Interesting botanical and ecological studies used the multivariate approach to describe underlying patterns in large data sets and to answer questions about the structure of the studied systems at various scales. This work aims to encourage the correct use of the multivariate approach and offers guidelines for the appropriate choice of the analysis techniques according to the objectives of the study and the characteristics of the data. Some appropriate applications of principal components, multidimensional scaling, correspondence analysis, discriminant, and cluster analysis in articles published in scientific journals of these disciplines are showed. We used reduced versions of the data matrices from some of these papers to present the methods of analysis in a simple way. The focus is placed on the correct interpretation of the results and the biological questions that can be answered through multivariate analysis.