Written by Dr. Hannes Nel
On face value sampling seems like a simple job.
And so it mostly is.
However, if you choose the wrong sample or you choose the sample incorrectly, you can destroy the validity and accuracy of your research project.
And you might have wasted a good number of years on fruitless research.
Think carefully about the examples that I offer in this post, especially the ones on systematic sampling.
I will discuss:
- Stratified sampling.
- Systematic sampling.
- Theoretical sampling.
- Time sampling.
In this post.
Stratified sampling is used to ensure that the sample is representative of a population with multiple characteristics that are evenly distributed amongst the population.
The research population is divided into homogeneous groups, with each group containing subjects with similar characteristics.
Such homogeneous groups are often called ‘sub-units’ or ‘strata’.
Samples are selected by making use of random selection procedures such as systematic sampling or simple random sampling.
For example, students at a specific university, which are the population on which the research will be conducted, can be grouped into a male and a female group.
Or they can be grouped per faculty.
Or per leisure time interests, etc.
If, for example, you wish to do research on the impact of leisure time interest on academic performance, you will need to investigate a representative sample from each leisure time interest group.
Representivity is achieved by identifying the parameters of the wider population and taking them into consideration when composing samples.
So, in this example leisure time utility will be the independent variable.
Factors such as gender, age, occupation, academic year, etc. can be the dependent variables.
For the sake of coming to valid conclusions and findings, the process of organizing a stratified sample requires ensuring that the characteristics typical of the wider community are present in the sample.
If you draw more than one sample, you must also ensure that the samples are homogeneous in terms of at least one characteristic, which would be your independent variable.
In qualitative research, you will probably not calculate the size of the sample in terms of a statistical level of accuracy.
Therefore, representivity will depend on your own judgement.
You do need to take certain factors into consideration, though.
For example, the size of the population, time and cost constraints, access to data, the need for simplicity and the purpose of the reach.
Although some simple calculations need to be done with systematic sampling, it is not enough to be called quantitative research.
Systematic sampling is a modified form of random sampling.
For example, in a population of 10,000 individuals, you might feel that you should have a sample of, say, 200 people.
This will mean that you should select every first person from each sub-unit of 50 for your sample.
Fifty is, thus, your sample interval, i.e. the distance between each element selected for the sample.
You can choose numbers 1, 51, 101, 151, etc. for your sample.
If, for example, the first 57 people on the list that you use are the only females, you will have only two females in your sample.
This will probably distort your findings.
Another example of a skewed list would be if you work on a number of name lists for different faculties and the faculty lists are ordered normatively with the best performing student as the first name on the list and the poorest performing student as the last name on the list.
To use an extreme example, if there are fifty names on each list, your sample will include only the poorest performing students.
Periodicity can be a problem with systematic sampling if the list is not a fully random one.
For example, if you start by selecting the first name on the list, then names numbered 1 to 49, 50 to 99, 100 to 149, etc. do not have any chance of being selected for the sample.
You can eliminate this problem by ‘randomizing’ the list first by ‘shuffling’ the names like you would a deck of playing cards, and then selecting the sample.
You can also deviate somewhat from a systematic selection. A sampling procedure is not cast in concrete and you can adapt it to your research needs.
Just as long as it improves the randomness of your sample.
You can, for example, use systematic sampling coupled with the condition that both genders are fairly represented in the sample.
This can be achieved by splitting the name lists for males and females and then selecting a number of males and females from each list randomly.
Theoretical sampling is the process of investigating incidents, events, occurrences or people over a period based on their potential to represent or demonstrate important theoretical constructs.
Researchers who follow an approach where deductions can be made from data with which theory can be developed or extended would be interested in finding individuals with the right makeup, or cases that embody theoretical constructs.
Theoretical sampling, therefore, is a special type of criterion sampling.
As the name implies, theoretical sampling is best used when the research focuses on theory and concept development.
Your goal would be to develop theory and concepts that are connected to, are grounded in, or emergent from real life events and circumstances.
To generate new theory will often require substantial research and is, therefore, a time-consuming process.
You will need to analyze and probably reconstruct and deconstruct existing theory until you manage to develop new theoretical ideas.
As opposed to purposeful sampling, you cannot know in advance precisely what to sample for and where it will lead you when you use theoretical sampling.
That is why theoretical sampling fits in well with grounded theory and why you will probably work towards solving a problem statement or question rather than hypothesis testing.
Time sampling is where observations of occurrences or events need to be taken and recorded at certain times.
You can use it if it is important to know the chronology of events.
Time sampling can be instantaneous, at specific intervals or measured in terms of how long it takes, i.e. duration.
Instantaneous sampling is achieved by observing an event or occurrence at standard intervals, for example every minute, hour, etc. on the dot.
You will need to take observations at a specific time and intervals that you planned on, or that are prescribed or necessary for whatever reason and you will take notes of your observations.
In the case of interval recording, you will observe and record events or occurrences during each interval.
This means that you will record observations during each interval for the entire time of the interval and not just at the moment each interval starts.
For example, you might wish to conduct research on the emotional state of a patient over a period and at set intervals, say every fifteen minutes for a day.
You can then count the number of times that the patient is happy, sad, angry, etc. and how the patient expressed the emotions.
The patient might have smiled, cried, laughed, etc.
You might also need to take note of what possibly might have triggered the emotion.
Duration sampling is where you will measure how long it takes for an individual or group to complete a certain task.
With duration sampling, you might, for example, need to record how long it takes the patient to overcome an anger attack or any other emotional state.
Or you might need to record how often the individual switches between different emotions, and many more.
The format of your notes will depend on the type of data that you wish to collect.
Time sampling will often require a quantitative research approach or at least some calculations.
This, however, does not mean that it cannot be used in qualitative research.
It might also be necessary to use a mixed approach, i.e. quantitative and qualitative research.
Stratified sampling is where you will select a representative sample from a diverse community. You will use random sampling to select the sample or samples.
In systematic sampling you will select individuals or items from a population at structured intervals.
In theoretical sampling you will select the sample based on certain criteria that will enable you to develop new theories and concepts.
Time sampling is where you will take samples at certain times. It can be instantaneous, at specific intervals or measured in terms of duration.