Skip to content
Register Sign in Wishlist

Quantitative Methods of Data Analysis for the Physical Sciences and Engineering

$64.99 (P)

  • Date Published: November 2018
  • availability: In stock
  • format: Hardback
  • isbn: 9781107029767
Average user rating
(1 review)

$ 64.99 (P)

Add to cart Add to wishlist

Other available formats:

Request examination copy

Instructors may request a copy of this title for examination

Product filter button
About the Authors
  • This book provides thorough and comprehensive coverage of most of the new and important quantitative methods of data analysis for graduate students and practitioners. In recent years, data analysis methods have exploded alongside advanced computing power, and it is critical to understand such methods to get the most out of data, and to extract signal from noise. The book excels in explaining difficult concepts through simple explanations and detailed explanatory illustrations. Most unique is the focus on confidence limits for power spectra and their proper interpretation, something rare or completely missing in other books. Likewise, there is a thorough discussion of how to assess uncertainty via use of Expectancy, and the easy to apply and understand Bootstrap method. The book is written so that descriptions of each method are as self-contained as possible. Many examples are presented to clarify interpretations, as are user tips in highlighted boxes.

    • Develops new, unfamiliar methods from basic principles
    • Features detailed illustrations to clarify difficult concepts
    • Self-contained chapters stand alone as individual resources
    Read more

    Reviews & endorsements

    'This text is suitable for undergraduates and graduates, as well as seasoned scientists and engineers seeking to broaden their statistical skills. It will have lasting value as it is comprehensive, containing detailed explanations of a wide range of statistical methods. The book is clearly written by a meticulous scientist who is an expert in the field and an award winning teacher.' James Hays, Columbia University, New York

    'At last: a guide for getting the most out of your data analysis while avoiding the many pitfalls, hazards and common mistakes. This book is an invaluable and inspired opus on the fundamentals of quantitative data analysis. It is both comprehensive and illuminating, with many a nugget of enlightened wisdom, as well as succinctly summarized ‘take-home’ points in each and every section. A very accessible must-have guide for exploring data in the most informed way, and a gem of a textbook for students, teachers and practitioners alike.' Sharon Stammerjohn, University of Colorado, Boulder

    'Coherent book-length treatments are so valuable in the Data Age: the internet is full of algorithms - but described flatly, and in myriad notations and nomenclatures. This long-time teacher’s lucid text expresses the spirit and strategy of data analysis, as well as the details. Boxes set off optional advanced derivations, appendices survey matrix algebra and uncertainty analysis, and the chapters aim for standalone readability, making this a valuable reference as well as a flexible textbook (with questions). Spectral estimation is especially well covered.' Brian Mapes, University of Miami

    See more reviews

    Customer reviews

    09th Dec 2018 by Epvdigit

    The best book about data processing in Earth sciences since a long time. Congratulations.

    Review was not posted due to profanity


    , create a review

    (If you're not , sign out)

    Please enter the right captcha value
    Please enter a star rating.
    Your review must be a minimum of 12 words.

    How do you rate this item?


    Product details

    • Date Published: November 2018
    • format: Hardback
    • isbn: 9781107029767
    • length: 626 pages
    • dimensions: 253 x 178 x 33 mm
    • weight: 1.38kg
    • availability: In stock
  • Table of Contents

    Part I. Fundamentals:
    1. The nature of data and analysis
    2. Probability theory
    3. Statistics
    Part II. Fitting Curves to Data
    4. Interpolation
    5. Smoothed curve fitting
    6. Special curve fitting
    Part III. Sequential Data Fundamentals:
    7. Serial products
    8. Fourier series
    9. Fourier transform
    10. Fourier sampling theory
    11. Spectral analysis
    12. Cross spectral analysis
    13. Filtering and deconvolution
    14. Linear parametric models
    15. Empirical orthogonal function (EOF) analysis
    A1. Overview of matrix algebra
    A2. Uncertainty analysis

  • Resources for

    Quantitative Methods of Data Analysis for the Physical Sciences and Engineering

    Douglas G. Martinson

    Instructor Resources

    Find resources associated with this title

    Type Name Unlocked * Format Size

    Showing of

    Back to top

    This title is supported by one or more locked resources. Access to locked resources is granted exclusively by Cambridge University Press to instructors whose faculty status has been verified. To gain access to locked resources, instructors should sign in to or register for a Cambridge user account.

    Please use locked resources responsibly and exercise your professional discretion when choosing how you share these materials with your students. Other instructors may wish to use locked resources for assessment purposes and their usefulness is undermined when the source files (for example, solution manuals or test banks) are shared online or via social networks.

    Supplementary resources are subject to copyright. Instructors are permitted to view, print or download these resources for use in their teaching, but may not change them or use them for commercial gain.

    If you are having problems accessing these resources please contact

  • Author

    Douglas G. Martinson, Columbia University, New York
    Douglas G. Martinson is a Lamont Research Professor in the Division of Ocean and Climate Physics at Columbia University's Lamont-Doherty Earth Observatory. A physical oceanographer who researches the role of polar oceans in global climate, his research involves the collection of a large amount of data and considerable quantitative analysis. He developed the course on Quantitative Methods of Data Analysis as an Adjunct Professor for the Department of Earth and Environmental Sciences at Columbia University, New York, and received an Outstanding Teacher Award in 2004.

Sign In

Please sign in to access your account


Not already registered? Create an account now. ×

Sorry, this resource is locked

Please register or sign in to request access. If you are having problems accessing these resources please email

Register Sign in
Please note that this file is password protected. You will be asked to input your password on the next screen.

» Proceed

You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner Please see the permission section of the catalogue page for details of the print & copy limits on our eBooks.

Continue ×

Continue ×

Continue ×

Find content that relates to you

Join us online

This site uses cookies to improve your experience. Read more Close

Are you sure you want to delete your account?

This cannot be undone.


Thank you for your feedback which will help us improve our service.

If you requested a response, we will make sure to get back to you shortly.

Please fill in the required fields in your feedback submission.