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Data Analysis (4th Edition)

Statistical and Computational Methods for Scientists and Engineers

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Publisher:

Springer

Pages: 523
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Recommend to library

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Paperback - 9783319347790

30 April 2017

$84.99

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Hardcover - 9783319037615

26 February 2014

$89.99

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Ebook - 9783319037622

14 February 2014

$64.99

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The fourth edition of this successful textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Equal weight is given to statistical theory and...

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The fourth edition of this successful textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Equal weight is given to statistical theory and practical problems. The concise mathematical treatment of the subject matter is illustrated by many examples and for the present edition a library of Java programs has been developed. It comprises methods of numerical data analysis and graphical representation as well as many example programs and solutions to programming problems.

The book is conceived both as an introduction and as a work of reference. In particular it addresses itself to students, scientists and practitioners in science and engineering as a help in the analysis of their data in laboratory courses, in working for bachelor or master degrees, in thesis work, and in research and professional work.

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Provides rigorous mathematical treatment of practical statistical methods for data analysis

Serves as a graduate textbook and reference guide for those interested in the fundamentals of data analysis

Useful for all fields of science and engineering requiring an understanding of statistical methods applied to experimental data

Includes example programs and solutions to programming problems which are written in the modern computer language Java

Modernizes the content in the previous edition and shortens the length of the text

Introduction
Probabilities
Random Variables: Distributions
Computer-Generated Random Numbers: The Monte Carlo Method
Some Important Distributions and Theorems
Samples
The Method of Maximum Likelihood
Testing Statistical Hypotheses
The Method of Least Squares
Function Minimization
Analysis of Variance
Linear and Polynomial Regression
Time-Series Analysis
A) Matrix Calculations
B) Combinatorics
C) Formulas and Methods for the Computation of Statistical Functions
D) The Gamma Function and Related Functions: Methods and Programs for their Computation
E) Utility Programs
F) The Graphics Class DatanGraphics
G) Problems, Hints and Solutions and Programming Problems
H) Collection of Formulas
I) Statistical Formulas
List of Computer Programs.
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Siegmund Brandt is Emeritus Professor of Physics at the University of Siegen. With his group he worked on experiments in elementary-particle physics at the research centers DESY in Hamburg and CERN in Geneva in which the analysis of the experimental data plays an important role. He is author or coauthor of textbooks which have appeared in ten languages.

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Siegmund Brandt is Emeritus Professor of Physics at the University of Siegen. With his group he worked on experiments in elementary-particle physics at the research centers DESY in Hamburg and CERN in Geneva in which the analysis of the experimental data plays an important role. He is author or coauthor of textbooks which have appeared in ten languages.

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