The false discovery rate is a way to measure the number of false discoveries when testing multiple hypotheses. It helps researchers focus on finding mostly true results among statistically significant findings. This method is particularly useful in exploratory analyses. The false discovery rate approach was first implemented by Benjamini & Hochberg in 1995 and is related to Bayesian misclassification rates and positive predictive value.