Sampling methods – What is it, definition and concept | 2022

Sampling methods are the different forms or ways that can be used to select the population that will be the subject of an investigation.

That is, the sampling method will be the technique used to study a representative set of the population. But trying to reduce the error in the research process to a minimum. Errors can be caused by factors such as chance, bias, or confounding.

Indeed, sampling methods are used when, at the time of conducting an investigation, it is difficult or almost impossible to study the entire population or take a census. Then, it is decided to choose a sample of the population that is sufficiently representative to carry out the study.

Of course, the sampling method helps us to better select the population group that will participate in the study. Depending on the type of study carried out, the most appropriate method for selecting the sample should be chosen. In general, the sampling method can be random or probability and non-random or non-probability.


We are in Financial Education Week, and at Economipedia we want to make our small contribution.

Only during this week, we open the Savings and Personal Finance Course for non-Financials to everyone. in him we see how to save, control expenses, increase income, invest and make better decisions with our money. After this week, it will once again be an exclusive course for Economipedia premium students.

Take advantage of! Free access here:

Random or probability sampling method

Basically, the random or probability sampling method is a sampling technique where the researcher establishes a limited set of criteria to randomly select the population sample to be studied. Clearly, each member of the population has an equal chance to be part of the sample.

Random or probabilistic sampling methods and ways to apply them

The four ways in which the random or probabilistic method can be applied are:

1. Simple random sampling method

First, we find that the simple method is a simple technique that is quite reliable for obtaining information about a study group. Plus, it helps save time and resources. The study group is chosen by chance and each subject has the same probability of being chosen.

For example, the method for choosing could be to use numbers and have each subject choose one. This gives the opportunity that anyone can be selected. This method works with small groups. It may be less representative than the systematic method and less precise than the stratified method.

2. Random cluster sampling method

Second, the cluster or cluster method can be used. To apply it, the population must be divided into parts or conglomerates that are representative of a population. In this case, demographic type parameters can be used. These may include gender, age, marital status, educational level; to mention a few. Therefore, its application is also very simple.

An example of application could be to study the difference in access to education between boys and girls in a region. To carry out the study, 5 schools from different cities in the region could be selected and with this the necessary information would be obtained. This method facilitates sample selection, but the results cannot be generalized.

3. Systematic random sampling method

Third, systematic random sampling consists of randomly selecting the first element of the sample. Subsequently, other elements are selected, but systematically or following fixed intervals, until the sample size is completed. That is, they follow regular intervals.

For example, if a chain of beauty salons needs to know the level of customer satisfaction. Applying the systematic method they decide to obtain a sample of 200 clients from a population of 1000 clients. Then the population is numbered from 1 to 1000 and the study is passed to every 5 clients who arrive at the salon.

The scheme used will be total population/sample size. In this example it would be 1000/200 = 5. This method predefines the sample size and saves time.

4. Stratified random sampling method

Finally, the stratified random method can be used. This method first divides the entire population into smaller groups. These smaller groups should represent the entire population and should not be interspersed. In this way, a particular sample is chosen from each separate group and each group must have similar characteristics.

An example would be to research a population group of women and then subdivide the group into age ranges. It could be a group from 15 to 30 years old, another group from 31 to 45 years old, another from 46 to 60 years old and a last group of 61 years and older.

Non-random or non-probability sampling methods

However, in this type of method the samples are selected through a process that does not offer the subjects the same opportunity to be selected.

Random or probabilistic sampling methods and ways to apply them

The ways to apply this method are:

  • For installments: In this method, the researcher selects within the sample only those subjects who meet certain conditions or specific requirements.
  • Intentional or for convenience: The researcher chooses the sample according to his own criteria that are convenient for him.
  • Snowball: In this case, the researcher chooses an individual and then that person contacts other people who will be part of the sample. The process is repeated until the required sample size is reached.
  • Discretionary: First, the researcher selects subjects according to their own criteria, but considering the contribution that these subjects provide to the investigation.

As a conclusion, we can note that there are different sampling methods. Of course, all of them are useful to choose appropriately the sample that will be used in an investigation. However, when choosing a particular method, the type of research to be carried out and the resources available should be taken into account.

See also  Cryptocurrencies and their tax implications

Leave a Comment