This week the SUMS talk is being given by undergraduate John Wormell. Abstract: Hypothesis testing using p values is the standard method of determining statistical significance in science. By themselves, p values are not well suited for multiple hypothesis testing. They are inflexible and somewhat opaque, and the standard correction is often too conservative for many purposes. The false discovery rate and its associated q values provide an adaptive and surprisingly informative alternative method of analysing the significance of data. Methods based on the false discovery rate have been widely used, especially in genomics, in the last twenty years. This talk presents some ideas from statistical inference for non-statisticians with some fun examples.