The sampling strategy that you select in your dissertation should naturally flow from your chosen research design and research methods , as well as taking into account issues of research ethics. If we were to examine the differences in male and female students, for example, the number of students from each group that we would include in the sample would be based on the proportion of male and female students amongst the 10, university students. For example, if you were interested in the effect of senior manager mentorship on employee motivation in a single firm with employees, you may need the Human Resources Director to act as the gatekeeper to ensure that you had access to the list of all senior managers within the firm. This article explains these key terms and basic principles. Process used in Sampling:

This can often help the researcher to identify common themes that are evident across the sample. These extreme or deviant cases are useful because they often provide significant insight into a particular phenomenon, which can act as lessons or cases of best practice that guide future research and practice. If you are new to sampling, there are a number of key terms and basic principles that act as a foundation to the subject. Self-selection sampling Self-selection sampling is appropriate when we want to allow units or cases, whether individuals or organisations, to choose to take part in research on their own accord. For example, in homogeneous sampling , units are selected based on their having similar characteristics because such characteristics are of particular interested to the researcher.

In sampling dissertation qualitative research laerd purposive

Units can be peoplecases e. During the course of lwerd qualitative or mixed methods research designmore than one type of purposive sampling technique may be used.

If I end up having to go through 1,00 surveys, it will take her more time 9 Ibid. Where this happens, it raises ethical issues because the picture being built through the research can be excessively narrow, and arguably, unethically narrow.


Qualitative research designs can involve multiple phases, with each phase building on the previous one. This can lead to your sample being unrepresentative of the population you are interested in. Thus, sampling method is employed due to which the researcher is able to provide a laerc analysis even in this vast universe.

laerd dissertation purposive sampling

Hence, despite having some limitations, purposive sampling is the only possible solution when some of the units are very important cannot be missed out. Principles of non-probability sampling Types of non-probability sampling. Unlike the various sampling techniques that can be used under probability sampling e. Examples of total population sampling The examples of total population sampling below attempt to highlight two of the characteristics of total population samples, discussed above: Whilst making generalisations from the sample to the population under study may be desirable, it is more often a secondary consideration.

If it happens there, it will happen anywhere? We also discuss each of these different types of non-probability sampling technique, how to carry them out, and their advantages and disadvantages [see the articles: If you are already confident that you understand these basic principles of sampling, we introduce you to the two major groups of sampling techniques that you could use to select the units that you will include in your sample:.

When sampling, you need to decide what units i. Assumptions underlying in sampling6 a. For example, if the population we were interested in was all million or more Facebook users, each of these Facebook users would be a unit. Contact all members on the list. Rather, it is a choice, the purpose of which varies depending on the type of purposing sampling technique that is used.

laerd dissertation purposive sampling

Sample size Whether you are using a probability sampling or non-probability sampling technique to help you create dissertatiln sample, you will need to decide how large your sample should be i. There are a wide range of purposive sampling techniques that you can use see Patton,; Kuzel,for a complete list. These units could be peoplecases and pieces of data.


Sampling: The Basics | Lærd Dissertation

Critical case dissertafion is a type of purposive sampling technique that is particularly useful in exploratory qualitative research, research with limited resourcesas well as research where a single case or small number of cases can be decisive in explaining the phenomenon of interest.

It must be such which results in a small sampling error. If you are following a probability sampling techniqueyou’ll know that you require a list of the population from which you select units for your sample. Usually, the sample being investigated is quite small, especially when compared with probability sampling techniques.

A homogeneous sample is often chosen when the research question that is being address is specific to the llaerd of the particular group of interest, which is subsequently examined in samping.

In this website, we use the word units whenever we are referring to those things that make samlling a population. Implement the plan12 Once you know your population, sampling frame, sampling method, and sample size, you can use all that information to choose your sample. When selecting units from the population to be included in your sample, it is sometimes desirable to get hold of a list of the population from which you select units.

laerd dissertation purposive sampling

Example 2 The effect of senior manager mentorship on employee motivation in a single firm with employees. For example, it is not uncommon when select units using convenience sampling that researchers’ natural dissertatiion and even prejudices will influence the selection process. The main goal of purposive sampling is to focus on particular characteristics of a population that are of interest, which will best enable you to answer your research questions.

Problems with gatekeepers can also affect the representativeness of the sample.