The sampling statistician is a process within the application of any study and it is essential to get it right for the expected results and have scientific validity. To do this, individuals from a specific population are used with the intention of conducting a study and thus being able to characterize the entire population. Sampling definition in research
For the statistical study to be efficient it is important to take into account each of the parameters and characters of the sample, a poor quality sample will not be able to show or answer the questions in question.
What is the sample?
It could easily be described as a set of individuals within the population. The sample is a small group of the universe or population on which a certain study or investigation is being carried out and sampling is the process through which these statistical units are chosen, which is worth noting that it must be random, this means that any individual or object of research within the population has the option of being chosen as part of the sample.
Simple random sampling
It is the subset of a sample selected from a larger population. As we mentioned, each individual can be chosen to be part of the sample, some experts assure that it is a difficult method to understand in practice despite its theoretical simplicity. Sampling definition in research
How to perform simple random sampling?
- The main thing is to prepare a list in which the members of the population are found and then assign each one a number.
- Then, to choose the number of individuals, it is best to use a computer program that generates random numbers to be sure that there is no human intervention that can influence the formation of the sample.
Lottery sampling method
This is a significant way in which the randomness of simple random sampling can be observed. The objective of this random form of sampling is to choose the individuals from a box, subsequently carrying out the numbering of each of the individuals.
Random number method
It is another method that also requires that you previously make a numbering of the population, only this time you will use a table with numbers to choose randomly to choose the sample you need.
Simple sampling in research
Something fundamental in any type of research, be it a market study or some scientific investigation. When conducting an investigation in which you do not have great economic resources, this type of sampling will be very useful and it is for this reason and because of its practicality that it is widely used in investigations of all kinds. Sampling definition in research
What are the advantages of simple random sampling?
It is ideal to reduce the possibility of some bias compared to some other sampling method as well as being a totally fair method. There are no restrictions on the size of the sample and for this reason the samples are usually good to carry out the statistical study.
It is not necessary that as a researcher you have data regarding the data to be collected, simply a question is enough to obtain the information you need. In the same way, no type of knowledge is needed at a technical level since this is a way to collect basic information.
What are the disadvantages of simple random sampling?
Despite its reliability at the level of resources, it can be expensive, since a list of possible candidates is necessary and it is not really recommended for studies that stand out for personal interviews since they are usually done in wide geographical areas. Sampling definition in research
The responsibility for collecting meaningful and quality data rests entirely with the researcher, for this reason their experience or inexperience in the research field could be crucial when carrying it out.
How big should a sample be?
It is worth noting that in a scientific investigation or of any type in which a sample is required, the size is essential, since the larger the sample you will be able to obtain more precise results. So the appropriate answer would be great so that in this way you can have a better chance of finding the elements you are looking for within it.
Before the computer age, when it was difficult for researchers to choose samples completely randomly, systematic sampling was used to carry out this task through a system, which consisted of choosing a first piece completely randomly and from there the researcher I would use every nth individual to form the sample. Sampling definition in research
It is a whole number chosen from the total number of uninvited, which must be less than the total number of numbers corresponding to the population. This integer number will be where the researcher draws the first or non-persistent subject from the sample.
The interval is another whole number, this time taken from the difference or subtraction of two numbers from the progression, there are also modified forms of random sampling, which will depend on what the researcher needs.
Advantages of systematic sampling
- It stands out for its simplicity, adding to the random selection a simple system to collect the necessary sample from the population. Sampling definition in research
- It is also a guarantee that the sampling will be done fairly on the population.
Disadvantages of systematic sampling
You run the risk of interacting with a periodicity trait that could be hidden in the population and that could make the sample not really random. For this reason it is important for the researcher that the interval does not reflect any pattern.
This type of sampling was designed to improve the quality of the sample. And some experts assure that this way a more precise random sampling is obtained than with a simple random sampling.
Regardless of the type of sampling you choose for your research, it is important as we mentioned to take the sample from a large population size, ask questions beforehand if you should ask them and rely on computer systems if necessary, to take an efficient statistical sample. Sampling definition in research