In undergraduate and master's level dissertations, the Sampling Strategy section is an important component of your Research Strategy chapter (usually Chapter Three: Research Strategy). Whilst students sometimes assume that sampling is only important when using a quantitative research design, questionnaires and/or quantitative data, this is not the case. It is equally important when using qualitative research designs, all types of research method, as well as both quantitative and qualitative data. Since the sampling strategy that you select can have a significant impact on the quality of your findings, this article explains what you need to think about to produce a strong Sampling Strategy section for your Research Strategy chapter.
To produce a strong Sampling Strategy section, you first need to understand the key sampling terms that you will come across. Once you have understood these sampling terms, it is possible to choose the sampling strategy that is most appropriate to your dissertation. You can then think about how you will actually write up the Sampling Strategy section of your Research Strategy chapter. Each of these is discussed in turn:
The purpose of sampling is to improve the quality of your findings by ensuring that the units you are studying are representative of the broader population that interests you.
Example
Imagine we were using structured interviews (i.e., our research method) to examine the career choices of students at the University of Bath, England. It would not be feasible or necessarily desirable for us to interview all 10,000 students (i.e., the students are the units we are studying, whilst the 10,000 students are our population). This would take a long time, could cost a lot of money, and would not necessarily lead to a significant improvement in our findings. Therefore, we use sampling techniques to select a smaller number of these units (i.e., students) that we intend to interview. In total, these units make up our sample. If we selected a sample size of 200 units, we would need to interview 200 students.
We could select these units using a variety of sampling techniques, which are broadly grouped into probability sampling techniques and non-probability sampling techniques. The goals of these sampling techniques vary. Some aim to ensure that the sample you use is representative of (i.e., has similar characteristics to) the population you are studying (i.e., probability sampling techniques). Others help you to select samples based on specific theoretical criteria you are interested in (e.g., purposive sampling; a type of non-probability sampling technique). Others still simply aim to make it easier and less costly to select units for your sample (e.g., convenience sampling; another type of non-probability sampling technique).
If you are new to sampling, many of these basic principles and key terms of sampling, including units, sample, sample size, sampling frame, population, probability and non-probability sampling, and so forth, may be unfamiliar to you. In the article, Sampling: The basics, we discuss each of these key terms and basic principles in more depth.
Once you understand these basic principles and key terms of sampling, you need to start thinking about the overall sampling strategy that you will use to collect the data needed for your dissertation. This sampling strategy, in turn, influences the choice of sampling technique that you use to select your sample, whether this is a probability or non-probability sampling technique. We have explained more about these two groups of sampling techniques in the articles, Probability sampling and Non-probability sampling.
One of the most important things to think about when choosing the most appropriate sampling strategy for your dissertation is the overall research strategy that you are using. This is because the different components of your research strategy (i.e., the research paradigm and research design guiding your dissertation, the research methods you use, etc.), help to determine your choice of sampling strategy and sampling technique.
For example
Dissertations that draw on a post-positivist research paradigm, a quantitative research design and a questionnaire as their research method would ideally use a probability sampling technique (e.g., simple random sampling, systematic random sampling, stratified random sampling). By contrast, dissertations that draw on a constructivist research paradigm, a qualitative research design (e.g., a case study approach), and semi-structured or unstructured interviews as their research method may prefer to use a non-probability sampling technique (e.g., purposive sampling).
When you have decided what sampling strategy you plan to use or after you have actually carried out your research, you will need to write up the Sampling Strategy section of your Research Strategy chapter. To help you do this, we suggest following the four steps below:
Describe what you are studying
Explain the types of sampling technique available to you
State and describe the sampling strategy you used
Justify your choice of sampling strategy
In the article, How to structure the Sampling Strategy section of your dissertation, we discuss each of these steps, providing an example to illustrate how to write up the Sampling Strategy section. However, if you are still just trying to get to grips with sampling, we recommend that you start by reading the article, Sampling: The basics.