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A Primer On Linear Algebra
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Book Synopsis A Primer on Linear Algebra by : I. N. Herstein
Download or read book A Primer on Linear Algebra written by I. N. Herstein and published by Macmillan College. This book was released on 1988-01-01 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Primer of Linear Algebra by : Gerald L. Bradley
Download or read book A Primer of Linear Algebra written by Gerald L. Bradley and published by Prentice Hall. This book was released on 1974 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to Linear Algebra by : Gordon Mills
Download or read book Introduction to Linear Algebra written by Gordon Mills and published by Routledge. This book was released on 2017-07-12 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book on linear algebra written specifically for social scientists. It deals only with those aspects of the subject applicable in the social sciences and provides a thorough understanding of linear algebra for those who wish to use it as a tool in the design, execution, and interpretation of research. Linear mathematical models play an important role in all of the social sciences. This book provides a step-by-step introduction to those parts of linear algebra which are useful in such model building. It illustrates some of the applications of linear analysis and helps the reader learn how to convert his formulation of a social science problem into algebraic terms. The author covers matrix algebra, computational methods, linear models involving discrete variables, and clear, complete explanations of necessary mathematical concepts. Prior knowledge of calculus is not required since no use is made of calculus or of complex numbers. A novel feature of the mathematical content of the book is the treatment of models expressed in terms of variables which must be whole numbers (integers). The book is distinguished by a step-by-step exposition that allows the reader to grasp quickly and fully the principles of linear algebra. All of the examples used to illustrate the text are drawn from the social sciences, enabling the reader to relate the subject to concrete problems in his field. Exercises are included as a necessary part of the text to develop points not covered in the text and to provide practice in the algebraic formulation of applied problems. An appendix gives solutions (or hints) for selected exercises.
Book Synopsis A Primer on Linear Models by : John F. Monahan
Download or read book A Primer on Linear Models written by John F. Monahan and published by CRC Press. This book was released on 2008-03-31 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample theory supporting common statistical methods.
Book Synopsis A Primer on Linear Algebra by : I. N. Herstein
Download or read book A Primer on Linear Algebra written by I. N. Herstein and published by Macmillan College. This book was released on 1988-03-01 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to Applied Linear Algebra by : Stephen Boyd
Download or read book Introduction to Applied Linear Algebra written by Stephen Boyd and published by Cambridge University Press. This book was released on 2018-06-07 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.
Book Synopsis A Mathematical Primer for Social Statistics by : John Fox
Download or read book A Mathematical Primer for Social Statistics written by John Fox and published by SAGE Publications. This book was released on 2021-01-11 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic "language" of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based and Bayesian methods. The volume concludes by applying mathematical concepts and operations to a familiar case, linear least-squares regression. The Second Edition pays more attention to visualization, including the elliptical geometry of quadratic forms and its application to statistics. It also covers some new topics, such as an introduction to Markov-Chain Monte Carlo methods, which are important in modern Bayesian statistics. A companion website includes materials that enable readers to use the R statistical computing environment to reproduce and explore computations and visualizations presented in the text. The book is an excellent companion to a "math camp" or a course designed to provide foundational mathematics needed to understand relatively advanced statistical methods.
Book Synopsis Introduction to Linear Algebra by : Gordon Mills
Download or read book Introduction to Linear Algebra written by Gordon Mills and published by Routledge. This book was released on 2017-07-12 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book on linear algebra written specifically for social scientists. It deals only with those aspects of the subject applicable in the social sciences and provides a thorough understanding of linear algebra for those who wish to use it as a tool in the design, execution, and interpretation of research. Linear mathematical models play an important role in all of the social sciences. This book provides a step-by-step introduction to those parts of linear algebra which are useful in such model building. It illustrates some of the applications of linear analysis and helps the reader learn how to convert his formulation of a social science problem into algebraic terms. The author covers matrix algebra, computational methods, linear models involving discrete variables, and clear, complete explanations of necessary mathematical concepts. Prior knowledge of calculus is not required since no use is made of calculus or of complex numbers. A novel feature of the mathematical content of the book is the treatment of models expressed in terms of variables which must be whole numbers (integers). The book is distinguished by a step-by-step exposition that allows the reader to grasp quickly and fully the principles of linear algebra. All of the examples used to illustrate the text are drawn from the social sciences, enabling the reader to relate the subject to concrete problems in his field. Exercises are included as a necessary part of the text to develop points not covered in the text and to provide practice in the algebraic formulation of applied problems. An appendix gives solutions (or hints) for selected exercises.
