Joseph S. Torok (Rochester Institute of Technology, New York)
ISBN: 0-471-33207-0
Hardcover
Pages: 376
Published: Oct 1999
Copyright: 2000
Imprint: Wiley-Interscience
Mechanics is that branch of science that deals with forces and
motion on a body. A blend of mathematics and engineering theory,
analytical mechanics focuses on analyzing the forces applied on
automobiles, spacecraft, and airplanes; in dynamic structures
such as
buildings, bridges, and roads; and in natural forces (such as
waves, wind shear, etc.) in the real world. Courses in analytical
mechanics deal
with solving problems in two- and three-dimensions using methods
with exact and approximate solutions techniques. Answering a
critical
need for a definitive updated reference, Analytical Mechanics is
replete with many more new illustrations, examples, and problems
than
currently existing texts while also rigorously covering course
basics. With computational methods for developing equations of
motion using
Mathematica software, here is a complete, thoroughly-updated
introduction for students and professional engineers alike.
Contents
Principles of Dynamics.
Lagrangian Dynamics.
Calculus of Variations.
Dynamics of Rotating Bodies.
Hamiltonian Systems.
Stability Theory.
Appendices.
George T. Gilbert
Rhonda L. Hatcher, (Both of Texas Christian Univ.)
ISBN: 0-471-13934-3
Hardcover
Pages: 704
Published: Oct 1999
Copyright: 2000
An applied, interesting approach to one of the most feared
subjects around mathematics! Readers can learn mathematics
without
intimidation, and the wide variety of applications helps everyone
see the critical role mathematics plays in our world.
Contents
Voting Methods.
Apportionment: Sharing What Cannot Be Divided Arbitrarily.
The Mathematics of Money.
Probability.
Statistics.
Paths and Networks.
Tilings and Polyhedra.
Number Theory.
Game Theory with an Introduction to Linear Programming.
Appendix.
Answers to Selected Exercises and Review Exercises.
Photo Credits.
Sources.
Index.
Franz Gross (College of William and Mary,
Williamsburg, Virginia and Continuous Electron Beam Accelerator
Facility,
Newport News, Virginia)
ISBN: 0-471-35386-8
Paperback
Published: Apr 1999
Copyright: 1999
Imprint: Wiley-Interscience
An accessible, comprehensive reference to modern quantum
mechanics and field theory.
In surveying available books on advanced quantum mechanics and
field theory, Franz Gross determined that while established books
were
outdated, newer titles tended to focus on recent developments and
disregard the basics. Relativistic Quantum Mechanics and Field
Theory fills this striking gap in the field. With a strong
emphasis on applications to practical problems as well as
calculations, Dr. Gross
provides complete, up-to-date coverage of both elementary and
advanced topics essential for a well-rounded understanding of the
field.
Developing the material at a level accessible even to newcomers
to quantum mechanics, the book begins with topics that every
physicist
should know?quantization of the electromagnetic field,
relativistic one body wave equations, and the theoretical
explanation of atomic
decay. Subsequent chapters prepare readers for advanced work,
covering such major topics as gauge theories, path integral
techniques,
spontaneous symmetry breaking, and an introduction to QCD, chiral
symmetry, and the Standard Model. A special chapter is devoted to
relativistic bound state wave equations?an important topic that
is often overlooked in other books.
Clear and concise throughout, Relativistic Quantum Mechanics and
Field Theory boasts examples from atomic and nuclear physics as
well
as particle physics, and includes appendices with background
material. It is an essential reference for anyone working in
quantum
mechanics today.
FRANZ GROSS is Professor of Physics at the College of William and
Mary in Williamsburg, Virginia, and senior staff theorist at the
Thomas
Jefferson National Accelerator Facility (JLAB). Widely published
in the field, Dr. Gross is well known for his research on
problems in
theoretical nuclear and particle physics and is an expert on the
relativistic few body problem.
Contents
QUANTUM THEORY OF RADIATION.
Quantization of the Nonrelativistic String.
Quantization of the Electromagnetic Field.
Interaction of Radiation with Matter.
RELATIVISTIC EQUATIONS.
The Klein-Gordon Equation.
The Dirac Equation.
Application of the Dirac Equation.
ELEMENTS OF QUANTUM FIELD THEORY.
Second Quantization.
Symmetries I.
Interacting Field Theories.
Quantum Electrodynamics.
Loops and Introduction to Renormalization.
Bound States and Unitarity.
SYMMETRIES AND GAUGE THEORIES.
Symmetries II.
Path Integrals.
Quantum Chromodynamics and the Standard Model.
Renormalization.
The Renormalization Group and Asymptotic Freedom.
Appendices.
References.
Index.
