‘Danger, lives have been lost!’ reads a sign on the rocks by a raging cascade near one of the authors' places of birth. A similar warning should accompany Experience Sampling data, for a novice could easily squander many years on the slippery terrain of ESM data analysis. Such a warning should be in bright neon for students trained in the positivist framework of experimental science; like the daily experience they attempt to mirror, ESM data have a complexity which defies traditional textbook analysis. Rarely do they fully oblige the stringent assumptions of inferential statistical tests. The many factors impinging on daily life, and thus upon these data, demand a constant vigilance to statistical artifact and possible confounds. Therefore, even the seasoned ESM researcher takes many trips back to the computer before finalizing an analysis in a way that most clearly expresses the relationship he or she wishes to capture.