Abstract
This chapter focuses on probability and random variables. To apply probability theory to the process under study in the chapter, it is viewed as a random experiment, that is, as an experiment whose outcome is not known in advance but for which the set of all possible individual outcomes is known. The sample space of a random experiment is the set of all possible simple outcomes of the experiment. These individual outcomes are also called sample points or elementary events. A sample space is a set and thus, is defined by specifying what are the objects in it. Sample spaces can be finite or infinite. Sample spaces are also classified as discrete if the number of sample points is finite or countably infinite. An event is a subset of a sample space satisfying certain axioms. The chapter highlights that an event A is said to occur if the random experiment is performed and the observed outcome is in A. The chapter also discusses about probability measures, and presents an overview of the combinatorial analysis.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