Alvin C. Rencher (Brigham Young Univ., Provo, Utah)
ISBN: 0-471-31564-8
Hardcover
Pages: 578
Published: Nov 1999
Copyright: 2000
Imprint: Wiley-Interscience
Linear Models in Statistics
Alvin C. Rencher
Linear models made easy with this unique introduction
Linear Models in Statistics discusses classical linear models
from a matrix algebra perspective, making the subject easily
accessible to
readers encountering linear models for the first time. It
provides a solid foundation from which to explore the literature
and interpret
correctly the output of computer packages, and brings together a
number of approaches to regression and analysis of variance that
more
experienced practitioners will also benefit from. With an
emphasis on broad coverage of essential topics, Linear Models in
Statistics
carefully develops the basic theory of regression and analysis of
variance, illustrating it with examples from a wide range of
disciplines.
Other features of this remarkable work include:
Easy-to-read proofs and clear explanations of concepts and
procedures
Special topics such as multiple regression with random xfs and
the effect of each variable on R2
Advanced topics such as mixed and generalized linear models as
well as logisticand nonlinear regression
The use of real data sets in examples, with all data sets
available over the Internet
Numerous theoretical and applied problems, with answers in an
appendix
A thorough review of the requisite matrix algebra
Graphs, charts, and tables as well as extensive references
ALVIN C. RENCHER, PhD, is Professor of Statistics at Brigham
Young University and a Fellow of the American Statistical
Association. He
is the author of Methods of Multivariate Analysis and
Multivariate Statistical Inference and Applications, both
available from Wiley.
Subject:
Statistics / Applied Probability & Statistics / Models
Series Title:
Wiley Series in Probability and Statistics: Texts and References
Section
Contents
Matrix Algebra.
Random Vectors and Matrices.
Multivariate Normal Distribution.
Distribution of Quadratic Forms in y.
Simple Linear Regression.
Multiple Regression: Estimation.
Multiple Regression: Tests of Hypotheses and Confidence
Intervals.
Multiple Regression: Model Validation and Diagnostics.
Multiple Regression: Random x's.
Analysis of Variance Models.
One-Way Analysis of Variance: Balanced Case.
Two-Way Analysis of Variance: Balanced Case.
Unbalanced Data.
Analysis of Covariance.
Random Effects Models and Mixed Effects Models.
Additional Models.
Thomas P. Ryan (Case Western Reserve Univ., Cleveland, Ohio)
ISBN: 0-471-19775-0
Hardcover
Projected Pub Date: Dec 1999
Copyright: 2000
Imprint: Wiley-Interscience
A comprehensive, up-to-date survey of statistical methods for
quality improvement
Statistical methods for quality improvement offer numerous
benefits for industry and business, both through identifying
existing trouble
spots and alerting management and technical personnel to
potential problems. In the Second Edition of his successful book
that is still
unrivaled in content, Tom Ryan continues to offer clear, thorough
coverage of all available techniques?from basic control charts to
regression and design of experiments, and the combined use of
these tools. This edition is fully expanded and revised, bringing
readers up
to date with very recent research and providing a solid
foundation from which to explore the statistical literature. Dr.
Ryan tackles
complicated topics in a logical, engaging, easy-to-understand
style, downplaying mathematical formulas and making the material
accessible
to industrial engineers and applied statisticians alike. Special
features of Statistical Methods for Quality Improvement, Second
Edition
include:
Series Title:
Wiley Series in Probability and Mathematical Statistics - Applied
Probability and Statistics Section
Contents
Basic Tools for Improving Quality.
Basic Concepts in Statistics and Probability.
Control Charts for Measurements with Subgrouping (For One
Variable).
Control Charts for Measurements without Subgrouping (For One
Variable).
Control Charts for Attributes.
Process Capability.
Alternatives to Shewhart Charts.
Multivariate Control Charts for Measurement Data.
Miscellaneous Control Chart Topics.
Other Graphical Methods.
Linear Regression.
Design of Experiments.
Contributions of Genichi Taguchi and Alternative Approaches.
Evolutionary Operation.
Analysis of Means.
Using Combinations of Quality Improvement Tools.
James R. Thompson (Rice Univ., Houston, Texas)
ISBN: 0-471-25184-4
Hardcover
Pages: 306
Published: Oct 1999
Copyright: 2000
Imprint: Wiley-Interscience
James Thompson, a highly respected computational statistician
well-known for his innovative ideas, offers a unique and
cutting-edge
approach to simulation. He guides readers through the use of
simulation in creating or dealing with models of reality,
emphasizing simulation
as an integral part of the modeling process. A considerable
portion of the book is devoted to resampling procedures, using
them to test
hypotheses and gain insight into the variability of the data.
Series Title:
Wiley Series in Probability and Mathematical Statistics - Applied
Probability and Statistics Section
Contents
The Generation of "Random" Numbers.
Random Quadrature.
Monte Carlo Solutions of Differential Equations.
Markov Chains, Poisson Processes and Linear Equations.
SIMEST, SIMDAT, and Pseudoreality.
Models for Stocks and Derivatives.
Simulation Assessment of Multivariate and Robust Procedures in
Statistical Process Control.
Noise and Chaos.
Bayesian Approaches.
Resampling Based Tests.
Optimization and Estimation in a Noisy World.
Modeling the USA AIDS Epidemic: Exploration, Simulation and
Conjecture.
Appendices.
Index.