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Mathematics  Numerical analysis  Engineering mathematics  Numerical analysis.  Data processing.  Mathematical analysis  Mathematics.  Engineering mathematics.  Engineering analysis  Math  Science
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No applied mathematician can be properly trained without some basic un derstanding ofnumerical methods, Le., numerical analysis. And no scientist and engineer should be using a package program for numerical computa tions without understanding the program's purpose and its limitations. This book is an attempt to provide some of the required knowledge and understanding. It is written in a spirit that considers numerical analysis not merely as a tool for solving applied problems but also as a challenging and rewarding part of mathematics. The main goal is to provide insight into numerical analysis rather than merely to provide numerical recipes. The book evolved from the courses on numerical analysis I have taught since 1971 at the University ofGottingen and may be viewed as a successor of an earlier version jointly written with Bruno Brosowski [10] in 1974. It aims at presenting the basic ideas of numerical analysis in a style as concise as possible. Its volume is scaled to a oneyear course, i.e., a twosemester course, addressing secondyearstudents at a German university or advanced undergraduate or firstyear graduate students at an American university.
Numerical analysis  Numerical analysis.  Analyse numérique  Analyse numérique  Applied mathematics.  Engineering mathematics.  Numerical Analysis.  Mathematical and Computational Engineering.  Engineering  Engineering analysis  Mathematical analysis  Mathematics
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Mathematical analysis  Engineering mathematics  Engineering mathematics.  Engineering  Engineering analysis  Mathematics  Differentiable dynamical systems  Dynamique différentiable  Control theory  Commande, Théorie de la
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This book is intended for students of mathematical statistics who are interested in the early history of their subject. It gives detailed algebraic descriptions of the fitting of linear relationships by the method of least squares (L ) and the related least absolute 2 deviations (L ) and minimax absolute deviations (Loo) procedures. These traditional line J fitting procedures are, of course, also addressed in conventional statistical textbooks, but the discussion of their historical background is usually extremely slight, if not entirely absent. The present book complements the analysis of these procedures given in S.M. Stigler'S excellent work The History of Statistics: The Quantification of Uncertainty before 1900. However, the present book gives a more detailed account of the algebraic structure underlying these traditional fitting procedures. It is anticipated that readers of the present book will obtain a clear understanding of the historical background to these and other commonly used statistical procedures. Further, a careful consideration of the wide variety of distinct approaches to a particular topic, such as the method of least squares, will give the reader valuable insights into the essential nature of the selected topic.
Mathematical statistics  History.  519.233  Parametric methods  519.233 Parametric methods  History  Applied mathematics.  Engineering mathematics.  Applications of Mathematics.  Engineering  Engineering analysis  Mathematical analysis  Mathematics
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Applied physical engineering  Functional analysis  Mathematical physics  Functional analysis.  Engineering mathematics.  Engineering  Engineering analysis  Mathematical analysis  Functional calculus  Calculus of variations  Functional equations  Integral equations  Mathematics  Engineering mathematics
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Engineering  Engineering mathematics  Computeraided engineering  Computeraided engineering.  Engineering mathematics.  Data processing  Data processing.  Engineering analysis  CAE  Mathematical analysis  Mathematics  Engineering sciences. Technology  Computer. Automation
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This is the second of a twovolume work intended to function as a textbook well as a reference work for economic for graduate students in economics, as scholars who are either working in theory, or who have a strong interest in economic theory. While it is not necessary that a student read the first volume before tackling this one, it may make things easier to have done so. In any case, the student undertaking a serious study of this volume should be familiar with the theories of continuity, convergence and convexity in Euclidean space, and have had a fairly sophisticated semester's work in Linear Algebra. While I have set forth my reasons for writing these volumes in the preface to Volume 1 of this work, it is perhaps in order to repeat that explanation here. I have undertaken this project for three principal reasons. In the first place, I have collected a number of results which are frequently useful in economics, but for which exact statements and proofs are rather difficult to find; for example, a number of results on convex sets and their separation by hyperplanes, some results on correspondences, and some results concerning support functions and their duals. Secondly, while the mathematical top ics taken up in these two volumes are generally taught somewhere in the mathematics curriculum, they are never (insofar as I am aware) done in a twocourse sequence as they are arranged here.
Mathematics  Economics, Mathematical  Economics, Mathematical.  Economic theory.  Applied mathematics.  Engineering mathematics.  Economic Theory/Quantitative Economics/Mathematical Methods.  Applications of Mathematics.  Engineering  Engineering analysis  Mathematical analysis  Economic theory  Political economy  Social sciences  Economic man
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Engineering mathematics  Inverse problems (Differential equations)  Engineering mathematics.  Engineering analysis  Differential equations  Mathematical analysis  Engineering.  Mathematics.  Science (General)  Engineering  Material Science and Metallurgy  Civil Engineering  Fluid Engineering  General and Others  Industrial Engineering  Composites  Applied Mathematics
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Engineering mathematics  Mathematics  Industrial applications  Mathematical Sciences  Applied Mathematics  Mathematics.  Industrial applications.  Math  Engineering  Engineering analysis  Science  Mathematical analysis  Operations research  Operations research.  Operational analysis  Operational research  Industrial engineering  Management science  Research  System theory  wiskunde  mathematics  Toegepaste wiskunde
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The overall goal of Modelling and Applications in Mathematics Education is to provide a comprehensive overview of the stateoftheart in the field of modelling and applications in mathematics education. Key issues are dealt with, among which are the following: Epistemology and the relationships between mathematics and the "rest of the world"; the meaning of mathematical modelling and its process components; the respect in which the distinction between pure mathematics and applications of mathematics make sense Authenticity and Goals dealing with modelling and applications in mathematics teaching; appropriate balance between modelling activities and other mathematical activities; the role that authentic problem situations play in modelling and applications activities Modelling Competencies: characterizing how a student's modelling competency can be characterized; identifiable subcompetencies, and the ways they constitute a general modelling competency; developing competency over time Mathematical Competencies: identifying the most important mathematical competencies that students should acquire, and how modelling and applications activities can contribute toward building up these competencies; the meaning of "Mathematical Literacy" in relation to modelling Modelling Pedagogy: appropriate pedagogical principles and strategies for the development of modelling courses and their teaching; the role of technology in the teaching of modelling and applications Implementation and Practice: the role of modelling and applications in everyday mathematics teaching; major impediments and obstacles; advancing the use of modelling examples in everyday classrooms; documenting successful implementation of modelling in mathematics teaching Assessment and Evaluation: assessment modes that capture the essential components of modelling competency; modes available for modelling and applications courses and curricula; appropriate strategies to implement new assessment and evaluation modes in practice The contributing authors are eminent members of the mathematics education community. Modelling and Applications in Mathematics Education will be of special interest to mathematics educators, teacher educators, researchers, education administrators, curriculum developers and student teachers.
Mathematics  Mathematical models.  Study and teaching.  Models, Mathematical  Simulation methods  Didactics of mathematics  Mathematics.  Mathematics Education.  Applications of Mathematics.  Math  Science  Mathematics—Study and teaching .  Applied mathematics.  Engineering mathematics.  Engineering  Engineering analysis  Mathematical analysis
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