Measuring and reasoning: numerical inference in the sciences
In Measuring and Reasoning, Fred L. Bookstein examines the way ordinary arithmetic and numerical patterns are translated into scientific understanding, showing how the process relies on two carefully managed forms of argument: • Abduction: the generation of new hypotheses to accord with findings tha...
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Cambridge
Cambridge University Press
2014
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Online-Zugang: | BSB01 FHN01 Volltext |
Zusammenfassung: | In Measuring and Reasoning, Fred L. Bookstein examines the way ordinary arithmetic and numerical patterns are translated into scientific understanding, showing how the process relies on two carefully managed forms of argument: • Abduction: the generation of new hypotheses to accord with findings that were surprising on previous hypotheses, and • Consilience: the confirmation of numerical pattern claims by analogous findings at other levels of measurement. These profound principles include an understanding of the role of arithmetic and, more importantly, of how numerical patterns found in one study can relate to numbers found in others. More than 200 figures and diagrams illuminate the text. The book can be read with profit by any student of the empirical nature or social sciences and by anyone concerned with how scientists persuade those of us who are not scientists why we should credit the most important claims about scientific facts or theories |
Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
Beschreibung: | 1 online resource (xxviii, 535 pages) |
ISBN: | 9781139161923 |
DOI: | 10.1017/CBO9781139161923 |
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505 | 8 | |a Machine generated contents note: Part I. The Basic Structure of a Numerical Inference: 1. Getting started; 2. Consilience as a rhetorical strategy; 3. Abduction and strong inference; Part II. A Sampler of Strategies: 4. The undergraduate course; Part III. Numerical Inference for General Systems: 5. Abduction and consilience in more complicated systems; 6. The singular value decomposition: a family of pattern engines for organized systems; 7. Morphometrics, and other examples; Part IV. What Is to Be Done?: 8. Retrospect and prospect | |
520 | |a In Measuring and Reasoning, Fred L. Bookstein examines the way ordinary arithmetic and numerical patterns are translated into scientific understanding, showing how the process relies on two carefully managed forms of argument: • Abduction: the generation of new hypotheses to accord with findings that were surprising on previous hypotheses, and • Consilience: the confirmation of numerical pattern claims by analogous findings at other levels of measurement. These profound principles include an understanding of the role of arithmetic and, more importantly, of how numerical patterns found in one study can relate to numbers found in others. More than 200 figures and diagrams illuminate the text. The book can be read with profit by any student of the empirical nature or social sciences and by anyone concerned with how scientists persuade those of us who are not scientists why we should credit the most important claims about scientific facts or theories | ||
650 | 4 | |a Statistical hypothesis testing | |
776 | 0 | 8 | |i Erscheint auch als |n Druckausgabe |z 978-1-107-02415-1 |
856 | 4 | 0 | |u https://doi.org/10.1017/CBO9781139161923 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
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Datensatz im Suchindex
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any_adam_object | |
author | Bookstein, Fred L. 1947- |
author_facet | Bookstein, Fred L. 1947- |
author_role | aut |
author_sort | Bookstein, Fred L. 1947- |
author_variant | f l b fl flb |
building | Verbundindex |
bvnumber | BV043943232 |
collection | ZDB-20-CBO |
contents | Machine generated contents note: Part I. The Basic Structure of a Numerical Inference: 1. Getting started; 2. Consilience as a rhetorical strategy; 3. Abduction and strong inference; Part II. A Sampler of Strategies: 4. The undergraduate course; Part III. Numerical Inference for General Systems: 5. Abduction and consilience in more complicated systems; 6. The singular value decomposition: a family of pattern engines for organized systems; 7. Morphometrics, and other examples; Part IV. What Is to Be Done?: 8. Retrospect and prospect |
ctrlnum | (ZDB-20-CBO)CR9781139161923 (OCoLC)982061724 (DE-599)BVBBV043943232 |
dewey-full | 519.5/4 |
