Series: Book 1 in the Springer Texts in Statistics series
Rating: *****
Tags: Lang:en
Publisher: Springer
Added: June 14, 2020
Modified: November 5, 2021
Summary
This book is based upon lecture notes developed by Jack
Kiefer for a course in statistical inference he taught at
Cornell University. The notes were distributed to the class
in lieu of a textbook, and the problems were used for
homework assignments. Relying only on modest prerequisites of
probability theory and cal culus, Kiefer's approach to
a first course in statistics is to present the central ideas
of the modem mathematical theory with a minimum of fuss and
formality. He is able to do this by using a rich mixture of
examples, pictures, and math ematical derivations to
complement a clear and logical discussion of the important
ideas in plain English. The straightforwardness of Kiefer's
presentation is remarkable in view of the sophistication and
depth of his examination of the major theme: How should an
intelligent person formulate a statistical problem and choose
a statistical procedure to apply to it? Kiefer's view, in the
same spirit as Neyman and Wald, is that one should try to
assess the consequences of a statistical choice in some
quan titative (frequentist) formulation and ought to
choose a course of action that is verifiably optimal (or
nearly so) without regard to the perceived "attractiveness"
of certain dogmas and methods. **