Book Description
Bean's PROBABILITY: THE SCIENCE OF UNCERTAINTY WITH APPLICATIONS TO INVESTMENTS, INSURANCE, AND ENGINEERING is an 'applied' book that will be of interest to instructors teaching probability in mathematics departments of operations research, statistics, actuarial science, management science, and decision science. Comprehensive, easy to read and comprehend, and current, the book uses investment, insurance, and engineering applications throughout as a unifying theme.
Customer Reviews:
Good for self-study.......2007-04-03
I used this textbook as my main study material for the SOA/CAS P/1 exam. I found it to be well-written and understandable. I have some background in calculus and probability (long-forgotten college courses). I'm hanging on to it for future reference. It's actually possible to learn the material from the book all on your own. All in all, one of the better textbooks out there.
I use this book almost every day.......2006-07-21
I appreciate that many people will be buying this because it has been endorsed by the Society of Actuaries. My review is for those who aren't being compelled to use the book in exam prep. I find "The Science of Uncertainty" to be the most consistently useful of the statistics texts in my office. The examples are clear, it has the right equations, and it's well organized.
Some people here are complaining of inaccuracies but they provide no examples and, frankly, I've never noticed a problem.
I like that authors provided an appendix explaining how to manipulate the distributions they discuss in the book using Mathematica. This was not new to me, but I can imagine it would save others some headaches.
Excellent for SOA exam P.......2005-05-26
I used this book to study for SOA exam P and loved it! If you already have some background in statistics and probability, this is the book to go. It will fill in the blanks left by your average school textbook and give you the nesessary coverage of the exam material.
A hard book to digest.......2005-01-18
As a statistics graduate, I found it hard to understand this book. There are not many friendly examples to help the readers to understand the concepts, even with the help of solution manual. There are some mistakes too.
Not a good learning book.......2003-03-02
Some gaffes in this book, I don't think the author has any real understanding. He even messes up the definition of expectation, and it doesn't get more elementary than that. There are many better probability books out there, don't choose this one.
Average customer rating:
- Great to reach an understanding
- Statistics
- Really good
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Fundamentals of Behavioral Statistics
Richard P. Runyon ,
Kay A Coleman , and
David Pittenger
Manufacturer: McGraw-Hill Humanities/Social Sciences/Languages
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ASIN: 0072286415 |
Book Description
A proven performer designed for today’s psychology students, Fundamentals of Behavioral Statistics combines current thinking with a clear presentation designed to foster complete student understanding. A classic text that features a modern, student-oriented approach to studying behavioral statistics with an emphasis on accessibility and comprehensiveness, it is built on four tenants of success: a strong mathematical foundation, clear and interesting examples, rich illustrations and abundant exercises. The revision will continue to place great emphasis on introducing students to exploratory data analytic techniques by replacing outdated techniques with the latest, most up to date methods. Real life examples, used to present the most current approaches to teaching statistics, will be revised to incorporate results from popular and familiar experiments.
Customer Reviews:
Great to reach an understanding.......2007-09-23
Great for those trying to get the basic understanding of behavioral statistics. The wording is very plain and easy to understand, yet they also don't ramble. The index works well, and the appendices are highly useful.
Statistics.......2007-09-16
I am using this book for an online graduate statistics course, so there is little direction from a formal instructor. All of my information so far is from this book. It is easy to read and the examples are easy to follow. I would recommend this book to anyone who is beginning the journey into statistics...very helpful
Really good.......2003-12-01
A unique introductory book in statistics. The hallmark of this book is nodoubt the clarity of detailed explanations of fundamental statistical concepts. A lot of invaluable material and explanantions here not to be found in other textbooks on statistics!
Highlights that spring to my mind are the excellent treatments of averages, correlation and regression, and hypothesis testing. A very important topic (usually missing in most textbooks) is the strength of evidence in hypothesis and significiance testing and is treated very nicely in various parts of the books. This book should not be missed by beginners (and probably experts) in the field.
