CHAPTER FOUR: SAMPLING
Outcomes
By the end of this chapter, the learner will be able to:
• Explain why sampling is fundamental to research
• Define the terms generalisation and representativeness
• Explain the difference between a sample and a population
• Discuss the appropriate usage of the various types of probability and non-probability
sampling techniques
• Be familiar with a range of sampling techniques
• Identify the different types of sampling.
INTRODUCTION
Sampling is a procedure of methodically choosing targets for consideration in a research
project. The assets of the sample or the group or subgroups of the population are then
generalised to the population. This process of sampling helps to solve the research problem.
• This process of selecting a small part from the relevant group of the population is
called sampling.
• The essential point is that by choosing a portion of the components in a populace and
concentrating research consideration on this limited group, the specialist may apply
the discoveries of the investigation to the entire populace of interest.
A population is the full arrangement of components from which an example is drawn. A
populace component is the single unit of the example from which estimations and
perceptions are drawn.
Note:
• In sampling, the term population is not used in the normal sense, as a full set of
elements may not necessarily be people. For instance, the researcher may wish to
examine the administrative effectiveness of local schools in Astana
– then the
population from which they would draw the sample would be local schools and each
local school would be an element in the population of local schools of Astana.
There are two types of sampling
–
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