#bayesian-statistics

Complete rest or light exercise for better next-day recovery?

As a long time user of WHOOP (900+ nights and counting) and someone keen on my own physical health, I aim to achieve high physical recovery…

#MeringkasArtikel — Bayesian Mindsponge: Mengapa Otak Anda Bertindak Seperti Spons dalam Menghadapi…

Di era digital yang serba cepat ini, kita tidak sekadar menerima informasi; kita dibombardir olehnya. Setiap detik, ribuan bit data — mulai…

Laplace’s Method: How to Solve an Integral You Can’t Solve

One Gaussian bump under the peak turns an impossible integral into Stirling’s formula — and much of statistical physics.

Bayesian Decision Trees: From “What Even Is This?” to “Oh, That’s Actually Elegant”

A journey through uncertainty, starting with how you make decisions, then how trees make them, then how to make trees honest about what…

Introducing BCAT: A Bayesian Approach to Understanding Cricket Performance

“Cricket fans remember the great feats of triumph against the odds a cricket GOAT shows, not just the score-lines. What if we could measure…

The Problem of Predictive Multiplicity And How GEMSS Deals With It

When your data has more than one story to tell, an ordinary feature selector will pick one and never mention the rest. GEMSS hands you the…

A Short Note on “ELECTRONIC SPAM FILTERING BASED ON NEURAL NETWORKS”

This entry reflects on a journal I encountered while searching for matrix multiplication in context of neural network, I came across a…

Creating the Problem, Then Winning the Argument: Enes Freedom, Iran, and the Politics of…

When You Have to Create the Problem to Prove It Exists

Why Bayesian Networks Are an Epistemology, Not Just a Statistical Tool

Why Bayesian Networks Are an Epistemology, Not Just a Statistical Tool

Zero-Knob Bayesian MMM: I Taught a Neural Network to Configure Marketing Models — and Built the…

What happens when a machine learns the expertise that made marketing measurement a consulting business — with working code, real…

The Illusion of Certainty: Why Everything in AI is a Statistical Bet

When you ask a Large Language Model (LLM) a question and it gives you a perfectly coherent answer, it looks like a deterministic machine…

The Architecture of Certainty

How a 300-Year-Old Gambler’s Panic Secrets a Multi-Million Dollar MMM (Marketing Mix Modelling) Algorithm

Can You Spot AI Writing by Em Dash Alone? (The Math Says No)

If you’ve spent time in the online writing world, you most definitely know that usage of AI is ubiquitous. How were you able to arrive at…

Heterogeneous Effects, Uplift, and Bandits: From Average Treatment Effects to Individualized…

Part 6 of 7. Personalizing treatment and learning policies online.

Bayesian Statistics in SBayesR: A Tutorial for Polygenic Score Estimation

A hands-on guide to understanding and running SBayesR, from Bayes’ theorem to posterior SNP effects

Should We Ship This Model? A Bayesian look at precision and recall, and how to turn it into actions

Every machine learning team eventually runs into the same uncomfortable moment. You’ve trained a new classification model, the numbers look…

Computational Inference for Bayesian Models: MCMC, HMC, NUTS, and Variational Inference Without the…

Part 2 of 7. The machinery that turns a generative model into a posterior.

Genes Before Gods: Reconstructing Ancient India Through Genetics Part 3

Turning DNA into a Time Machine

Calibration in machine learning

Operador Fatorial!

Bayesian Thinking for Industry: From Prior Belief to Production Decisions

Part 1 of 7. Foundations of Bayesian inference for serious practitioners.

