![]() ![]() ![]() It is a basic statistical principle with which we define the sample size before we start a clinical study so as to avoid bias in interpreting results. The sample size, the topic of this article, is, simply put, the number of participants in a sample. Ideally, choice of one participant should not affect the chance of another's selection (hence we try to select the sample randomly – thus, it is important to note that random sampling does not describe the sample or its size as much as it describes how the sample is chosen). Thus a “sample” is a portion, piece, or segment that is representative of a whole. ![]() In a statistical context, the “population” is defined as the complete set of people (e.g., Indians), the “target population” is a subset of individuals with specific clinical and demographic characteristics in whom you want to study your intervention (e.g., males, between ages 45 and 60, with blood pressure between 140 mmHg systolic and 90 mmHg diastolic), and “sample” is a further subset of the target population which we would like to include in the study. This set of individuals is known as the “sample.” Hence, a set of participants is selected from the population, which is less in number (size) but adequately represents the population from which it is drawn so that true inferences about the population can be made from the results obtained. It is naturally neither practical nor feasible to study the whole population in any study. One of the pivotal aspects of planning a clinical study is the calculation of the sample size. ![]()
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