Book Synopsis Quantum Algorithms via Linear Algebra by : Richard J. Lipton
Download or read book Quantum Algorithms via Linear Algebra written by Richard J. Lipton and published by MIT Press. This book was released on 2014-12-05 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum computing explained in terms of elementary linear algebra, emphasizing computation and algorithms and requiring no background in physics. This introduction to quantum algorithms is concise but comprehensive, covering many key algorithms. It is mathematically rigorous but requires minimal background and assumes no knowledge of quantum theory or quantum mechanics. The book explains quantum computation in terms of elementary linear algebra; it assumes the reader will have some familiarity with vectors, matrices, and their basic properties, but offers a review of all the relevant material from linear algebra. By emphasizing computation and algorithms rather than physics, this primer makes quantum algorithms accessible to students and researchers in computer science without the complications of quantum mechanical notation, physical concepts, and philosophical issues. After explaining the development of quantum operations and computations based on linear algebra, the book presents the major quantum algorithms, from seminal algorithms by Deutsch, Jozsa, and Simon through Shor's and Grover's algorithms to recent quantum walks. It covers quantum gates, computational complexity, and some graph theory. Mathematical proofs are generally short and straightforward; quantum circuits and gates are used to illuminate linear algebra; and the discussion of complexity is anchored in computational problems rather than machine models. Quantum Algorithms via Linear Algebra is suitable for classroom use or as a reference for computer scientists and mathematicians.
Book Synopsis Linear Models and the Relevant Distributions and Matrix Algebra by : David A. Harville
Download or read book Linear Models and the Relevant Distributions and Matrix Algebra written by David A. Harville and published by CRC Press. This book was released on 2023-10-23 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: • Exercises and solutions are included throughout, from both the first and second volume • Includes coverage of additional topics not covered in the first volume • Highly valuable as a reference book for graduate students or researchers
Book Synopsis Primer for Linear Algebra by : Stephen G. Demko
Download or read book Primer for Linear Algebra written by Stephen G. Demko and published by Scott Foresman & Company. This book was released on 1989-01-01 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Solutions Manual - a Linear Algebra Primer for Financial Engineering by : Dan Stefanica
Download or read book Solutions Manual - a Linear Algebra Primer for Financial Engineering written by Dan Stefanica and published by . This book was released on 2016-08-22 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Linear Algebra Primer for Financial Engineering by : Dan Stefanica
Download or read book A Linear Algebra Primer for Financial Engineering written by Dan Stefanica and published by . This book was released on 2014-09-25 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Primer for the Mathematics of Financial Engineering by : Dan Stefanica
Download or read book A Primer for the Mathematics of Financial Engineering written by Dan Stefanica and published by . This book was released on 2011 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Linear Algebra and Matrix Analysis for Statistics by : Sudipto Banerjee
Download or read book Linear Algebra and Matrix Analysis for Statistics written by Sudipto Banerjee and published by CRC Press. This book was released on 2014-06-06 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear Algebra and Matrix Analysis for Statistics offers a gradual exposition to linear algebra without sacrificing the rigor of the subject. It presents both the vector space approach and the canonical forms in matrix theory. The book is as self-contained as possible, assuming no prior knowledge of linear algebra. The authors first address the rudimentary mechanics of linear systems using Gaussian elimination and the resulting decompositions. They introduce Euclidean vector spaces using less abstract concepts and make connections to systems of linear equations wherever possible. After illustrating the importance of the rank of a matrix, they discuss complementary subspaces, oblique projectors, orthogonality, orthogonal projections and projectors, and orthogonal reduction. The text then shows how the theoretical concepts developed are handy in analyzing solutions for linear systems. The authors also explain how determinants are useful for characterizing and deriving properties concerning matrices and linear systems. They then cover eigenvalues, eigenvectors, singular value decomposition, Jordan decomposition (including a proof), quadratic forms, and Kronecker and Hadamard products. The book concludes with accessible treatments of advanced topics, such as linear iterative systems, convergence of matrices, more general vector spaces, linear transformations, and Hilbert spaces.
Book Synopsis Matrices and Linear Transformations by : Charles G. Cullen
Download or read book Matrices and Linear Transformations written by Charles G. Cullen and published by Courier Corporation. This book was released on 2012-09-20 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Undergraduate-level introduction to linear algebra and matrix theory. Explores matrices and linear systems, vector spaces, determinants, spectral decomposition, Jordan canonical form, much more. Over 375 problems. Selected answers. 1972 edition.
Book Synopsis Introduction to Quantum Algorithms via Linear Algebra, second edition by : Richard J. Lipton
Download or read book Introduction to Quantum Algorithms via Linear Algebra, second edition written by Richard J. Lipton and published by MIT Press. This book was released on 2021-04-06 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum computing explained in terms of elementary linear algebra, emphasizing computation and algorithms and requiring no background in physics. This introduction to quantum algorithms is concise but comprehensive, covering many key algorithms. It is mathematically rigorous but requires minimal background and assumes no knowledge of quantum theory or quantum mechanics. The book explains quantum computation in terms of elementary linear algebra; it assumes the reader will have some familiarity with vectors, matrices, and their basic properties, but offers a review of the relevant material from linear algebra. By emphasizing computation and algorithms rather than physics, it makes quantum algorithms accessible to students and researchers in computer science who have not taken courses in quantum physics or delved into fine details of quantum effects, apparatus, circuits, or theory.