Why read A First Course in Statistical Programming with R?

Book cover of A First Course in Statistical Programming with R

Book description

This third edition of Braun and Murdoch's bestselling textbook now includes discussion of the use and design principles of the tidyverse packages in R, including expanded coverage of ggplot2, and R Markdown. The expanded simulation chapter introduces the Box-Muller and Metropolis-Hastings algorithms. New examples and exercises have been added throughout.…

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Why read it?

1 author picked A First Course in Statistical Programming with R as one of their favorite books. Why do they recommend it?

Tilman M. Davies

Author

From well-known authorities in the R-sphere (including a former R Core Team member), this is a long-standing text whose first edition was one of the early books intended to teach R to beginners. It provides concise instructions and examples on how R is used as a programming language before focusing on 'number-crunching' statistical methods that are typically seen as computationally intensive. One of the notable features of this book is the statistical methods at hand are not just illustrated using 'black-box' code--the reader is provided with the necessary mathematical detail to understand what's going on behind the scenes for those…

From Tilman's list on The best introductory books for programming and data science with R.