Types of Sampling Methods to Use for Dissertation Writing

Sampling Methods for Dissertation

When it comes to writing a dissertation for undergraduate and master’s level dissertation, knowing the right types of sampling methods is important and occupies a significant place in research. Students often assume that sampling is only important when they are using a quantitative research design, questionnaires, or quantitative data but this is not the case.  Sampling methods matter a lot when using qualitative research designs, all types of research methods as well as both qualitative and quantitative data.

Recommended by a dissertation writing service, students must understand that the strategy they select can have a crucial impact on the quality of their findings. Thus, they need to use a strong sampling method that helps them come up with a good research strategy chapter. Samples are important because research is required for writing a dissertation to collect data but it is not possible to collect data from every person in research. To make things easy, a sample is selected and that sample will participate in the research which will help to draw valid conclusions. It is up to the students to carefully decide how they will select the right sample that will represent the group as a whole. There are two main types of sample methods:

  • Probability Sampling: It involves random selection, allowing students to make strong statistical inferences about the whole group.
  • Non-Probability Sampling: It involves non-random selection based on convenience or other criteria, allowing students to easily collect data.

The methodology section will explain how the right sample was selected to research dissertation writing.

Probability Sampling Methods:

Simple Random Sampling:

In this method, every member of the population has an equal chance of being selected and the whole population can be included in the sampling frame. To conduct this type of sampling, students can use tools like random number generators or other techniques that are based entirely on chance.

Systematic Sampling:

It is similar to simple random sampling, but it is usually easier to conduct. Every member of the population is listed with a number, but instead of randomly generating numbers, individuals are chosen at regular intervals.

Stratified Sampling:

Stratified sampling involves dividing the population into subpopulations that differ in important ways. It helps students draw more precise conclusions by ensuring that every subgroup is properly represented in the sample. For this sampling method, the population into subgroups based on the relevant characteristic such as gender, age range, income bracket, job role.

Cluster Sampling:

It also involves dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample. Instead of sampling individuals from each subgroup, students randomly select entire subgroups. If it is practically possible, students can include every individual from each sampled cluster. If the clusters are large, students can also sample individuals from within each cluster using one of the techniques above. This method works best when students have to deal with large populations but there is a risk of error too.

Non-Probability Sampling Methods:

Convenience Sampling:

It simply includes the individuals who are most accessible to the researcher. It is an easy and inexpensive way to collect data.

Voluntary Response Sampling:

A voluntary response sample is mainly based on ease of access. Instead of the researcher choosing participants and directly contacting them, people volunteer themselves for the research either by responding to a public online survey.

Purposive Sampling:

Also known as judgment sampling, this method involves the students rely on their judgment to select a sample that is most useful to the purposes of the dissertation research.  It is mostly used for qualitative research when the students are looking forward to collecting detailed information regarding any specific criteria rather than looking for statistical inferences or where the population is small and specific.

Snowball Sampling:

This sampling method works best when the popular is hard to access for research; it helps to find participants with help of people who are already a part of the research. People who are already participating in the research act like a snowball, as they help to bring in more people.

The various types of sampling methods to use for dissertation writing help students immensely in conducting research and accumulating data for their papers. As they are used to make inferences about a population, students need to find the best sampling methods that can help them come up with the best information and data that makes their research work essays. The better they choose the type of sampling method that would work best for their research, the better results they will obtain for their dissertation.