dewey-hundreds | 500 - Natural sciences and mathematics |
dewey-ones | 519 - Probabilities and applied mathematics |
dewey-raw | 519.5/4 |
dewey-search | 519.5/4 |
dewey-sort | 3519.5 14 |
dewey-tens | 510 - Mathematics |
discipline | Mathematik |
doi_str_mv | 10.1017/CBO9781139161923 |
format | Electronic eBook |
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id | DE-604.BV043943232 |
illustrated | Not Illustrated |
indexdate | 2024-07-10T07:39:19Z |
institution | BVB |
isbn | 9781139161923 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029352202 |
oclc_num | 982061724 |
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owner_facet | DE-12 DE-92 |
physical | 1 online resource (xxviii, 535 pages) |
psigel | ZDB-20-CBO ZDB-20-CBO BSB_PDA_CBO_Kauf ZDB-20-CBO FHN_PDA_CBO |
publishDate | 2014 |
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publisher | Cambridge University Press |
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spelling | Bookstein, Fred L. 1947- Verfasser aut Measuring and reasoning numerical inference in the sciences Fred L. Bookstein Measuring & Reasoning Cambridge Cambridge University Press 2014 1 online resource (xxviii, 535 pages) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 05 Oct 2015) Machine generated contents note: Part I. The Basic Structure of a Numerical Inference: 1. Getting started; 2. Consilience as a rhetorical strategy; 3. Abduction and strong inference; Part II. A Sampler of Strategies: 4. The undergraduate course; Part III. Numerical Inference for General Systems: 5. Abduction and consilience in more complicated systems; 6. The singular value decomposition: a family of pattern engines for organized systems; 7. Morphometrics, and other examples; Part IV. What Is to Be Done?: 8. Retrospect and prospect In Measuring and Reasoning, Fred L. Bookstein examines the way ordinary arithmetic and numerical patterns are translated into scientific understanding, showing how the process relies on two carefully managed forms of argument: • Abduction: the generation of new hypotheses to accord with findings that were surprising on previous hypotheses, and • Consilience: the confirmation of numerical pattern claims by analogous findings at other levels of measurement. These profound principles include an understanding of the role of arithmetic and, more importantly, of how numerical patterns found in one study can relate to numbers found in others. More than 200 figures and diagrams illuminate the text. The book can be read with profit by any student of the empirical nature or social sciences and by anyone concerned with how scientists persuade those of us who are not scientists why we should credit the most important claims about scientific facts or theories Statistical hypothesis testing Erscheint auch als Druckausgabe 978-1-107-02415-1 https://doi.org/10.1017/CBO9781139161923 Verlag URL des Erstveröffentlichers Volltext |
spellingShingle | Bookstein, Fred L. 1947- Measuring and reasoning numerical inference in the sciences Machine generated contents note: Part I. The Basic Structure of a Numerical Inference: 1. Getting started; 2. Consilience as a rhetorical strategy; 3. Abduction and strong inference; Part II. A Sampler of Strategies: 4. The undergraduate course; Part III. Numerical Inference for General Systems: 5. Abduction and consilience in more complicated systems; 6. The singular value decomposition: a family of pattern engines for organized systems; 7. Morphometrics, and other examples; Part IV. What Is to Be Done?: 8. Retrospect and prospect Statistical hypothesis testing |
title | Measuring and reasoning numerical inference in the sciences |
title_alt | Measuring & Reasoning |
title_auth | Measuring and reasoning numerical inference in the sciences |
title_exact_search | Measuring and reasoning numerical inference in the sciences |
title_full | Measuring and reasoning numerical inference in the sciences Fred L. Bookstein |
title_fullStr | Measuring and reasoning numerical inference in the sciences Fred L. Bookstein |
title_full_unstemmed | Measuring and reasoning numerical inference in the sciences Fred L. Bookstein |
title_short | Measuring and reasoning |
title_sort | measuring and reasoning numerical inference in the sciences |
title_sub | numerical inference in the sciences |
topic | Statistical hypothesis testing |
topic_facet | Statistical hypothesis testing |
url | https://doi.org/10.1017/CBO9781139161923 |
work_keys_str_mv | AT booksteinfredl measuringandreasoningnumericalinferenceinthesciences AT booksteinfredl measuringreasoning |