Looking for an examination copy?
This title is not currently available for examination. However, if you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact firstname.lastname@example.org providing details of the course you are teaching.
The authors believe that a proper treatment of probability theory requires an adequate background in the theory of finite measures in general spaces. The first part of their book sets out this material in a form that not only provides an introduction for intending specialists in measure theory but also meets the needs of students of probability. The theory of measure and integration is presented for general spaces, with Lebesgue measure and the Lebesgue integral considered as important examples whose special properties are obtained. The introduction to functional analysis which follows covers the material (such as the various notions of convergence) which is relevant to probability theory and also the basic theory of L2-spaces, important in modern physics. The second part of the book is an account of the fundamental theoretical ideas which underlie the applications of probability in statistics and elsewhere, developed from the results obtained in the first part. A large number of examples is included; these form an essential part of the development.
Not yet reviewed
Be the first to review
Review was not posted due to profanity×
- Date Published: November 2008
- format: Paperback
- isbn: 9780521090322
- length: 416 pages
- dimensions: 229 x 152 x 24 mm
- weight: 0.61kg
- availability: Available
Table of Contents
1. Theory of sets
2. Point set topology
3. Set functions
4. Construction and propertied of measures
5. Definitions and properties of the integral
6. Related spaces and measures
7. The space of measurable functions
8. Linear functionals
9. Structure of measures in special spaces
10. What is probability?
11. Random variables
12. Characteristic functions
14. Finite collections of random variables
15. Stochastic processes.
Sorry, this resource is locked
Please register or sign in to request access. If you are having problems accessing these resources please email email@example.comRegister Sign in
You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.Continue ×
Are you sure you want to delete your account?
This cannot be undone.
Thank you for your feedback which will help us improve our service.
If you requested a response, we will make sure to get back to you shortly.×