The Seven Habits of Highly Effective Data Users

Abstract

Effective data interpretation is a habit, not a random event. By applying the seven habits outlined in this article, any otolaryngologist—regardless of the level of statistical knowledge or lack thereof—will be able to use data effectively. The seven habits are (1) check quality before quantity, (2) describe before you analyze, (3) accept the uncertainty of all data, (4) measure error with the right statistical test, (5) put clinical importance before statistical significance, (6) seek the sample source, and (7) view science as a cumulative process. The same habits apply whether interpreting one's own data, interpreting someone else's data, reviewing an unpublished manuscript for a journal, or reviewing a grant application for a funding agency. The basic principles that underlie these habits provide a systematic process for moving from observations to generalizations with predictable degrees of certainty—and uncertainty.