Data manipulation involves altering or selecting data to achieve a desired outcome. This can include p-hacking, where researchers test multiple hypotheses until they find statistically significant results, or cherry-picking data that supports a preconceived notion. Such practices undermine the integrity of epidemiological research and can lead to misleading conclusions.