This week focuses on statistical inference: specifically, hypothesis testing. The learning goals for this week are: (1) an intuition for what null hypothesis, model, and null distribution of a test statistic is; (2) an understanding of what a p-value is and isn't; (3) how to simulate from a null model and use these simulations for inference.
The slides are here.
The presentation uses some shiny apps–code for these apps is found on the GitHub site. For now you will have to run them locally–we're looking at having them hosted online so they can be played with at will.
An R script (a demo/practical) which uses some of the concepts in the lecture are also on the GitHub site.
