Elementary Probability With Applications
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Elementary Probability with Applications
Elementary Probability with Applications, Second Edition shows students how probability has practical uses in many different fields, such as business, politics, and sports. In the book, students learn about probability concepts from real-world examples rather than theory. The text explains how probability models with underlying assumptions are used to model actual situations. It contains examples of probability models as they relate to: Bloc voting Population genetics Doubling strategies in casinos Machine reliability Airline management Cryptology Blood testing Dogs resembling owners Drug detection Jury verdicts Coincidences Number of concert hall aisles 2000 U.S. presidential election Points after deuce in tennis Tests regarding intelligent dogs Music composition Based on the author’s course at The College of William and Mary, the text can be used in a one-semester or one-quarter course in discrete probability with a strong emphasis on applications. By studying the book, students will appreciate the subject of probability and its applications and develop their problem-solving and reasoning skills.
Basic Probability Theory with Applications
Author: Mario Lefebvre
language: en
Publisher: Springer Science & Business Media
Release Date: 2009-10-03
The main intended audience for this book is undergraduate students in pure and applied sciences, especially those in engineering. Chapters 2 to 4 cover the probability theory they generally need in their training. Although the treatment of the subject is surely su?cient for non-mathematicians, I intentionally avoided getting too much into detail. For instance, topics such as mixed type random variables and the Dirac delta function are only brie?y mentioned. Courses on probability theory are often considered di?cult. However, after having taught this subject for many years, I have come to the conclusion that one of the biggest problems that the students face when they try to learn probability theory, particularly nowadays, is their de?ciencies in basic di?erential and integral calculus. Integration by parts, for example, is often already forgotten by the students when they take a course on probability. For this reason, I have decided to write a chapter reviewing the basic elements of di?erential calculus. Even though this chapter might not be covered in class, the students can refer to it when needed. In this chapter, an e?ort was made to give the readers a good idea of the use in probability theory of the concepts they should already know. Chapter 2 presents the main results of what is known as elementary probability, including Bayes’ rule and elements of combinatorial analysis.
Elementary Probability
Author: David Stirzaker
language: en
Publisher: Cambridge University Press
Release Date: 2003-08-18
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.