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:
- Presents the fundamentals in probability and statistics along with relevant applications.
- Explains the concept of probabilistic modelling and the process of model selection, verification and analysis.
- Definitions and theorems are carefully stated and topics rigorously treated.
- Includes a chapter on regression analysis.
- Covers design of experiments.
- Demonstrates practical problem solving throughout the book with numerous examples and exercises purposely selected from a variety of engineering fields.
- Includes an accompanying Solutions Manual for instructors containing complete step-by-step solutions to all problems.
Author(s): T. T. Soong
Edition: 1
Publisher: John Wiley & Sons
Year: 2004
Language: English
Pages: 408
City: Hoboken, NJ
Contents......Page 10
Preface......Page 16
1:
Introduction......Page 18
Part A:
Probability and Random Variables......Page 22
2:
Basic Probability Concepts......Page 24
3:
Random Variables and Probability
Distributions......Page 54
4:
Expectations and Moments......Page 92
5:
Functions of Random Variables......Page 136
6:
Some Important Discrete
Distributions......Page 178
7:
Some Important Continuous
Distributions......Page 208
Part B:
Statistical Inference, Parameter
Estimation, and Model Verification......Page 262
8:
Observed Data and Graphical
Representation......Page 264
9:
Parameter Estimation......Page 276
10:
Model Verification......Page 332
11: Linear Models and Linear Regression......Page 352
Appendix A: Tables......Page 382
Appendix B: Computer Software......Page 392
Appendix C: Answers to Selected
Problems......Page 396
Subject Index......Page 406
