This lecture is part of Yale's online course Understanding Medical Research: Your Facebook Friend is Wrong, which teaches non-specialists how to read and question published studies. Here the instructor covers information bias, the systematic errors that creep into data collection itself rather than into who gets studied. The talk works through how misclassification, recall problems, and inconsistent measurement can distort a study's findings even when the sample and design are otherwise sound, using examples of how survey answers or diagnostic records can mislead researchers without anyone intending to cheat. The point is practical: knowing these patterns lets a reader spot when a headline claim about a health study rests on shaky measurement rather than a real effect. At twelve minutes, it is a short, focused segment meant to build on earlier lectures in the series about study design and bias.