1. Sampling
Which do we choose and why?

2. Overview Recap Aims and outcomes Sampling Process Sampling Techniques
Applying sampling to your research plan
Look forward

4. Aims
To consolidate our appreciation of methods of data collection and the role of sampling in the research process

5. Intended outcomes By the end of the session you will have:
Explained the value of different research methods;
Explored the 7 stages in the sampling process
Critically evaluated 7 different sampling techniques
Made links to your research plan and explained which sampling techniques you will use.

7. The principal issues surrounding sampling are:
Whole vs sample
Probability vs Non-probability
Sampling size

8. The 7 stages of the sampling process
Defining the population for study, e.g. Experience of students studying Level 3 courses at a school
Specifying a sampling frame - accessible information on your population so you can draw a sample from it. e.g. students who are on the class lists for all Level 3 courses
Specifying a sampling method for selecting items or events from the frame, e.g. stratified sampling
Determining the sample size, e.g. 80 males and 60 females.
Implementing the sampling plan
Sampling and data collecting
Reviewing the sampling process

9. A group selected from the population to represent it
Sample
A group selected from the population to represent it
All the existing members of a specified group

10. Sampling techniques Non-Probability Probability (Qualitative)
Purposive
Snowball
Convenience
Quota
Probability
(Quantitative)
Random
Systematic
Stratified
(Wellington, 2000, p60)

11. Random sampling
…involves the selection of people or events literally ‘at random’. Behind the use of random sampling lies the assumption that, if there are a sufficiently large number of examples selected and if their selection has been genuinely ‘at random’, then the resulting sample is likely to provide a representative cross- section of the whole. (Denscombe, 2003, p12)

12. This method is sometimes termed as the lottery method

13. Systematic sampling
is often used instead of random sampling. It is also called an Nth name selection technique.
After the required sample size has been calculated, every Nth record is selected from a list of population members.
As long as the list does not contain any hidden order, this sampling method is as good as the random sampling method.
Its only advantage over the random sampling technique is simplicity. Systematic sampling is frequently used to select a specified number of records from a computer file.

15. Stratified sampling
…can be defined as one in which every member of the population has an equal chance of being selected in relation to their proportion within the total population…It is something of a mix of random selection and selecting on the basis of specific identity or purpose. (Denscombe, 2003, p13) Stratified sampling is often used when one or more of the categories in the population have a low incidence relative to the other categories

16. Purposive sampling
…the sample is ‘hand picked’ for the research...In effect, they are selected with a specific purpose in mind and that purpose reflects the particular qualities of the people or events chosen and their relevance to the topic of the investigation. (Denscombe, 2003, p15)

17. Snowball sampling
With snowballing, the sample emerges through a process of reference from one person to the next. (Denscombe, 2003,p16) is a special non-probability method used when the desired sample characteristic is rare. While this technique can dramatically lower research costs, it can come at the expense of introducing bias because the technique itself reduces the likelihood that the sample will represent a good cross section from the population.

18. Convenience sampling
…is built upon selections which suit the convenience of the researcher and which are ‘first to hand’. (Denscombe,2003, p16)
is used in exploratory research where the researcher is interested in getting an inexpensive approximation of the truth.

20. Quota sampling
‘is widely used in market research. It operates on very similar principles to stratified sampling’. (Denscombe, 2003, p13)
Like stratified sampling, the researcher first identifies the categories and their proportions as they are represented in the population, e.g. By gender or ethnicity
Then convenience or purposive sampling is used to select the required number of subjects from each category.
This differs from stratified sampling, where the categories are filled by random sampling.

21. Sampling size Consider: Response rates Bias from non-respondents
Representativeness
Sufficient numbers?
Difference between quantitative and qualitative approaches

22. Sample size
Whatever the theoretical issues, the simple fact is that surveys and sampling are frequently used in small-scale research involving between 30 and 250 cases…In the case for qualitative research there is a different logic for the size of the sample and…a small sample size is quite in keeping within the nature of qualitative data. (Denscombe,2003, p24)

23. Reviewing your sampling
Remember to check that your actual sample is what you intended sample, e.g. Have you actually interviewed who you said you would interview?
A particular problem can be non-response rates with surveys or people dropping out.

24. References
Denscombe, M., (2003) The Good Research Guide (2ed) Maidenhead: OUP Wellington,J., (2000) Educational Research: Contemporary Issues and Practical Approaches London: Continuum