Dealing with outliers... July 10, 2018, 09:52:33 PM I was checking my data quality before running PCA/PLS, but am confused by different articles I've read concerning this. Basically they say that Hotelling's T2 identifies severe outliers, and DModX identifies moderate outliers. What I am seeing in my data: -My QC's all cluster to the center of a PCA - I have some samples located outside the Hotelling's T2 ellipse. - Depending on how many PCA components I include in the DModX plot, I get different samples that are larger than the D-Crit value. My questions: - How should I decide on how many PCA components to include in the DModX? - Should I remove all outliers detected by the DModX graph and the Hotelling's T2 plot from my data set to prevent skewing of my PCA/PLS? - Is it possible that the outliers could be of interest and I should leave them in further analysis? I really appreciate any and all advice!!!!