ISBN: 0-471-27214-0
Hardcover, 544 pages, May 2004
Description
This user-friendly resource helps readers grasp the concepts of
probability and stochastic processes, so they can apply them in
professional engineering practice. The book presents concepts
clearly as a sequence of building blocks that are identified
either as an axiom, definition, or theorem. This approach
provides a better understanding of the material, which can be
used to solve practical problems.
Table of Contents
Preface.
1. Experiments, Models, and Probabilities.
2. Discrete Random Variables.
3. Continuous Random Variables.
4. Pairs of Random Variables.
5. Random Vectors.
6. Sums of Random Variables.
7. Parameter Estimation Using the Sample Mean.
8. Hypothesis Testing.
9. Estimation of a Random Variable.
10. Stochastic Processes.
11. Random Signal Processing.
12. Markov Chains.
Appendix A: Families of Random Variables.
Appendix B: A Few Math Facts.
References.
Index.
ISBN: 0-471-69280-8
Paperback
760 pages
August 2004
Description
WILEY-INTERSCIENCE PAPERBACK SERIES
The Wiley-Interscience Paperback Series consists of selected
books that have been made more accessible to consumers in an
effort to increase global appeal and general circulation. With
these new unabridged softcover volumes, Wiley hopes to extend the
lives of these works by making them available to future
generations of statisticians, mathematicians, and scientists.
"This book will be an aid to survey statisticians and to
research workers who must work with survey data."
?Short Book Reviews, International Statistical Institute
Measurement Errors in Surveys documents the current state of the
field, reports new research findings, and promotes
interdisciplinary exchanges in modeling, assessing, and reducing
measurement errors in surveys. Providing a fundamental approach
to measurement errors, the book features sections on the
questionnaire, respondents and responses, interviewers and other
means of data collection, the respondent-interviewer
relationship, and the effects of measurement errors on estimation
and data analysis.
ISBN: 0-471-69121-6
Paperback
686 pages
August 2004
Description
WILEY-INTERSCIENCE PAPERBACK SERIES
The Wiley-Interscience Paperback Series consists of selected
books that have been made more accessible to consumers in an
effort to increase global appeal and general circulation. With
these new unabridged softcover volumes, Wiley hopes to extend the
lives of these works by making them available to future
generations of statisticians, mathematicians, and scientists.
"In recent years many monographs have been published on
specialized aspects of multivariate data-analysis?on cluster
analysis, multidimensional scaling, correspondence analysis,
developments of discriminant analysis, graphical methods,
classification, and so on. This book is an attempt to review
these newer methods together with the classical theory. . . .
This one merits two cheers."
?J. C. Gower, Department of Statistics
Rothamsted Experimental Station, Harpenden, U.K.
Review in Biometrics, June 1987
Multivariate Observations is a comprehensive sourcebook that
treats data-oriented techniques as well as classical methods.
Emphasis is on principles rather than mathematical detail, and
coverage ranges from the practical problems of graphically
representing high-dimensional data to the theoretical problems
relating to matrices of random variables. Each chapter serves as
a self-contained survey of a specific topic. The book includes
many numerical examples and over 1,100 references.
ISBN: 0-471-46842-8
Hardcover
384 pages
September 2004
Description
An essential introductory text linking traditional biostatistics
with bayesian methods
In recent years, Bayesian methods have seen an explosion of
interest, with applications in fields including biochemistry,
ecology, medicine, oncology, pharmacology, and public health. As
an interpretive system integrating data with observation, the
Bayesian approach provides a nuanced yet mathematically rigorous
means of conceptualizing biomedical statistics?from diagnostic
tests to DNA evidence.
Biostatistics: A Bayesian Introduction offers a pioneering
approach by presenting the foundations of biostatistics through
the Bayesian lens. Using easily understood, classic Dutch Book
thought experiments to derive subjective probability from a
simple principle of rationality, the book connects statistical
science with scientific reasoning. The author shows how to
compute, interpret, and report Bayesian statistical analyses in
practice, and illustrates how to reinterpret traditional
statistical reporting?such as confidence intervals, margins of
error, and one-sided p-values?in Bayesian terms.
Topics covered include:
Probability and subjective probability
Distributions and descriptive statistics
Continuous probability distributions
Comparing rates and means
Linear models and statistical adjustment
Logistic regression and adjusted odds ratios
Survival analysis
Hierarchical models and meta-analysis
Decision theory and sample size determination
The book includes extensive problem sets and references in each
chapter, as well as complete instructions on computer analysis
with the versatile SAS and WinBUGS software packages as well as
the Excel spreadsheet program. For professionals and students,
Biostatistics: A Bayesian Introduction offers an unique, real-world
entry point into a remarkable alternative method of interpreting
statistical data.
238 pages 38 line diagrams 10 exercises 28 worked examples
Hardback | ISBN: 0-88385-035-4 | Not yet published - available
from September 2004
In this second edition of a Carus Monograph Classic, Steven G.
Krantz, a leading worker in complex analysis and a winner of the
Chauvenet Prize for outstanding mathematical exposition, develops
material on classical non-Euclidean geometry. He shows how it can
be developed in a natural way from the invariant geometry of the
complex disk. He also introduces the Bergmann kernel and metric
and provides profound applications, some of which have never
appeared in print before. In general, the new edition represents
a considerable polishing and re-thinking of the original
successful volume. A minimum of geometric formalism is used to
gain a maximum of geometric and analytic insight. The climax of
the book is an introduction to several complex variables from the
geometric viewpoint. Poincare's theorem, that the ball and bidisc
are biholomorphically inequivalent, is discussed and proved.
Contents
Preface; 0. Principal ideas of classical function theory; 1.
Basic notions of differential geometry; 2. Curvature and
applications; 3. Some new invariant metrics; 4. Introduction to
the Bergmann theory; 5. A glimpse of several complex variables; 6.
Appendix; Symbols; References; Index.
Reviews
‘A first-rate book, which can be used either as a text or a
reference.’ Choice
‘In five very nicely written chapters this book gives an
introduction to the approach to function theory via Riemannian
geometry. Very little function-theoretic background is needed and
no knowledge whatsoever of differential geometry is assumed.’
Mathematical Reviews
Pure and Applied Mathematics series.Volume: 175
Textbook | Print Published: 07/15/2004
Hard Cover
320 pages | Illustrated
Print ISBN: 0-8247-5402-6
Description
This impressive work sees the theory of products of random
variables through from distributions and limit theorems, to
characterizations, to applications in physics, order statistics,
and number theory?using entirely probabilistic arguments in
actualizing the potential of the asymptotic theory of products of
independent random variables and obtaining results with dependent
variables using a new Bonferroni-type argument.
Table of Contents
Foundations
Limit Theorems
Characterization
Interacting Particles
Arithmetical Functions
Miscellaneous Results
Bibliography
Author Index
Subject Index