Are my data normal?
Many inferences from statistical methods use the assumption that experimental data form a random sample (using that word in the statistical, not the chemical or physical, sense) from a population with a normal (Gaussian) distribution of measurement errors or other variations. In most cases this assumption is not actually tested, so if it is not valid false deductions may be made from the data. This Technical Brief considers cases where the normal distribution is generally taken to be valid, discusses how likely that is to be true, and how it is possible to test whether a data sample might come from a normally distributed population.
- This article is part of the themed collection: Analytical Methods Committee Technical Briefs