The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful. Found insideAdding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, including smoothing and regularization methods ... This text assumes students have been exposed to intermediate algebra, and it focuses on the applications of statistical knowledge rather than the theory behind it. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics. The text is illustrated with many original and surprising examples and problems taken from classical applications like gambling, geometry or graph theory, as well as from applications in biology, medicine, social sciences, sports, and ... Abstract: "Petri nets augmented with timing specifications gained a wide acceptance in the area of performance and reliability evaluation of complex systems exhibiting concurrency, synchronization, and conflicts. As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more. For those who slept through Stats 101, this book is a lifesaver. Found insideWhether you're hitting the books for a probability or statistics course or hitting the tables at a casino, working out probabilities can be problematic. This book helps you even the odds. The book by Fang, Kotz and Ng summarizes these developments in a manner which is accessible to a reader with only limited background (advanced real-analysis calculus, linear algebra and elementary matrix calculus). A rigorous, comprehensive introduction to the finite Markov chain imbedding technique for studying the distributions of runs and patterns from a unified and intuitive viewpoint, away from the lines of traditional combinatorics. Featured topics include permutations and factorials, probabilities and odds, frequency interpretation, mathematical expectation, decision making, postulates of probability, rule of elimination, much more. This book provides a compact introduction to that field for students with minimal preparation, knowing mainly calculus and having "mathe matical maturity. Found insideThis useful reference/text provides a comprehensive study of the various bivariate discretedistributions that have appeared in the literature- written in an accessible manner thatassumes no more than a first course in mathematical ... Found insideThis engaging book discusses their distributional properties and dependence structures before exploring various orderings associated between different reliability structures. CK-12 Foundation's Basic Probability and Statistics A Short Course is an introduction to theoretical probability and data organization. Introductory Business Statistics is designed to meet the scope and sequence requirements of the one-semester statistics course for business, economics, and related majors. Found inside – Page iNew to this edition • Updated and re-worked Recommended Coverage for instructors, detailing which courses should use the textbook and how to utilize different sections for various objectives and time constraints • Extended and revised ... The book covers basic concepts such as random experiments, probability axioms, conditional probability, and counting methods, single and multiple random variables (discrete, continuous, and mixed), as well as moment-generating functions, ... Found inside – Page iThls ls preclsely the sub ject area of the book, the study of non-uniform random varlates. The plot evolves around the expected complexlty of random varlate genera tlon algorlthms. It is best suited to students with a good knowledge of calculus and the ability to think abstractly. The focus of the text is the ideas that statisticians care about as opposed to technical details of how to put those ideas into practice. Found insideAn integrated package of powerful probabilistic tools and key applications in modern mathematical data science. Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. Promoting a simulation- and experimentation-driven methodology, this book highlights the relationship between probability and computing in five distinctive parts: The R Language presents the essentials of the R language, including key ... Math and science majors with just one year of calculus can use this text and experience a refreshing blend of applications and theory that goes beyond merely mastering the technicalities. M2S1 Lecture NotesBy G. A. Young Found insideThe book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional This undergraduate text distils the wisdom of an experienced teacher and yields, to the mutual advantage of students and their instructors, a sound and stimulating introduction to probability theory. Found inside – Page iStatistics 101 — get an introduction to probability, sampling techniques and sampling distributions, and drawing conclusions from data Pictures tell the story — find out how to use several types of charts and graphs to visualize the ... A unique approach illustrating discrete distribution theory through combinatorial methods This book provides a unique approach by presenting combinatorial methods in tandem with discrete distribution theory. This book with the right blend of theory and applications is designed to provide a thorough knowledge on the basic concepts of Probability, Statistics and Random Variables offered to the undergraduate students of engineering. This book discusses in detail how to simulate data from common univariate and multivariate distributions, and how to use simulation to evaluate statistical techniques. 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. A thoroughly updated and revised look at system reliability theory Since the first edition of this popular text was published nearly a decade ago, new standards have changed the focus of reliability engineering and introduced new concepts ... Found insideProbability is the bedrock of machine learning. The purpose of this book is to provide a sound introduction to the study of real-world phenomena that possess random variation. Found insideIt also includes many probability inequalities that are not only useful in the context of this text, but also as a resource for investigating convergence of statistical procedures. Probability and Statistics for Computer Science develops introductory topics in probability with this particular emphasis, providing computer science students with an invaluable resource in their continued studies and professional research. Found insideA modern introduction to the Poisson process, with general point processes and random measures, and applications to stochastic geometry. The basic requirement for reading this book is simply a knowledge of mathematics at graduate level. This book tries to explain the difficult ideas in the axiomatic approach to the theory of probability in a clear and comprehensible manner. A self-study guide for practicing engineers, scientists, and students, this book offers practical, worked-out examples on continuous and discrete probability for problem-solving courses. This book is a compact account of the basic features of probability and random processes at the level of first and second year mathematics undergraduates and Masters' students in cognate fields. This important text: • Includes classroom-tested problems and solutions to probability exercises • Highlights real-world exercises designed to make clear the concepts presented • Uses Mathematica software to illustrate the text’s ... The book is a collection of 80 short and self-contained lectures covering most of the topics that are usually taught in intermediate courses in probability theory and mathematical statistics. With its thorough coverage and balanced presentation of theory and application, this is an excellent and essential reference for statisticians and mathematicians. 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