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NEW!
Box
on Quality and Discovery: wtih Design, Control, and Robustness
George C. Tiao, Univ. of Chicago
SØren Bisgaard, Univ. of St. Gallen, Switzerland
William J. Hill, Allied Signal Chemicals
Daniel Peña, Univ. Carlos III de Madrid,
Stephen M. Stigler,
ISBN: 0-471-38768-1
Hardcover
Price: US$125.00
Pages: 632
Published: Aug 2000
Copyright: 2000
Imprint: Wiley-Interscience
A collection of masterworks on quality technology from the giant in the field
The chapters of this book are from the recent writings of George E. P. Box, an acknowledged world leader in the application and theory of quality methodology to management, process improvement, process design, and discovery.
Box’s unique ability to explain complex ideas simply and appealingly with wit and cogent illustration is well known. It draws on profound knowledge and extensive industrial experience. In the past, these abilities have led to the creation of such techniques as response surface methods, time series analysis for forecasting and control, evolutionary operation, and applied Bayesian methods.
Over the past fifteen years, Box’s work with many distinguished colleagues has been directed to the development and better understanding of quality techniques and how they can drive creativity and discovery. Key features of Box on Quality and Discovery include:
- Five separate sections on (I) management issues, (II) experimental design, (III) sequential investigation for discovery, (IV) process control for monitoring and feedback adjustment, and (V) reduction of variation and design of robust products and processes
- Edited by five eminent quality practitioners and statisticians from industry and academia
- Superb subject and author index for easy reference
- An additional key contribution from Stu Hunter
Published in celebration of George Box’s 80th birthday, this incomparable volume is destined to remain the definitive reference on statistical quality for many years to come.
Bayesian Inference in Statistical Analysis
George E. P. Box (Univ. of Wisconsin)
George C. Tiao (Univ. of Chicago)
Paperback
Item# 0-471- 57428-7
Price: US $99.95
Pages: 608
Published: Mar 1992
Copyright: 1992 Imprint: Wiley-Interscience
Its main objective is to examine the application and relevance of Bayes' theorem
to problems that arise in scientific investigation in which inferences must be
made regarding parameter values about which little is known a priori. Begins
with a discussion of some important general aspects of the Bayesian approach
such as the choice of prior distribution, particularly noninformative prior
distribution, the problem of nuisance parameters and the role of sufficient
statistics, followed by many standard problems concerned with the comparison of
location and scale parameters. The main thrust is an investigation of questions
with appropriate analysis of mathematical results which are illustrated with
numerical examples, providing evidence of the value of the Bayesian approach.
Empirical Model-Building and Response Surfaces
George E. P. Box
Norman R. Draper
Hardcover
Item# 0-471-81033-9
Price: US $125.00
Pages: 688
Published: Jan 1987
Copyright: 1986 Imprint: Wiley-Interscience
An innovative discussion of building empirical models and the fitting of
surfaces to data. Introduces the general philosophy of response surface
methodology, and details least squares for response surface work, factorial
designs at two levels, fitting second-order models, adequacy of estimation and
the use of transformation, occurrence and elucidation of ridge systems, and
more. Some results are presented for the first time.
Includes real-life exercises, nearly all with solutions.
Evolutionary Operation: A Statistical Method for Process Improvement
George E. Box
Norman R. Draper, (Both of Univ. of Wisconsin, Madison)
Item# 0-471-25551-3
Paperback
Item# Price: US $64.95
Pages: 237
Published: Feb 1998
Copyright: 1998 Imprint: Wiley-Interscience
This book is about the philosophy and practice of Evolutionary Operation
(called EVOP for short), a simple but powerful statistical tool with wide
application in industry. Experience has long shown that statistical methods,
sometimes quite sophisticated in character, can be of great value in improving
the efficiency of laboratory and pilot-plant investigations made by specially
trained chemists and engineers. What originally motivated the introduction of
EVOP, however, was the idea that the widespread and daily use of simple
statistical design and analysis during routine production by process operatives
themselves could reap enormous additional rewards.
Statistical Control: By Monitoring and Feedback Adjustment
George E. Box (Univ. of Wisconsin, Madison)
Alberto Luceño (Univ. of Cantabria, Santander, Spain)
Hardcover
Item# B19046-2
Price: US $99.95
Pages: 327
Published: Sep 1997
Copyright: 1997 Imprint: Wiley-Interscience
This book examines the development of simple, but powerful, techniques of
feedback adjustment for use by statistical process control (SPC) practitioners
and the work force.
Statistics for Experimenters:
An Introduction to Design, Data Analysis, and Model Building
George E. P. Box (Univ. of Wisconsin)
William G. Hunter (Univ. of Wisconsin)
J. Stuart Hunter (Princeton Univ., New Jersey)
Hardcover
Item# 0-471-09315-7
Price: US $89.95
Published: Jun 1978
Copyright: 1978
Introduces the philosophy of experimentation and the part that statistics play
in experimentation. Emphasizes the need to develop a capability for
"statistical thinking'' by using examples drawn from actual case studies.
Applied Statistics and
Probability for Engineers
Douglas C. Montgomery (Arizona State Univ.)
George C. Runger (Rensselaer Polytechnic Institute)
Hardcover
Item# 0-471-54041-2
Price: US $101.95
Published: Jan 1994
Copyright: 1994
Written by engineers, it uses a practical, applied approach that is more
oriented to engineering than any other text available. Instead of a few
engineering examples mixed in with examples from other fields, all of its
unique problem sets reflect the types of situations encountered by engineers in
their working lives.
Applied Statistics and Probability for Engineers, 2nd Ed.
