The article discusses how increasing sample sizes and testing multiple hypotheses can lead to errors in scientific studies. By controlling the False Discovery Rate, researchers can avoid inflating error rates when testing many hypotheses. This can be achieved by increasing sample sizes for all hypotheses simultaneously and only rejecting hypotheses based on final analysis results. This approach does not impact error rates, except in cases where all hypotheses are true. Stopping rules are also proposed to control error rates when testing multiple hypotheses. The method is demonstrated using data from microarray experiments.