Principles and practice in the analysis of multivariate data. Correlation, partial correlation, principle components, factor analysis, discriminant functions, canonical correlation, cluster analysis, multidimensional scaling. Emphasis on computer analysis of actual data.
P: MATH 260 with at least a C, MATH 306 with at least a C, MATH 320 with at least a C, and MATH 329 with at least a C
Spring Odd.