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Classical Numerical Methods in Scientific Computing

Contributors: van Kan, Segal, and Vermolen

Publisher: TU Delft Open

License: CC BY

Partial differential equations are paramount in mathematical modelling with applications in engineering and science. The book starts with a crash course on partial differential equations in order to familiarize the reader with fundamental properties such as existence, uniqueness and possibly existing maximum principles. The main topic of the book entails the description of classical numerical methods that are used to approximate the solution of partial differential equations. The focus is on discretization methods such as the finite difference, finite volume and finite element method. The manuscript also makes a short excursion to the solution of large sets of (non)linear algebraic equations that result after application of discretization method to partial differential equations. The book treats the construction of such discretization methods, as well as some error analysis, where it is noted that the error analysis for the finite element method is merely descriptive, rather than rigorous from a mathematical point of view. The last chapters focus on time integration issues for classical time-dependent partial differential equations. After reading the book, the reader should be able to derive finite element methods, to implement the methods and to judge whether the obtained approximations are consistent with the solution to the partial differential equations. The reader will also obtain these skills for the other classical discretization methods. Acquiring such fundamental knowledge will allow the reader to continue studying more advanced methods like meshfree methods, discontinuous Galerkin methods and spectral methods for the approximation of solutions to partial differential equations.

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Numerical Methods in Scientific Computing

Contributors: van Kan, Segal, and Vermolen

Publisher: TU Delft Open

License: CC BY

This is a book about numerically solving partial differential equations occurring in technical and physical contexts and the authors have set themselves a more ambitious target than to just talk about the numerics. Their aim is to show the place of numerical solutions in the general modeling process and this must inevitably lead to considerations about modeling itself. Partial differential equations usually are a consequence of applying first principles to a technical or physical problem at hand. That means, that most of the time the physics also have to be taken into account especially for validation of the numerical solution obtained. This book aims especially at engineers and scientists who have ’real world’ problems. It will concern itself less with pesky mathematical detail. For the interested reader though, we have included sections on mathematical theory to provide the necessary mathematical background. Since this treatment had to be on the superficial side we have provided further reference to the literature where necessary.

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Υπολογιστική Φυσική: Ένα βιβλίο του Κωνσταντίνου Αναγνωστόπουλου - δεύτερη έκδοση

Contributor: Αναγνωστόπουλος

Publisher: National Technical University of Athens

License: CC BY-SA

Το βιβλίο αυτό είναι μια εισαγωγή στις υπολογιστικές μεθόδους που χρησιμοποιούνται στη φυσική και άλλα επιστημονικά πεδία. Απευθύνεται σε κοινό που έχει ήδη εκτεθεί σε μαθήματα γενικής φυσικής που διδάσκονται στα δύο πρώτα έτη πανεπιστημιακών τμημάτων θετικών επιστημών και επιστημών του μηχανικού. Δεν υποθέτει κανένα υπόβαθρο αριθμητικής ανάλυσης, προγραμματισμού ή χρήσης υπολογιστή και παρουσιάζει ό,τι είναι απαραίτητο για την επίλυση των προβλημάτων που παρουσιάζονται στο βιβλίο. Μπορεί να χρησιμοποιηθεί ως κύριο σύγγραμμα σε εισαγωγικά μαθήματα υπολογιστικής φυσικής και επιστημονικού προγραμματισμού.

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COMPUTATIONAL PHYSICS: A Practical Introduction to Computational Physics and Scientific Computing (using C++) - Second Edition

Contributor: Anagnostopoulos

Publisher: National Technical University of Athens

License: CC BY-SA

This book is an introduction to the computational methods used in physics, but also in other scientific fields. It is addressed to an audience that has already been exposed to the introductory level of college physics, usually taught during the first two years of an undergraduate program in science and engineering. It assumes no prior knowledge of numerical analysis, programming or computers and teaches whatever is necessary for the solution of the problems addressed in the text. It can be used as a textbook in introductory computational physics or scientific computing classes.

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The Art of Polynomial Interpolation

Contributor: Murphy

Publisher: Pennsylvania State University

License: CC BY-NC

The inspiration for this text grew out of a simple question that emerged over a number of years of teaching math to Middle School, High School and College students.

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Mathematics for Biomedical Physics

Contributor: Wadehra

Publisher: Wayne State University Library System

License: CC BY

Mathematics for Biomedical Physics is an open access peer-reviewed textbook geared to introduce several mathematical topics at the rudimentary level so that students can appreciate the applications of mathematics to the interdisciplinary field of biomedical physics. Most of the topics are presented in their simplest but rigorous form so that students can easily understand the advanced form of these topics when the need arises. Several end-of-chapter problems and chapter examples relate the applications of mathematics to biomedical physics. After mastering the topics of this book, students would be ready to embark on quantitative thinking in various topics of biology and medicine

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Introduction to Applied Statistics for Psychology Students

Contributor: Sarty

Publisher: University of Saskatchewan

License: CC BY-NC-SA

Introduction to Applied Statistics for Psychology Students, by Gordon E. Sarty (Professor, Department of Psychology, University of Saskatchewan) began as a textbook published in PDF format, in various editions between 2014-2017. The book was written to meet the needs of University of Saskatchewan psychology students at the undergraduate (PSY 233, PSY 234) level.

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Evidence-based Software Engineering

Contributor: Jones

Publisher: Knowledge Software

License: CC BY-SA

This book discusses what is currently known about software engineering, based on an analysis of all the publicly available data. This aim is not as ambitious as it sounds, because there is not a great deal of data publicly available.

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Mostly Harmless Statistics

Contributor: Webb

Publisher: Portland State University Library

License: CC BY-SA

This text is for an introductory level probability and statistics course with an intermediate algebra prerequisite. The focus of the text follows the American Statistical Association’s Guidelines for Assessment and Instruction in Statistics Education (GAISE). Software examples provided for Microsoft Excel, TI-84 & TI-89 calculators. A formula packet and pdf version of the text are available on the website http://mostlyharmlessstatistics.com. Students new to probability and statistics are sure to benefit from this fully ADA accessible and relevant textbook. The examples resonate with everyday life, the text is approachable, and has a conversational tone to provide an inclusive and easy to read format for students.

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Intermediate Statistics with R

Contributor: Greenwood

Publisher: Montana State University

License: CC BY-NC

Introductory statistics courses prepare students to think statistically but cover relatively few statistical methods. Building on the basic statistical thinking emphasized in an introductory course, a second course in statistics at the undergraduate level can explore a large number of statistical methods. This text covers more advanced graphical summaries, One-Way ANOVA with pair-wise comparisons, Two-Way ANOVA, Chi-square testing, and simple and multiple linear regression models. Models with interactions are discussed in the Two-Way ANOVA and multiple linear regression setting with categorical explanatory variables. Randomization-based inferences are used to introduce new parametric distributions and to enhance understanding of what evidence against the null hypothesis “looks like”. Throughout, the use of the statistical software R via Rstudio is emphasized with all useful code and data sets provided within the text. This is Version 3.0 of the book.

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