1.

Record Nr.

UNINA9910460294903321

Titolo

The nature of scientific evidence [[electronic resource] ] : statistical, philosophical and empirical considerations / / edited by Mark L. Taper and Subhash R. Lele

Pubbl/distr/stampa

Chicago, : University of Chicago Press, 2004

ISBN

1-283-05860-X

9786613058607

0-226-78958-6

Descrizione fisica

1 online resource (586 p.)

Altri autori (Persone)

TaperMark L. <1952->

LeleSubhash

Disciplina

507/.2

Soggetti

Science - Statistical methods

Science - Methodology

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

pt. 1. Scientific process -- pt. 2. Logics of evidence -- pt. 3. Realities of nature -- pt. 4. Science, opinion and evidence -- pt. 5. Models, realities and evidence -- pt. 6. Conclusion.

Sommario/riassunto

An exploration of the statistical foundations of scientific inference, The Nature of Scientific Evidence asks what constitutes scientific evidence and whether scientific evidence can be quantified statistically. Mark Taper, Subhash Lele, and an esteemed group of contributors explore the relationships among hypotheses, models, data, and inference on which scientific progress rests in an attempt to develop a new quantitative framework for evidence. Informed by interdisciplinary discussions among scientists, philosophers, and statisticians, they propose a new "evidential" approach, which may be more in keeping with the scientific method. The Nature of Scientific Evidence persuasively argues that all scientists should care more about the fine points of statistical philosophy because therein lies the connection between theory and data. Though the book uses ecology as an exemplary science, the interdisciplinary evaluation of the use of



statistics in empirical research will be of interest to any reader engaged in the quantification and evaluation of data.