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Philosophies, Puzzles and Paradoxes
ISBN/GTIN

Philosophies, Puzzles and Paradoxes

A statistician´s search for truth
BuchKartoniert, Paperback
Verkaufsrang2092inEnglish Non Fiction A-Z
CHF86.00

Beschreibung

Aimed at undergraduate students of statistics and researchers interested in the philosophical foundations of statistics. Of interest to philosophers of science, as well as a general audience interested in puzzles and paradoxes.
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Details

ISBN/GTIN978-1-032-37739-1
ProduktartBuch
EinbandKartoniert, Paperback
Erscheinungsdatum21.03.2024
Auflage1. A.
Seiten331 Seiten
SpracheEnglisch
IllustrationenFarb., s/w. Abb.
Artikel-Nr.59788236
WarengruppeEnglish Non Fiction
DetailwarengruppeEnglish Non Fiction A-Z
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Autor

Yudi Pawitan graduated with a PhD in statistics in 1987 from the University of California at Davis and has been a professor of biostatistics since 2001 at the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. He has worked in many areas of statistical applications, including time series analyses and medical imaging, and for the last 20 years in the modelling and analysis of high-throughput genetic and molecular data with applications in cancer. He has published more than 200 peer-reviewed research papers, split about equally between methodology and applied publications. He is the author of the monograph In All Likelihood (2001) and co-author of Generalized Linear Models with Random Effects (2017) together with Youngjo Lee and John Nelder, both covering likelihood-based statistical modelling and inference. Philosophy of science, statistical puzzles and paradoxes have been lifelong interests.

Youngjo Lee graduated with a PhD in statistics in 1983 from Iowa State University. He is currently a professor emeritus of statistics at Seoul National University, an endowed-chair professor of data and knowledge service engineering at Dankook University, and a vice president of the Korean Academy of Science and Technology. Alongside the late John Asworth Nelder, he is an originator of hierarchical generalized models and h-likelihood, having co-authored over 200 peer-reviewed research papers on the application of h-likelihood in various statistical areas. He is also a co-author of monographs on h-likelihood theory and applications. Furthermore, he has developed related software and is currently extending h-likelihood procedures to deep neural networks.