Probability is now a central component of scientific literacy. As science and engineering move forward, we end up dealing with more and more complex systems. And in a complex system, we cannot expect to have a perfect model of each component or to know the exact state of every piece of the system. So uncertainty is now at the foreground and needs to be modeled. The second factor is that we live in an information society. Data and information play an increasingly central role, both in our individual lives and in the economy as a whole. Now, data and information are only useful because they can tell us something we did not know. Their reason for existence is to reduce uncertainty. But if your goal is to reduce uncertainty, to fight it, you'd better understand its nature. You'd better have the tools to describe it and analyze it. And this is why probability theory and its children-- statistics and inference-- is a must.
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