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:

- Understanding key terms and basic principles of sampling
- Choosing your sampling strategy and sampling technique
- Writing up the Sampling Strategy section of your Research Strategy chapter

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 Strateg**y 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.