Linear algebra and linear models, second edition [electronic resource] / R. B. Bapat.

Bapat, R. B.
Call Number
512.5
Author
Bapat, R. B.
Title
Linear algebra and linear models, second edition R. B. Bapat.
Edition
2nd ed.
Physical Description
1 online resource (198 pages)
Series
Texts and Readings in Mathematics ; 1
Contents
Linear algebra and linear models, second edition -- Contents -- Preface -- About the Second Edition -- Chapter 1: Vector Spaces and Matrices -- Chapter 2: Linear Estimation -- Chapter 3: Tests of Linear Hypotheses -- Chapter 4: Singular Values and Their Applications -- Chapter 5: Block Designs and Optimality -- Chapter 6: Rank Additivity -- Notes -- References -- Index -- Notation Index.
Summary
Linear Algebra and Linear Models comprises a concise and rigorous introduction to linear algebra required for statistics followed by the basic aspects of the theory of linear estimation and hypothesis testing. Emphasis is given to the approach using generalized inverses. Topics such as the multivariate normal distribution and distribution of quadratic forms are included. For this third edition, the material has been reorganised to develop the linear algebra in the first six chapters. It will serve as a first course on linear algebra that is especially suitable for students of statistics or those looking for a matrix theoretic approach to the subject. Other key features include: - coverage of topics such as rank additivity, inequalities for eigenvalues and singular values - a new chapter on linear mixed models - over seventy additional problems on rank: the matrix rank is an important and rich topic with connections to many aspects of linear algebra such as generalized inverses, idempotent matrices and partitioned matrices This text is aimed primarily at advanced undergraduate and first-year graduate students taking courses in linear algebra, linear models, multivariate analysis and design of experiments. A wealth of exercises, complete with hints and solutions, help to consolidate understanding. Researchers in mathematics and statistics will also find the book a useful source of results and problems
Subject
BUSINESS & ECONOMICS / Statistics.
MATHEMATICS / Algebra / Linear.
MATHEMATICS / Probability & Statistics / General.
Electronic books.
Multimedia
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$a Linear algebra and linear models, second edition -- Contents -- Preface -- About the Second Edition -- Chapter 1: Vector Spaces and Matrices -- Chapter 2: Linear Estimation -- Chapter 3: Tests of Linear Hypotheses -- Chapter 4: Singular Values and Their Applications -- Chapter 5: Block Designs and Optimality -- Chapter 6: Rank Additivity -- Notes -- References -- Index -- Notation Index.
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$a Linear Algebra and Linear Models comprises a concise and rigorous introduction to linear algebra required for statistics followed by the basic aspects of the theory of linear estimation and hypothesis testing. Emphasis is given to the approach using generalized inverses. Topics such as the multivariate normal distribution and distribution of quadratic forms are included.  For this third edition, the material has been reorganised to develop the linear algebra in the first six chapters. It will serve as a first course on linear algebra that is especially suitable for students of statistics or those looking for a matrix theoretic approach to the subject. Other key features include: - coverage of topics such as rank additivity, inequalities for eigenvalues and singular values - a new chapter on linear mixed models - over seventy additional problems on rank: the matrix rank is an important and rich topic with connections to many aspects of linear algebra such as generalized inverses, idempotent matrices and partitioned matrices  This text is aimed primarily at advanced undergraduate and first-year graduate students taking courses in linear algebra, linear models, multivariate analysis and design of experiments. A wealth of exercises, complete with hints and solutions, help to consolidate understanding. Researchers in mathematics and statistics will also find the book a useful source of results and problems
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Summary
Linear Algebra and Linear Models comprises a concise and rigorous introduction to linear algebra required for statistics followed by the basic aspects of the theory of linear estimation and hypothesis testing. Emphasis is given to the approach using generalized inverses. Topics such as the multivariate normal distribution and distribution of quadratic forms are included. For this third edition, the material has been reorganised to develop the linear algebra in the first six chapters. It will serve as a first course on linear algebra that is especially suitable for students of statistics or those looking for a matrix theoretic approach to the subject. Other key features include: - coverage of topics such as rank additivity, inequalities for eigenvalues and singular values - a new chapter on linear mixed models - over seventy additional problems on rank: the matrix rank is an important and rich topic with connections to many aspects of linear algebra such as generalized inverses, idempotent matrices and partitioned matrices This text is aimed primarily at advanced undergraduate and first-year graduate students taking courses in linear algebra, linear models, multivariate analysis and design of experiments. A wealth of exercises, complete with hints and solutions, help to consolidate understanding. Researchers in mathematics and statistics will also find the book a useful source of results and problems
Contents
Linear algebra and linear models, second edition -- Contents -- Preface -- About the Second Edition -- Chapter 1: Vector Spaces and Matrices -- Chapter 2: Linear Estimation -- Chapter 3: Tests of Linear Hypotheses -- Chapter 4: Singular Values and Their Applications -- Chapter 5: Block Designs and Optimality -- Chapter 6: Rank Additivity -- Notes -- References -- Index -- Notation Index.
Subject
BUSINESS & ECONOMICS / Statistics.
MATHEMATICS / Algebra / Linear.
MATHEMATICS / Probability & Statistics / General.
Electronic books.
Multimedia