Population and sampling are the two essential components of research design. A population comprises of a group of people who have some common interests. A small part of the population is a sample.
The size of the same is determined by the number of individuals present in a group. In research design, a systematic approach is followed to study a particular issue. The researchers get quality results if the sample population is more.
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Kinds Of Sampling Methods
You can understand the importance of sampling by the following example. For instance, research needs to be conducted by the researcher, about the ill effects of working in a coal mine on the health of the workers.
But it is a difficult task to study the vast population of coal workers. In this scenario, the researcher has made a sample (a group of coal workers) to collect the data.
Types Of Sampling Methods:
- Probability sampling – In this type, each member of the population has the chance to become a part of the sample.
- Non- Probability sampling – It is rather difficult that each member of the population can become part of the sample. When the criteria are to select the members, the researchers take non- probability sampling. You can use both types and it depends on your needs.
Qualitative research comprises of non-numerical data used for the study under natural settings. It is helpful to know how certain elements affect human beings. It has 3 types:
- Purposive sampling – This type of sampling has a purpose behind it. A preselected methodology is used to do the research and to collect data.
- Quota sampling – Participant quota is established before doing the sampling. Like selecting the candidates that fulfill the requirements and meet the traits like age, sex etc.
- Snowball sampling – The participants present in the study are the other individuals who meet the requirements needed for the study.
Quantitative research is done to measure the numerical data. The researchers do the task of establishing laws of behavior, which you can see in different types of contexts. The theory is tested and it may be selected or rejected. It is of three types:
- Random sampling – This sampling gives an adequate chance of selection to all the individuals in a population.
- Stratified sampling – It is based on the criteria which are defined by the researcher. For example, when you are doing a study on the smoking habits of the individual, it can be broken down by age, race and the status of the individuals.
- Systematic sampling – It is a systematic type. The researcher looks at the population and selects every fifth or tenth name depending on the size of the sample.
Why there Is a Necessity of Choosing an Appropriate Sampling Method
Good sampling results in giving excellent results to the researchers. As the amount of data collected is very vast, so you must use the most relevant sampling method for this task.
There are chances of having common sampling errors. It may happen that your sample is not reflecting the features of your population. Chances of having systematic errors occur when you find the difference in the results from the sample and the population.
After knowing the goals of your market research project, decide which sampling method you are going to use. It is important to know about the cost and the time, which is utilized in sampling so that it is possible to balance your requirements.