The present collection utilizes a number of user defined m-programs, in combination with built in MATLAB functions, for solving a variety of probabilistic problems. These m-files are included as text files in the collection New Prob m-files. We use the term m-function to designate a user-defined fun
Introduction to Applied Probability
β Scribed by Paul E. Pfeiffer and David A. Schum (Auth.)
- Publisher
- Elsevier Inc, Academic Press Inc
- Year
- 1973
- Tongue
- English
- Leaves
- 392
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
Content:
Front Matter, Page iii
Copyright, Page iv
Preface, Pages xi-xiii
Acknowledgments, Page xv
Chapter 1 - An Approach to Probability, Pages 3-9
Chapter 2 - Some Elementary Strategies of Counting, Pages 10-36
Chapter 3 - Sets and Events, Pages 39-66
Chapter 4 - A Probability System, Pages 67-83
Chapter 5 - Conditional Probability, Pages 84-112
Chapter 6 - Independence in Probability Theory, Pages 113-136
Chapter 7 - Composite Trials and Sequences of Events, Pages 137-157
Chapter 8 - Random Variables, Pages 161-184
Chapter 9 - Distribution and Density Functions, Pages 185-206
Chapter 10 - Joint Probability Distributions, Pages 207-224
Chapter 11 - Independence of Random Variables, Pages 225-236
Chapter 12 - Functions of Random Variables, Pages 237-253
Chapter 13 - Mathematical Expectation and Mean Value, Pages 257-273
Chapter 14 - Variance and Other Moments, Pages 274-295
Chapter 15 - Correlation and Covariance, Pages 296-310
Chapter 16 - Conditional Expectation, Pages 311-327
Chapter 17 - Sequences of Random Variables, Pages 331-348
Chapter 18 - Constant Markov Chains, Pages 349-371
Appendix A - Numerical Tables, Pages 373-379
Appendix B - Some Mathematical Aids, Pages 381-385
Selected References, Pages 387-388
Selected Answers and Hints, Pages 389-393
Index of Symbols and Abbreviations, Pages 395-396
Index, Pages 397-403
π SIMILAR VOLUMES
This book provides the elements of probability and stochastic processes of direct interest to the applied sciences where probabilistic models play an important role, most notably in the information and communications sciences, computer sciences, operations research, and electrical engineering, but a
This book provides the elements of probability and stochastic processes of direct interest to the applied sciences where probabilistic models play an important role, most notably in the information and communications sciences, computer sciences, operations research, and electrical engineering, but a
I am a PhD student in Computer Science at UMass Boston and I do research in data mining. I am particularly interested in probabilistic solutions to problems in data mining, which is why I wanted to know about probability and statistics. I had the privilege of learning the subject matter from the aut
I am a PhD student in Computer Science at UMass Boston and I do research in data mining. I am particularly interested in probabilistic solutions to problems in data mining, which is why I wanted to know about probability and statistics. I had the privilege of learning the subject matter from the aut