that tells you which to use, and the math worked out on small examples. A model returns 0.8 for “will this user click?” Another predicts 3.7 support tickets for the next hour. A third…...


medium.com > @charan050304 > mastering-descriptive-statistics-why-identical-means-lie-and-how-to-profile-real-world-data-ec981f98ef5c

Mastering Descriptive Statistics: Why Identical Means Lie and How to Profile Real-World Data

1+ day, 1+ hour ago   (614+ words) The Math, Edge Cases, and Visualizations Behind Production Exploratory Data Analysis (EDA) Imagine evaluating two separate machine learning models on a batch of inference requests. Both models report an average latency of 75 milliseconds. At first glance, they look identical. But…...


medium.com > @jroberts1504 > the-confidence-threshold-f914febb2bc5

The Confidence Threshold

1+ day, 9+ hour ago   (1414+ words) I’ve probably missed out on more than a handful of great opportunities playing what I like to call the “gotta get ready to be ready” game. You know the game. I’ll apply when I get one more certification.I’ll start…...


medium.com > @atticusli > why-you-can-never-change-a-running-experiment-and-what-to-do-instead-f4f6528f5c16

Why You Can Never Change a Running Experiment (And What To Do Instead)

1+ day, 11+ hour ago   (1176+ words) It happens in every testing program. A designer notices a typo in the variant copy. A developer “just tweaks” the CTA color slightly. A product manager updates the traffic allocation because they’re worried about revenue impact. A stakeholder asks to…...


medium.com > @dpavanvamsikrishna > the-foundational-pillar-of-data-science-descriptive-vs-inferential-statistics-1a2273844624

The Foundational Pillar of Data Science: Descriptive vs. Inferential Statistics

1+ day, 18+ hour ago   (346+ words) Imagine sitting in your morning math class as your teacher hands back the latest algebra exam. At the top of your paper, you see a score written 88%. As you look around the room, your mind starts forming questions that naturally…...


thequantasticjournal.com > how-strong-would-a-hidden-confounder-have-to-be-2c13354809c6

How Strong Would a Hidden Confounder Have to Be?

1+ day, 19+ hour ago   (329+ words) Sensitivity analysis for causal machine learning, and why the benchmark is harder than the bound—By the late 1950s the statistical association between cigarette smoking and lung cancer was no longer in dispute; its interpretation was. The most serious objection, pressed…...


medium.com > @boddumeenakshi.0 > descriptive-vs-inferential-statistics-what-every-data-analyst-should-know-a1f4b589aef9

Descriptive vs Inferential Statistics: What Every Data Analyst Should Know

2+ day, 17+ hour ago   (736+ words) Every dataset can answer two very different questions: What does this data show? and What can I conclude beyond it? Most beginners only learn to answer the first one. And that leads to the most common mistake in data analysis:…...