Sinposis

Each chapter introduces statistical and graphical ideas for analysis, underpinned by real datasets. Those ideas are then implemented via principled, step-by-step, workflows in the programming environment R. Key features include: Extensive real-world data sets and data analysis scenarios. Code examples fully-integrated into main text, with code that builds in complexity and sophistication. Quarto template files for each chapter to support literate programming practices. Functional programming examples, using tidyverse, for generating empirical statistics (bootstrap resamples, permutation tests) and working programmatically over model outputs. Unusual but important programming tricks for generating sophisticated data graphics such as network visualizations, dot-density maps, OD maps, glyphmaps, icon arrays, hypothetical outcome plots and graphical line-ups plots Every data graphic in the book is implemented via ggplot2