The size of the sample, which is enough to meet the criteria set by the researcher.

In the case of random sampling schemes, the most common criteria for determining the sample size are the absolute standard error of estimation or the relative standard error of estimation. In more complex sampling schemes (stratified sampling, cluster sampling), the additional criterion for minimization may be the general costs of the survey or the sampling itself. The problem of determining the minimum sample size in non-random sampling techniques is unfortunately more complex. First of all, the concept of random error, which control could lead to the determination of the minimum sample size, does not function here anymore. Secondly, practice shows that in many non-random schemes, the selection of a sample to increase its size does not necessarily lead to a reduction in errors in the inference of the population. In practice, in the case of non-random selection of the sample, its size is determined based on the researcher's time and financial capabilities, population diversity due to the studied statistical characteristics, the level of knowledge of the population due to different characteristics and the researcher's own experience.

• Random error
• Stratified sampling
• Cluster sampling
• Maximum estimate error
• Non random sampling
• general population