In clinical research, we often encounter the problem of multiple testing. When testing many hypotheses at the same time, how to control the type I error to ensure the accuracy of the results is the primary problem faced by researchers. However, the proportion of articles that didn't correct the multiple testing remains substantial. Starting with the simple hypothesis of a single test, this article provides an introduction to multiple testing issues, answers why and when multiple corrections are needed, introduces two important error rates which are family-wise error rate (FWER) and false discovery rate (FDR), and the Bonferroni and Benjamini-Hochberg correction methods based on them, thereby avoiding confusion caused by multiple testing.