Bayesian vs Frequentist A/B Testing: What Practitioners Need to Know

A practical guide to the Bayesian vs Frequentist debate in A/B testing, why it matters less than you think, and what practitioners should…

Naïve Bayes Classification

So far, we’ve looked at Decision trees, logistic regression which are all classifiers that use entropy and a threshold probability…

Naïve Bayes: The Algorithm That’s Wrong About Everything But Right About Results

How a 270-Year-Old Theorem Became One of the Best Spam Detectors Ever Built

Statistics Concept — Monty Hall Paradox: When Intuition Fails but Bayesian Reasoning Prevails

A step-by-step probabilistic breakdown using Bayes’ theorem, graphical illustration, and Monte Carlo simulation using Python

Predictable Society: Living in The Age of Algorithms

I was no longer surprised when Netflix suggested a few good movies for my weekend. After years of watching the same kinds of genre, I think…

Bayesian Thinking in Clinical Research Part 2: Learning While the Trial Is Still Running

Traditional clinical trials are often built around a fixed sequence. Patients are enrolled, treatments are assigned, follow-up is…

Bayesian Thinking in Clinical Research

Part 1: What Do We Actually Mean by a “Prior”?

Ten Years of Big Air Leaderboards and One Jump That Broke the Trend

Predicting the next kitesurfing world record jump with Bayesian statistics

Updating the Prior

Why Physical Therapy Needs Bayesian Thinking to Navigate What Comes Next

argonx: A Bayesian Decision Engine for A/B Experiments

A Trick of the Mind: I Find My Daughter Naughty, Only Because I Am Slow

I recently picked up A Trick of the Mind: How the Brain Invents Your Reality by Daniel Yon, after being fascinated by the idea of the…

Bayesian Decision Making -2

STATISTICAL DECISION MAKING PART-II

Your MMM Priors are being set by the platforms you’re trying to measure.

Why transaction spending data , not Meta Lift or Google Geo Experiments , should anchor your Bayesian Marketing Mix Model calibration.

Classical versus Bayesian Modeling With Bayesian Networks

Parameter Learning With Hiearchical Bayesian Networks - A Bayesian hierarchy of data, uncertainty, and hidden probabilities

Interlude — Reality is Bayesian

The ongoing evolution of reality

Using Bayesian Regime Detection to Read Stock Market States

A Practical Regime Filter for Stock Research

Everything Is Predictable: 300 Years Ago, People Talked About Math for Fun

I recently finished reading Everything Is Predictable: How Bayes’ Remarkable Theorem Explains the World by Tom Chivers.

A Story of Bayesian Quantum Phase Estimation

The Lighthouse Keeper and the Foggy Sea

Think Bayesian Dice!

This comes from the second edition of this book: THINK BAYES 2e! by author and educator Allen Downey (with an accompanying website and…

Statistical Rethinking — With Bayesian Networks

Bayesian Parameter learning

Bayesian Thinking: Every New Piece of Information Is a Chance to Update

“The world is not certain. Human understanding has to be continuously calibrated. And every new piece of information is an opportunity to…

Bayesian Price Elasticity with PyMC

From a simple log-log model to cross-price substitution

Baby Bayes: Predicting Infant Sleep Patterns

As a new parent, there is a lot on my mind. Is my baby healthy? Am I saving enough money for their future? Can I be helping my family more…

Constructing a Bayesian Belief Network — Who Wins This Game?

This exercise comes from a very recent (2025) online textbook on Bayesian Reasoning and Machine Learning by David Barber.

Mastering Causal Thinking: How to Build Causal Strategies For Real-World Environments.

The journey from raw data to actionable results goes through four progressive stages of analytics: Descriptive, Diagnostic, Predictive, and…

Beyond the Point Estimate: Calibrating Uncertainty in Production Systems

Structural Reliability and Distribution-Free Guarantees for High-Stakes Machine Learning

How Bayes’ Theorem Finally Killed My Monty Hall Intuition

I’ll be honest: for the longest time, the Monty Hall problem felt like it was trying to gaslight me with math.

데이터는 변하지 않지만, 당신의 믿음은 변해야 합니다

베이지안 통계의 쉬운 접근: PyMC로 구현하는 확률프로그래밍

"Fairness” Is Not a Metric

Rethinking Algorithms