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When comparing random-variable sequences generated from probability distributions, what's a formal proof that a distribution with higher entropy produces a sequence that's "harder" to compress?

In background reading, I haven't come across this analysis for a general, abstract probability distribution. The information theory texts I've looked at, rather, tend to focus their analysis on comparing compression algorithms rather than comparing the distributions producing the data.

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You are looking for Shannon's source coding theorem.

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