hardcover
0-8018-8235-4
December 2005 528 pp. 3 line drawings
Description
Jacob Bernoulli's Ars Conjectandi, published posthumously in
Latin in 1713 by the Thurneysen Brothers Press in Basel, is the
founding document of mathematical probability. Here, Edith Dudley
Sylla offers the first complete English translation of this
monumental work.
Part I reprints and reworks Huygens's On Reckoning in Games of
Chance. Part II offers a thorough treatment of the mathematics of
combinations and permutations, including the numbers since known
as "Bernoulli numbers." In Part III, Bernoulli solves
more complicated problems of games of chance using that
mathematics. In the final part, Bernoulli's crowning achievement
in mathematical probability is manifest: he applies the
mathematics of games of chance to the problems of epistemic
probability in civil, moral, and economic matters, proving what
we now know as the weak law of large numbers.
Sylla provides an extensive introduction and detailed
translator's notes. She includes as supplemental texts
Bernoulli's "Letter to a Friend on Sets in Court Tennis"
and "Thesis 32" of Theses Logicae de conversione et
oppositione enunciationum.
Reviews
"Bernoulli's The Art of Conjecturing has always been
recognized as one of the outstanding texts in the history of
probability, marking a dramatic development in the theory. The
lack of a complete translation has hampered an understanding of
the exact nature of its achievement. With Sylla's translation, it
becomes clear what a comprehensive and revolutionary work it was."--James
Franklin, University of South Wales
Author Information
Edith Dudley Sylla is a professor of history at North Carolina
State University.
Volume 196 NATO Science Series: Computer & Systems
Sciences
April 2005, 336 pp., hardcover
ISBN: 1-58603-505-3 NEW
This publication gives a good insight in the interplay between
commutative and non-commutative algebraic geometry. The
theoretical and computational aspects are the central theme in
this study. The topic is looked at from different perspectives in
over 20 lecture reports. It emphasizes the current trends in
Commutative and Non-Commutative Algebraic Geometry and Algebra.
The contributors to this publication present the most recent and
state of the art progresses which reflect the topic discussed in
this publication. Both researchers and graduate students will
find this book a good source of information on commutative and
non-commutative algebraic geometry.
table of contents
ISBN: 0-471-67969-0
Hardcover
486 pages
May 2005
This text begins with chapters that develop probability theory
and introduce the axioms of probability, random variables, and
joint distributions. The next sections introduce limit theorems
and simulation. Also included is a chapter on statistical
inference, with a section on Bayesian statistics which is an
important, though often neglected, topic for undergraduate-level
texts. Markov chains in discrete and continuous time is also
discussed within the book. More than 400 examples are
interspersed throughout the text to help illustrate concepts and
theory and to assist the reader to develop an intuitive sense of
the subject. Readers will find many of the examples to be both
entertaining and thought provoking. This is also true for the
carefully selected problems that appear at the end of each
chapter.
Contents
Preface.
1. Basic Probability Theroy.
2. Random Variables.
3. Joint Distributions.
4. Limit Theorems.
5. Simulation.
6. Statistical Inference.
7. Stochastic Processes.
Appendix A: Tables.
Appendix B: Answers to Selected Problems.
References.
ISBN: 0-471-73580-9
Hardcover
352 pages
June 2005
Description
The Second Edition of this popular text provides an insightful
introduction to the use of finite difference and finite element
methods for the computational solution of ordinary and partial
differential equations. Readers gain a thorough understanding of
the theory underlying themethods presented in the text. The
author emphasizes the practical steps involved in implementing
the methods, culminating in readers learning how to write
programs using FORTRAN90 and MATLAB(r) to solve ordinary and
partial differential equations.
The book begins with a review of direct methods for the solution
of linear systems, with an emphasis on the special features of
the linear systems that arise when differential equations are
solved. The following four chapters introduce and analyze the
more commonly used finite difference methods for solving a
variety of problems, including ordinary and partial differential
equations and initial value and boundary value problems. The
techniques presented in these chapters, with the aid of carefully
developed exercises and numerical examples, can be easilymastered
by readers.
The final chapter of the text presents the basic theory
underlying the finite element method. Following the guidance
offered in this chapter, readers gain a solid understanding of
the method and discover how to use it to solve many problems.
A special feature of the Second Edition is Appendix A, which
describes a finite element program, PDE2D, developed by the
author. Readers discover how PDE2D can be used to solve difficult
partial differential equation problems, including nonlinear time-dependent
and steady-state systems, and linear eigenvalue systems in 1D
intervals, general 2D regions, and a wide range of simple 3D
regions. The software itself is available to instructors who
adopt the text to share with their students.
Table of Contents
Direct Solution of Linear Systems.
1. Initial Value Ordinary Differential Equations.
2. The Initial Value Diffusion Problem.
3. The Initial Value Transport and Wave Problems.
4. Boundary Value Problems.
5. The Finite Element Method.
Appendix A: Solving PDEs with PDE2D.
