Anyone who can type commands into R but that is not the same as actually 'doing' statistics for analytics. They may even misuse those methods, and it's an entirely different thing to really understand what's happening. Knowledge is what really drives each phase of your analysis, and create effective models for the business to use in order to create actionable insights. It can be difficult to see when someone is building faulty statistical models, especially when their intentions are good, and their results look pretty! Results are important, and it's down to you to create models that are sound and robust. In this session, we will look at modeling techniques in Analytics using R, using our boozy day at the Guinness factory as a backdrop to understanding why statistical learning is important for analytics today.