See JMP’s Multiple Factor Analysis (MFA) in action. Using a dataset on wine ratings, JMP’s Olivia Lippincott shows you how you can specify “column blocks” to easily identify outliers (in this case, outlier “expert panelist ratings”) and generate a Consensus Map to further examine variation in our data. Once identified, Oliva shows you an example of a sensory analysis technique to find groupings of similar products and identify outlier panelists.