Description

This book offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a comprehensive description of the general data analysis paradigm, from exploratory analysis (principal component analysis, self-organizing maps and clustering) to modeling (classification, regression) and validation (including variable selection). It also includes a special section discussing several more specific topics in the area of chemometrics, such as outlier detection, and biomarker identification. The corresponding R code is provided for all the examples in the book; and scripts, functions and data are available in a separate R package. This second revised edition features not only updates on many of the topics covered, but also several sections of new material (e.g., on handling missing values in PCA, multivariate process monitoring and batch correction).

Chemometrics with R: Multivariate Data Analysis in the Natural and Life Sciences

Product form

£54.99

Includes FREE delivery
Usually despatched within 3 days
Paperback / softback by Ron Wehrens

1 in stock

Short Description:

This book offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a comprehensive... Read more

    Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
    Publication Date: 21/08/2020
    ISBN13: 9783662620267, 978-3662620267
    ISBN10: 366262026X

    Number of Pages: 308

    Non Fiction , Mathematics & Science , Education

    Description

    This book offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a comprehensive description of the general data analysis paradigm, from exploratory analysis (principal component analysis, self-organizing maps and clustering) to modeling (classification, regression) and validation (including variable selection). It also includes a special section discussing several more specific topics in the area of chemometrics, such as outlier detection, and biomarker identification. The corresponding R code is provided for all the examples in the book; and scripts, functions and data are available in a separate R package. This second revised edition features not only updates on many of the topics covered, but also several sections of new material (e.g., on handling missing values in PCA, multivariate process monitoring and batch correction).

    Customer Reviews

    Be the first to write a review
    0%
    (0)
    0%
    (0)
    0%
    (0)
    0%
    (0)
    0%
    (0)

    Recently viewed products

    © 2025 Book Curl,

      • American Express
      • Apple Pay
      • Diners Club
      • Discover
      • Google Pay
      • Maestro
      • Mastercard
      • PayPal
      • Shop Pay
      • Union Pay
      • Visa

      Login

      Forgot your password?

      Don't have an account yet?
      Create account