 the analysis of multivariate data: given a <span class="math inline">\(N\times P\)</span> dataset <span class="math inline">\(\mathbf{X}\)</span>, how can we tease apart information that is shared between feature correlations and sample correlations? More concretely, to learn something about the samples we require some information or assumptions about the features, and vice-versa.  How is information shared between feature correlations and sample correlations? This simple fact comes from a basic result in 