Book Description
Using high-quality, real-world case studies and examples, this introduction to mathematical statistics shows how to use statistical methods and when to use them. This book can be used as a brief introduction to design of experiments. This successful, calculus-based book of probability and statistics, was one of the first to make real-world applications an integral part of motivating discussion. The number of problem sets has increased in all sections. Some sections include almost 50% new problems, while the most popular case studies remain.
For anyone needing to develop proficiency with Mathematical Statistics.
Customer Reviews:
dry and difficult.......2007-07-07
In case you're unclear on the matter, "mathematical statistics" is code talk for "statistics with calculus." So don't think this is book is a high-school or even undergraduate-level "introduction" for statistics. For that I would recommend the friendlier but still meaty Stats: Modeling the World (2nd Edition) (DeVeaux/Velleman/Bock).
At my university, this book is usually used in the first math class required of those in graduate school majoriing in the statistical social sciences.
So make sure you're ready. The authors assume you are quite solid at the calculus.
Confused and confusing.......2007-04-12
I used this as the text in a sequence on probability and statistics I taught recently, and I soon came to regret this choice. The authors are obviously quite confused about basic concepts. Here are some examples: the "definition" of the median ignores obvious problems with existence and uniqueness; the "proof" of the central limit theorem is thoroughly incomplete; the "theorems" on the tests in Sect. 9.2, 9.3 summarize previous discussions, but the "proofs" of these theorems (we are even referred to an appendix - no small surprise when the statements seem obvious) establish something entirely different; finally, to conclude this (very incomplete) selection, there is the delightful claim that the golden ratio is a transcendental number (which just proves that the authors don't have the slightest idea what a transcendental number really is, but then it might have been wise to avoid the use of the term).
In addition to these blatant problems, the authors' treatment frequently misses the point and/or is confusing.
Infuriating.......2006-11-08
The text presents all relevant information, but does so in such a confusing and poorly explained fashion as to prompt the reader to wonder if the authors have ever met anyone who hasn't known all subtleties of probability since the womb. There is no avenue for the student who does not understand, no pedagogy whatsoever. Everything is presented at lightning pace with blisteringly difficult proofs and, often, no meaningful explanation of the physical meaning of the concepts explained. A very solid background in calculus is an absolute necessity, to the point where many problems in the text are more challenging in evaluating integrals than they are in actually applying concepts. This is a serious problem that recurs over and over.
Examples worked out in the chapter sections also almost never bear any resemblance to the problems students are expected to complete. Although the examples vary in terms of difficulty, a student stuck on an exercise almost definitely will not find any help in the teaching material of the section in completing it simply because the examples never entirely cover the concepts demanded in the exercises.
s
Excellent intro to the mathematics of traditional statistics.......2005-03-19
The first half of the book begins with basic discrete and continuous probability theory. It continues with thorough overviews of the basic distributions (normal, Poisson, binomial, multinomial, chi-squared and student-T). The focus is on basic probability and variance analysis, though it briefly covers higher-order moments.
The second half of this book is devoted to hypothesis testing and regression. There is an excellent explanation of the mathematical presuppositions of the various classical experimental methodologies ranging from chi-square to t-tests to generalized likelihood ratio testing. It contains a very nicely organized chapter on general regression analysis, concentrating on the common least squares case under the usual transforms (e.g. exponential, logistic, etc.).
Like many books in mathematics, this introduction starts from first principles in the topic it's introducing, but assumes some "mathematical sophistication". In this case, it assumes you're comfortable with basic definition-example-theorem style and that you understand the basics of multivariate differential equations. I was a math and computer science undergrad who did much better in abstract algebra and set theory than analysis and diff eqs, but I found this book extremely readable. I couldn't have derived the proofs, but I could follow them because they were written as clearly as anything I've ever read in mathematics. I found the explanation of the central limit theorem and the numerous normal approximation theorems for sampling to be exceptionally clear.
The examples were both illuminating and entertaining. One of the beauties of statistics is that the examples are almost always interesting real-world problems, in this case ranging from biological (e.g. significance testing for cancer clusters) to man-made (e.g. Poisson models of football scoring) to physical (e.g. loaded dice). The examples tied directly to the techniques being explored. The exercises were more exercise-like in this book than in some math books where they're a dumping ground for material that wouldn't fit into the body of the text. This book has clearly been tuned over many years of classroom use with real students.
