Statistical information and likelihood. Lecture notes in statistics.

Basu, Debabrata:

ISBN 10: 3540967516 / ISBN 13: 9783540967514

Published by New York, Springer, 1988

About this Item

XVIII, 365 S. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. Ex-library with stamp and library-signature. GOOD condition, some traces of use. X-15765 3540967516 Sprache: Deutsch Gewicht in Gramm: 550.

Seller Inventory # 2391714

Bibliographic Details

• Title: Statistical information and likelihood. Lecture notes in statistics.
• Publisher: New York, Springer
• Publication Date: 1988
• Language: German
• ISBN 10: 3540967516
• ISBN 13: 9783540967514
• Binding: Softcover
• Seller catalogs:
  • AA Varia

About this title

Synopsis

It is an honor to be asked to write a foreword to this book, for I believe that it and other books to follow will eventually lead to a dramatic change in the current statistics curriculum in our universities. I spent the 1975-76 academic year at Florida State University in Tallahassee. My purpose was to complete a book on Statistical Reliability Theory with Frank Proschan. At the time, I was working on total time on test processes. At the same time, I started attending lectures by Dev Basu on statistical inference. It was Lehmann's hypothesis testing course and Lehmann's book was the text. However, I noticed something strange - Basu never opened the book. He was obviously not following it. Instead, he was giving a very elegant, measure theoretic treatment of the concepts of sufficiency, ancillarity, and invariance. He was interested in the concept of information - what it meant. - how it fitted in with contemporary statistics. As he looked at the fundamental ideas, the logic behind their use seemed to evaporate. I was shocked. I didn't like priors. I didn't like Bayesian statistics. But after the smoke had cleared, that was all that was left. Basu loves counterexamples. He is like an art critic in the field of statistical inference. He would find a counterexample to the Bayesian approach if he could. So far, he has failed in this respect.