Large-sample techniques are essential because they provide solutions for complex problems where exact distributions are intractable. As noted by Jiming Jiang in the preface, these techniques simplify and justify statistical solutions while guiding researchers toward better methods, though he warns that misuse can lead to serious errors, such as misinterpreting the asymptotic null distribution of a likelihood ratio test. Hardcover: ISBN 978-3-030-91694-7 Paperback: ISBN 978-3-030-91697-8 eBook: ISBN 978-3-030-91695-4
A foundational course in calculus and mathematical statistics is required. Why It Matters Large Sample Techniques for Statistics (Springe...
Explores limit theorems for various types of observational data. Why It Matters Explores limit theorems for various
It is designed for a broad academic range, from senior undergraduates to doctoral researchers. Key Topics: The second edition includes a new
The book is divided into 16 chapters, with the first ten including case studies to demonstrate real-world utility. Key Topics:
The second edition includes a new chapter on random matrix theory and expanded sections on mixed effects models.
The 2nd edition (2022) of this comprehensive guide bridges the gap between formal theory and practical application. Unlike many texts that focus solely on rigorous proofs, this book emphasizes developing analytical thinking skills and intuition for asymptotic arguments.