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Uncertainty, Calibration and Probability: The Statistics of Scientific and Industrial Measurement (The Adam Hilger Series on Measurement Science and)
C.F Dietrich
Manufacturer: Taylor & Francis
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ASIN: 0750300604 |
Book Description
All measurements are subject to error because no quantity can be known exactly; hence, any measurement has a probability of lying within a certain range. The more precise the measurement, the smaller the range of uncertainty. Uncertainty, Calibration and Probability is a comprehensive treatment of the statistics and methods of estimating these calibration uncertainties. The book features the general theory of uncertainty involving the combination (convolution) of non-Gaussian, student t, and Gaussian distributions; the use of rectangular distributions to represent systematic uncertainties; and measurable and nonmeasurable uncertainties that require estimation. The author also discusses sources of measurement errors and curve fitting with numerous examples of uncertainty case studies. Many useful tables and computational formulae are included as well. All formulations are discussed and demonstrated with the minimum of mathematical knowledge assumed. This second edition offers additional examples in each chapter, and detailed additions and alterations made to the text. New chapters consist of the general theory of uncertainty and applications to industry and a new section discusses the use of orthogonal polynomials in curve fitting. Focusing on practical problems of measurement, Uncertainty, Calibration and Probability is an invaluable reference tool for R&D laboratories in the engineering/manufacturing industries and for undergraduate and graduate students in physics, engineering, and metrology.
Book Description
A careful blend of theory and practice, this book presents a comprehensive approach to assessing the impact of unplanned events on the cost of engineering complex systems. It illustrates how probability theory is applied to model, measure, and manage risk in the cost of a systems engineering project. The book contains numerous mathematical and professional anecdotes, case studies, results, observations, and interpretations that clarify the challenges in cost risk analysis. It includes references, equations, and illustrations, provides theoretical and applied exercises, and uses examples and case discussions derived from systems engineering projects to describe key concepts.
Customer Reviews:
Best technical book written yet, on this subject.......2003-12-12
Well written and very thorough in its treatment of how probability methods are used to quantify cost risk; excellent textbook for students (lots of exercises), as well as for professional cost analysts.
A Must Book for Engineers and Engineering Managers!.......2000-07-08
This is a must book for engineers, scientists, and engineering managers. Garvey's book presents how probability theory is applied to model, measure, and manage risk in the cost of a systems engineering project. The work is a first of its kind in the engineering, cost engineering/analysis, and operations research communities.
The book provides readers a clear discussion on the nature of uncertainty, how it affects the cost of a systems engineering project, and how probability methods are used to model, measure, and control risk from a systems engineering perspective. Readers benefit from the numerous mathematical and professional anecdotes, case discussions, results, observations, and interpretations found throughout the chapters.
The book contains 110 applied and theoretical exercises. It is an outstanding text for students in engineering and the related fields.
Book Description
A novel, practical approach to modeling spatial uncertainty.
This book deals with statistical models used to describe natural variables distributed in space or in time and space. It takes a practical, unified approach to geostatistics-integrating statistical data with physical equations and geological concepts while stressing the importance of an objective description based on empirical evidence. This unique approach facilitates realistic modeling that accounts for the complexity of natural phenomena and helps solve economic and development problems-in mining, oil exploration, environmental engineering, and other real-world situations involving spatial uncertainty.
Up-to-date, comprehensive, and well-written, Geostatistics: Modeling Spatial Uncertainty explains both theory and applications, covers many useful topics, and offers a wealth of new insights for nonstatisticians and seasoned professionals alike. This volume:
* Reviews the most up-to-date geostatistical methods and the types of problems they address.
* Emphasizes the statistical methodologies employed in spatial estimation.
* Presents simulation techniques and digital models of uncertainty.
* Features more than 150 figures and many concrete examples throughout the text.
* Includes extensive footnoting as well as a thorough bibliography.
Geostatistics: Modeling Spatial Uncertainty is the only geostatistical book to address a broad audience in both industry and academia. An invaluable resource for geostatisticians, physicists, mining engineers, and earth science professionals such as petroleum geologists, geophysicists, and hydrogeologists, it is also an excellent supplementary text for graduate-level courses in related subjects.
Customer Reviews:
Highly recommended!.......2000-03-16
Highly recommended! This is easily the most comprehensive, scholarly, and up-to-date work in the area.
The authors cover the entire range of geostatistics - structural analysis (variogram fitting), kriging, multivariate and nonlinear methods, conditional simulation, scale effects, and inverse problems. The chapter on geostatistical simulation is particularly impressive, and much unpublished work of Georges Matheron and the Center for Geostatistics at Fontainebleau, France, is made available here for the first time. Practical and theoretical aspects of geostatistics balance each other very nicely.
