Skip to main content
SpringerLink
Log in

Exact Statistical Methods for Data Analysis

  • Book
  • © 1995

Overview

Authors:
  1. Samaradasa Weerahandi

    1. Milburn, USA

    View author publications

    You can also search for this author in PubMed   Google Scholar

Part of the book series: Springer Series in Statistics (SSS)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 16.99 USD 39.99
Discount applied Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 16.99 USD 54.99
Discount applied Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (10 chapters)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Preliminary Notions

    • Samaradasa Weerahandi
    Pages 1-24

  3. Notions in Significance Testing of Hypotheses

    • Samaradasa Weerahandi
    Pages 25-47

  4. Review of Special Distributions

    • Samaradasa Weerahandi
    Pages 48-76

  5. Exact Nonparametric Methods

    • Samaradasa Weerahandi
    Pages 77-107

  6. Generalized p-Values

    • Samaradasa Weerahandi
    Pages 108-142

  7. Generalized Confidence Intervals

    • Samaradasa Weerahandi
    Pages 143-168

  8. Comparing Two Normal Populations

    • Samaradasa Weerahandi
    Pages 169-202

  9. Analysis of Variance

    • Samaradasa Weerahandi
    Pages 203-241

  10. Mixed Models

    • Samaradasa Weerahandi
    Pages 242-271

  11. Regression

    • Samaradasa Weerahandi
    Pages 272-300

  12. Back Matter

    Pages 301-329
    Download chapter PDF
Back to top

Keywords

About this book

Now available in paperback. This book covers some recent developments in statistical inference. The author's main aim is to develop a theory of generalized p-values and generalized confidence intervals and to show how these concepts may be used to make exact statistical inferences in a variety of practical applications. In particular, they provide methods applicable in problems involving nuisance parameters such as those encountered in comparing two exponential distributions or in ANOVA without the assumption of equal error variances. The generalized procedures are shown to be more powerful in detecting significant experimental results and in avoiding misleading conclusions.

Authors and Affiliations

  • Milburn, USA

    Samaradasa Weerahandi

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation