This book is designed to bridge the gap between traditional textbooks in statistics and more advanced books that include the sophisticated nonparametric techniques. It covers topics in parametric and nonparametric large-sample estimation theory. The exposition is based on a collection of relatively simple statistical models. It gives a thorough mathematical analysis for each of them with all the rigorous proofs and explanations. The book also includes a number of helpful exercises.
Prepare students for assessment with plenty of practice questions, worked examples and skill-focused exercises. Help build connections between topics with...
This series has been developed specifically for the Cambridge International AS & A Level Mathematics (9709) syllabus to be examined from 2020. Cambridge...
G.H. Hardy’s text is a good single volume refresher course for work in analysis and more advanced algebra, including number theory. Not quite as modern...
Add Comment