Description

The formal description of non-precise data before their statistical analysis is, except for error models and interval arithmetic, a relatively young topic. Fuzziness is described in the theory of fuzzy sets but only a few papers on statistical inference for non-precise data exist. In many cases, for example when very small concentrations are being measured, it is necessary to describe the imprecision of data. Otherwise, the results of statistical analysis can be unrealistic and misleading. Fortunately, there is a straightforward technique for dealing with non-precise data. The technique - the generalized inference method - is explained in Statistical Methods for Non-Precise Data. Anyone who understands elementary statistical methods and simple stochastic models will be able to use this book to understand and work with non-precise data.
The book includes explanations of how to cope with non-precise data in different practical situations, and makes an excellent graduate level text book for students, as well as a general reference for scientists and practitioners.

Features

Statistical Methods for Non-Precise Data

Product form

£150.00

Includes FREE delivery
Usually despatched within 4 days
Hardback by Reinhard Viertl

1 in stock

Short Description:

The formal description of non-precise data before their statistical analysis is, except for error models and interval arithmetic, a relatively... Read more

    Publisher: Taylor & Francis Inc
    Publication Date: 29/11/1995
    ISBN13: 9780849382420, 978-0849382420
    ISBN10: 0849382424

    Number of Pages: 208

    Non Fiction , Technology, Engineering & Agriculture , Education

    Description

    The formal description of non-precise data before their statistical analysis is, except for error models and interval arithmetic, a relatively young topic. Fuzziness is described in the theory of fuzzy sets but only a few papers on statistical inference for non-precise data exist. In many cases, for example when very small concentrations are being measured, it is necessary to describe the imprecision of data. Otherwise, the results of statistical analysis can be unrealistic and misleading. Fortunately, there is a straightforward technique for dealing with non-precise data. The technique - the generalized inference method - is explained in Statistical Methods for Non-Precise Data. Anyone who understands elementary statistical methods and simple stochastic models will be able to use this book to understand and work with non-precise data.
    The book includes explanations of how to cope with non-precise data in different practical situations, and makes an excellent graduate level text book for students, as well as a general reference for scientists and practitioners.

    Features

    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