The objectives of scientific investigations to which multivariate methods most naturally lend themselves include the following: 1. Data reduction or structural simplification. The phenomenon being studied is represented as simply as possible without sacrificing valuable information. It is hoped that this will make interpretation easier. 2. Sorting and grouping. Groups of "similar" objects or variables are created, based upon measured characteristics. Alternatively, rules for classifying objects into well-defined groups may be required. 3. Investigation of the dependence among variables. The nature of the relation- ships among variables is of interest. Are all the variables mutually independent or are one or more variables dependent on the others? If so, how? 4. Prediction. Relationships between variables must be determined for the pur- pose of predicting the values of one or more variables on the basis of observa- tions on the other variables. 5. Hypothesis construction and testing. Specific statistical hypotheses, formulated in terms of the parameters of multivariate populations, are tested. This may be done to validate assumptions or to reinforce prior convictions. 3. Identify what multivariate techniques are used for the above objectives