Tracking vs Experimenting

Two different activities

Tracking means recording something over time, such as steps, sleep times, mood or meals, without changing anything on purpose. Experimenting means changing one thing deliberately and comparing what happens with and without the change. Many people do the first and call it the second. The distinction matters because tracking can show a pattern, while only a fair comparison can begin to show whether a change caused it.

Tracking is the lower-risk, lower-burden activity, and it is where this library starts. See Quantified Self Explained for the background.

What a single-person experiment is

A formal single-person experiment is called an N-of-1 trial. One description is that it observes outcomes over time in the same person under periods of exposure to an intervention and a comparator. [1] N-of-1 trials were popularized in the 1980s and are used to assess the effects of interventions in single individuals. [1]

Researchers describe N-of-1 trials as a rigorous way to evaluate individual treatment responses, but also note practical and theoretical challenges to doing them well. [2] Even a simple idea can require strong assumptions in the analysis to estimate cause and effect. [1]

An example from the literature shows the realism needed. One person tracked mood every eight hours across a month-long alcohol-abstinence period and the time before and after (264 data points). After adjusting for other influences, the average individual effect on mood was small and the confidence interval included zero. [1] The point is not the result for that one person; it is how much careful design and analysis even a simple personal question needs.

Why informal personal experiments often mislead

Everyday "try it and see" experiments usually lack the features that make a comparison fair. The sources above stress comparators and explicit assumptions. In practice, common problems include:

• No comparison period. Without a clear before-and-after or on-and-off comparison, you cannot tell a change from ordinary ups and downs. See Baseline Variation and Normal Fluctuation.
• Several changes at once. If sleep, food and training all change together, you cannot tell which mattered. See Changing One Low-Risk Variable at a Time.
• Expectation. Knowing what you are testing can influence how you feel. See Placebo and Expectancy Effects in Wellness Tracking.
• Choosing a number that is not the point. A number that moves is not necessarily a benefit. See What Counts as a Meaningful Outcome?