Abstract
In many situations, we must consider models of probabilistic phenomena which involve more than one random variable. These models enable us to examine the interaction among variables associated with the underlying experiment. For example, in studying the performance of a telemedicine system, variables such as cosmic radiation, sun spot activity, solar wind, and receiver thermal noise might be important noise level attributes of the received signal. The experiment is modeled with n random variables. Each outcome in the sample space is mapped by the n RVs to a point in real n-dimensional Euclidean space.
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© 2006 Springer Nature Switzerland AG
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Enderle, J., Farden, D., Krause, D. (2006). Bivariate Random Variables. In: Intermediate Probability Theory for Biomedical Engineers. Synthesis Lectures on Biomedical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-01614-1_2
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DOI: https://doi.org/10.1007/978-3-031-01614-1_2
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-00486-5
Online ISBN: 978-3-031-01614-1
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