I read this book because I found I couldn't understand the applied statistics I was reading in machine learning and Bayesian data analysis research papers in my field (computational linguistics). In paticular, I wanted the background to be able to tackle books such as Hastie et al.'s "Elements of Statistical Learning" or Gelman et al.'s "Bayesian Data Analysis", both of which pretty much assume a good grounding in the topics covered in this book by Larsen and make excellent follow-on reading.
Master your calculus.......2005-02-07
I took up this book for my course in economics and i found the book clear and examples quite relevant. However, our calculus background was rather weak and we were left to study integrals by oursleves. Because of this, most of us floundered in the text and could not fully appreciate some of the more essential steps of the proofs. The solutions to many examples requires a solid background in calculus to fully appreciate and, at times, even understand since certain steps are ommited. So much so that our eco teacher, with a degree in engineering mind you, admitted the book was a bit too terse and spent most of the time explaining the calculus that we learnt very little of actual statistics.
In short, master your calculus or this book will only give you a rough feel for elementary statistics but will definitely not arm you to take up higher stat courses.
Book Description
"The book is outstanding and admirable in many respects. ... is necessary reading for all kinds of readers from undergraduate students to top authorities in the field." Journal of Symbolic Logic Written by two experts in the field, this is the only comprehensive and unified treatment of the central ideas and their applications of Kolmogorov complexity. the book presents a thorough treatment of the subject with a wide range of illsutrative applications. Such applications include the randomeness of finite objects or infinite sequences, Martin-Loef tests for randomness, information theory, computationla learning theory, the complexity of algorithms, and the thermodynamics of computing. It will be ideal for advanced undergraduate students, graduate students, and researchers in computer science, mathematics, cognitive sciences, philosophy, artificial intelligence, statistics, and physics. the book is self-contained in that it contains the basic requirements from mathematics and computer science. Included are also numerous problem sets, comments, source references, and himnts to solutions of problems. In this new edition the authors have added new material on circuit theory, distributed algorithms, data compression, and other topics.
Customer Reviews:
Biggest return for the biggest investment.......2005-05-08
This was the second-hardest book I ever read. Honestly, it took me years and years to get through it. I even had to buy a 2nd copy, because I kept getting frustrated and throwing the first copy across the room until it was destroyed. So yes, this book requires a substantial effort to read.
But the payback!! I've gotten more return on investment from this book than from any other book I've ever read. If you dilligently read and master this book, you will be able to analyze and solve problems your collegues just can't.
The basic idea behind Kolmogorov complexity is straighforward: a good measure of the complexity of an object is the length of the shortest computer program which will construct that object. From this basic idea an amazing variety of insights and powerful techniques have been developed, and this book is quite comprehensive in cataloging and explaining them.
For computer scientists and working programmers, probably the most useful result of Kolmogorov complexity would be the "Incompressibility Method", which is a powerful technique for the analysis of the runtime of algorithms. Typically, it is relatively easy to figure out what the best case or the worst case runtime of an algorithm is. Until now, it was hard to calculate the average runtime of an algorithm, because it usually involved a tricky counting problem, to enumerate all possible runs of the the algorithm and summing over them. The incompressibility method eliminates the need for doing these complicated enumerations, by letting you perform the analysis on a single run of the algorithm which is guarunteed to be representative of the average runtime of the algorithm. If you program for a living like I do, this will give you an edge, because if you can accurately predict that the worst-case runtimes almost never happen, you can usually simplify and streamline your programs by optimizing it for the average case. If your competitors are wasting time optimizing for a worst case which almost never happens--at the expense of _not_ optimizing for the average case, you win bigtime.
For philosophers of science and AI/knowledge representation folks, the most useful results of Kolmogorov complexity are probably the contributions of Kolmogorov complexity to Baysianism. To be a Baysian is to follow a two step process: (STEP 1) for every possible sentence, assign to it a number between 0 and 1 which represents how certain you are that that sentence is true. This initial assignment should be a probability distribution over all possible sentences. It should be a "good" probability distrubution, but of course it won't be perfect, since you don't know everything. (STEP 2) when confronted with new evidence, e.g. an observation, update your current "good" degrees of belief by using Bayes' law, to yield a new "better" set of degrees of belief.
The Baysians always had a good story for Step 2--just use Bayes law. But until now, they were mostly hand-waving on Step 1--what would constitude a "good" initial probability distribution? There were many proposals (e.g. maximum entropy) but all proposals had benefits and drawbacks. What Kolmogorov complexity provides is the so-called "universal" distribution, which is guarunteed to be a "good" initial distirbution. This book devotes much time to explaining and exploring this, and shows how previous techniques, like maximum entropy, minimum description length, etc all can be seen as computable approximations to the (unfortunately uncomputable) universal distribution. This really gives a nice framework for evalutating and formulating good prior distributions.
