Multivariate observations are best organized and manipulated as a matrix of sample values, of size (n × P), where n is the number of samples and P is the number of attributes or variables. For example, a (5 × 3) matrix might represent five core samples at different depths on which frequencies of occurrence of three different fossils are recorded. The purposes of multivariate data analysis is to study the relationships among the P attributes, classify the n collected samples into homogeneous groups, and make inferences about the underlying populations from the sample. | Multivariate observations are best organized and manipulated as a matrix of sample values, of size (n × P), where n is the number of samples and P is the number of attributes or variables. For example, a (5 × 3) matrix might represent five core samples at different depths on which frequencies of occurrence of three different fossils are recorded. The purposes of multivariate data analysis is to study the relationships among the P attributes, classify the n collected samples into homogeneous groups, and make inferences about the underlying populations from the sample. |