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Why the patterns in your dashboards might be lying to youContinue reading on Medium »
*This is the introduction to a series on causal inference — one of the most practically important and least taught topics in data science…Continue reading on Medium »
Theiss Bendixen and Benjamin Grant Purzycki wrote this book. He writes: The website holds: – All data and code used in the book – Free sample chapters – Bonus material These aren’t...
I want to show you a tool I just open-sourced. It's called CausalLens, and it answers one specific question that most analytics stacks get completely wrong: did this intervention a...
A practitioner's warning about generated variables in causal analysis The post LLM Themes Are Not Observations appeared first on Towards Data Science.
Causal Inference with Observational Data Half Day Short Course | Register here 2026 APSA Annual Meeting & Exhibition — Boston, MA 9:00 am – 1:00 pm Estimating treatment effects...
My PhD models tried to explain why people engage. My industry models predict who will. The statistics barely changed. Everything around them did. The post Building Models in Two Wo...
A non-parametric variable selection for Structural VARs The post Granger Causal Networks and Indirect Feedback appeared first on Towards Data Science.
The 3:00 AM Incident That Changed Everything It was a Tuesday morning when the alerts started firing. Our recommendation engine, the one that drives 30% of our revenue, had tanke...
Most healthcare AI predicts who is at risk. This project explores a harder question: what sequence of actions could change a patient’s…Continue reading on Medium »
“If you torture the data enough, it will confess to anything.” — Ronald CoaseContinue reading on Medium »
Why small samples can produce large correlations by chance, and why large does not always mean meaningful The post Inside the Subspace Where Spurious Correlations Are Born appeared...
Donna Spiegelman shares this presentation she gave at the recent American Causal Inference Conference. I like what she has to say. Here are the two parts of the stable treatment va...
AI built on transparent, causal reasoning, systems that ground every output in validated biological mechanisms, show the pathway behind each recommendation, and cite their sources...
Любой аналитик знает, что самым надёжным способом проверки гипотез являются рандомизированные контролируемые эксперименты (RCT), или, как их называют в народе — A/B-тесты. На практ...
by Yajing Zhou, Kecheng Wei, Yahang Liu, Zhaoyang Li, Chen Huang, Guoyou Qin, Yongfu Yu Substantial progress has been made in the area of causal inference utilizing large-scale da...
I tried to predict air pollution. The simplest model almost won. Then cross-validation showed me what was really going on.Continue reading on Medium »
by Zhaotong Lin, Wei Pan, Haoran Xue Inferring a causal network among multiple traits is essential for unraveling complex biological relationships and informing interventions. Men...
How Feature Engineering Taught Me That Better Data Often Beats Better Algorithms When I first started learning Machine Learning, I believed what many beginners believe: If my mo...
The Data Science Discovery That Changed Retail Analytics ForeverContinue reading on Medium »
Mean reversion in marketing channels, the diminishing returns curve, and when to trust your model vs. your gut. Why the past is an…Continue reading on Medium »
I’ve often seen confusion between interactions in a regression model and correlations among the predictors. To keep it simple, consider the model y = b0 + b1*x1 + b2*x2 + b3*x1*x2...
In today’s digital-first world, data has become the most valuable asset for businesses. Every click, purchase, search, and interaction…Continue reading on Medium »
This is Jessica. We often idealize science as proceeding primarily by the scientific method, where scientists approach the objects of their investigation with a healthy dose of det...
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