Part of Yale's open course Understanding Medical Research: Your Facebook Friend is Wrong, this lecture explains meta-analysis, the statistical technique for combining results from multiple studies into a single estimate of effect. The instructor walks through why single studies can mislead, how researchers pool data across trials, and what forest plots and confidence intervals reveal about the strength and consistency of evidence. The lecture also covers common pitfalls, including publication bias and heterogeneity between studies, and why a meta-analysis is not automatically more trustworthy than the studies feeding into it. Aimed at a general audience trying to evaluate health claims, it uses plain language and simple visual aids rather than heavy statistical notation, making the case that understanding how evidence is aggregated is essential to judging medical news and social media claims about research findings.