As time and resources available are limited, we cannot interview all members of a population. Therefore, researchers use sampling to obtain the information they need. They select a limited number of people (a sample) to represent the characteristics of a whole population. There are different methods to select a sample. We can divide them into two major groups: the probability sampling and the non-probability sampling. A good sample survey can give important and interesting results. However, a bad sample survey (wrong people interviewed) can have disastrous results on a company, for example. When you use a probability sampling method, you must find some process or procedure that assure that the different units in your population have equal probabilities of being chosen in the sample for the survey being conducted. It is scientific, operationally convenient and simple in theory. You give a number to every member of the population. Then you use a table of random numbers, a computer random number generator or a mechanical technique (to close your eyes and pull out the numbers which refer to people) to select your sample. Finally, you pull out a number and you interview the person who has this number.
[...] Judgmental sampling has its place, so long as the auditor is aware of its limitations. Where the audit objectives are fully met by a judgmental sample, where would be no valid reason to insist on the discipline of added statistical support. Definition of the common terms used in sampling A sampling frame It is the list of all elements in the population from which the sample is taken. It should be comprehensive, complete and up-to-date. Examples of sampling frame: Electoral Register; Postcode Address File; telephone book. [...]
[...] In addition, stratified sampling do the sample in accordance with the importance of each group of customers in the market. This method is viable because the statistical proportions of such strata are well known: the information comes from basic sources like the census of population, for example. However, a lot of information is required to do it and you spend time to collect them.People prefer using stratified sampling instead of simple random sampling because the cost per observation in the survey can be reduced and it improves the accuracy of the results. [...]
[...] Sample of children in each class This method is quite rich because you combine many different sampling methods. In addition, it enables you to reduce the distance and so to reduce costs and time. Moreover, you also reduce the number of people that you are going to interview. This technique of sampling is used when you select large groups. Cluster Sampling Cluster sampling is typically used when the researcher cannot get a complete list of the members of a population they wish to study but can get a complete list of groups or 'clusters' of the population. [...]
[...] In addition, you have a quick reply and you do not need any sampling frame. Nevertheless, you have no idea how representative the information collected about the sample is to the population as a whole. In addition, there are many biases, because the persons interviewed, are not representative of the population. Moreover, it is difficult to check your answers. Therefore, the quality and the accuracy of your survey are limited. However, this method is often the only feasible one, particularly for students or others with restricted time and resources, and can legitimately be used provided its limitations are clearly understood and stated. [...]
[...] This can make quota sampling very difficult, as there is no real definition of what constitutes, say, the upper middle class, and certainly you can seldom tell a person's social class by looking at him. Such a requirement necessitates the interviewer being given detailed definitions and descriptions of what the survey body means by each term it uses. This method is often used in market research because it is less costly and administratively easy to do. It requires little knowledge about the population. [...]
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