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Sampling methods

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  1. Introduction.
  2. Meaning of Probability sampling.
  3. Simple random sampling.
  4. Systematic sampling.
    1. Advantages and disadvantages.
  5. Stratified random sampling.
  6. Random route sampling.
  7. Multistage sampling.
  8. Cluster sampling.
  9. Non-probability sampling.
    1. Advantages.
  10. Convenience sampling.
  11. Quota sampling.
  12. Judgemental sampling.
  13. Definition of the common terms used in sampling.
    1. A sampling frame.
    2. A survey.
    3. A sampling error.
    4. A respondent.
    5. A sample.
    6. A random sampling.
    7. Bias.
    8. Standard error.
  14. Sources.

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. [...]


[...] Researchers prefer the random sampling methods because it is more rigorous. It isn't always possible to undertake a probability method of sampling, such as in random sampling. For example, there is not a complete sampling frame available for certain groups of the population e.g. the elderly; people who are attending a football match; people who shop in a particular part of town. Another factor to bear in mind is that many of the probability sampling methods described above may mean that researchers would have to undertake a postal or telephone survey delivery or might be expected to go from house to house. [...]

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