Survivorship bias refers to the logical error of focusing on the instances that 'survived' some process and inadvertently overlooking those that did not because of their lack of visibility. This bias can lead to false conclusions in several different ways. The survivors may be actual people, as in a medical study, or could be companies or research participants or students… or anything that must make it past some selection process to be included in the study or analysis. For example, if three of the five students with the best college grades went to the same high school, that can lead one to believe that the high school must offer an excellent education. This could be true, but the question overlooks the students from that same high school who didn't get into college at all. The overlooked group can potentially lead to a vastly different conclusion.