Lecture1

# Lecture1 - Discrete Probabilities Marius Ionescu Fall 2005...

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Unformatted text preview: Discrete Probabilities Marius Ionescu Fall 2005 Random Variables and Sample Spaces • We represent the outcome of the experiment by a capital Roman letter, such as X , called a random variable . • The sample space of the experiment is the set of all possible outcomes. If the sample space is either finite or countably infinite, the random variable is said to be discrete . • The elemnts of a sample space are called outcome. • A subset of the sample space is called an event. 1 Distribution Functions Let X be a random variable which denotes the value of the outcome of a certain experiment, and assume that this experiment has only finitely many possible outcomes. Let Ω be the sample space of the experiment (i.e., the set of all possible values of X , or equivalently, the set of all possible outcomes of the experiment.) A distribution function for X is a real-valued function m whose domain is Ω and which satisfies: 1. m ( ω ) ≥ , for all ω ∈ Ω , and 2....
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Lecture1 - Discrete Probabilities Marius Ionescu Fall 2005...

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