After remarking on how hard this book was to read, I should emphasize that this is not due to bad writing on the part of the authors! Indeed, after throwing the book across the room, I was always drawn back by Li & Vitanyi's most engaging writing style to pick the book back up, dust it off, and have another go at it. If it were not for their wonderul ability to expain a very complicated subject matter, I never would have gotten through it.
An unsung hero of this book is Peter Gacs, who wrote a set of lecture notes which really could be considered to be an Urtext for this book. If you tackle this book, I highly recommend that you also get ahold of these notes, because it is sometimes very useful, when trying to puzzle out a difficult argument, to get another description/explaination of it from a different point of view. These notes are available on the web, just google for "Lecture note on descriptional complexity and randomness" by Peter Gacs.
If you're up to the challange, then buy this book, dilligently read it, swear at it--then swear by it.
A must.......2003-10-29
The book provides all the tools needed for a productive use of the theory. Written by leading experts in the field, the book is both a fascinating introduction as well as a comprehensive reference for experts.
The authors are careful to place the development of the theory in its historical context, give a face to the main players in the field and explore frictions with other lines of thought. But the main storyline is the mathematical world of Kolmogorov complexity. Neccessary background knowledge is provided, most proofs are given and the open problems are presented. Most chapters are more or less self sufficient, making it possible to skip those that are of less relevance to you. In the later chapters much thought is given to the different fields of application.
A third edition is in the making which will include recent advances. But since the authors make new discoveries available on the web, the present edition will continue for a long time to hold a prominent place in the book shelves of many computer scientist.
Excellent if you have the math..........2002-08-13
to understand it. This book is intended for serious students of computer science or those who have some similar training - it is definitely set up as a textbook. However, that being said, if you have the background the authors' delivery is fist-class and very clear.
The reviews below give more than enough information so I won't belabour the Kolmogorov complexity here. Suffice it to say you won't find the subject detailed more fully in any other reference work in existence today.
However, this book does need to be revised and updated. There has been a lot of development in the field and the sections overviewing Solomonoff's work, in particular, could be expanded. Also, I found it hard to believe that nothing about the 'philosophical' importance of the whole induction question - this is at the core of many very important questions and should not be treated trivially.
There should also be some overview of two other areas that, in combination with the theory outlined in this text, are starting to form the nexus of a "new kind of science" (definitely not Wolfram's pathetic attempt). I refer to some information regarding non-classical logical systems as well as anticipatory computing systems. Both will, I predict, become core areas in addition to extensions to Kolmogorov/Chaitin complexity in the future.
All textbooks should be as clear and concise as this example.
The only one of its kind...........2001-09-23
The theory of Kolmogorov complexity attempts to define randomness in terms of the complexity of the program used to compute it. The authors give an excellent overview of this theory, and even discuss some of its philosophical ramifications, but they are always careful to distinguish between mathematical rigor and philosophical speculation. And, interestingly, the authors choose to discuss information theory in physics and the somewhat radical idea of reversible computation. The theory of Kolmogorov complexity is slowly making its way into applications, these being coding theory and computational intelligence, and network performance optimization, and this book serves as a fine reference for those readers interested in these applications. Some of the main points of the book I found interesting include: 1. A very condensed but effective discussion of Turing machines and effective computability. 2. The historical motivation for defining randomness and its defintiion using Kolmogorov complexity. 3. The discussion of coding theory and its relation to information theory. The Shannon-Fano code is discussed, along with prefix codes, Kraft's inequality, the noiseless coding theorem, and universal codes for infinite source word sets. 4. The treatment of algorithmic complexity. The authors stress that the information content of an object must be intrinsic and independent of the means of description. 5. The discussion of the explicit universal randomness test. 6. The discussion (in an exercise) of whether a probabilistic machine can perform a task that is impossible on a deterministic machine. 7. The notion of incompressibility of strings. 8. The discussion of randomness in the Diophantine equations; it is shown that the set of indices of the Diophantine equations with infinitely many different solutions is not recursively enumerable; with the initial segment of length n in the characteristic sequence having Kolmogorov complexity n. 9. The discussion on algorithmic probability, especially the test for randomness by martingales. 10. The Solomonoff theory of prediction and its ability to solve the problem of induction. 11. The treatment of Pac-learning and the resultant formalization of Occam's razor. 12. The discussion of compact routing; the optimal space to represent routing schemes in communication networks on the average for all static networks. 13. Computational complexity and its connection to resource-bounded complexity. 14. The notion of logical depth, i.e. the time required by a universal computer to compute the object from its compressed original description. 15. The connection between algorithmic complexity and Shannon's entropy. 16. The discussion on reversible computation, i.e. logically reversible computers that do not dissipate heat. 17. The treatment of information distance, i.e. for two strings, the minimal quantity of information sufficient to translate from one to the other.
