In statistics, many results are only approximate; meaning they are similar but not equal to the actual result. An approximation can turn a complex calculation into a less complicated one.
For instance, the calculation of a Poisson distribution is more complicated than that of a binomial distribution. If both only differ slightly in their end result, it is permissible to approximate the Poisson distribution by a more simple-to-use binomial distribution. Prerequisite for such approximations is a sufficient sample size. In this example, at least 100 respondents are necessary in order to justify a sufficient proximity of the two distributions. An approximation based on too small a sample can lead to errors – for example, an accidental similarity of the two distributions.
Please note that the definitions in our statistics encyclopedia are simplified explanations of terms. Our goal is to make the definitions accessible for a broad audience; thus it is possible that some definitions do not adhere entirely to scientific standards.