1. Discriminant Analysis Objective Classify sample objects into two or more groups on the basis of a priori information

2. Discriminant Analysis Prediction of group membership is done using one or more predictor variables and one criterion variable. The criterion variable is categorical

3. Two variables of interest

6. A multivariate analysis must first show a significant difference between the groups The Wilks Lambda statistic

7. Example Distinguish between tropical and temperate countries Variables: calories, urban pop, pop, GDP D = a * calories + b * urban + c * population + d * GDP

8. Assumptions –The predictor variables follow a multivariate normal distribution –Covariance matrices of different groups are homogeneous

9. Cluster Analysis Cluster Analysis is used to identify groups Given a large sample with multivariate data, identify a subset of the sample which is homogeneous

10. Distinguishing between groups Cluster Analysis Discriminant Analysis Neural Networks