Описание: MATLAB is a programme which lends itself to the implementation of most numerical algorithms. This text, which uses MATLAB, gives an overview of structured programming and numerical methods and covers numerical methods for solving a range of problems, from integration to the numerical solution of differential equations.
Описание: This introductory textbook for business statistics teaches statistical analysis and research methods via business case studies and financial data using Excel, Minitab, and SAS. Every chapter in this textbook engages the reader with data of individual stock, stock indices, options, and futures.One studies and uses statistics to learn how to study, analyze, and understand a data set of particular interest. Some of the more popular statistical programs that have been developed to use statistical and computational methods to analyze data sets are SAS, SPSS, and Minitab. Of those, we look at Minitab and SAS in this textbook. One of the main reasons to use Minitab is that it is the easiest to use among the popular statistical programs. We look at SAS because it is the leading statistical package used in industry. We also utilize the much less costly and ubiquitous Microsoft Excel to do statistical analysis, as the benefits of Excel have become widely recognized in the academic world and its analytical capabilities extend to about 90 percent of statistical analysis done in the business world. We demonstrate much of our statistical analysis using Excel and double check the analysis and outcomes using Minitab and SAS—also helpful in some analytical methods not possible or practical to do in Excel.
Автор: Al Malah Kamal Название: MATLAB Numerical Methods with Chemical Engineering Applicati ISBN: 0071831282 ISBN-13(EAN): 9780071831284 Издательство: McGraw-Hill Рейтинг: Цена: 20075.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A practical, professional guide to MATLAB applications, numerical techniques, and scientific computing
Описание: Learn how to program by diving into the R language, and then use your newfound skills to solve practical data science problems. With this book, you`ll learn how to load data, assemble and disassemble data objects, navigate R`s environment system, write your own functions, and use all of R`s programming tools
Описание: The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style employed is more accessible and concise, in keeping with the needs of engineering students.
Автор: ?ke Bj?rck Название: Numerical Methods in Matrix Computations ISBN: 3319356143 ISBN-13(EAN): 9783319356143 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a comprehensive and up-to-date treatment of modern methods in matrix computation. It uses a unified approach to direct and iterative methods for linear systems, least squares and eigenvalue problems.
Автор: Kharab, Abdelwahab (department Of Mathematics, Abu Dhabi University, United Arab Emirates) Guenther, Ronald Название: Introduction to numerical methods ISBN: 1138093076 ISBN-13(EAN): 9781138093072 Издательство: Taylor&Francis Рейтинг: Цена: 13014.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An Introduction to Numerical Methods: A MATLAB (R) Approach, Fourth Edition presents a wide range of useful and important algorithms for scientific and engineering applications.
Автор: Wellin Название: Programming with Mathematica ® ISBN: 1107009464 ISBN-13(EAN): 9781107009462 Издательство: Cambridge Academ Рейтинг: Цена: 11880.00 р. Наличие на складе: Поставка под заказ.
Описание: Starting from first principles, this book covers all of the foundational material needed to develop a clear understanding of the Mathematica language, with a practical emphasis on solving problems. Concrete examples throughout the text demonstrate how Mathematica can be used to solve problems in science, engineering, economics/finance, computational linguistics, geoscience, bioinformatics, and a range of other fields. The book will appeal to students, researchers and programmers wishing to further their understanding of Mathematica. Designed to suit users of any ability, it assumes no formal knowledge of programming so it is ideal for self-study. Over 290 exercises are provided to challenge the reader's understanding of the material covered and these provide ample opportunity to practice using the language. Mathematica notebooks containing examples, programs and solutions to exercises are available from www.cambridge.org/wellin.
