The paper examines the nature, structure, probability content and application of systematic sampling, a type of probability sampling technique. It seeks to draw a line of divide between systematic sampling, quasi or pseudo-probability systematic sampling and the real systematic probability sampling technique and how to achieve the real systematic probability sampling. The research method adopted here is more of a desk top approach relying on secondary data while deploying very robust literature in statistics, research methods and other related discipline. One of the arguments posed is that systematic sampling-(selection of members from a population on the basis of a predetermined sampling interval k), is not enough to ascribe the word probability to the systematic approach. Similarly, the selection of the ith element from the first sampling interval through randomisation and the subsequent addition of k to the previous elements selected to determine subsequent elements do not also suffice, as the selection of subsequent elements from the succeeding intervals is predicated on the choice of ith element. The paper posits that the real systematic sampling requires the application of simple probability sampling method(s) in such a manner that every element in the population has a fair chance of being chosen. This is line with Gy’s Sampling theory. In the light of the foregoing, study suggests the application of any simple random sampling method in every sampling interval as against the first interval only. This no doubt guarantees every member of the population a fair chance of being selected. The emerging method is the real systematic probability sampling technique. The paper further advance that where there is no randomisation at all in any of the sampling intervals or predetermined sampling interval this will result in ordinary systematic sampling and where randomisation is applied in only one or the first sampling interval, the emerging technique is quasi or pseudo-probability sampling.
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