Many scientists have problems and difficulties in making a statistical analysis of their data, which they need to interpret their results. One problem is that applying a statistical method requires knowledge of the conditions (assumptions) about the data that must be met in order to apply it. These initial conditions are not usually checked and researchers simply apply a statistical method, in most cases taken from a similar published work, which is unsuited to their data set. As a result, their conclusions can be incorrect. This kind of misunderstanding is all too common in the research community. To become familiar with statistical methods, we provide a short tutorial on how to perform statistical analysis of food data. The study uses authentic food data on fatty acid profiles and the isotope composition of milk samples. In addition, we present an in-house developed and freely available e-learning tool for advanced statistics in natural sciences and technologies that has the benefit of checking the required conditions of each statistical method and offering only those methods that are appropriate for analysing the experimental data.