Springer, 2006. - 363 p. - ISBN 0387284540.
This book is based mainly on the lecture notes that I have been using
since 1993 for a course on applied probability
for engineers that I teach at the
Ecole Polytechnique de Montreal. This course is given to
electrical, computer and physics engineering students, and is normally taken during the second or third year of their curriculum. Therefore, we assume that the reader has acquired a basic knowledge of differential and integral calculus.
The main objective of this textbook is to provide a reference that covers the topics that every student
in pure or applied sciences, such as physics, computer science, engineering, etc., should learn in probability theory, in addition to the basic notions of stochastic processes and statistics. It is not easy to find a single work on all these topics that is both succinct and also accessible to
non-mathematicians. Because the students, who for the most part have never taken a course on probability theory, must do a lot of exercises in order to master the material presented, I included
a very large number of problems in the book, some of which are solved
in detail. Most of the exercises proposed after each chapter are problems written especially
for examinations over the years. They are
not, in general, routine problems, like the ones found in numerous textbooks.
Preface.
Introduction.
Elementary Probabilities.
Random Variables.
Random Vectors.
Stochastic Processes.
Estimation and Testing.
Simple Linear Regression.
App. A: Mathematical Formulas.
App. B: Quantiles of the Sampling Distributions.
App. C: Classification of the Exercises.
App. D: Answers to the Multiple Choice Questions.
App. E: Answers to Selected Supplementary Exercises.
Bibliography.
Index.
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