Statistical Evidence: A Likelihood Paradigm

Author:   Richard Royall ,  R.J. Tibshirani ,  N. Reid (University of Toronto, Ontario, Canada) ,  Valerie Isham
Publisher:   Taylor & Francis Ltd
ISBN:  

9781032478005


Pages:   208
Publication Date:   21 January 2023
Format:   Paperback
Availability:   In Print   Availability explained
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Statistical Evidence: A Likelihood Paradigm


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Author:   Richard Royall ,  R.J. Tibshirani ,  N. Reid (University of Toronto, Ontario, Canada) ,  Valerie Isham
Publisher:   Taylor & Francis Ltd
Imprint:   CRC Press
Weight:   0.244kg
ISBN:  

9781032478005


ISBN 10:   1032478004
Pages:   208
Publication Date:   21 January 2023
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Reviews

...provides the explicit concept of evidence missing from the other approaches. -Aslib Book Guide ...the book is well written and readable. --Hoben Thomas, Journal of Mathematical Psychology This (hardback) book provides a very readable discussion of a possible alternative to both the Neyman-Pearson and the Fisherian approaches to the problem of interpreting data as evidence...present this area of work in a accessible manner with a clear readable style. The main ideas are made easy to understand and well illustrated with some interesting examples, including in an appendix the paradox of the ravens. Diagrams and tables are well used in this respect and the number of formulae is kept low, which aids readability...provides a well-presented discussion of an interesting new way of looking at data which would be accessible to most with some understanding of statistics. For this reason I would recommend it to a library. --Thomas Chadwick, University of Newcastle, Biometrics


"""...provides the explicit concept of evidence missing from the other approaches."" -Aslib Book Guide ""…the book is well written and readable."" --Hoben Thomas, Journal of Mathematical Psychology ""This (hardback) book provides a very readable discussion of a possible alternative to both the Neyman-Pearson and the Fisherian approaches to the problem of interpreting data as evidence…present this area of work in a accessible manner with a clear readable style. The main ideas are made easy to understand and well illustrated with some interesting examples, including in an appendix the paradox of the ravens. Diagrams and tables are well used in this respect and the number of formulae is kept low, which aids readability…provides a well-presented discussion of an interesting new way of looking at data which would be accessible to most with some understanding of statistics. For this reason I would recommend it to a library."" --Thomas Chadwick, University of Newcastle, Biometrics"


""...provides the explicit concept of evidence missing from the other approaches."" -Aslib Book Guide ""…the book is well written and readable."" --Hoben Thomas, Journal of Mathematical Psychology ""This (hardback) book provides a very readable discussion of a possible alternative to both the Neyman-Pearson and the Fisherian approaches to the problem of interpreting data as evidence…present this area of work in a accessible manner with a clear readable style. The main ideas are made easy to understand and well illustrated with some interesting examples, including in an appendix the paradox of the ravens. Diagrams and tables are well used in this respect and the number of formulae is kept low, which aids readability…provides a well-presented discussion of an interesting new way of looking at data which would be accessible to most with some understanding of statistics. For this reason I would recommend it to a library."" --Thomas Chadwick, University of Newcastle, Biometrics


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Richard Royall

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