Statistical Population

an aggregate of social entities or phenomena that share general characteristics but differ in a number of variable attributes. The entities or phenomena constitute the elements, or units, of the statistical population. Thus, the elements of a statistical population may be the inhabitants of a country at a particular time; this is used as the qualitative basis for uniting the elements into the statistical population. However, the inhabitants differ in such characteristics as social position, sex, age, family status, or education. In view of the manifold and diverse forms of relations and links between entities, a series of partial statistical populations may be isolated for the same entity. For example, partial populations may be isolated from the general aggregate of enterprises on the basis of first one feature (such as level of technology or rate of profit), then another one, and so on.

In statistics, fundamental relationships are distinguished from secondary relationships. The most important statistical populations are those linked by relationships arising from the nature of productive forces and the mode of production—for example, branches of the economy, socioeconomic groups of enterprises, and classes and social groups.

A statistical population may be qualitatively homogeneous, if the most significant indicator (or indicators) is the same for all its elements, or heterogeneous, if it comprises different types of phenomena. A population may be homogeneous in one respect but heterogeneous in another. In bourgeois statistics, variables from a heterogeneous statistical population are often used as apologia (for example, calculation of mean income for a population consisting of socially diverse strata). In his analysis of the development of capitalism, V. I. Lenin examined in depth the problem of isolating a socioeconomically homogeneous population. In sample surveys, a distinction is made between general populations, which include all the units of the statistical population being studied, and sampling populations.