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Fundamentals of Probability and Statistics for Engineers
T. T. Soong (Author)
9780470868140, Wiley
Paperback / softback, published 20 February 2004
400 pages
22.8 x 15.6 x 2.6 cm, 0.595 kg
“For most practising engineers, this book would make a superb reference text, simply because there are so many worked examples, all extremely relevant to engineers.” (Significance, 1 March 2005) "...the many engineering related examples and exercise problems are a strong feature..." (Technometrics, May 2005) "...designed for students, and as reference for lecturers, the book provides a comprehensive understanding of probability and statistics..." (New Civil Engineer, 18 March, 2004) "...written in an accessible and clear way...gives important techniques of the basic standard methods." (Zentralblatt Math, Vol.1049 2004) "...a good introduction to the ideas of probability and statistics...I would recommend it to anyone as a reference for basic theory..." (Journal of Applied Statistics, Vol 32 (6) August 2005)
This textbook differs from others in the field in that it has been prepared very much with students and their needs in mind, having been classroom tested over many years. It is a true “learner’s book” made for students who require a deeper understanding of probability and statistics. It presents the fundamentals of the subject along with concepts of probabilistic modelling, and the process of model selection, verification and analysis. Furthermore, the inclusion of more than 100 examples and 200 exercises (carefully selected from a wide range of topics), along with a solutions manual for instructors, means that this text is of real value to students and lecturers across a range of engineering disciplines. Key features:
Preface. 1. Introduction. Part A: Probability and Random Variables. 2. Basic Probability Concepts. 3. Random Variables and Probability Distributions. 4. Expectations And Moments. 5. Functions of Random Variables. 6. Some Important Discrete Distributions. 7. Some Important Continuous Distributions. Part B: Statistical Inference, Parameter Estimation, and Model Verification. 8. Observed Data and Graphical Representation. 9. Parameter Estimation. 10. Model Verification. 11. Linear Models and Linear Regression. Appendix A: Tables. Appendix B: Computer Software. Appendix C: Answers to Selected Problems. Subject Index.
Subject Areas: Mathematics [PB]
