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Educational, eloquent, and entertaining, Probabilities: The Little Numbers That Rule Our Lives is the ideal companion for anyone who wants to obtain a better understanding of the mathematics of chance.
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Ross's classic bestseller, Introduction to Probability Models, has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. It provides an introduction to elementary probability theory and stochastic processes, and shows how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. With the addition of several new sections relating to actuaries, this text is highly recommended by the Society of Actuaries. A new section (3.7) on COMPOUND RANDOM VARIABLES, that can be used to establish a recursive formula for computing probability mass functions for a variety of common compounding distributions. A new section (4.11) on HIDDDEN MARKOV CHAINS, including the forward and backward approaches for computing the joint probability mass function of the signals, as well as the Viterbi algorithm for determining the most likely sequence of states. Simplified Approach for Analyzing Nonhomogeneous Poisson processes Additional results on queues relating to the (a) conditional distribution of the number found by an M/M/1 arrival who spends a time t in the system,; (b) inspection paradox for M/M/1 queues (c) M/G/1 queue with server breakdown Many new examples and exercises.
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With comprehensive integration of the PC-based statistical software Minitab and online support through WileyPLUS, this newest edition of Engineering Statistics will serve as a practical introduction for students and a reliable reference for every stage of your engineering career.
Probabilities. --- Statistics. --- Statistics --- Probabilities
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"[Cet ouvrage] est consacré à l'exposition des notions de base du calcul des probabilités. Il s'appuie de façon essentielle sur la théorie de la mesure et de l'intégration de Lebesgue. Les mesures de probabilité discrètes ou à densité sont donc étudiées dans un même cadre, au titre d'exemples privilégiés les plus usuels. Après des rappels sur l'intégration, l'ouvrage développe successivement les thèmes suivants : lois de variables aléatoires, indépendance et addition des variables aléatoires indépendantes, convergence de suites de variables aléatoires et théorèmes limites, conditionnement, martingales à temps discret et chaines de Markov à espace d'états dénombrable. Chaque chapitre est complété par une série d'exercices destinés à appronfondir et illustrer les éléments de la théorie venant d'être introduits." (source : 4e de couv.)
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Introduction to Probability, Second Edition, is written for upper-level undergraduate students in statistics, mathematics, engineering, computer science, operations research, actuarial science, biological sciences, economics, physics, and some of the social sciences. With his trademark clarity and economy of language, the author explains important concepts of probability, while providing useful exercises and examples of real world applications for students to consider. After introducing fundamental probability concepts, the book proceeds to topics including special distributions, the joint probability density function, covariance and correlation coefficients of two random variables, and more. Demonstrates the applicability of probability to many human activities with examples and illustrationsDiscusses probability theory in a mathematically rigorous, yet accessible wayEach section provides relevant proofs, and is followed by exercises and useful hintsAnswers to even-numbered exercises are provided and detailed answers to all exercises are available to instructors on the book companion site.
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Chance --- Probabilities --- Hasard --- Probabilités --- History --- Histoire --- Probabilities, --- Probabilités --- Probabilities - History
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