Comprehensive and Excellent.......1999-07-31
This is one of the best-written mathematical texts I've read. It builds up the theory from basic principles, and illustrates it with numerous examples and applications. A definitive work.
Average customer rating:
|
Introduccion a La Estadistica Y Sus Aplicaciones/ Introduction to Statistics and Its Applications (Ciencia Y Tecnica / Science and Technology)
Ricardo Cao Abad ,
Mario F. Fernandez , and
Manuel A. Presedo Quindimil
Manufacturer: Piramide
ProductGroup: Book
Binding: Paperback
 Probability & Statistics
| Applied
| Mathematics
| Science
| Subjects
| Books
Statistics
| Applied
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
Spanish
| Foreign Language Nonfiction
| Nonfiction
| Subjects
| Books
Probabilidad y Estadística
| Aplicada
| Matemáticas
| Ciencia
| Libros en español
| Formats
| Books
No-Ficción
| Libros en español
| Formats
| Books
| Automotriz
| Ciencias Sociales
| Crimen y Criminales
| Educación
| Estudios de la Mujer
| Feriados
| Filosofía
| Gobierno
| Hechos Verídicos
| Planeamiento Urbano y Desarrollo
| Política
| Sucesos de Actualidad
| Transportación
Estadística
| Aplicada
| Matemáticas
| Ciencia Profesional
| Profesional y Técnico
| Libros en español
| Formats
| Books
ASIN: 8436815432 |
Average customer rating:
|
Mathematical Approaches for Emerging and Reemerging Infectious Diseases: An Introduction (The IMA Volumes in Mathematics and its Applications)
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover
Forensic Science
| Crime & Criminals
| Nonfiction
| Subjects
| Books
General
| Biology
| Biological Sciences
| Science
| Subjects
| Books
General
| Applied
| Mathematics
| Science
| Subjects
| Books
Biomathematics
| Applied
| Mathematics
| Science
| Subjects
| Books
General
| Mathematics
| Science
| Subjects
| Books
Immunology
| Basic Science
| Medicine
| Subjects
| Books
General
| Medicine
| Subjects
| Books
Communicable Diseases
| Infectious Disease
| Internal Medicine
| Medicine
| Subjects
| Books
Epidemiology
| Infectious Disease
| Internal Medicine
| Medicine
| Subjects
| Books
Forensic Medicine
| Pathology
| Specialties
| Medicine
| Subjects
| Books
Immunology
| Basic Sciences
| Medical
| Professional & Technical
| Subjects
| Books
Communicable Diseases
| Infectious Disease
| Internal Medicine
| Medicine
| Medical
| Professional & Technical
| Subjects
| Books
Epidemiology
| Internal Medicine
| Medicine
| Medical
| Professional & Technical
| Subjects
| Books
Forensic Medicine
| Pathology
| Internal Medicine
| Medicine
| Medical
| Professional & Technical
| Subjects
| Books
General
| Biology
| Biological Sciences
| Professional Science
| Professional & Technical
| Subjects
| Books
General
| Applied
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
Biology
| Medicine
| New & Used Textbooks
| Stores
| Books
Biostatistics & Epidemiology
| Medicine
| New & Used Textbooks
| Stores
| Books
General
| Medicine
| New & Used Textbooks
| Stores
| Books
Nursing
| Medicine
| New & Used Textbooks
| Stores
| Books
General
| Mathematics
| Sciences
| New & Used Textbooks
| Stores
| Books
All Amazon Upgrade
| Amazon Upgrade
| Stores
| Books
Medicine
| Amazon Upgrade
| Stores
| Books
Nonfiction
| Amazon Upgrade
| Stores
| Books
Professional & Technical
| Amazon Upgrade
| Stores
| Books
Science
| Amazon Upgrade
| Stores
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Medicine
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Nonfiction
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Professional
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Science
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Accessories:
-
Systems Biology: International Research and Development
-
Mathematics for Ecology and Environmental Sciences (Biological and Medical Physics, Biomedical Engineering)
-
Mathematics for Life Science and Medicine (Biological and Medical Physics, Biomedical Engineering)
ASIN: 038795354X |
Book Description
This book grew out of the discussions and presentations that began during the Workshop on Emerging and Reemerging Diseases (May 17-21, 1999) sponsored by the Institute for Mathematics and its Application (IMA) at the University of Minnesota with the support of NIH and NSF. The workshop started with a two-day tutorial session directed to ecologists, epidemiologists, immunologists, mathematicians, and scientists interested in the study of disease dynamics. The core of this first volume, Volume 125, covers tutorial and research contributions on the use of dynamical systems (deterministic discrete, delay, PDEs, and ODEs models) and stochastic models in disease dynamics. The volume includes the study of cancer, HIV, pertussis, and tuberculosis. Beginning graduate students in applied mathematics, scientists in the natural, social, or health sciences or mathematicians who want to enter the fields of mathematical and theoretical epidemiology will find this book useful.
