An introduction to statistical inference--3.

Abstract

Statistics inference is used to make comments about a population based upon data from a sample. In a similar manner it can be applied to a population to make an estimate about a sample. It is commonly seen in medical publications when the null hypothesis is being tested. This calculates the probability (p value) of a type I error--that is, that a particular finding is attributable to chance. It is also important to be aware of the chances of a type II error--that is, accepting the null hypothesis when it does not apply. Sample size, point estimate and variability are common factors that will affect the chances of making these two types of errors. Interpreting results therefore needs to take these factors into account as well as the clinical relevance of the findings. Statistical significance does not necessarily mean clinical significance.