Abstract
In Chapters 5-9 we discussed discrete random variables and the methods employed to describe them probabilistically. The principal assumption necessary in order to do so is that the sample space, which is the set of all possible outcomes, is finite or at most countably infinite. It followed then that a probability mass function (PMF) could be defined as the probability of each sample point and used to calculate the probability of all possible events (which are subsets of the sample space).
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© 2012 Steven M. Kay
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Kay, S.M. (2012). Continuous Random Variables. In: Intuitive Probability and Random Processes Using MATLAB®. Springer, Boston, MA. https://doi.org/10.1007/0-387-24158-2_10
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DOI: https://doi.org/10.1007/0-387-24158-2_10
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-24157-9
Online ISBN: 978-0-387-24158-6
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