Version 1.1.0 Edited on April 21, 2021, to remove the broom::tidy() portion of the workflow. tl;dr When researchers decide on a sample size for an upcoming project, there are more things to consider than null-hypothesis-oriented power. Bayesian researchers might like to frame their concerns in terms of precision. Stick around to learn what and how. Are Bayesians doomed to refer to \(H_0\) 1 with sample-size planning? If you read the first post in this series (click here for a refresher), you ...
