Cargando…
Error and the Growth of Experimental Knowledge /
We may learn from our mistakes, but Deborah Mayo argues that, where experimental knowledge is concerned, we haven't begun to learn enough. Error and the Growth of Experimental Knowledge launches a vigorous critique of the subjective Bayesian view of statistical inference, and proposes Mayo'...
| Autor principal: | |
|---|---|
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Chicago :
University of Chicago Press,
[1996]
|
| Colección: | Science and Its Conceptual Foundations series
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | DEGRUYTERUP_9780226511993 | ||
| 003 | DE-B1597 | ||
| 005 | 20220424125308.0 | ||
| 006 | m|||||o||d|||||||| | ||
| 007 | cr || |||||||| | ||
| 008 | 220424t19961996ilu fo d z eng d | ||
| 020 | |a 9780226511993 | ||
| 035 | |a (DE-B1597)535792 | ||
| 035 | |a (OCoLC)701704591 | ||
| 040 | |a DE-B1597 |b eng |c DE-B1597 |e rda | ||
| 041 | 0 | |a eng | |
| 044 | |a ilu |c US-IL | ||
| 072 | 7 | |a SCI000000 |2 bisacsh | |
| 100 | 1 | |a Mayo, Deborah G., |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Error and the Growth of Experimental Knowledge / |c Deborah G. Mayo. |
| 264 | 1 | |a Chicago : |b University of Chicago Press, |c [1996] | |
| 264 | 4 | |c ©1996 | |
| 300 | |a 1 online resource (509 p.) : |b 12 line drawings, 6 tables | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 0 | |a Science and Its Conceptual Foundations series | |
| 505 | 0 | 0 | |t Frontmatter -- |t Contents -- |t Preface -- |t 1. Learning from Error -- |t 2. Ducks, Rabbits, and Normal Science: Recasting the Kuhn's-Eye View of Popper -- |t 3. The New Experimentalism and the Bayesian Way -- |t 4. Duhem, Kuhn, and Bayes -- |t 5. Models of Experimental Inquiry -- |t 6. Severe Tests and Methodological Underdetermination -- |t 7. The Experimental Basis from Which to Test Hypotheses: Brownian Motion -- |t 8. Severe Tests and Novel Evidence -- |t 9. Hunting and Snooping: Understanding the Neyman-Pearson Predesignationist Stance -- |t 10. Why You Cannot Be Just a Little Bit Bayesian -- |t 11. Why Pearson Rejected the Neyman-Pearson (Behavioristic) Philosophy and a Note on Objectivity in Statistics -- |t 12. Error Statistics and Peircean Error Correction -- |t 13. Toward an Error-Statistical Philosophy of Science -- |t References -- |t Index |
| 506 | 0 | |a restricted access |u http://purl.org/coar/access_right/c_16ec |f online access with authorization |2 star | |
| 520 | |a We may learn from our mistakes, but Deborah Mayo argues that, where experimental knowledge is concerned, we haven't begun to learn enough. Error and the Growth of Experimental Knowledge launches a vigorous critique of the subjective Bayesian view of statistical inference, and proposes Mayo's own error-statistical approach as a more robust framework for the epistemology of experiment. Mayo genuinely addresses the needs of researchers who work with statistical analysis, and simultaneously engages the basic philosophical problems of objectivity and rationality. Mayo has long argued for an account of learning from error that goes far beyond detecting logical inconsistencies. In this book, she presents her complete program for how we learn about the world by being "shrewd inquisitors of error, white gloves off." Her tough, practical approach will be important to philosophers, historians, and sociologists of science, and will be welcomed by researchers in the physical, biological, and social sciences whose work depends upon statistical analysis. | ||
| 538 | |a Mode of access: Internet via World Wide Web. | ||
| 546 | |a In English. | ||
| 588 | 0 | |a Description based on online resource; title from PDF title page (publisher's Web site, viewed 24. Apr 2022) | |
| 650 | 7 | |a SCIENCE / General. |2 bisacsh | |
| 653 | |a experimental knowledge, statistical inference, error-statistical approach, experiment, analysis, objectivity, rationality, logical inconsistencies, error, errors, mathematics, math, bayesian decision theory, science, methodological underdetermination, brownian motion, neyman-pearson predesignationist stance, peircean correction, inquiry. | ||
| 773 | 0 | 8 | |i Title is part of eBook package: |d De Gruyter |t University of Chicago Press eBook Package Archive 1990-1999 |z 9783110667851 |
| 856 | 4 | 0 | |u https://degruyter.uam.elogim.com/isbn/9780226511993 |z Texto completo |
| 912 | |a 978-3-11-066785-1 University of Chicago Press eBook Package Archive 1990-1999 |c 1990 |d 1999 | ||
| 912 | |a EBA_FAO | ||
| 912 | |a GBV-deGruyter-alles | ||