there is quite standard. It starts by introducing Kolmogorov’s axioms, which are instantiated in the context of discrete sample spaces. The narrative then transitions to a comprehensive discussion of distributions on the real line, both discrete and continuous, and also multivariate. This is followed by an introduction of the basic concentration inequalities and limit theorems. (A construction of the Lebesgue integral is not included, and measure-theoretic matters are mostly avoided.) Part I ends with a brief discussion of Markov chains and related stochastic processes. Some utilitarian, but absolutely critical, aspects of probability and statistics are discussed in Part II. These include probability sampling and pseudo-random number generation – the practical side of randomness; as well as survey sampling and experimental design – the practical side of data collection.
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