{"product_id":"probability-9780471458920","title":"Probability","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eImprove Your Probability of Mastering This Topic\u003cbr\u003e \u003cbr\u003e This book takes an innovative approach to calculus-based probability theory, considering it within a framework for creating models of random phenomena. The author focuses on the synthesis of stochastic models concurrent with the development of distribution theory while also introducing the reader to basic statistical inference. In this way, the major stochastic processes are blended with coverage of probability laws, random variables, and distribution theory, equipping the reader to be a true problem solver and critical thinker.\u003cbr\u003e \u003cbr\u003e Deliberately conversational in tone, Probability is written for students in junior- or senior-level probability courses majoring in mathematics, statistics, computer science, or engineering. The book offers a lucid and mathematicallysound introduction to how probability is used to model random behavior in the natural world. The text contains the following chapters:\u003cbr\u003e * Modeling\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\"Many instructors will find this book a useful adjunct to their courses.\" (\u003ci\u003eThe American Statistician\u003c\/i\u003e, August 2007)  \u003cp\u003e\"…a very pleasant and highly accessible textbook that perfectly meets the goal…[of making] probability theory accessible without sacrificing mathematical accuracy.\" (\u003ci\u003eMathematical Reviews\u003c\/i\u003e, 2007h)\u003c\/p\u003e \u003cp\u003e\"This book more than lives up to its ambitious title…can hold its own against any comparable text.\" (\u003ci\u003eMAA Reviews\u003c\/i\u003e, January 30, 2007)\u003c\/p\u003e \u003cp\u003e\"This book is very useful for scientists and for students who study mathematics, statistics, economics and engineering.\" (\u003ci\u003eZentralblatt MATH\u003c\/i\u003e, 1105,52)\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePreface.  \u003cp\u003eTo the Student.\u003c\/p\u003e \u003cp\u003eTo the Instructor.\u003c\/p\u003e \u003cp\u003eCoverage.\u003c\/p\u003e \u003cp\u003eAcknowledgments.\u003c\/p\u003e \u003cp\u003eChapter 1. Modeling.\u003c\/p\u003e \u003cp\u003e1.1  Choice and Chance.\u003c\/p\u003e \u003cp\u003e1.2  The Model Building Process.\u003c\/p\u003e \u003cp\u003e1.3  Modeling in the Mathematical Sciences.\u003c\/p\u003e \u003cp\u003e1.4  A First Look at a Probability Model: The Random Walk.\u003c\/p\u003e \u003cp\u003e1.5  Brief Applications of Random Walks.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eChapter 2.  Sets and Functions.\u003c\/p\u003e \u003cp\u003e2.1  Operations with Sets.\u003c\/p\u003e \u003cp\u003e2.2  Functions.\u003c\/p\u003e \u003cp\u003e2.3  The Probability Function and the Axioms of Probability.\u003c\/p\u003e \u003cp\u003e2.4  Equally Likely Sample Spaces and Counting Rules.\u003c\/p\u003e \u003cp\u003eRules.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eChapter 3.  Probility Laws I: Building on the Axioms.\u003c\/p\u003e \u003cp\u003e3.1  The Complement Rule.\u003c\/p\u003e \u003cp\u003e3.2  The Addition Rule.\u003c\/p\u003e \u003cp\u003e3.3  Extensions and Additional Results.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eChapter 4.  Probility Laws II: Results of Conditioning.\u003c\/p\u003e \u003cp\u003e4.1  Conditional Probability and the Multiplication Rule.\u003c\/p\u003e \u003cp\u003e4.2  Independent Events.\u003c\/p\u003e \u003cp\u003e4.3  The Theorem of Total Probabilities and Bayes' Rule.\u003c\/p\u003e \u003cp\u003e4.4  Problems of Special Interest: Effortful Illustrations of the Probability Laws.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eChapter 5.  Random Variables and  Stochastic Processes.\u003c\/p\u003e \u003cp\u003e5.1  Roles and Types of Random Variables.\u003c\/p\u003e \u003cp\u003e5.2  Expectation.\u003c\/p\u003e \u003cp\u003e5.3  Roles, Types, and Characteristics of  Stochastic Processes.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eChapter 6.  Discrete Random Variables and Applications in Stochastic Processes.\u003c\/p\u003e \u003cp\u003e6.1  The Bernoulli and Binomial Models.\u003c\/p\u003e \u003cp\u003e6.2  The Hypergeometric Model.\u003c\/p\u003e \u003cp\u003e6.3  The Poisson Model.\u003c\/p\u003e \u003cp\u003e6.4  The Geometric and Negative Binomial.\u003c\/p\u003e \u003cp\u003eModels.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eChapter 7.  Continuous Random Variables and Applications in Stochastic Processes.\u003c\/p\u003e \u003cp\u003e7.1  The Continuous Uniform Model.\u003c\/p\u003e \u003cp\u003e7.2  The Exponential Model.\u003c\/p\u003e \u003cp\u003e7.3  The Gamma Model.\u003c\/p\u003e \u003cp\u003e7.4  The Normal Model.\u003c\/p\u003e \u003cp\u003eChapter 8.  Covariance and Correlation Among Random Variables.\u003c\/p\u003e \u003cp\u003e8.1  Joint, Marginal and Conditional Distributions.\u003c\/p\u003e \u003cp\u003e8.2  Covariance and Correlation.\u003c\/p\u003e \u003cp\u003e8.3  Brief  Examples and Illustrations in Stochastic Processes and Times Series.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eBibliography.\u003c\/p\u003e \u003cp\u003eTables.\u003c\/p\u003e \u003cp\u003eIndex.\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49402598719831,"sku":"9780471458920","price":163.76,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780471458920.jpg?v=1730480916","url":"https:\/\/bookcurl.com\/products\/probability-9780471458920","provider":"Book Curl","version":"1.0","type":"link"}