Theory of Sampling

There are certain important steps that naturally precede chemical analysis if the result
or data generated is to have any significance.

These steps include:
(i) Sampling

(ii) Production of a homogenous mixture for analysis and

(iii) Drying the
collected sample.
Sampling wrongly done will not yield any meaningful result no matter how painstaking or laborious the analysis is. Materials to be analysed more often than not, exist not only in a large size but also in complex non homogeneous forms. Hence, attention, commitment and expertise are required to obtain a true representative sample. The number or size of the sample is all geared towards desired result, achievable only when the problem of analytical exercise is well defined.

Basic principles of sampling.

Sampling can be described as the operations involved in procuring a laboratory size
that is a true representative of “a whole lot” for a particular analytical exercise. Sampling is indeed the most difficult step in the entire analytical process; however, it remains the only key to the success of the whole analytical programme. Good sample irrespective of the type or method of sampling should possess the
following properties:
(i) A good sample must have the same characteristic or features with that of the original population from where it is selected.
(ii) The nature of the sample must be the same with that of the population and must remain so throughout the analytical exercise.
(iii) The number of samples should be large enough to make the result reliable. Indeed, the methods used in collecting a true representative sample depends on
various factors which include:
(i) The knowledge and experience of the analyst or sampler

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(ii) The result of survey on the nature, size and configuration of the site of materials to be sampled.
(iii) The level of sensitivity of the desired result.

It is important to note that, there is virtually no single technique that can satisfy all requirements in any sampling case. Modifications and combination of some techniques may be necessary in some sampling cases.

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