The second edition represents an ongoing effort to make probability accessible to students in a wide range of fields such as mathematics, statistics and data science, engineering, computer science, and business analytics. The book is written for those learning about probability for the first time. Revised and updated, the book is aimed specifically at statistics and data science students who need a solid introduction to the basics of probability.While retaining its focus on basic probability, including Bayesian probability and the interface between probability and computer simulation, this edition's significant revisions are as follows:The approach followed in the book is to develop probabilistic intuition before diving into details. The best way to learn probability is by practising on a lot of problems. Many instructive problems together with problem-solving strategies are given. Answers to all problems and worked-out solutions to selected problems are also provided.Henk Tijms is the author of several textbooks in the area of applied probability. In 2008, he had received the prestigious INFORMS Expository Writing Award for his work. He is active in popularizing probability at Dutch high schools.

This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.

Now available in a fully revised and updated second edition, this well established textbook provides a straightforward introduction to the theory of probability. The presentation is entertaining without any sacrifice of rigour; important notions are covered with the clarity that the subject demands. Topics covered include conditional probability, independence, discrete and continuous random variables, basic combinatorics, generating functions and limit theorems, and an introduction to Markov chains. The text is accessible to undergraduate students and provides numerous worked examples and exercises to help build the important skills necessary for problem solving.

Comprehensive, yet concise, this textbook is the go-to guide to learn why probability is so important and its applications.

"The book uses the approach of probabilistic intuition before getting into details; An inter-weaved treatment of basic probability and Monte Carlo simulation; A carefully designed collection of motivational examples and problems; The student is guided in both creative and algorithmic thinking"--

'What makes this book unique among books of similar size and scope is that when the author decided to include something in the book, he has treated it in a way similar to the common practice in textbooks, with very detailed and reader-friendly explanations, fully worked-out examples, and even numerous exercises … There are no prerequisites beyond second-semester calculus and the book can be used for self-study as well as in the classroom.'CHOICEWritten by international award-winning probability expert Henk Tijms, Basic Probability: What Every Math Student Should Know presents the essentials of elementary probability. The book is primarily written for high school and college students learning about probability for the first time. In a highly accessible way, a modern treatment of the subject is given with emphasis on conditional probability and Bayesian probability, on striking applications of the Poisson distribution, and on the interface between probability and computer simulation.In modern society, it is important to be able to critically evaluate statements of a probabilistic nature presented in the media in order to make informed judgments. A basic knowledge of probability theory is indispensable to logical thinking and statistical literacy. The book provides this knowledge and illustrates it with numerous everyday situations.

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.