The objective of inferential statistics is to describe population parameters using samples. In the lecture, we will study extensively inferential statistics when constructed from a probabilistic model, and in the lab we will see how to use R to perform analysis based on these methods. Prior to that, though, we explore techniques based on computational methods such as simulation and bootstrapping. Not only do computational methods provide a good first step for thinking about later methods, they are also very useful when one does not have a probability model available for inference, perhaps because such a model would be very difficult to construct.