Low statistical power in studies increases the chances of missing real differences between groups and also raises the risk of falsely positive results. This means that studies with low power are more likely to report significant effects that are actually incorrect. The likelihood of false positives is even higher when the null hypothesis (no difference) is likely to be true. This paper uses examples familiar to doctors to show how low statistical power can lead to misleading results.