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Soham Gaichor18h ago · 4 min read

Group Statistics Explained Using a Monster Bakery 🍪

If you’ve ever opened a dataset with 50,000 rows, stared at it for two minutes, and felt your brain slowly shut down, you are not alone. Raw data is chaotic. A table full of random numbers doesn't tel

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Soham Gaichor18h ago · 5 min read

The t-test, Explained Without the Textbook Voice

The first time I ran a t-test, I had no idea what I was looking at. The code ran, a p-value appeared, and I nodded like I understood. I didn't. So here's the explanation I wish I'd had. No formulas un

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Rene Haase1d ago · 3 min read

Six ways an ML pipeline fools itself (and the devices that caught them)

I run a nightly pipeline that trains scoring models for sixteen stock chart pattern detectors. It has run nearly 800 times since May 2026, and most of its 88,000 lines of Python are not modelling. The

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Ruchita Daga4d ago · 23 min read

A/B Testing at Scale: Power, Sequential Testing, and Practical Pitfalls

Author: Ruchita Daga | Faculty: Prof. Jayashree Bagade Abstract Online businesses decide what to ship with A/B tests, yet the error rates they quote (5% false positives, 80% power) hold only if the te

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Astra Quant4d ago · 3 min read

What 73% Really Means: Reading Probabilities Like an Engineer

Somewhere right now, a dashboard says "73%," and someone is reading it as "basically yes." That's the most common mistake people make with probabilities: rounding them into certainties. Engineers deal

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Dr. Barış Öztürk, MD6d ago · 10 min read

How WHO and CDC growth percentiles are computed (the LMS method), and the edge cases we hit

I'm an emergency physician, and I also write the code behind Growo, a set of child growth calculators in 17 languages and an MCP server that AI assistants can call. Parents kept asking me what the per

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Vimal Jyothi JosephOct 22 · 2 min read

Principal Component Analysis Explained: A Practical Guide to PCA

Principal Component Analysis Explained: A Practical Guide to PCA Principal Component Analysis (PCA) is a statistical technique that helps simplify complex datasets by reducing the number of variables

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FindUtilsOct 20 · 10 min read

Standard Deviation in Code: The Shortcut Formula That Returns 0, Welford's Fix, and Merging Daily Stats

FindUtils' explainer on sample vs population standard deviation covers the divisor question: n or n − 1, and which default Excel, NumPy, pandas and Python's statistics module use. This post covers wha

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Robert StarkOct 16 · 6 min read

I built one place to learn data science from the original sources

Learning data science usually means juggling a dozen tabs: a blog post that explains gradient descent one way, a video that explains it another, a textbook PDF you mean to read "properly" one day, and

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kestrelfieldOct 16 · 4 min read

Decision models, in plain words: AI that picks instead of writes

A new kind of AI model gives a probability for each option you hand it, in well under a second. What it's good for, and the one check to run before you trust its numbers. A note on how this was writte

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