This document discusses critical thinking in statistics and common misuses of statistics. It identifies 13 common misuses: 1) bad samples, like voluntary response samples where conclusions can only be made about respondents, 2) small samples where conclusions shouldn't be based on too small a sample, 3) misleading graphs that exaggerate differences, 4) pictographs that also exaggerate differences, 5) percentages that can be unclear or misleading, and 6) other issues like loaded questions, order of questions, refusals, confusing correlation with causation, biased studies, imprecise numbers, and partial pictures. The purpose is to illustrate how common sense is needed to properly interpret data and statistics.