Description:
<jats:p>This article shows how to interpret the scores and loadings based around a simulated dataset, consisting of two groups of 10 objects in each group, and 5 variables, to demonstrate how principal components analysis (PCA) can be used to discriminate between the groups when individual variables cannot, and how the loadings can show which variables are most likely markers for each group.</jats:p>