This second edition textbook provides a practical introduction to probability for undergraduates, accommodating various backgrounds. It covers essential concepts with sensitivity to calculus difficulties and includes new examples and exercises. The text expands on estimation in the last chapters, forming a foundation for further study in mathematical statistics.
The textbook offers a comprehensive transition from undergraduate analysis to graduate-level measure theory, emphasizing classical foundations and modern topics such as metric spaces and Lebesgue integration. It is structured for a two-semester course, focusing on metric spaces and topology to prepare students for the abstraction and rigor of graduate studies. By striking a balance between overly formal and too casual approaches, it provides an accessible yet rigorous introduction to real analysis.