Matrix algebra; random vectors; multivariate distributions; copulas; multivariate generalizations of classical testing; principle component analysis; discriminant analysis; clustering; multidimensional scaling; factor analysis; canonical analysis. Prerequisites: MATH 304 or MATH 323; STAT 212; STAT 415 or equivalent Credits 3. 3 Lecture Hours.
Matrix algebra; random vectors; multivariate distributions; copulas; multivariate generalizations of classical testing; principle component analysis; discriminant analysis; clustering; multidimensional scaling; factor analysis; canonical analysis. Prerequisites: MATH 304 or MATH 323; STAT 212; STAT 415 or equivalent Credits 3. 3 Lecture Hours.
