Statistics and Analysis of Scientific Data

Massimiliano Bonamente

ISBN 10: 1493982397 / ISBN 13: 9781493982394

Published by Springer New York, Springer US Jun 2018, 2018

About this Item

Neuware -The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribution functions of statistics, fits to two-dimensional data and parameter estimation, Monte Carlo methods and Markov chains.Features new to this edition include:¿ a discussion of statistical techniques employed in business science, such as multiple regression analysis of multivariate datasets.¿ a new chapter on the various measures of the mean including logarithmic averages.¿ new chapters on systematic errors and intrinsic scatter, and on the fitting of data with bivariate errors.¿ a new case study and additional worked examples.¿ mathematical derivations and theoretical background material have been appropriately marked, to improve the readability of the text.¿ end-of-chapter summary boxes, for easy reference.As in the first edition, the main pedagogical method is a theory-then-application approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and practical application of the material. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data, as well as exercises and examples to aid the readers' understanding of the topic.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 336 pp. Englisch.

Seller Inventory # 9781493982394

Bibliographic Details

• Title: Statistics and Analysis of Scientific Data
• Publisher: Springer New York, Springer US Jun 2018
• Publication Date: 2018
• Language: English
• ISBN 10: 1493982397
• ISBN 13: 9781493982394
• Binding: Taschenbuch
• Edition: 1st Edition
• Condition: Neu
• Dimensions: 235W x 155H x 19D millimeters 235 millimeters width by 155 millimeters height by 19 millimeters depth
• Weight: 511 grams

About this title

Synopsis

The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribution functions of statistics, fits to two-dimensional data and parameter estimation, Monte Carlo methods and Markov chains. 

Features new to this edition include: 

• a discussion of statistical techniques employed in business science, such as multiple regression analysis of multivariate datasets.
• a new chapter on the various measures of the mean including logarithmic averages.
• new chapters on systematic errors and intrinsic scatter, and on the fitting of data with bivariate errors.
• a new case study and additional worked examples.
• mathematical derivations and theoretical background material have been appropriately marked, to improve the readability of the text.
• end-of-chapter summary boxes, for easy reference.

As in the first edition, the main pedagogical method is a theory-then-application approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and practical application of the material. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data, as well as exercises and examples to aid the readers' understanding of the topic.

About the Author

Max Bonamente is Professor of Astrophysics at the University of Alabama, Huntsville.