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Computer Based Numerical and Statistical Techniques

Computer Based Numerical and Statistical Techniques
Author: Santosh Kumar Sengar
Publisher: S. Chand Publishing
Total Pages:
Release:
Genre:
ISBN: 9352833988

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Computer Based Numerical and Statistical Techniques has been written to provide fundamental introduction of numerical analysis for the students who take a course on Engineering Mathematics and for the students of computer science engineering. The book has been divided into 14 chapters covering all important aspects starting from high speed computation to Interpolation and Curve Fitting to Numerical Integration and Differentiation and finally focusing on Test of Significance


COMPUTER BASED NUMERICAL AND STATISTICAL TECHNIQUES

COMPUTER BASED NUMERICAL AND STATISTICAL TECHNIQUES
Author: Rakesh Kumar
Publisher: CBS Publishers & Distributors Private Limited
Total Pages: 11
Release: 2018-01-30
Genre:
ISBN: 9387085120

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The book introduces subject techniques to approximate mathematical procedures/solutions of problems that arise in science and engineering. It handles carefully a detailed elucidation of errors in numerical analysis. It aims to fully cater to the needs of students of the courses: BSc/MSc (mathematics and physics), BSc (computer science), BTech (all courses in engineering) and MCA.


Computer Based Numerical & Statistical Techniques

Computer Based Numerical & Statistical Techniques
Author: A. K. Jaiswal
Publisher: New Age International
Total Pages: 42
Release: 2009
Genre: Numerical analysis
ISBN: 812242466X

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About the Book: Application of Numerical Analysis has become an integral part of the life of all the modern engineers and scientists. The contents of this book covers both the introductory topics and the more advanced topics such as partial differential equations. This book is different from many other books in a number of ways. Salient Features: Mathematical derivation of each method is given to build the students understanding of numerical analysis. A variety of solved examples are given. Computer programs for almost all numerical methods discussed have been presented in C̀ ̀langu.


A Handbook of Numerical and Statistical Techniques

A Handbook of Numerical and Statistical Techniques
Author: J. H. Pollard
Publisher: CUP Archive
Total Pages: 372
Release: 1977
Genre: Mathematics
ISBN: 9780521297509

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This handbook is designed for experimental scientists, particularly those in the life sciences. It is for the non-specialist, and although it assumes only a little knowledge of statistics and mathematics, those with a deeper understanding will also find it useful. The book is directed at the scientist who wishes to solve his numerical and statistical problems on a programmable calculator, mini-computer or interactive terminal. The volume is also useful for the user of full-scale computer systems in that it describes how the large computer solves numerical and statistical problems. The book is divided into three parts. Part I deals with numerical techniques and Part II with statistical techniques. Part III is devoted to the method of least squares which can be regarded as both a statistical and numerical method. The handbook shows clearly how each calculation is performed. Each technique is illustrated by at least one example and there are worked examples and exercises throughout the volume.


Numerical Methods of Statistics

Numerical Methods of Statistics
Author: John F. Monahan
Publisher: Cambridge University Press
Total Pages: 465
Release: 2011-04-18
Genre: Computers
ISBN: 1139498002

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This book explains how computer software is designed to perform the tasks required for sophisticated statistical analysis. For statisticians, it examines the nitty-gritty computational problems behind statistical methods. For mathematicians and computer scientists, it looks at the application of mathematical tools to statistical problems. The first half of the book offers a basic background in numerical analysis that emphasizes issues important to statisticians. The next several chapters cover a broad array of statistical tools, such as maximum likelihood and nonlinear regression. The author also treats the application of numerical tools; numerical integration and random number generation are explained in a unified manner reflecting complementary views of Monte Carlo methods. Each chapter contains exercises that range from simple questions to research problems. Most of the examples are accompanied by demonstration and source code available from the author's website. New in this second edition are demonstrations coded in R, as well as new sections on linear programming and the Nelder–Mead search algorithm.