The Science is in the Sample – provided it is Representative
Current sampling practice is a result of the combination of statistics with scientific knowledge about the product/material being sampled. Such knowledge is acquired through experimentation and the use of various sampling techniques until reproducible results, from representative samples, can be obtained.
Two key questions that need to be asked prior to a sampling campaign are “How many samples are needed for a viable study and; how should they be selected?”
In most research and testing facilities that utilize and test repeat products, these questions have already been answered and is documented in the form of a test procedure. However, for new or untested products/materials, the researcher or technician will need to conduct a few trials in order to determine the most suitable sampling technique.
Sampling techniques can be classified as Probability Sampling and Non-probability Sampling.
The former makes use of random unbiased sampling, allowing for an equal chance of all particles in the population to be selected and is the technique employed in obtaining a scientific sample.
Probability sampling can be further classified into simple random sampling (samples are obtained completely at random); stratified sampling (random samples are obtained from groups or strata into which the population has been divided); cluster sampling (random samples of clusters are obtained from clusters into which the population has been divided); systematic sampling (samples are obtained according to a random starting point and fixed periodic intervals) and multistage sampling (samples are obtained through a combination of the above-mentioned types, in stages).
Once a technique(/s) has been identified, suitable equipment is then required in order to conduct the trials and finalize the test method. The equipment thereafter remains a key component in the sampling process of that product/material.
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