Скачать или смотреть PRP 01: Sample and Event Space

This lecture introduces fundamental concepts in probability theory, beginning with definitions of functions, their properties (injective, surjective, bijective), and cardinality. It then delves into the core ideas of a random experiment, defining sample space as the set of all possible outcomes. The lecture explains event space as a σ-algebra of subsets of the sample space, outlining its key properties, including closure under complements and countable unions. It concludes by discussing how an event space can be generated by a family of sets, including examples like countably infinite coin tosses and the Borel event space.

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