This book is meant for BSc, BSc (Honors), and MSc students who offer statistics as a primary subject. The book is very different from the existing books in many ways. Apart from regular topics covered in the Statistical Inference course, it also covers some of the author's research work.
The book includes eleven chapters, out of which five chapters are on the theory of estimation, and the remaining are on the testing of hypotheses. The purpose of this book is to give an up-to-date exposition of Statistical Inference with less rigorous treatment on mathematics, giving realistic illustrations and simple proofs of the theorems so that the readers may easily digest it. The author's thirty-three years of teaching experience in postgraduate and refreshers courses programs enhanced the book's quality to a new level to have fresh expertise in statistics.
Table of Contents
Sufficiency and Completeness
Unbiased Estimations
Efficiency of Estimator
Criteria and Methods of Estimation in Large Sample
Decision Theory
Basic Principles of Testing of Hypotheses
Neyman Theory
Unbiased Tests
Similar Tests
Sequential Probability Ratio Test (SPRT) and Likelihood Ration Test (LRT)
Non - Parametric Methods
UMP Tests for Truncated Distributions
Asymptotic Tests for Several Exponential Family of Distribution
Asymptotic Tests for Several Truncated Distributions
Appendix
References
Index
Author
- Shantilal R. Patel
