Seth Roberts:"The Growth of Personal Science: Implications for Statistics"<p>"<i>Personal science is science done for personal reasons (to help yourself) rather thanprofessional ones (as a job). The most common personal science is health self-measurement, which has recently become much more popular. This article describes 14examples of personal science involving health. The topics include blood sugar, sleep,mood, body weight, resistance to infection, and brain function. Most of the examples areabout new ways to improve these measures. For example, the results suggest that: 1.Skipping breakfast reduces early awakening. 2. Looking at faces in the morningimproves mood. 3. Flaxseed oil improves balance. 4. Butter improves arithmetic speed.Overall, the results suggest that personal science plus expert advice can produce betterhealth than expert advice alone. Personal science may influence statistics in two ways: 1.A new audience. Personal scientists want to learn statistics. 2. Better understanding.Learning about personal science may help statisticians understand science in general</i>"<p><a href="http://media.sethroberts.net/blog/pdf/2012-09-24-The-Growth-of-Personal-Science-Implications-For-Statistics.pdf" rel="nofollow">http://media.sethroberts.net/blog/pdf/2012-09-24-The-Growth-...</a><p>---
---<p>Seth Roberts:"The unreasonable effectiveness of my self-experimentation"<p><i>"Over 12years, my self-experimentation found new and useful ways to improve sleep, mood, health, and weight. Why did it work so well? First, my position was unusual. I had the subject-matter knowledge of an insider, the freedom of an outsider, and the motivation of a person with the problem. I did not need to publish regularly. I did not want to display status via my research. Second, I used a powerful tool. Self-experimentation about the brain can test ideas much more easily (by a factor of about 500,000) than conventional research about other parts of the body. When you gather data, you sample from a power-law-like distribution of progress. Most data helps a little; a tiny fraction of data helps a lot. My subject-matter knowledge and methodological skills (e.g., in data analysis) improved the distribution from which I sampled (i.e., increased the average amount of progress per sample). Self-experimentation allowed me to sample from it much more often than conventional research. Another reason my self-experimentation was unusually effective is that, unlike professional science, it resembled the exploration of our ancestors, including foragers, hobbyists, and artisans."</i><p>Medical Hypotheses<p>Volume 75, Issue 6 , Pages 482-489, December 2010<p><a href="http://media.sethroberts.net/articles/2010%20The%20unreasonable%20effectiveness%20of%20my%20self-experimentation.pdf" rel="nofollow">http://media.sethroberts.net/articles/2010%20The%20unreasona...</a>