This is not an introductory text - there are other books in the area which are custom-tailored to beginners - but it is an invaluable, and very carefully written, reference. For anyone applying geostatistical techniques in environmental sciences, earth sciences, engineering, or related fields, this book is a must-have!
the reference book in geostatistics.......2000-02-17
There are a large number of books on geostatistics, usually introductory books dealing with parts of the subject. The volume by Chiles and Delfiner is THE comprehensive reference book in geostatistics that has been missing up to now.
It covers every part of geostatistics. After a useful introduction and preliminaries, different chapters are devoted successively to structural analysis, kriging, the intrinsic model of order k, multivariate methods, nonlinear methods, conditional simulations, scale effects and inverse problems.
Within each section, the book offers an accurate perspective of the different geostatistical methods. Practical approaches as well as theoretical developments are jointly considered, providing a sound basis to the user.
The writing is fluent, with an extensive documentation and a most helpful index.
The book will benefit those who want to know more about a specific method, as well as those who are looking for different approaches to a given problem. It will be valuable for academics and students, as well as scientists, engineers and practitioners from different domains such as mining, hydrogeology, oil exploration, soil science, forestry, and environmental sciences.
Book Description
A lively and informal introduction to the role of uncertainty and probability in people's lives from an everyday perspective
From television game shows and gambling techniques to weather forecasting and the financial markets, virtually every aspect of modern life involves situations in which the outcomes are uncertain and of varying qualities. But as noted statistician Dennis Lindley writes in this distinctive text, "We want you to face up to uncertainty, not hide it away under false concepts, but to understand it and, moreover, to use the recent discoveries so that you can act in the face of uncertainty more sensibly than would have been possible without the skill."
Accessibly written at an elementary level, this outstanding text examines uncertainty in various everyday situations and introduces readers to three rules—craftily laid out in the book—that prove uncertainty can be handled with as much confidence as ordinary logic. Combining a concept of utility with probability, the book insightfully demonstrates how uncertainty can be measured and used in everyday life, especially in decision-making and science.
With a focus on understanding and using probability calculations, Understanding Uncertainty demystifies probability and:
- Explains in straightforward detail the logic of uncertainty, its truths, and its falsehoods
- Explores what has been learned in the twentieth century about uncertainty
- Provides a logical, sensible method for acting in the face of uncertainty
- Presents vignettes of great discoveries made in the twentieth century
- Shows readers how to discern if another person—whether a lawyer, politician, scientist, or journalist—is talking sense, posing the right questions, or obtaining sound answers
Requiring only a basic understanding of mathematical concepts and operations, Understanding Uncertainty is useful as a text for all students who have probability or statistics as part of their course, even at the most introductory level.
Customer Reviews:
Simply brilliant.......2007-05-01
I started by reading the prologue, then the epilogue, and then I could not let go of this book any more: The thinking is razor sharp, the beauty of the writing breathtaking. Dennis Lindley has a phenomenal gift to explain complex concepts to a broad audience. The content is relevant to all of us involved and interested in the underpinning of decision-making. If only the second round of this oeuvre (ie the result of another lifetime of thinking), understanding uncertainty in a context of conflict, had already been written, preferably by somebody as brilliant and eloquent as Dennis Lindley.
Book Description
This magnificent book is the first comprehensive history of statistics from its beginnings around 1700 to its emergence as a distinct and mature discipline around 1900.
Stephen M. Stigler shows how statistics arose from the interplay of mathematical concepts and the needs of several applied sciences including astronomy, geodesy, experimental psychology, genetics, and sociology. He addresses many intriguing questions: How did scientists learn to combine measurements made under different conditions? And how were they led to use probability theory to measure the accuracy of the result? Why were statistical methods used successfully in astronomy long before they began to play a significant role in the social sciences? How could the introduction of least squares predate the discovery of regression by more than eighty years? On what grounds can the major works of men such as Bernoulli, De Moivre, Bayes, Quetelet, and Lexis be considered partial failures, while those of Laplace, Galton, Edgeworth, Pearson, and Yule are counted as successes? How did Galton's probability machine (the quincunx) provide him with the key to the major advance of the last half of the nineteenth century?
Stigler's emphasis is upon how, when, and where the methods of probability theory were developed for measuring uncertainty in experimental and observational science, for reducing uncertainty, and as a conceptual framework for quantative studies in the social sciences. He describes with care the scientific context in which the different methods evolved and identifies the problems (conceptual or mathematical) that retarded the growth of mathematical statistics and the conceptual developments that permitted major breakthroughs.
