Advertisement

Statistics and Analysis of Scientific Data

  • Massimiliano Bonamente

Part of the Graduate Texts in Physics book series (GTP)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Massimiliano Bonamente
    Pages 1-15
  3. Massimiliano Bonamente
    Pages 17-33
  4. Massimiliano Bonamente
    Pages 55-83
  5. Massimiliano Bonamente
    Pages 107-115
  6. Massimiliano Bonamente
    Pages 117-146
  7. Massimiliano Bonamente
    Pages 147-164
  8. Massimiliano Bonamente
    Pages 165-175
  9. Massimiliano Bonamente
    Pages 177-193
  10. Massimiliano Bonamente
    Pages 195-201
  11. Massimiliano Bonamente
    Pages 203-210
  12. Massimiliano Bonamente
    Pages 211-223
  13. Massimiliano Bonamente
    Pages 225-236
  14. Massimiliano Bonamente
    Pages 237-247
  15. Massimiliano Bonamente
    Pages 249-271
  16. Back Matter
    Pages 273-318

About this book

Introduction

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.

Keywords

Fitting Data with Bivariate Errors Goodness of Fit and Parameter Uncertainty Maximum Likelihood Fit Median, Weighted Mean and Linear Average Monte Carlo Methods and Markov Chains Probability Theory for Physicists Statistical Methods for Science and Engineering Statistics for Business Science Systematic Errors and Intrinsic Scatter Textbook Statistical Methods

Authors and affiliations

  • Massimiliano Bonamente
    • 1
  1. 1.University of AlabamaHuntsvilleUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4939-6572-4
  • Copyright Information Springer Science+Busines Media New York 2017
  • Publisher Name Springer, New York, NY
  • eBook Packages Physics and Astronomy
  • Print ISBN 978-1-4939-6570-0
  • Online ISBN 978-1-4939-6572-4
  • Series Print ISSN 1868-4513
  • Series Online ISSN 1868-4521
  • Buy this book on publisher's site