Average customer rating:
|
One-dimensional Variational Problems: An Introduction (Oxford Lecture Series in Mathematics and Its Applications, 15)
Giuseppe Buttazzo ,
Mariano Giaquinta , and
Stefan Hildebrandt
Manufacturer: Oxford University Press, USA
ProductGroup: Book
Binding: Hardcover
General
| Science
| Subjects
| Books
General
| Applied
| Mathematics
| Science
| Subjects
| Books
Probability & Statistics
| Applied
| Mathematics
| Science
| Subjects
| Books
Calculus
| Pure Mathematics
| Mathematics
| Science
| Subjects
| Books
General
| Mathematics
| Science
| Subjects
| Books
Mathematical Analysis
| Mathematics
| Science
| Subjects
| Books
General
| Medicine
| Subjects
| Books
Mathematical Analysis
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
Calculus
| Pure Mathematics
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
Calculus
| Mathematics
| Sciences
| New & Used Textbooks
| Stores
| Books
Statistics
| Mathematics
| Sciences
| New & Used Textbooks
| Stores
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
ASIN: 0198504659 |
Book Description
One-dimensional variational problems have been somewhat neglected in the literature on calculus of variations, as authors usually treat minimal problems for multiple integrals which lead to partial differential equations and are considerably more difficult to handle. One-dimensional problems are connected with ordinary differential equations, and hence need many fewer technical prerequisites, but they exhibit the same kind of phenomena and surprises as variational problems for multiple integrals. This book provides an modern introduction to this subject, placing special emphasis on direct methods. It combines the efforts of a distinguished team of authors who are all renowned mathematicians and expositors. Since there are fewer technical details graduate students who want an overview of the modern approach to variational problems will be able to concentrate on the underlying theory and hence gain a good grounding in the subject. Except for results from the theory of measure and integration and from the theory of convex functions, the text develops all mathematical tools needed, including the basic results on one-dimensional Sobolev spaces, absolutely continuous functions, and functions of bounded variation.
Books:
- Animal Disease Surveillance and Survey Systems: Methods and Applications
- Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences
- Basic Business Statistics: Concepts and Applications and CD package (10th Edition)
- Bringing Out the Best in Yourself at Work: How to Use the Enneagram System for Success
- : Business Process Management and the Balanced Scorecard : Focusing Processes on Strategic Drivers
- Business Statistics: First Course and Student CD (4th Edition)
- Business Statistics: First Course and Student CD (4th Edition)
- Contemporary Engineering Economics (3rd Edition)
- Continuous Improvement Tools: A Practical Guide to Achieve Quality Results (Volume 2)
- Data Analysis and Decision Making with Microsoft Excel (with InfoTrac and CD-ROM)
Books Index
Books Home
Recommended Books
- Smart Talk for Achieving Your Potential: 5 Steps to Get You from Here to There
- Concrete Countertops: Design, Form, and Finishes for the New Kitchen and Bath
- Teaching Analysis of Film Language
- The Simple Sounds of Freedom : The True Story of the Only Soldier to Fight for Both America and the
- We Need to Talk About Kevin: A Novel
- Democracy in America
- Apple Pro Training Series: Advanced Color Correction and Effects in Final Cut Pro 5
- Of Permanent Value: The Story of Warren Buffett, Updated and Expanded Edition
- The Intelligent Negotiator: What to Say, What to Do, How to Get What You Want--Every Time
- WHITE BUTTERFLY: Featuring an Original Easy Rawlins Short Story "Lavender"
Student Solutions Manual: An Introduction to Mathematical Statistics: And Its Applications Fourth Edition
Probability and Statistics (3rd Edition)
Microeconomic Analysis, Third Edition
Game Theory for Applied Economists
Advanced Macroeconomics