Appendix B: The Fourier Stability Method.
Appendix C: MATLAB Programs.
Appendix D: Can 'Anything' Happen in an Open System?
Appendix E: Answers to Selected Exercises.
References.
ISBN: 0-471-66259-3
Hardcover
600 pages
July 2005
Description
Intended for a first course in linear models at either the upper
undergraduate or beginning graduate level, Introduction to Linear
Models and Statistical Inference provides a basic introduction to
probability distribution theory and statistical inference. It
includes descriptive methods for building models with an emphasis
on linear regression, variance, and covariance. In an effort to
extend reader comprehension and intrigue, there is a general
discussion of analysis of model fit and modern robust techniques
at the end of the book.
* The exercises are a mix of both the theoretical and the
practical; some are marked as requiring calculus, linear algebra,
or computer skills.
* The text utilizes output from MINITAB to illustrate many of the
examples. An appendix introduces the reader to MINITAB.
* The text includes an introduction to matrix algebra in an
appendix for those readers who have a weak background in the
topic. Optional sections are included at chapter ends for use in
courses where the integration of linear algebra techniques is
desired. The sections can be omitted without loss of continuity.
* The text can serve as a first course in general statistics for
students with some mathematical background at the first-year
graduate level or as a second course for those readers pursuing a
more quantitative emphasis in the social or natural sciences at
the undergraduate level.
* Actual data from readily available (interdisciplinary) sources
is used both in-text and on an author-maintained web site.
* Both intuitive and mathematical explanations are given in an
effort to balance the overall treatment and comprehension.
Table of Contents
Introduction.
1. Data: Plots and Location.
2. Data: Dispersion and Correlation.
3. Random Variables: Probability.
4. Random Variables: Expectation and Variance.
5. Statistical Inference.
6. Simple Linear Models.
7. Linear Model Diagnostics.
8. Linear Models: Two Independent Variables.
9. Linear Models: Several Independent Variables.
10. Model Building.
11. Extended Linear Models.
Appendix A: Data References.
Appendix B: MINITAB Reference.
Appendix C: Introduction to Linear Algebra.
Appendix D: Statistical Tables.
References.
Index.
ISBN: 0-471-72781-4
Hardcover
720 pages
July 2005
Description
The previous edition of this title has an excellent track record,
and its continued comprehensive coverage is unparalleled by the
competition. The author, who is renowned throughout the world,
has significantly and thoroughly refined and retooled this
edition.
This updated volume continues its straightforward, authoritative
review of basic statistical methods for clinical trials. Even
though numerous books have appeared on the subject matter, very
few of them, except for this title, emphasize accessible coverage
of statistical methods -- the crucial building blocks of medical
research. The author's hands-on approach, embracing a number of
different trial designs and clinical fields, guides readers
through the process of planning an experiment, putting together a
study cohort, assessing data, and reporting results, and
addresses the problems that are likely to confront any such study.
Paramount throughout is the effort to strike a common ground
between qualitative clinical and rigorous statistical methods.
Covers vital design considerations
Emphasizes experimental designs to search for treatment advances
Focuses on concepts that unify
Explores areas of controversy such as ethics (now greatly
expanded) and offers pragmatic information regarding allegations
of fraud or misconduct
Includes summaries, revised discussion questions, and updated
references in each chapter
Accompanied by an ftp site, dozens of new, redrawn, and/or
updated illustrations, a comprehensive bibliography, and multiple
indexes
Incorporates new content, including new chapters on contexts,
perspectives, transitional trials, and early developmental drug
design
Now, extensively class-tested
Table of Contents
1. Preliminaries.
2. Clinical Trails as Research.
3. Why Clinical Trials Are Ethical.
4. Contexts for Clinical Trials.
5. Statistical Perspectives.
6. Clinical Trials as Experimental Designs.
7. Random Error and Bias.
8. Objectives and Outcomes.
9. Translational Clinical Trials.
10. Dose Finding Designs.
11. Sample Size and Power.
12. The Study Cohort.
13. Treatment Allocation.
14. Treatment Effects Monitoring. 15. Counting Patients and
Events.
16. Estimating Clinical Effects.
17. Prognostic Factor Analyses.
18. Reporting and Authorship.
19. Factorial Designs.
20. Cross-Over Designs.
21. Meta-Analyses.
22. Misconduct and Fraud in Clinical Research.
Appendix A: Data and Programs.
Appendix B: Notation and Terminology.
Appendix C: Abbreviations.
Appendix D: Nuremberg Code.
Appendix E: Declaration of Helsinki.
Appendix F: NCI Data and Safety Monitoring Policy.
Appendix G: NIH Data and Safety Monitoring Policy.
Appendix H: Royal Statistical Society Code of Conduct.