Presents a practical approach to rank-based univariate inference and explores the links between the theories of stochastic processes and robustness and efficiency of rank tests and estimators. Novel visualisation tools for data diagnostics for rank-based procedures are introduced along with practical examples of R-codes and R-packages with applications and case-studies from the biosciences field. A supporting website features datasets and R code enabling readers to implement rank procedures computationally in R and to support the inference with a proper data diagnostics. Practical examples, exercises and solutions are presented throughout.