Why is multiple testing a big issue in biostatistics? In this video, we will explain why multiple testing is so dangerous when analysing large datasets, and how to correct for it. We will cover some of the most common methods: Bonferroni correction, Benjamini-Hochberg (BH) and q-values. Don't let the monster of multiple testing eat your data! -------------------------------------------------------------------------------------------------------------------- Watched it already? If you liked this video or found it useful, please let me know! Your comments and feedback are very much appreciated😊 If you have questions, don't hesitate to leave me a comment down below, I will answer as soon as I can:) -------------------------------------------------------------------------------------------------------------------- For more biostatistics tools and resources, you can visit: https://biostatsquid.com/ for more • simple and clear explanations of biostatistics methods • computational biology tools • easy step-by-step tutorials in R and Python to analyse and visualise your biological data! Or follow me on Instagram at @biostatsquid: https://www.instagram.com/biostatsquid/ Don’t forget to subscribe if you don’t want to miss another video from me! -------------------------------------------------------------------------------------------------------------------- More multiple testing resources: Check the difference between different multiple testing corrections in R: https://www.stat.berkeley.edu/~mgoldman/Section0402.pdf A really cool explanation of the FDR from Statquest! https://www.youtube.com/watch?v=K8LQSvtjcEo ------------------------------------------------------------------------------------------------------------ Trash FM by Alexander Nakarada | https://www.serpentsoundstudios.com/ Music promoted by https://www.free-stock-music.com/ Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/