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Mathematicalstatisticsparimalmukhopadhyay
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Valrie Furch
Dec 10, 2023, 12:39:38 AM12/10/23
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Mathematical Statistics by Parimal Mukhopadhyay: A Comprehensive Textbook for Students and Researchers
Mathematical statistics is a branch of mathematics that deals with the collection, analysis, interpretation, and presentation of data. It is used to draw conclusions and make decisions based on data from various fields such as science, engineering, economics, social sciences, and more.
One of the most popular and widely used textbooks on mathematical statistics is Mathematical Statistics by Parimal Mukhopadhyay. This book covers all the major topics of mathematical statistics, such as probability theory, random variables, distributions, sampling theory, estimation, testing of hypotheses, regression analysis, analysis of variance, multivariate analysis, and more. The book also includes numerous examples, exercises, and applications to illustrate the concepts and methods.
mathematicalstatisticsparimalmukhopadhyay
Download Zip https://ckonti.com/2wJwhp
Parimal Mukhopadhyay is a professor of statistics at the Indian Statistical Institute in Kolkata. He has more than 40 years of teaching and research experience in mathematical statistics and its applications. He has authored several other books on statistics, such as Applied Statistics, Multivariate Statistical Analysis, Nonparametric Statistical Inference, and more. He has also published many research papers in reputed journals and received several awards and honors for his contributions to statistics.
Mathematical Statistics by Parimal Mukhopadhyay is a comprehensive and rigorous textbook that provides a solid foundation for students and researchers who want to learn and apply mathematical statistics. The book is suitable for undergraduate and postgraduate courses in statistics, mathematics, engineering, and other related disciplines. The book is also a valuable reference for practitioners and professionals who use statistical methods in their work.
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The book is divided into 15 chapters, each covering a specific topic of mathematical statistics. The first chapter introduces the basic concepts and tools of statistics, such as data types, descriptive statistics, graphical methods, and set theory. The second chapter deals with the fundamentals of probability theory, such as axioms, rules, conditional probability, independence, Bayes' theorem, and combinatorics. The third chapter discusses the properties and functions of random variables, such as expectation, variance, moment generating function, characteristic function, and transformation.
The fourth chapter introduces the concept of distribution and describes some of the most common discrete and continuous distributions, such as binomial, Poisson, normal, exponential, gamma, beta, and chi-square. The fifth chapter covers the topics of sampling theory and sampling distributions, such as random sampling, sampling methods, central limit theorem, standard error, t-distribution, F-distribution, and chi-square distribution. The sixth chapter explains the principles and methods of point estimation, such as unbiasedness, consistency, efficiency, sufficiency, completeness, Rao-Blackwell theorem, Lehmann-Scheffe theorem, maximum likelihood estimation, method of moments, and confidence intervals.
The seventh chapter deals with the topics of testing of hypotheses and decision theory, such as types of errors, power function, Neyman-Pearson lemma, likelihood ratio test, uniformly most powerful test, unbiased test, invariant test, sequential test, Bayesian test, minimax criterion, and admissibility. The eighth chapter discusses the methods of linear regression analysis and correlation analysis, such as simple linear regression model, least squares method, coefficient of determination and correlation coefficient. The ninth chapter covers the topics of analysis of variance and experimental design.
d8cbe59d7d
Mathematical Statistics by Parimal Mukhopadhyay: A Comprehensive Textbook for Students and Researchers
Mathematical statistics is a branch of mathematics that deals with the collection, analysis, interpretation, and presentation of data. It is used to draw conclusions and make decisions based on data from various fields such as science, engineering, economics, social sciences, and more.
One of the most popular and widely used textbooks on mathematical statistics is Mathematical Statistics by Parimal Mukhopadhyay. This book covers all the major topics of mathematical statistics, such as probability theory, random variables, distributions, sampling theory, estimation, testing of hypotheses, regression analysis, analysis of variance, multivariate analysis, and more. The book also includes numerous examples, exercises, and applications to illustrate the concepts and methods.
mathematicalstatisticsparimalmukhopadhyay
Download Zip https://ckonti.com/2wJwhp
Parimal Mukhopadhyay is a professor of statistics at the Indian Statistical Institute in Kolkata. He has more than 40 years of teaching and research experience in mathematical statistics and its applications. He has authored several other books on statistics, such as Applied Statistics, Multivariate Statistical Analysis, Nonparametric Statistical Inference, and more. He has also published many research papers in reputed journals and received several awards and honors for his contributions to statistics.
Mathematical Statistics by Parimal Mukhopadhyay is a comprehensive and rigorous textbook that provides a solid foundation for students and researchers who want to learn and apply mathematical statistics. The book is suitable for undergraduate and postgraduate courses in statistics, mathematics, engineering, and other related disciplines. The book is also a valuable reference for practitioners and professionals who use statistical methods in their work.
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The book is divided into 15 chapters, each covering a specific topic of mathematical statistics. The first chapter introduces the basic concepts and tools of statistics, such as data types, descriptive statistics, graphical methods, and set theory. The second chapter deals with the fundamentals of probability theory, such as axioms, rules, conditional probability, independence, Bayes' theorem, and combinatorics. The third chapter discusses the properties and functions of random variables, such as expectation, variance, moment generating function, characteristic function, and transformation.
The fourth chapter introduces the concept of distribution and describes some of the most common discrete and continuous distributions, such as binomial, Poisson, normal, exponential, gamma, beta, and chi-square. The fifth chapter covers the topics of sampling theory and sampling distributions, such as random sampling, sampling methods, central limit theorem, standard error, t-distribution, F-distribution, and chi-square distribution. The sixth chapter explains the principles and methods of point estimation, such as unbiasedness, consistency, efficiency, sufficiency, completeness, Rao-Blackwell theorem, Lehmann-Scheffe theorem, maximum likelihood estimation, method of moments, and confidence intervals.
The seventh chapter deals with the topics of testing of hypotheses and decision theory, such as types of errors, power function, Neyman-Pearson lemma, likelihood ratio test, uniformly most powerful test, unbiased test, invariant test, sequential test, Bayesian test, minimax criterion, and admissibility. The eighth chapter discusses the methods of linear regression analysis and correlation analysis, such as simple linear regression model, least squares method, coefficient of determination and correlation coefficient. The ninth chapter covers the topics of analysis of variance and experimental design.
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