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Sampling procedures1 are used to obtain information about a population from part of the population only instead of having to study every person (110-2). The part of the population studied is called a sample2. A population is a collection of elements3 which are the object of the investigation. A sampling unit4may be an element or a group of elements of the population and is used for selecting samples. In demographic samples the elements are generally individuals (110-2), families (112-1) or households (110-3), and sampling units may be individuals, households, blocks of houses, municipalities or areas. The sample will consist a number of sampling units selected in accordance with a sampling scheme5 or sampling plan5.
A sample whose elements are selected by a chance process is called a probability sample1. If a complete list of sampling units is available this is called a sampling frame3. In simple random sampling4 a proportion of sampling units is selected from the frame at random2. This proportion is called the sampling fraction5. Systematic samples6 are taken from a frame in which the sampling units are consecutively numbered. The sample is drawn by taking the nth, (n + s)th, (n + 2s)th..., etc. unit, where n is not larger than s and is selected at random. In cluster sampling7 population elements are not drawn individually, but in groups which are called clusters8.
- 2. random — randomness n. — randomize v.
In stratified random sampling1 the population is divided into a number of strata2 which are in some sense more homogeneous than the population as a whole with respect to the characteristics studied, and a simple random sample (cf. 161-4) is drawn in each stratum. Variable sampling fractions (161-5) may be used in different strata. Multi-stage sampling3 is a method where the selection of the sample is carried out in several stages. A sample of primary sampling units (160-4) is first selected and each of these units is then regarded as a population from which a sub-sample4 is selected, and the process may be repeated. Where there is no good sampling frame, a sample of areas delimited on a map may be selected: this procedure is called area sampling5.
In probability sampling (161-1), chance methods are used to obtain a representative sample1, i. e., a sample which is a relatively faithful reflection of the population with respect to the character or characters studied. In quota sampling2, on the other hand, the sample is purposely selected so as to reflect the population in certain characteristics, and each interviewer (204-2) is given a quota3 of different types of sampling units which are to be included in his sample. Within the limits of the quota the interviewer is free to select the sampling units.
A population parameter1 is a numerical value that characterizes a population. Statistical estimation2 is the name given to the procedure by which the values of such parameters can be estimated from the sample. Such estimates are subject to sampling errors3 and a measure of the magnitude of the sampling error is generally given by the standard error4. Sometimes a confidence interval5 is associated with an estimate to show the limits within which the estimated quantity may be expected to lie. A difference between two values is called a significant difference6 when the probability that it is due to chance is less than a given value which is called the level of significance7. Thus a difference will be significant at the 5 per cent level if the probability that it could have arisen by chance is less than 0.05.
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