Abstract
Statistics are essentially based on concentration phenomena, which are consequences of the law of large numbers. We review the weak law of large numbers and the consistency of a parameter estimator. The lecture introduces the estimation of the parameters of a probability distribution by maximum likelihood and score cancellation. This estimator is applied to Laplace and Gaussian distributions, as well as to logistic regression.
