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Guides and analysis on biohacker.co.hu

Twelve in-depth articles by Zoltán Varga. Each one answers a single question, starting with the short answer.

Guide

How to Design an n-of-1 Self-Experiment

A step-by-step guide to running rigorous personal trials using evidence-based medicine principles.

Checklist

Stopping Rules: When to End a Self-Experiment

Define clear exit criteria before you begin to distinguish between genuine results, noise, and potential harm.

Concept

Baseline, Confounder, Washout: A Self-Experiment Glossary

Master the vocabulary of personal science to distinguish signal from noise in your own data.

Explainer

Regression to the Mean and Placebo in Self-Tracking

Understanding why initial improvements often fade helps you design self-experiments that reveal true causal effects rather than statistical illusions.

Guide

Subjective Ratings vs Device Metrics in Self-Experimentation

A practical guide to selecting feedback signals that combine bodily awareness with calibrated device readings.

Analysis

Why Your n-of-1 Result Does Not Generalize, and Why That Is Fine

Personal success proves nothing about the general population until you apply rigorous triangulation and understand the limits of individual variability.

Pattern

Pattern: A Sleep-Routine Experiment Run Properly

An anonymized template for running a behavioral sleep experiment that isolates variables and establishes clear stopping rules.

Checklist

Safety Limits: What Not to Self-Experiment With

Establish clear boundaries for self-experimentation to prevent harm when testing diet, sleep, or lifestyle changes.

Guide

Keeping an Experiment Log in Your Notes System for Clear Results

Structure your n-of-1 trials with a one-page template and a Map of Content to turn raw data into verified personal knowledge.

Q&A

Self-Experimentation FAQ: Validity, Duration, and Safety Rules

A practical guide to designing, running, and concluding personal health experiments with scientific rigor and safety.

Explainer

Calibrated Confidence: How Sure Are You About Your Result?

Apply calibrated confidence language from intelligence analysis to distinguish observation from speculation in your self-experiments.