A statistical population is a set of elements that, through sampling, are analyzed to obtain data.
Population is a term that comes from the late Latin populatio . Of the different meanings that the Royal Spanish Academy ( RAE ) mentions in its dictionary, in this case we are interested in staying with its meaning as the group of elements that, through sampling, are evaluated at a statistical level .
Statistics is called the specialization of mathematics that, appealing to the calculation of probabilities, generates inferences from numerical data. The idea of statistics, in turn, refers to the quantitative analysis of data.
What is a statistical population
The statistical population is a group of elements that is relevant to an experiment or research . By statistically analyzing the population, information is generated that allows conclusions to be drawn.
It is important to note that the statistical population can be small, large, or even potentially infinite. The usual thing is that we do not work with all the elements of the population, but rather a subset is chosen, which is called a statistical sample .
The link between population size and sample size is known as sampling fraction . Starting from this relationship, projections can be made of the data produced with the analysis.
Samples to examine are obtained from the statistical population.
The importance of sampling
Sampling consists of choosing a sample that represents the average conditions or characteristics of a set. If we focus on statistics, the process involves selecting a part of the population and then inferring the group's qualities or values.
Each element that makes up one of these subsets is called a sampling unit . The key is that the properties seen in them can be extrapolated to the rest of the population.
Therefore, certain requirements must be met for the sampling to be valid and this extrapolation to be carried out successfully. When necessary, several samples can be extracted from the population, generating a sample space .
At a general level, there is a difference between random sampling and judgmental sampling . In the first case, the choice is made at random, while in the second there is a deliberate determination.
Examples of statistical population
Let's take the case of a club . where various sports disciplines are practiced. The 3,000 people who play sports in said institution can constitute a statistical population.
From this total, various samples can be taken. If you want to investigate how many of these individuals play soccer , you can randomly select 500 people , to mention one possibility, and investigate. These 500 subjects constitute the sample.
Let's now see what happens in a nursery. The 3,000 specimens from this place are taken as the statistical population, while if 200 specimens are selected, a sample is formed for study. This way you can investigate how many phanerogamous plants are or other questions.
As can be seen, the sample is necessary to facilitate the study. In certain contexts , sampling is simply indispensable, since the statistical population is enormous to analyze.
The planets in the universe , for example, are virtually infinite. It is not feasible to carry out an examination or obtain a conclusion from such a large number of elements, which requires sampling.