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.
The revised and expanded edition of this textbook presents concepts and applications of random processes with the addition of material on biological modeling. While still treating many problems in fields such as engineering and mathematical physics, the book also focuses on the topics of cancerous mutations, influenza evolution, drug resistance, and immune response
Ideal for undergraduates entering their first analysis course, this concise textbook covers essential calculus concepts and number systems. It features unique examples and exercises designed to reinforce understanding of basic principles, ensuring a solid foundation for more advanced studies in analysis.