About this Event
Partial Least Squares (PLS) analysis is a statistical method that straddles the line between multiple regression and principal component analysis (PCA). PLS focuses on predicting dependent variables from a set of independent variables. It reduces the predictors into a smaller set of uncorrelated components, much like PCA does. This is particularly useful when dealing with complex data structures or when the predictors are highly collinear. PLS is effective with small sample sizes relative to the number of predictors, including situations where there are more predictor variables than observations.
