'The book provides a comprehensive review of the DRM approach to data fusion. It is well written and easy to follow, although the technical details are not trivial. The authors did an excellent job in making a concise introduction of the statistical techniques in data fusion. The book contains several real data … Overall, I found that the book covers an important topic and the DRM is a promising tool in this area. Researchers on data fusion will surely find this book very helpful and I wil...

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share n...

An Introduction to Stochastic Modeling, Student Solutions Manual (e-only)

Everyone who's had to get to grips with chance knows how tricky even its simplest manifestations can be. Its workings are a constant challenge to common sense: a run of luck goes bad just when you trust it; expert predictions of everything from the weather to elections prove hopelessly unreliable; proven health advice turns out to be anything but.Award-winning scientist and writer Robert Matthews shows us how we can cut through the conundrums of chance. He gives us access to some o...

Chance and Luck: The Laws of Luck, Coincidences, Wagers, Lotteries, and the Fallacies of Gambling The false ideas prevalent among all classes of the community, cultured as well as uncultured, respecting chance and luck, illustrate the truth that common consent (in matters outside the influence of authority) argues almost of necessity error. This, by the way, might be proved by the method of probabilities. For if, in any question of difficulty, the chance that an ...

A decade ago, computer scientist Douglas Hofstadter coined the term innumeracy, which aptly described the widespread ailment of poor quantitative thinking in American society. So, in What the Numbers Say, Derrick Niederman and David Boyum present clear and comprehensible methods to help us process and calculate our way through the world of “data smog” that we live in. Avoiding abstruse formulations and equations, Niederman and Boyum anchor their presentations in the real ...

This textbook systematically presents fundamental methods of statistical analysis: from probability and statistical distributions, through basic concepts of statistical inference, to a collection of methods of analysis useful for scientific research. It is rich in tables, diagrams, and examples, in addition to theoretical justification of the methods of analysis introduced. Each chapter has a section entitled “Exercises and Problems” to accompany the text. There are altogether about 300 ex...

Praise for the First Edition"...a reference for everyone who is interested in knowing and handling uncertainty."—Journal of Applied StatisticsThe critically acclaimed First Edition of Understanding Uncertainty provided a study of uncertainty addressed to scholars in all fields, showing that uncertainty could be measured by probability, and that probability obeyed three basic rules that enabled uncertainty t...

Covers basic statistics and applications of major statistical tests. Preents the material in a sequence and approach that can be understood and used by almost anyone. Although this can be(and is) used as a text it is equally as useful as a study-aid for use with courses using more conventional texts. It is especially useful for those frightened by math or who are otherwise not well-prepared mathematically. It was developed as a text for Bachelor and Masters level students who have previous...

Mathematical statistics typically represents one of the most difficult challenges in statistics, particularly for those with more applied, rather than mathematical, interests and backgrounds. Most textbooks on the subject provide little or no review of the advanced calculus topics upon which much of mathematical statistics relies and furthermore contain material that is wholly theoretical, thus presenting even greater challenges to those interested in applying advanced statistics to a spec...

Based on a well-established and popular course taught by the authors over many years, Stochastic Processes: An Introduction, Third Edition, discusses the modelling and analysis of random experiments, where processes evolve over time. The text begins with a review of relevant fundamental probability. It then covers gambling problems, random walks, and Markov chains. The authors go on to discuss random processes continuous in time, including Poisson, birth and death processes, and general po...

Introduction to Probability Models, Tenth Edition, provides an introduction to elementary probability theory and stochastic processes. There are two approaches to the study of probability theory. One is heuristic and nonrigorous, and attempts to develop in students an intuitive feel for the subject that enables him or her to think probabilistically. The other approach attempts a rigorous development of probability by using the tools of measure theory. The first approach is employed in this...