Douglas C. Montgomery
George C. Runger, (Both of Arizona State Univ.)
Hardcover
Item# 0-471-17027-5
Price: US $101.95
Published: Dec 1998
Copyright: 1999
This text brings statistical tools to engineers and scientists who design and
develop new products, new manufacturing systems and processes and who improve
existing systems. Written by engineers for engineers, the examples and
exercises are engineering-based, containing real data. And because computers
are used to apply statistical methods to solve problems, output is presented
from Statgraphics and SAS to illustrate what can be done with modern
statistical software. Readers will master discrete and continuous random
variables and probability distributions; point and interval estimation; testing
hypotheses; simple and multiple linear regression; design of experiments;
nonparametric statistics; and statistical quality control.
Design
and Analysis of Experiments, 4th Ed.
Douglas C. Montgomery (Arizona State Univ.)
Hardcover
Item# 0-471-15746-5
Price: US $93.95
Published: Oct 1996
Copyright: 1997
This book describes the methods and techniques used in the design and analysis
of experiments. It emphasizes the connection between the experiment and the
model that the experimenter can develop from the results of the experiment and
features a new chapter on experiments with random factors.
Engineering
Statistics
Douglas C. Montgomery
George C. Runger
Norma Faris Hubele, (All of Arizona State Univ.)
Hardcover
Item# 0-471-17026-7
Price: US $93.95
Published: Dec 1997
Copyright: 1998
This book helps readers understand statistical methodology and use it to solve
engineering problems. It introduces the role of statistics and probability in
engineering problem solving and illustrates the useful information contained in
simple summary and graphical displays. Then it introduces the concepts of
random variable, and the probability distribution that describes the behavior
of that random variable presenting the basic tools of statistical inference;
point estimation, confidence intervals, and hypothesis testing. It also
explores empirical model-building, the design of engineering experiments and
statistical quality control.
Engineering Statistics, 2nd Edition
Douglas C. Montgomery / George C. Runger / Norma Faris Hubele
0-471-38879-3
Hardcover: US$93.95
Published: Oct 2000
Copyright: 2001
Introduction to Statistical Quality Control, 3rd Ed.
Douglas C. Montgomery (Arizona State Univ.)
Hardcover
Item# 0-471-30353-4
Price:US $102.95
Published: Aug 1996
Copyright: 1997
This book explores the modern use of statistical methods in quality control and
improvement. It provides comprehensive coverage of the subject from basic
principles to state-of-the-art concepts and applications. While statistical
techniques are emphasized throughout, the book has a strong engineering and
management orientation, showing how modern engineers use quality control today.
Introduction to Linear Regression Analysis, 2nd Ed.
Douglas C. Montgomery (Arizona State Univ.)
Elizabeth A. Peck (The Coca-Cola Company)
Hardcover
Item# 0-471-53387-4
Price: US $99.95
Published: Feb 1992
Copyright: 1992 Imprint: Wiley-Interscience
Covers both theory and application so the reader can understand the basic
principles and apply regression methods in a variety of practical settings.
Revisions include new material on regression diagnostics, more sample computer output
with expanded interpretations, a discussion on handling missing observations
and introductions to handling generalized linear models and nonlinear
regression.
Applied Regression Analysis, 3rd Ed.
Norman R. Draper
Harry Smith
Hardcover
Item# 0-471-17082-8
Price: US $94.95
Published: Apr 1998
Copyright: 1998 Imprint: Wiley-Interscience
A major goal of scientific exploration is the discovery of relationships among
variables. Regression is the analysis or measure of the relationship between a
dependent variable and one or more independent variables. This text covers a
commonly used statistical tool in constructing mathematical models from
experimental data.
Nonlinear Regression Analysis and Its Applications
Douglas M. Bates (Univ. of Wisconsin)
Donald G. Watts (Queen's Univ., Kingston, Ontario, Canada)
Hardcover
Item# B81643-4
Price: US $105.00
Pages: 384
Published: Aug 1988
Copyright: 1988
A balanced presentation of the theoretical, practical, and computational
aspects of nonlinear regression. Provides background material on linear
regression, including a geometrical development for linear and nonlinear least
squares. The authors2 employ real data sets throughout, and their extensive use
of geometric constructs and continuing examples makes the progression of ideas
appear very natural. Includes pseudocode for computing algorithms.
Statistical Quality Control: Strategies and Tools for Continual
Improvement
Johannes Ledolter
Claude W. Burrill, (Both of
Hardcover
Item# 0-471-18378-4
Price: US $95.95
Published: Jul 1998
Copyright: 1999
This text provides the reader with a general and widely-applicable problem
solving strategy for use in quality improvement. It covers a variety of
statistical and "non-statistical" problem-solving tools, and
discusses techniques that are useful when problems are solved by groups or
teams of people. It also shows how the success of problem solving is influenced
by the style of management and the type of management-employee
interaction.
SPC Methods for Quality Improvement
Charles P. Quesenberry
Hardcover
Item# 0-471-13807-7
Price: US $140.00
Pages: 694
Published: Mar 1997
Copyright: 1997
Statistical process control (SPC) methods are excellent tools for streamlining
a process to save time and money while producing a quality product. Instead of
actually testing each part after manufacturing -- SPC uses mathematical and
statistical models and charts to determine the numbers of acceptable vs.
unacceptable products that will be produced from a manufacturing process. In
analyzing these processes, SPC takes into account the number of parts or
components used, and other variables that effect the final product. This book
covers the basics of SPC from a statistical/mathematical perspective and
translates these concepts into real world applications.