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5. Sample Size
5.1. Sampling Error
In statistics, sampling error may occur when the characteristics of a population are estimated from a subset, or sample, of that population. Since the sample does not include all members of the population, statistics on the sample will differ from parameters under evaluation for the entire population. For example, if one measures the blood pressure of a hundred individuals from a population of one million, the average value for blood pressure won’t be the same as the average value of all one million people.
Since sampling is typically done to determine the characteristics of a population, the difference between the sample and population values is considered a sampling error. The severity of the sampling error can be reduced by increasing the size of the study sample.