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Sampling strategies in research


What is sampling?

According to Gratton & Jones (2009) a sample can be defined as a subset of a specific population. Its purpose is, in most cases, to gain information about the overall population by selecting a smaller number of individual cases from the population. Researchers need to have good sampling strategies  for their research.

Why taking a sample?

There are a number of reasons as to why a sample should be taken for the purpose of research. Firstly, total population is sometimes too large and collecting data from everyone is almost impossible unless it is a census. Secondly, if the data needs to be collected urgently, involving everyone may be very time-consuming. Thirdly, by studying carefully selected sample, the researcher may generalise results back to the population as a whole from which they were taken.

Sampling strategies 

Sampling strategies include issues such as type of sampling & size of sample.

Sampling types

Generally speaking, sampling is divided into two types: probability sampling and non-probability sampling.  Both types of sampling have further categories within.

Probability sampling

It is also called random sampling. All members of the population have (same) chance of being selected in probability sampling. Random sampling has generally four types of its own namely simple random sampling, systematic random sampling, stratified random sampling and cluster sampling.

Non-probability sampling

Members of the population do not all have the same chance of being selected in non-probability sampling. Non-probability sampling has different types e.g. snowball sampling, convenience/accessibility sampling, and judgment sampling.

Sample size

Researchers are often concerned about the sample size. How big should the sample be? Unfortunately, there is no clear answer to this question. It is true that a larger sample can provide more accurate results; however, dealing with a larger sample can be both expensive and time-consuming. Therefore, the researchers need to determine few things about the population and sample before an effectively representative sample size can be calculated. Issues such as population size, margin of error, confidence level, and standard deviation are relevant here in this regard.

In a nutshell, sampling is very important to carry out research. As mentioned above, the researchers need to have good sampling strategies  for their research. They should spend enough time to decide on the sample size. In addition, they need to understand that the selection of type of sampling may depend on issues such as research method and approach. For example, probability sampling is usually used in quantitative research. Any research conducted without appropriate sampling strategies will be questioned from validity point of view.

The article publication date: September 2016

Further reading/references

Gratton, C. & Jones, I. (2009) Research Methods for Sports Studies, 2nd edition, London: Routledge

Saunders, M., Lewis, P., & Thornhill, A. (2007) Research Methods for Business Students, 4th edition, UK: Pearson Education Limited

Author: M Rahman

M Rahman writes extensively online and offline with an emphasis on business management, marketing, and tourism. He is a lecturer in Management and Marketing. He holds an MSc in Tourism & Hospitality from the University of Sunderland. Also, graduated from Leeds Metropolitan University with a BA in Business & Management Studies and completed a DTLLS (Diploma in Teaching in the Life-Long Learning Sector) from London South Bank University.

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