by Paul E Pfeiffer
Publisher: Connexions 2008
Number of pages: 634
This textbook covers most aspects of advanced and applied probability. The book utilizes a number of user defined m-programs, in combination with built in MATLAB functions, for solving a variety of probabilistic problems.
Home page url
Download or read it online for free here:
by Pawel J. Szablowski - arXiv
We formulate conditions for convergence of Laws of Large Numbers and show its links with of parts mathematical analysis such as summation theory, convergence of orthogonal series. We present also various applications of Law of Large Numbers.
by Edward Nelson - Princeton University Press
In this book Nelson develops a new approach to probability theory that is just as powerful as but much simpler than conventional Kolmogorov-style probability theory used throughout mathematics for most of the 20th century.
by Leif Mejlbro - BookBoon
Contents: Some theoretical background; Exponential Distribution; The Normal Distribution; Central Limit Theorem; Maxwell distribution; Gamma distribution; Normal distribution and Gamma distribution; Convergence in distribution; 2 distribution; etc.
by S. R. S. Varadhan - New York University
These notes are based on a first year graduate course on Probability and Limit theorems given at Courant Institute of Mathematical Sciences. The text covers discrete time processes. A small amount of measure theory is included.