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Published in honor of the sixty-fifth birthday of Professor Ingram
Olkin of Stanford University. Part I contains a brief biography of
Professor Olkin and an interview with him discussing his career and
his research interests. Part II contains 32 technical papers
written in Professor Olkin's honor by his collaborators,
colleagues, and Ph.D. students. These original papers cover a
wealth of topics in mathematical and applied statistics, including
probability inequalities and characterizations, multivariate
analysis and association, linear and nonlinear models, ranking and
selection, experimental design, and approaches to statistical
inference. The volume reflects the wide range of Professor Olkin's
interests in and contributions to research in statistics, and
provides an overview of new developments in these areas of
research.
Written by renowned experts in the field, this reissue of a
textbook has as its unifying theme the role that probability models
have had, and continue to have, in scientific and practical
applications. It includes many examples, with actual data, of
real-world use of probability models, while expositing the
mathematical theory of probability at an introductory
calculus-based level. Detailed descriptions of the properties and
applications of probability models that have successfully modeled
real phenomena are given, as well as an explanation of methods for
testing goodness of fit of these models. Readers will receive a
firm foundation in techniques for deriving distributions of various
summaries of data that will prepare them for subsequent studies of
statistics, as well as a solid grounding in concepts such as that
of conditional probability that will prepare them for more advanced
courses in stochastic processes.
Written by renowned experts in the field, this reissue of a
textbook has as its unifying theme the role that probability models
have had, and continue to have, in scientific and practical
applications. It includes many examples, with actual data, of
real-world use of probability models, while expositing the
mathematical theory of probability at an introductory
calculus-based level. Detailed descriptions of the properties and
applications of probability models that have successfully modeled
real phenomena are given, as well as an explanation of methods for
testing goodness of fit of these models. Readers will receive a
firm foundation in techniques for deriving distributions of various
summaries of data that will prepare them for subsequent studies of
statistics, as well as a solid grounding in concepts such as that
of conditional probability that will prepare them for more advanced
courses in stochastic processes.
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