Population and sample

Population refers to the universe, set or totality of elements on which studies are investigated or carried out. Sample is a part or subset of elements that are previously selected from a population to carry out a study.

Usually a sample of a population is selected for study, because studying all the elements of a population would be very extensive and impractical.

DefinitionUniverse of elements to be studied.Selection of a part of the population that is going to be the subject of the study.
  • It can be classified according to the number of individuals that make it up.
  • It has statistical variables.

  • It is part of the population: it should be between 5% and 10% to be most effective.
  • Items must be random.
  • It must be representative of the population.
objectivesAnalyze the data collected regarding the common characteristics shared by the elements for various purposes.Study the behavior, characteristics, tastes or properties of a representative part of the population.
  • The people who inhabit a country.
  • The number of cars in a city.
  • The students of a country.
For the study of the performance of students from five universities in a city in a specific subject, 500 students are randomly taken as a sample (100 from each institution) who are studying the same level so that the sample is representative.

What is population?

The statistical population, also known as the universe, is the set or all of the elements to be studied.

The elements of a population are made up of each of the associated individuals, because they share some common characteristic .

The statistical population can be a collection of real people, places, or things. For example, teenagers in a town or the possible uses of sugar in recipes.

As it is very difficult to carry out a study with all the elements that make up a population, especially if it is considered an infinite population, a representative sample of it is taken to carry out the studies.

Types of populations

The population can be classified as follows according to the number of individuals that make it up:

  • Finite population : it is one that can be counted and its members can be studied more easily. For example, the number of people enrolled in a gym.
  • Infinite population : they are immense populations where it is very difficult to count their members, so only a portion of it is usually taken into account when conducting a study, thus selecting a sample. For example, the number of grains of sand on a beach.
  • Real population : they are groups of tangible members. For example, the number of animals in a zoo.
  • Hypothetical population: these are possible populations that can be studied in an eventuality. For example, the number of preterm births.

What is sample?

The sample is a representative part of a population where its elements share common or similar characteristics.

It is used to study the population in a more feasible way , because it can be easily accounted for. When a study is going to be carried out on the behavior, properties or tastes of the total of a specific population, samples are usually taken.

These studies that are carried out on the samples serve to create norms or guidelines that will allow taking actions or simply knowing more about the population studied.

The sampling is a research tool that, properly being used, allows for specific conclusions and avoid biased results.

The main advantages of using samples is cost reduction, since it reduces the elements to be studied and can be done in less time.

The most important factors when sampling are representativeness , so that the elements have common qualities depending on the purpose, and randomness when selecting the elements to avoid a flawed sample.

Sample types

There are different types of techniques to make a sample.

Random sampling

It is a technique that offers the same possibility to the elements to be selected, by being taken at random. The types of random sampling are:

  • Simple Random Sampling – Items are chosen from a list at random. It works most effectively when the universe is small and homogeneous.
  • Systematic sampling: the first element is chosen at random and then the remaining elements are chosen at constant intervals.
  • Stratified sampling : it is carried out by dividing the population into parts or strata that respond to established characteristics and then the individuals to be studied are randomly chosen.
  • Cluster sampling : the population is divided into heterogeneous groups and these in turn are subdivided into homogeneous groups with common characteristics to be studied as required by the researcher.

Non-random sampling or by intentional selection

It is chosen based on the information management of the elements to be studied, so the representativeness of the sample can be subjective. In this case, there is a risk that the results will be biased.

When only one of the studies is not sufficient because the population to be studied is very large, two or more types of sampling can be used.

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