Statisticians, historians of science, and social and behavioral scientists will gain from this book a deeper understanding of the use of statistical methods and a better grasp of the promise and limitations of such techniques. The product of ten years of research, The History of Statistics will appeal to all who are interested in the humanistic study of science.
Customer Reviews:
Excellent content, turgid prose.......2003-07-05
Professor Stigler is an academic, and writes like one. He is obviously knowledgeable; this book will appeal to professional statisticians.
For intelligent laymen with a general interest in the history of statistics, "Against the Gods: The Story of Risk" by Peter Bernstein and "The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century" by David Salsburg will be equally informative and far more enjoyable. Both authors are as knowledgeable as Professor Stigler, but write more clearly.
typical authoritative work of Stigler.......2001-04-21
Stigler is unrivaled as a statistician who researches the history of statistics. This covers the famous mathematicians and statisticians who developed the foundation on which probability and statistics blossomed in the 20th Century. He is thorough and accurate and his writing is always clear and interesting. After reading this try Salsburg's "Lady Tasting Tea" to see how Fisher, Cramer, Neyman and Pearson and Kolmogorov and others formally developed probabilty and mathematical statistics as important disciplines in the 20th Century.
The difinitive work on the development of ststistics.......2000-01-19
This book is THE definitive work on the early development of statistics. Obviously written by a man in love with his subject. Bernoulli, de Moivre, Bayes, Laplace, Gauss, Quetelet, Lexis, Galton, Edgeworth and Pearson all but come alive. I particularly enjoyed the reproductions of first sources included that you would otherwise have to travel to Paris to see.
Average customer rating:
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Probability and Statistics: The Science of Uncertainty
Michael J. Evans , and
Jeffrey S. Rosenthal
Manufacturer: W. H. Freeman
ProductGroup: Book
Binding: Hardcover
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ASIN: 0716747421 |
Customer Reviews:
Dissapointing.......2005-04-19
I have used this textbook for two of my statistics courses: One being introduction to theoretical probability, and another one was mostly about statistical inference. Part of this book that contains probability is actually written quite nicely. It has a lot of useful chapters on introductory probability theory. However, do not expect many combinatorial problems to be presented here.
However, while taking the second course in statistics, I realized that part of this book that covers statistical methods is rather garbage. Reading those sections it just a total waste of time. This book overcomplicates even easy things and tends to use a lot of random letters to represent various variables, which I have never seen in any other book on this subject.
PROS:
Probability part is well written and clear, good excercises.
Contains advanced things that are not done on introductory level
CONS:
Everything else
In my opinion this book is simply not worth buying. Try to borrow one from a friend, get it from the library. Just don't waste your time and money on this one.
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Risk, Reliability, Uncertainty & Robustness of Water Resource Systems
Manufacturer: Cambridge University Press
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ASIN: 0521800366 |
Book Description
In Risk, Reliability, Uncertainty and Robustness of Water Resources Systems, thirty-five leading scientists provide state-of-the-art reviews of topical areas of research on water resources systems, including aspects of extreme hydrological events: floods and droughts, water quantity and quality, dams, reservoirs and hydraulic structures, evaluating sustainability and climate change impacts. As well as discussing essential challenges and research directions, the book will assist in applying theoretical methods to the solution of practical problems in water resources.
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Measurement Uncertainty: An Approach via the Mathematical Theory of Evidence (Springer Series in Reliability Engineering)
Simona Salicone
Manufacturer: Springer
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ASIN: 0387306552 |
Book Description
The expression of uncertainty in measurement is a challenging aspect for researchers and engineers working in instrumentation and measurement because it involves physical, mathematical and philosophical issues. This problem is intensified by the limitations of the probabilistic approach used by the current standard (GUM).
This text is the first to make full use of the mathematical theory of evidence to express the uncertainty in measurements. It gives an overview of the current standard, then pinpoints and constructively resolves its limitations through its unique approach. The text presents various tools for evaluating uncertainty, beginning with the probabilistic approach and concluding with the expression of uncertainty using random-fuzzy variables. The exposition is driven by numerous examples. The book is designed for immediate use and application in research and laboratory work.
Apart from a classroom setting, this book can be used by practitioners in a variety of fields (including applied mathematics, applied probability, electrical and computer engineering, and experimental physics), and by such institutions as the IEEE, ISA, and National Institute of Standards and Technology.
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- Real Analysis: Measure Theory, Integration, and Hilbert Spaces (Princeton Lectures in Analysis)
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