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This lecture covers the concept of subgaussian random variables, including their definition, properties, and examples. It also introduces subexponential random variables and their characteristics, such as the moment-generating function. The lecture further explores conditional expectation and Orlicz norms, providing insights into tail bounds for subexponential distributions.