Part of Yale's open course Understanding Medical Research: Your Facebook Friend is Wrong, this session breaks down the p-value, the statistic behind almost every headline claiming a new food, drug, or habit is linked to disease. The instructor walks through what a p-value actually measures, the null hypothesis it tests against, and why a result below 0.05 is not the same as proof that a finding is true or important. Examples show how small sample sizes, multiple comparisons, and publication bias can produce statistically significant results that do not hold up, and why a shared study on social media often strips out exactly the caveats a p-value depends on. The lecture is aimed at general viewers rather than statisticians, building the concept from first principles so that a claim like reduces risk by half becomes something you can actually question rather than accept.