Estimating R: Multiple Testing and P-values

This lecture covers the estimation of R in multiple testing scenarios, where numerous P-values are computed for similar hypotheses. An example of a genome-wide analysis is presented, assessing the association between single nucleotide polymorphisms and protein expression. The calculation of P-values is explained, focusing on the reliability of the process and the challenges of normal approximation. Various plots and statistical methods are discussed to analyze the data, including exponential plotting positions and mean excess plots. The lecture concludes with a discussion on changepoint analysis and the use of threshold values to test hypotheses, providing insights into the significance of certain data points.