Once data analysis is complete, results need to be shared with a variety of audiences. As statisticians, it is imperative that we explain everything from a simple t-test to a complex nonlinear model in an approachable way. We need to: explain the results of the analyses; encourage the understanding of what the results do and do not imply; and engage the audience to use the results to take appropriate action. This session will provide a brief guide of how to explain things in non-statistical jargon without insulting the intelligence of our audience. This will include examples of both language to use as well as suggestions for displaying results as well.