The concepts of randomness and probability are central to statistics. It is an empirical fact that most experiments and investigations are not perfectly reproducible. The degree of irreproducibility may vary: Some experiments in physics may yield data that are accurate to many decimal places, whereas data on biological systems are typically much less reliable. However, the view of data as something coming from a statistical distribution is vital to understanding statistical methods. In this section, we outline the basic ideas of probability and the functions that R has for random sampling and handling of theoretical distributions.
CITATION STYLE
Ghatak, A. (2017). Probability and Distributions. In Machine Learning with R (pp. 31–56). Springer Singapore. https://doi.org/10.1007/978-981-10-6808-9_2
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