Broadly speaking, the sample is the group of people whom researchers actually examine and the population is the group of people whom
the survey is about. For example, the population in a study might be EFL learners in Taiwanese secondary schools and the actual sample might involve three Taiwanese secondary classes. That is, the target population of a study consists of all the people to whom the survey's findings are to be applied or generalized.
Why don't we include every member of the population in the survey? This is a valid question and, indeed, there is one particular survey type where we do just that: the 'census.' In most other cases, however, investigating the whole population is not necessary and would in fact be a waste of resources. By adopting appropriate sampling procedures to select a smaller number of people to be questioned we can save a considerable amount of time, cost, and effort and can still come up with accurate results - opinion polls, for example, succeed in providing national projections based on as few as 1,0003,000 respondents. The key question, then, is what do we mean by 'appropriate sampling procedures?'
A good sample is very similar to the target population in its most important general characteristics (e.g., age, gender, ethnicity, educational background, academic capability, social class, or socioeconomic status, etc.) and in all the more specific features that are known to be significantly related to the items included on the questionnaire (e.g., L2 learning background or the amount and type of L2 instruction received). That is, the sample is a subset of the population which is representative of the whole population. Sampling procedures have been designed to ensure this representativeness.
Selecting a truly representative sample is a painstaking and costly process, and several highly technical monographs have been written about the topic (e.g., Cochran, 1977; Levy & Lemeshow, 1999). In most L2 survey research it is unrealistic or simply not feasible to aim for perfect representativeness in the psychometric sense. Therefore, in the following overview I will not discuss the details of the statistical procedures of 'probability sampling,' which is the generic term used for a number of scientific procedures such as simple random sampling, systematic sampling, stratified random sampling, and cluster sampling.
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