Название: Statistics by Simulation: A Synthetic Data Approach
Автор: Carsten F. Dormann, Aaron M. Ellison
Издательство: Princeton University Press
Год: 2025
Страниц: 457
Язык: английский
Формат: pdf (true)
Размер: 12.9 MB
An accessible guide to understanding statistics using simulations, with examples from a range of scientific disciplines. Real-world challenges such as small sample sizes, skewed distributions of data, biased sampling designs, and more predictors than data points are pushing the limits of classical statistical analysis. This textbook provides a new tool for the statistical toolkit: data simulations. It shows that using simulation and data-generating models is an excellent way to validate statistical reasoning and to augment study design and statistical analysis with planning and visualization. All of our examples are accompanied by reproducible code (in the R programming language) that can be modified easily for related problems or translated into comparable software or programming languages such as Python or Julia using large language models such as Llama, StarCoder, or BLOOM. The 12 chapters of the book could be comfortably covered in a semester-long, discipline-specific course in applied statistics for (post)graduate students or advanced undergraduates.