Parameters are numbers which characterize random variables. They make possible the summarizing description of the observations, serve as the basis of statistical decisions and are calculated from the data. Point estimations and confidence estimations are introduced. Samples of the observed random variable are a starting point. The maximum-likelihood method for the construction of parameter estimations is introduced here. Examples concern the normal distributions and the binomial distributions. Approximate methods of the parameter estimation also can be too inaccurate at large sample sizes. This is demonstrated in an example from genetics.