* End-of-chapter summaries reinforce the main topics and goals of the chapter.

Integrating interesting and widely used concepts of financial engineering into traditional statistics courses, Introduction to Probability and Statistics for Science, Engineering, and Finance illustrates the role and scope of statistics and probability in various fields. The text first introduces the basics needed to understand and create

This is a textbook on applied probability and statistics with computer science applications for students at the upper undergraduate level. It may also be used as a self study book for the practicing computer science professional. The successful first edition of this book proved extremely useful to students who need to use probability, statistics and queueing theory to solve problems in other fields, such as engineering, physics, operations research, and management science. The book has also been successfully used for courses in queueing theory for operations research students. This second edition includes a new chapter on regression as well as more than twice as many exercises at the end of each chapter. While the emphasis is the same as in the first edition, this new book makes more extensive use of available personal computer software, such as Minitab and Mathematica.

Now with even more examples with real data, real-world applications, and computer exercise, the Fourth Edition of this accessible text prepares you for situations you're likely to encounter as a professionakl engineer. Together with new co-authors David Goldsman and Connie Borror, William Hines and Douglas Montgomery have refined their highly effective pedagogical framework to make their text even more user friendly. This Fourth Edition also features a new chapter on statistical methods for computer situation, as well exceptionally clear statistical coverage, expanded discussions of quiality control, experimental design, and different types of interval estimation, and coverage of such special topics as nonparametric statistics, p-values in hypothetical testing, and residual analysis. Highlights of the Fourth Edition: * New examples and applications provide a real-world perspective on how engineers use probability and statistics in professional practice. * Over 600 exercises, including many new computation problems, provide opportunities for hands-on learning. * An entirely new chapter on statistical methods for computer simulation methods covers Monte Carlo experimentation, random number and variate generation, and simulation output data analysis. * New chapter organization starts with probability theory and progresses through random variables, discrete and continuous distributions, and normal distribution, before introducing statistics and data description techniques. * Each chapter starts with an introduction that describes the importance of the topic and features interesting historical information related to the topic. * End-of-chapter summaries reinforce the main topics and goals of the chapter.