Abstract
Random variables and probability functions are two important ingredients in statistics as well as for many machine learning methods. In this chapter, we will see how these concepts relate to the sample space on the one hand and how we can use them for making complex calculations about “distributions” on the other hand.
Anyone who attempts to generate random numbers by deterministic means is, of course, living in a state of sin.
John von Neumann (1903–1857)
Hungarian-American mathematician and computer scientist
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Notes
- 1.
In probability theory, a boldface \(\boldsymbol {X}\) is often used as a short form for a set of random variables \(X_i\). In this text, we use this notation for convenience (and brevity) but in particular for consistency with the later chapters.
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Sandfeld, S. (2024). Random Variables and Probability Functions. In: Materials Data Science. The Materials Research Society Series. Springer, Cham. https://doi.org/10.1007/978-3-031-46565-9_6
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DOI: https://doi.org/10.1007/978-3-031-46565-9_6
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