当一个人同时进行多个测试时，这称为多次测试。一个例子是进行一项研究以发现某些基因是否与某些疾病有关。假设考虑了1,000,000个基因和100种疾病，并进行了一项测试以查看每个基因-疾病对是否相关。然后进行100,000,000个测试。尽管已知一些针对多种测试进行调整的简单方法，但它们仅在相对简单的情况下才有效，例如，当进行的所有测试均基于独立的测试统计信息时。因此，为我们面临的复杂的“大数据”世界开发强大的多项测试调整方法是当前最有趣的统计领域之一。
When one is simultaneously conducting more than one test, this is called multiple testing. An example is when a study is done to find if certain genes are associated with certain diseases. Suppose 1,000,000 genes and 100 diseases are considered, with a test conducted to see if each gene-disease pair is associated. Then one is conducting 100,000,000 tests. While some simple methods of adjusting for multiple testing are known, they are effective only in relatively simple cases, such as when all the tests being conducted are based on independent test statistics. Thus developing powerful multiple testing adjustments for the complex ?big data? world we face is one of the current most interesting areas of statistics.