Deborah G. Mayo
Statistical Inference as Severe Testing
Deborah G. Mayo
Statistical Inference as Severe Testing
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- Produkterinnerung
- Produkterinnerung
Unlock today's statistical controversies and irreproducible results by viewing statistics as probing and controlling errors.
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Unlock today's statistical controversies and irreproducible results by viewing statistics as probing and controlling errors.
Produktdetails
- Produktdetails
- Verlag: Cambridge University Press
- Seitenzahl: 504
- Erscheinungstermin: 16. Oktober 2018
- Englisch
- Abmessung: 235mm x 157mm x 34mm
- Gewicht: 963g
- ISBN-13: 9781107054134
- ISBN-10: 1107054133
- Artikelnr.: 50759457
- Verlag: Cambridge University Press
- Seitenzahl: 504
- Erscheinungstermin: 16. Oktober 2018
- Englisch
- Abmessung: 235mm x 157mm x 34mm
- Gewicht: 963g
- ISBN-13: 9781107054134
- ISBN-10: 1107054133
- Artikelnr.: 50759457
Deborah G. Mayo is Professor Emerita in the Department of Philosophy at Virginia Tech. Author of Error and the Growth of Experimental Knowledge (1996), she won the 1998 Lakatos Prize for an outstanding contribution to philosophy of science. She directed the NEH Summer Seminar (1999) on Philosophy of Experimental Inference. She co-founded, with G. W. Chatfield, the Fund for Experimental Reasoning, Reliability and Objectivity and Rationality (E.R.R.O.R) in 2006 which has co-sponsored 10 conferences, workshops and distinguished lecture series. She's a visiting professor at the London School of Economics and Political Science, Centre for the Philosophy of Natural and Social Science (CPNSS) (2007-present).
Preface
Excursion 1. How to Tell What's True about Statistical Inference: Tour I. Beyond probabilism and performance
Tour II. Error probing tools vs. logics of evidence
Excursion 2. Taboos of Induction and Falsification: Tour I. Induction and confirmation
Tour II. Falsification, pseudoscience, induction
Excursion 3. Statistical Tests and Scientific Inference: Tour I. Ingenious and severe tests
Tour II. It's the methods, stupid
Tour III. Capability and severity: deeper concepts
Excursion 4. Objectivity and Auditing: Tour I. The myth of 'the myth of objectivity'
Tour II. Rejection fallacies: whose exaggerating what?
Tour III. Auditing: biasing selection effects and randomization
Tour IV. More auditing: objectivity and model checking
Excursion 5. Power and Severity: Tour I. Power: pre-data and post-data
Tour II. How not to corrupt power
Tour III. Deconstructing the N-P vs. Fisher debates
Excursion 6. (Probabilist) Foundations Lost, (Probative) Foundations Found: Tour I. What ever happened to Bayesian foundations?
Tour II. Pragmatic and error statistical Bayesians
Souvenir (Z) farewell
References
Index.
Excursion 1. How to Tell What's True about Statistical Inference: Tour I. Beyond probabilism and performance
Tour II. Error probing tools vs. logics of evidence
Excursion 2. Taboos of Induction and Falsification: Tour I. Induction and confirmation
Tour II. Falsification, pseudoscience, induction
Excursion 3. Statistical Tests and Scientific Inference: Tour I. Ingenious and severe tests
Tour II. It's the methods, stupid
Tour III. Capability and severity: deeper concepts
Excursion 4. Objectivity and Auditing: Tour I. The myth of 'the myth of objectivity'
Tour II. Rejection fallacies: whose exaggerating what?
Tour III. Auditing: biasing selection effects and randomization
Tour IV. More auditing: objectivity and model checking
Excursion 5. Power and Severity: Tour I. Power: pre-data and post-data
Tour II. How not to corrupt power
Tour III. Deconstructing the N-P vs. Fisher debates
Excursion 6. (Probabilist) Foundations Lost, (Probative) Foundations Found: Tour I. What ever happened to Bayesian foundations?
Tour II. Pragmatic and error statistical Bayesians
Souvenir (Z) farewell
References
Index.
Preface
Excursion 1. How to Tell What's True about Statistical Inference: Tour I. Beyond probabilism and performance
Tour II. Error probing tools vs. logics of evidence
Excursion 2. Taboos of Induction and Falsification: Tour I. Induction and confirmation
Tour II. Falsification, pseudoscience, induction
Excursion 3. Statistical Tests and Scientific Inference: Tour I. Ingenious and severe tests
Tour II. It's the methods, stupid
Tour III. Capability and severity: deeper concepts
Excursion 4. Objectivity and Auditing: Tour I. The myth of 'the myth of objectivity'
Tour II. Rejection fallacies: whose exaggerating what?
Tour III. Auditing: biasing selection effects and randomization
Tour IV. More auditing: objectivity and model checking
Excursion 5. Power and Severity: Tour I. Power: pre-data and post-data
Tour II. How not to corrupt power
Tour III. Deconstructing the N-P vs. Fisher debates
Excursion 6. (Probabilist) Foundations Lost, (Probative) Foundations Found: Tour I. What ever happened to Bayesian foundations?
Tour II. Pragmatic and error statistical Bayesians
Souvenir (Z) farewell
References
Index.
Excursion 1. How to Tell What's True about Statistical Inference: Tour I. Beyond probabilism and performance
Tour II. Error probing tools vs. logics of evidence
Excursion 2. Taboos of Induction and Falsification: Tour I. Induction and confirmation
Tour II. Falsification, pseudoscience, induction
Excursion 3. Statistical Tests and Scientific Inference: Tour I. Ingenious and severe tests
Tour II. It's the methods, stupid
Tour III. Capability and severity: deeper concepts
Excursion 4. Objectivity and Auditing: Tour I. The myth of 'the myth of objectivity'
Tour II. Rejection fallacies: whose exaggerating what?
Tour III. Auditing: biasing selection effects and randomization
Tour IV. More auditing: objectivity and model checking
Excursion 5. Power and Severity: Tour I. Power: pre-data and post-data
Tour II. How not to corrupt power
Tour III. Deconstructing the N-P vs. Fisher debates
Excursion 6. (Probabilist) Foundations Lost, (Probative) Foundations Found: Tour I. What ever happened to Bayesian foundations?
Tour II. Pragmatic and error statistical Bayesians
Souvenir (Z) farewell
References
Index.