Quantified You: A Practical Guide to Signal, Noise, and Self-Tracking

Your wearable gives you a score. Your CGM shows a spike. Your recovery app says you are not ready. What should you actually do with the number? Quantified You is a practical guide to interpreting personal health data without turning every fluctuation into a verdict. Through clear self-tracking examples, Adrian Keller explains how to check measurement quality, build useful personal baselines, distinguish ordinary variability from unusual observations, recognize confounding and regression to the mean, and design safer N-of-1 experiments. Using examples from sleep, glucose, workouts, HRV, recovery scores, and biological-age testing, the book shows how to separate statistical unusualness from practical or clinical importance - and when a spreadsheet should give way to professional medical guidance. The goal is not to turn daily life into a laboratory. It is to use personal data with more discipline, less reactivity, and better judgment.