Probability is the last topic in this book and perhaps the most
important.  Many algorithms rely on randomization.  Investigating
their correctness and performance requires probability theory.
Moreover, many aspects of computer systems, such as memory management,
branch prediction, packet routing, and load balancing are designed
around probabilistic assumptions and analyses.  Probability also comes
up in information theory, cryptography, artificial intelligence, and
game theory.  Beyond these engineering applications, an understanding
of probability gives insight into many everyday issues, such as
polling, DNA testing, risk assessment, investing, and gambling.

So probability is good stuff.

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