Bayesian inference is a method of learning about the relationship between variables from data, in the presence of uncertainty, in real-world problems. It is one of the frameworks of probability theory. Any reader interested in Bayesian inference should have a good knowledge of probability theory to understand and use Bayesian inference. This chapter covers an overview of probability theory, which will be sufficient to understand the rest of the chapters in this book.
It was Pierre-Simon Laplace who first proposed a formal definition of probability with mathematical rigor. This definition is called the Classical Definition and it states the following:
The theory of chance consists in reducing all the ... |
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