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Introduction to the Theory of Statistics
  • Language: en
  • Pages: 564

Introduction to the Theory of Statistics

This text offers a sound and self-contained introduction to classical statistical theory. The material is suitable for students who have successfully completed a single year's course in calculus, and no prior knowledge of statistics or probability is assumed. Practical examples and problems are included.

An Introduction to the Theory of Statistics
  • Language: en
  • Pages: 426

An Introduction to the Theory of Statistics

  • Type: Book
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  • Published: 2018-02-19
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  • Publisher: Palala Press

This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

Introduction to the Theory of Statistical Inference
  • Language: en
  • Pages: 284

Introduction to the Theory of Statistical Inference

  • Type: Book
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  • Published: 2016-04-19
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  • Publisher: CRC Press

Based on the authors’ lecture notes, Introduction to the Theory of Statistical Inference presents concise yet complete coverage of statistical inference theory, focusing on the fundamental classical principles. Suitable for a second-semester undergraduate course on statistical inference, the book offers proofs to support the mathematics. It illustrates core concepts using cartoons and provides solutions to all examples and problems. Highlights Basic notations and ideas of statistical inference are explained in a mathematically rigorous, but understandable, form Classroom-tested and designed for students of mathematical statistics Examples, applications of the general theory to special case...

Introduction to the Theory of Statistics
  • Language: en
  • Pages: 564

Introduction to the Theory of Statistics

None

Introduction to Probability Theory and Statistical Inference
  • Language: en
  • Pages: 430

Introduction to Probability Theory and Statistical Inference

  • Type: Book
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  • Published: 1974
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  • Publisher: Unknown

Discusses probability theory and to many methods used in problems of statistical inference. The Third Edition features material on descriptive statistics. Cramer-Rao bounds for variance of estimators, two-sample inference procedures, bivariate normal probability law, F-Distribution, and the analysis of variance and non-parametric procedures. Contains numerous practical examples and exercises.

Information Theory and Statistics
  • Language: en
  • Pages: 416

Information Theory and Statistics

Highly useful text studies logarithmic measures of information and their application to testing statistical hypotheses. Includes numerous worked examples and problems. References. Glossary. Appendix. 1968 2nd, revised edition.

Introduction to the Theory of Statistical Inference
  • Language: en
  • Pages: 284

Introduction to the Theory of Statistical Inference

  • Type: Book
  • -
  • Published: 2016-04-19
  • -
  • Publisher: CRC Press

Based on the authors’ lecture notes, Introduction to the Theory of Statistical Inference presents concise yet complete coverage of statistical inference theory, focusing on the fundamental classical principles. Suitable for a second-semester undergraduate course on statistical inference, the book offers proofs to support the mathematics. It illustrates core concepts using cartoons and provides solutions to all examples and problems. Highlights Basic notations and ideas of statistical inference are explained in a mathematically rigorous, but understandable, form Classroom-tested and designed for students of mathematical statistics Examples, applications of the general theory to special case...

Asymptotic Theory of Statistics and Probability
  • Language: en
  • Pages: 722

Asymptotic Theory of Statistics and Probability

This unique book delivers an encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical problems and probabilistic issues and tools. The book is unique in its detailed coverage of fundamental topics. It is written in an extremely lucid style, with an emphasis on the conceptual discussion of the importance of a problem and the impact and relevance of the theorems. There is no other book in large sample theory that matches this book in coverage, exercises and examples, bibliography, and lucid conceptual discussion of issues and theorems.

Introduction to the theory of statistics
  • Language: en
  • Pages: 242

Introduction to the theory of statistics

Probability; Populations and samples; Estimation; Confidence sets; Tests of hypotheses; Decision theory and bayesian methods; Linear models; Nonparametric methods.

An Elementary Introduction to Statistical Learning Theory
  • Language: en
  • Pages: 288

An Elementary Introduction to Statistical Learning Theory

A thought-provoking look at statistical learning theory and its role in understanding human learning and inductive reasoning A joint endeavor from leading researchers in the fields of philosophy and electrical engineering, An Elementary Introduction to Statistical Learning Theory is a comprehensive and accessible primer on the rapidly evolving fields of statistical pattern recognition and statistical learning theory. Explaining these areas at a level and in a way that is not often found in other books on the topic, the authors present the basic theory behind contemporary machine learning and uniquely utilize its foundations as a framework for philosophical thinking about inductive inference....