**Autor**: Erio Castagnoli

**Publisher:** EGEA spa

**ISBN:** 8823811511

**File Size**: 76,56 MB

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Today probability turns out to be one of the most pervasive mathematical topics. It actually affects a number of quite different fields, proving particularly relevant to courses ranging from Statistics to Economics, from Finance to Management Science. Recently it has even found significant applications in some sectors of Law. This book contains a short presentation of the most basic aspects of probability theory. As a result, it should come in handy and help students grasp the main concepts of the discipline as well as acquire a basic probabilistic vocabulary, thus capturing at least the flavour of possible relevant applications. The book includes a sketch of von Neumann Đ Morgenstern utility theory, which is useful per se as well as being an enlightening bridge between probability and decision theories. The book also provides a substantial set of exercises with solutions.
**Autor**: Frank Blume

**Publisher:** Createspace Independent Publishing Platform

**ISBN:** 9781519161659

**File Size**: 44,41 MB

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Probability is a beautiful mathematical theory in its own right, but it also is a theory that can be very widely applied. Quantum mechanics and statistical mechanics are vitally informed by it, and its methods of analysis are frequently encountered in just about every field of knowledge or endeavor that uses quantitative methods: economics, business, psychology, sociology, meteorology, biology, chemistry---the list goes on. Consequently, it is the goal of Undergraduate Probability to enable its readers to see how the mathematical formalisms of probability theory are naturally relevant to various real-world phenomena. Some of the application topics that are discussed in this text include velocities and pressures in ideal gases, climate data correlations, randomness and consciousness, and of course also a number of elementary random experiments involving coin flips or darts or rolls of a die. Moreover and more specifically, the great importance of the normal distribution and the Central Limit Theorem is consistently emphasized and thoroughly explored.
**Autor**: John E. Freund

**Publisher:** Courier Corporation

**ISBN:** 0486158438

**File Size**: 40,78 MB

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Featured topics include permutations and factorials, probabilities and odds, frequency interpretation, mathematical expectation, decision making, postulates of probability, rule of elimination, much more. Exercises with some solutions. Summary. 1973 edition.
**Autor**: Boris Vladimirovich Gnedenko

**Publisher:** Courier Corporation

**ISBN:** 9780486601557

**File Size**: 59,58 MB

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This compact volume equips the reader with all the facts and principles essential to a fundamental understanding of the theory of probability. It is an introduction, no more: throughout the book the authors discuss the theory of probability for situations having only a finite number of possibilities, and the mathematics employed is held to the elementary level. But within its purposely restricted range it is extremely thorough, well organized, and absolutely authoritative. It is the only English translation of the latest revised Russian edition; and it is the only current translation on the market that has been checked and approved by Gnedenko himself. After explaining in simple terms the meaning of the concept of probability and the means by which an event is declared to be in practice, impossible, the authors take up the processes involved in the calculation of probabilities. They survey the rules for addition and multiplication of probabilities, the concept of conditional probability, the formula for total probability, Bayes's formula, Bernoulli's scheme and theorem, the concepts of random variables, insufficiency of the mean value for the characterization of a random variable, methods of measuring the variance of a random variable, theorems on the standard deviation, the Chebyshev inequality, normal laws of distribution, distribution curves, properties of normal distribution curves, and related topics. The book is unique in that, while there are several high school and college textbooks available on this subject, there is no other popular treatment for the layman that contains quite the same material presented with the same degree of clarity and authenticity. Anyone who desires a fundamental grasp of this increasingly important subject cannot do better than to start with this book. New preface for Dover edition by B. V. Gnedenko.
**Autor**: John Haigh

**Publisher:** Oxford University Press

**ISBN:** 0199588481

**File Size**: 63,11 MB

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Making good decisions under conditions of uncertainty requires an appreciation of the way random chance works. In this Very Short Introduction, John Haigh provides a brief account of probability theory; explaining the philosophical approaches, discussing probability distributions, and looking its applications in science and economics.
**Autor**: William Mendenhall

**Publisher:** Cengage Learning Editores

**ISBN:** 9780534387778

**File Size**: 55,25 MB

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This brief version of the authors' classic text retains the traditional outline for the coverage of descriptive and inferential statistics. The user-friendly presentation includes features such as Key Concepts and Formulas, and helps students grasp the material while not sacrificing the statistical integrity of the subject. MINITABTM (Versions 12 and 13) is used exclusively as the computer package for statistical analysis in this text.
**Autor**: Charles Miller Grinstead

