: The foundational theory used to construct the Most Powerful (MP) and Uniformly Most Powerful (UMP) tests for simple and composite hypotheses.
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Point estimation involves choosing a single statistic (a specific value) to estimate a population parameter. Srivastava provides a thorough analysis of what makes an estimator "good."
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: A method to improve an estimator's efficiency by conditioning it on a sufficient statistic.
The work is divided into two distinct but complementary volumes, each designed for a specific level of study and focused on a primary branch of inference.
Crucial methods for regression models and categorical data analysis. Testing of Hypotheses : The foundational theory used to construct the
Co-authored with Namita Srivastava, this text focuses on the Neyman-Pearson mathematical foundations for hypothesis testing. Methodology
Understanding the risks of falsely rejecting a true null hypothesis versus failing to reject a false one.
If you are looking to access the insights from Manoj Kumar Srivastava's work on statistical inference, consider the following legitimate avenues: Point estimation involves choosing a single statistic (a
Determining the unknown parameters of a population.
The book "Statistical Inference" by Manoj Kumar Srivastava covers a wide range of topics, including:
: Chapters discuss the Method of Maximum Likelihood, Bayes, Empirical Bayes, and Minimax estimation. Asymptotic Theory