A linear combination is an expression formed by multiplying each element of a set of vectors by a corresponding scalar and then summing the results. In the context of multivariate normal distributions, linear combinations are essential as they allow us to understand how multiple random variables interact and combine to form new distributions, which can be crucial for modeling complex data relationships.
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