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Co-authored with Namita Srivastava, this text focuses on the Neyman-Pearson mathematical foundations for hypothesis testing. Methodology
: The foundational theory used to construct the Most Powerful (MP) and Uniformly Most Powerful (UMP) tests for simple and composite hypotheses.
Manoj Kumar Srivastava has authored two primary textbooks on statistical inference, often used in undergraduate and postgraduate statistics courses. These books are published by PHI Learning (formerly Prentice Hall of India). Statistical Inference: Testing of Hypotheses Statistical Inference By Manoj Kumar Srivastava Pdf
: It begins with the foundations of data summarization, specifically the principle of sufficiency and minimal sufficient statistics. Key Estimators
The PDF edition (which generally mirrors the latest printed edition) is sprawling, often exceeding 500 pages. Here is a breakdown of the major modules you will find inside:
If you are looking for specific concepts or a summary of a specific chapter (e.g., "Neyman-Pearson Lemma" or "Method of Moments"), I can provide a detailed explanation here. Legal research sharing platforms and Google Scholar can
Academic reviewers and students frequently highlight specific features that give Manoj Kumar Srivastava’s work an "edge" over other international texts like Casella & Berger: Statistical Inference Definition - BYJU'S
The text does not stick purely to the classical (frequentist) approach. It offers a strong section on Bayesian inference, including: Hierarchical Bayes Models. Equivariant Estimators within a Bayesian framework. Why Choose This Book?
Srivastava’s text meticulously breaks down statistical inference into its primary mathematical components. Understanding these pillars is essential for mastering the subject. 1. Point Estimation Manoj Kumar Srivastava has authored two primary textbooks
A detailed table of contents for the 2014/2022 edition reveals the book's systematic structure:
A sequel to the first volume, this 808-page text introduces estimation problems based on the work of Sir R.A. Fisher. It provides a detailed account of Uniformly Minimum Variance Unbiased Estimators (UMVUE) , the Rao-Blackwell theorem, and Bayesian approaches including Empirical and Hierarchical Bayes. Key Topics and Curriculum Coverage
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