**Publisher:** American Mathematical Soc.

**ISBN:** 0821894145

**File Size**: 60,97 MB

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This text is designed for an introductory probability course at the university level for sophomores, juniors, and seniors in mathematics, physical and social sciences, engineering, and computer science. It presents a thorough treatment of ideas and techniques necessary for a firm understanding of the subject. The text is also recommended for use in discrete probability courses. The material is organized so that the discrete and continuous probability discussions are presented in a separate, but parallel, manner. This organization does not emphasize an overly rigorous or formal view of probability and therefore offers some strong pedagogical value. Hence, the discrete discussions can sometimes serve to motivate the more abstract continuous probability discussions. Features: Key ideas are developed in a somewhat leisurely style, providing a variety of interesting applications to probability and showing some nonintuitive ideas. Over 600 exercises provide the opportunity for practicing skills and developing a sound understanding of ideas. Numerous historical comments deal with the development of discrete probability. The text includes many computer programs that illustrate the algorithms or the methods of computation for important problems. The book is a beautiful introduction to probability theory at the beginning level. The book contains a lot of examples and an easy development of theory without any sacrifice of rigor, keeping the abstraction to a minimal level. It is indeed a valuable addition to the study of probability theory. --Zentralblatt MATH
**Autor**: Kenneth Baclawski

**Publisher:** CRC Press

**ISBN:** 9781420065220

**File Size**: 76,87 MB

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Based on a popular course taught by the late Gian-Carlo Rota of MIT, with many new topics covered as well, Introduction to Probability with R presents R programs and animations to provide an intuitive yet rigorous understanding of how to model natural phenomena from a probabilistic point of view. Although the R programs are small in length, they are just as sophisticated and powerful as longer programs in other languages. This brevity makes it easy for students to become proficient in R. This calculus-based introduction organizes the material around key themes. One of the most important themes centers on viewing probability as a way to look at the world, helping students think and reason probabilistically. The text also shows how to combine and link stochastic processes to form more complex processes that are better models of natural phenomena. In addition, it presents a unified treatment of transforms, such as Laplace, Fourier, and z; the foundations of fundamental stochastic processes using entropy and information; and an introduction to Markov chains from various viewpoints. Each chapter includes a short biographical note about a contributor to probability theory, exercises, and selected answers. The book has an accompanying website with more information.
**Autor**: Dimitri P. Bertsekas

**Publisher:**

**ISBN:** 9781886529236

**File Size**: 49,60 MB

**Format:** PDF, ePub

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**Autor**: Géza Schay

**Publisher:** Birkhäuser

**ISBN:** 3319306200

**File Size**: 26,49 MB

**Format:** PDF, Docs

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Now in its second edition, this textbook serves as an introduction to probability and statistics for non-mathematics majors who do not need the exhaustive detail and mathematical depth provided in more comprehensive treatments of the subject. The presentation covers the mathematical laws of random phenomena, including discrete and continuous random variables, expectation and variance, and common probability distributions such as the binomial, Poisson, and normal distributions. More classical examples such as Montmort's problem, the ballot problem, and Bertrand’s paradox are now included, along with applications such as the Maxwell-Boltzmann and Bose-Einstein distributions in physics. Key features in new edition: * 35 new exercises * Expanded section on the algebra of sets * Expanded chapters on probabilities to include more classical examples * New section on regression * Online instructors' manual containing solutions to all exercises“/p> Advanced undergraduate and graduate students in computer science, engineering, and other natural and social sciences with only a basic background in calculus will benefit from this introductory text balancing theory with applications. Review of the first edition: This textbook is a classical and well-written introduction to probability theory and statistics. ... the book is written ‘for an audience such as computer science students, whose mathematical background is not very strong and who do not need the detail and mathematical depth of similar books written for mathematics or statistics majors.’ ... Each new concept is clearly explained and is followed by many detailed examples. ... numerous examples of calculations are given and proofs are well-detailed." (Sophie Lemaire, Mathematical Reviews, Issue 2008 m)